Implication des microorganismes dans les biotransformations et ... [PDF]

UNIVERSITE MONTPELLIER Habilitation à Diriger des Recherches Spécialité : Sciences de la Terre et de l’Environnement

Implication des microorganismes dans les biotransformations et processus de transfert des métaux et métalloïdes dans les environnements contaminés par les mines par

Odile BRUNEEL Chargée de Recherches à l’IRD HydroSciences Montpellier UMR 5569

Soutenue le 29 mars 2016 devant le jury composé de

Bernard OLLIVIER Philippe NORMAND Pascale BAUDA Pascal SIMONET Michel LEBRUN

Directeur de Recherche IRD, UMR 7294, Marseille Directeur de Recherche CNRS UMR 5557, Lyon Professeur Université de Lorraine, UMR 7360, Metz Directeur de Recherche CNRS, UMR 5005, Lyon Professeur Université de Montpellier, UMR LSTM

Rapporteur Rapporteur Rapporteure Examinateur Examinateur

Ecole Doctorale : Systèmes Intégrés en Biologie, Agronomie, Géosciences, HydroSciences, Environnement

SOMMAIRE

I CURRICULUM VITAE....................................................................................................... 3
Diplômes et formation......................................................................................................... 3
Parcours professionnel........................................................................................................ 3
Responsabilités récentes, animations scientifiques, comités............................................ 4
Collaborations récentes....................................................................................................... 4
Evaluation de la recherche.................................................................................................. 5 II CONTRATS DE RECHERCHE ET FINANCEMENTS ............................................... 6 III ENCADREMENT D’ETUDIANTS ET ENSEIGNEMENT…...................................... 8
Encadrement d’étudiants.................................................................................................... 8
Activité d’enseignement....................................................................................................... 9 IV PUBLICATIONS ET COMMUNICATIONS............................................................... 10
Synthèse de la production scientifique............................................................................. 10
Publications........................................................................................................................ 11
Communications, conférences et poster........................................................................... 14 V ACTIVITE DE RECHERCHE…......................................................................................15
Préambule ........................................................................................................................... 15
Travaux antérieurs ............................................................................................................ 19
Travaux actuels................................................................................................................... 47 VI PROJET DE RECHERCHE .......................................................................................... 55 VII REFERENCES BIBLIOGRAPHIQUES……….…..................................................... 60 VIII ANNEXES : SELECTION DE 5 PUBLICATIONS……….……............................. 67

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I CURRICULUM VITAE Odile BRUNEEL IRD-CR1 [email protected]

Née le 1er avril 1973 Mariée, un enfant

Affectation actuelle : En expatriation depuis février 2012 au Laboratoire de Microbiologie et Biologie Moléculaire Université Mohammed V, Faculté des Sciences, Av Ibn Batouta BP1014 Rabat, Maroc Laboratoire HydroSciences Montpellier, UMR5569 (CNRS/IRD/UM) Université de Montpellier, CC0057 (MSE), 163 rue Auguste Broussonet 34090 Montpellier, France

Domaine de recherche : Implication des microorganismes dans les biotransformations et processus de transfert des métaux et métalloïdes dans les environnements contaminés par les mines


DIPLOMES ET FORMATIONS • 2004 : Doctorat en Sciences de l’eau dans l’Environnement Continental, Ecole Doctorale Sciences de la Terre et de l’Eau. Laboratoire HydroSciences Montpellier. Université Montpellier II • 2001 : DESS Diagnostic, Prévention et Traitements en Environnement, Faculté Libre des Sciences de Lille, Mention Bien • 1997 : DEA de Biologie, option Biologie des Protistes de Clermont-Ferrand I et II


PARCOURS PROFESSIONNEL Recherche • Février 2012 - aujourd’hui : en affectation au sein du Laboratoire de Microbiologie et Biologie Moléculaire, Faculté des Sciences, Université Mohammed V, Rabat, Maroc • Depuis Octobre 2008: Chargée de Recherches 1ère classe à l’IRD • Octobre 2004 - aujourd’hui : Chargée de Recherches à l’IRD au sein du Laboratoire HydroSciences Montpellier (UMR 5569, CNRS-Université Montpellier-IRD) • 2001-2004 : Recherche en géomicrobiologie à l’Université Montpellier II dans le cadre de ma thèse. Laboratoire HydroSciences Montpellier, UMR 5569 3

Activités salariées • 1999-2000 : Professeur des écoles en CE2 à Djibouti (Afrique de l’Est) dans le cadre d’une coopération civile d’aide au développement


RESPONSABILITES RECENTES, ANIMATIONS SCIENTIFIQUES, COMITES • Représentante par Intérim de l’IRD au Maroc (août 2014-aujourd’hui) • Membre du comité de pilotage du réseau SICMED Mistrals « Activités minières dans le bassin méditerranéen – Interactions contaminants métalliques / écosystèmes − Interfaces avec la santé, l’environnement » • Membre élue depuis 2012 de la commission scientifique sectorielle n°1 (CSS1, Sciences physiques et chimiques de l’environnement planétaire) de l’IRD


COLLABORATIONS RECENTES  Instituto de Biologıa Molecular y Biotecnologıa (Volga Iñiguez), Facultad de Ciencias Puras, Universidad Mayor de San Andres, C. 27 Campus Universitario Cota Cota, La Paz, Bolivie (laboratoire soutenus par le DSF de l'IRD dans le cadre du programme "jeunes équipes")  Laboratoire de Microbiologie et Biologie Moléculaire (LMBM, L. Sbabou, J. Aurag et A. Filali-Maltouf), Faculté des Sciences, Université Mohamed V, Rabat, Maroc  Laboratoire de Physiologie et Biotechnologie Végétale (LPBV, A. Smouni, M. Fahr), Faculté des Sciences, Université Mohamed V, Rabat, Maroc  Equipe de recherche E2G, (R. Hakkou) Département des Sciences de la terre, Faculté des Sciences et Techniques de Guéliz, Université de Cadi Ayyad, Avenue Abdelkarim Elkhattabi, Gueliz, P.O. Box 549, Marrakech, Maroc  Laboratoire Géoexplorations et Géotechniques (A. Ddekayir), Département de Géologie, Faculté des Sciences, BP. 11201, Zitoune, Meknès, Maroc  Institut de Minéralogie et de Physique des milieux Condensés (IMPMC, G. Morin), UMR CNRS 7590, UPMC, 4 Place Jussieu, 75252 Paris, France  Laboratoire AMPERE (E. Navarro), UMR CNRS 5005, Ecole Centrale de Lyon, Université de Lyon, 36 avenue Guy de Collongue, 69134 Ecully, France et Laboratoire des Symbioses Tropicales et Méditerranéennes, LSTM, UMR 113, TA A-82/J Campus de Baillarguet, 34398 Montpellier, France  Laboratoire Biochimie et Physiologie Moléculaire des Plantes (BPMP, Patrick Doumas), 2, place Pierre Viala, 34060 Montpellier, France  Equipe Environnement et Microbiologie (EEM, R. Duran, B. Lauga), UMR 5254 IPREMEEM, Pau, France  Laboratoire de Génétique Moléculaire, Génomique et Microbiologie (GMGM, P. Bertin, F. Ploetze), UMR 7156, Univ Louis Pasteur–CNRS, Strasbourg, France

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EVALUATION DE LA RECHERCHE Participaption à un jury de thèse L. Giloteaux en décembre 2009 Participation à différents jurys de Licence, M1 et M2 tous les ans depuis 2005 Evaluations pour les journaux: FEMS Microbiology Ecology, Microbial Ecology, Extremophiles, Environmental Science and Pollution Research, Geomicrobioloy Journal, Journal of Applied Microbiology, PLOS ONE Evaluations de projets : ANR (Blanc, JC), Ec2co (Microbiologie environnementale), FRB (Fondation pour la recherche sur la biodiversité

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II CONTRATS DE RECHERCHE ET FINANCEMENT Contrats de recherches nationaux et internationaux • 2003-2005. Projet labélisé RITEAU (Ministère de l’Industrie, 677 k€). As5 : Mise au point d’un procédé biologique de potabilisation des eaux arséniées. Partenaires : IRH Environnement, BEFS-PEC, LMCP UMR 7590 (G. Morin). • 2004-2006. Projet ECODYN (AC, FNS, ECCO, 30 k€). « Processus de transfert et écotoxicité de l’arsenic et des métaux associés dans un hydrosystème en aval d’un drainage minier. Contrôles physico-chimiques et microbiologiques ». Partenaires : UMR 7590-CNRSUniversités Paris 6 et 7-IPG (G. Morin), LCABIE, UMR 5034, CNRS Université de Pau (O. Donard), LEM, Université de Pau (R. Durand), CB UPR 9043, Marseille (V. Bonnefoy), INERIS (J-M. Porcher), BRGM (M. Motelica), ECOLAG, UMR 5119 CNRS (C. Aliaume) • 2004-2006. Projet PICS CNRS (21 k€), Université de Huelva, Espagne). « Signature de l’activité bactérienne dans les précipités riches en fer des drainages miniers acides ». Partenaires: Departamento de Geologia, Universidad de Huelva, Espagne (JM. Nieto) • 2006-2007. PAI Protea (Ministères des Affaires Etrangères et de l’Education Nationale, de l’Enseignement Supérieur et de la Recherche, 10 k€) avec l’Afrique du Sud. « Metal and metalloid biotransformations in South African acid mine drainage systems”. Partenaires : Department of Biotechnology (D. Cowan), Department of Chemistry (L. Petrik) University of Western Cape, Capetown, Afrique du Sud • 2006-2008. Projet EC2CO-3BIO (INSU, CNRS, 40 k€) « Biologie, biominéraux et biotransformations dans les eaux acides minières ». Partenaires : IMPMC, UMR CNRS7590, Paris (G. Morin), IPREM, UMR 5254, CNRS- Université de Pau (R. Duran) • 2007-2008. Coordinatrice pour HSM du P2R Safe-Water (Afrique du Sud, 15 k€). « Study of the metal and metalloid biotransformations in South African acid mine drainage”. Partenaires : Department of Biotechnology (D. Cowan), Department of Chemistry (L. Petrik) University of Western Cape, Capetown, Afrique du Sud • 2007-2009. Coordinatrice du projet EC2CO-MicroBien (INSU CNRS, 90 k€) « Impact des microorganismes sur les transformations des métaux et métalloïdes dans des drainages miniers riches en sélénium ». Partenaires : IMPMC, UMR CNRS 7590, Paris (G. Morin), IPREM, UMR 5254, Pau (R. Duran) • 2007-2010. Projet ANR RARE, programme blanc (Agence Nationale pour la Recherche, 166 k€) « Reactivity of an arsenic-rich ecosystem: an integrated genomics approach ». Partenaires : GMGM, UMR 7156 de Strasbourg (P. Bertin) ; IMPMC, UMR 7590, Paris (G. Morin) ; IPREM, UMR 5254, Pau (R. Duran) • Depuis 2009- aujourd’hui. OSU OREME (INSU, INEE, 12 k€/an). Tâche d’Observation 1 (TO1, environ 10 k€/ans) « Suivi des processus hydrobiogéochimiques de transfert des métaux et métalloïdes issus des activités minières sur le site de Carnoulès ». Labelisée par l’OSU OREME (http://www.oreme.univ-montp2.fr/spip.php?rubrique41). Système d’Observation Pollution et adaptabilité biologique en aval des anciens sites miniers • 2009-2011. Bourse de thèse présidente environnée de l’UM2 (Université Montpellier II, 30 k€, A. Volant). « Etude des processus microbiens et géochimiques de mobilisation et de piégeage des éléments métalliques issus des activités minières ». • 2010-2011. Projet FRB MIGR’AMD (Fondation pour la Recherche sur la Biodiversité, 40 k€). « Microbial biogeography of acid mine drainage: a study of genetic 6

diversity and species diversity from an evolutionary perspective ». Partenaires : IPREM, UMR 5254, Pau (B. Lauga). Responsable du projet pour HSM • 2011-2012. Projet Ec2co Microbien. (INSU CNRS, 38 k€) « Rôle des bactéries du genre Thiomonas dans les transformations de polluants métalliques au sein d’écosystèmes miniers ». Partenaires : GMGM, UMR 7156, Strasbourg (F. Ploetze) et LSMBO, UMR 7509, Strasbourg (C. Carapito). Responsable du projet pour HSM • 2011-2013. Projet MISTRALS (INSU CNRS). Mediterranean integrated studies at regional and local scales. Aide au montage d’un réseau sur les activités minières dans le bassin méditerranéen – Interactions contaminants métalliques / écosystèmes - interfaces avec la santé, l’environnement et la société (Coordinateur : P. Doumas, UMR BPMP Montpellier). Membre du comité de pilotage • 2012-2013. Coordinatrice du Projet Ec2co ECODYN/MICROBIEN (INSU CNRS, 60 k€). « Etude des interactions plantes-microorganismes dans un contexte de réhabilitation de sites miniers au Maroc: mécanismes adaptatifs et effets sur le devenir des polluants métalliques ». Partenaires : LMBM, Rabat (L. Sbabou, J. Aurag, A. Filali-Maltouf) ; LPBV, Rabat (A. Smouni, M. Fahr) ; AMPERE, Lyon-LSTM, Montpellier (E. Navarro) ; UMR BPMP, (P. Doumas) ; • 2012-2014. Projet de coopération CNRS-CNRST avec le Maroc (CNRS, 4 k€). « Dynamique des métaux et métalloïdes et processus biogéochimiques mis en jeu dans les lacs de carrière du district minier de Zeïda (Maroc) ». Partenaire : Laboratoire d'Ingénierie Géologique de Meknes (A. Dekayir) • 2014-2017. Projet ANR ECO-TS IngECOST-DMA (ANR, Programme Ecotechnologies & Eco-Services, 850 k€). « Ingénierie écologique appliquée à la gestion intégrée de stériles et drainages miniers acides riches en arsenic ». Partenaires : BRGM, Orléans (F. Battaglia-Brunet, C. Joulian) ; IMPMC, UMR 7590, Paris (G. Morin) ; Sol Environnement, Nanterre (A. Esnault) ; IRH, Gennevilliers (G. Grapin)

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III ENCADREMENT D’ETUDIANTS ET ENSEIGNEMENT
ENCADREMENT D’ETUDIANTS Licence et IUT • Julie Mougeot (2008) 2ème année DUT Génie Biologique option Analyses Biologiques et Biochimiques. UM2, Montpellier • Sandrine Gavalda (2009) 2ème année DUT Génie Biologique option Analyses Biologiques et Biochimiques. UM2, Montpellier • Cédric Bocquet (2009) 1ère année BTS Analyses Biologiques et Biotechnologie. Castelnaudary • Blandine Luce (2009-2010, 19 oct au 19 fév). Licence professionnalisante Géosciences, Traitement et Prévention des Pollutions 5GTPT). UM2, Montpellier • Aurélia Aidi (2010) 2ème année DUT Génie Biologique option Analyses Biologiques et Biochimiques. UM2, Montpellier • Coencadrement L. Rubini (2011) 2ème année DUT Génie Biologique, option Analyses Biologiques et Biochimiques. UM2, Montpellier • Co-encadrement M. Dufour (2012) 2ème année DUT Génie Biologique, option Analyses Biologiques et Biochimiques. UM2, Montpellier • Co-encadrement L. Causse (2013) 2ème année DUT Génie Biologique, option Analyses Biologiques et Biochimiques. UM2, Montpellier • Encadrement Keltoum Ouassal (2013) Licence en Sciences de la Vie, module PFE. Faculté des sciences. Université Mohammed V, Rabat, Maroc Masters • Noémie Pascault (2006) Master 2 BGAE (Biologie, Géologie, Agroressources et Environnement). Spécialité BIMP (Biodiversité et Interactions Microbiennes et Parasitaires), parcours SM (Systèmes Microbiens). UM2, Montpellier Publication : Bruneel et al., 2008. Archaeal diversity in a Fe-As rich acid mine drainage at Carnoulès (France). Extremophiles. 12, 563-571

• Amélie Bardil (2007) Master 1 BGAE TEE, R2E (Terre, Eau et Environnement/Recherches en Eau). UM2, Montpellier • Amélie Bardil (2008) Master 2 BGAE, TEE, R2E (Terre, Eau et Environnement/Recherches en Eau). UM2, Montpellier Publication : Bruneel et al., 2011. Characterization of the active bacterial community involved in natural attenuation processes in arsenic-rich creek sediments. Microbial Ecology. 61, 793-810

• Anouk Favri (2008) Master 2 Pro Gestion des Ressources en Eaux. Parcours dans le cadre de la formation permanente. UM2, Montpellier • Camila Cordier (2010) Master 2 BGAE. Spécialité BIMP (Biodiversité et Interactions Microbiennes et Parasitaires), parcours SM (Systèmes Microbiens), UM2, Montpellier • Encadrement d’une étudiante chilienne, V. Verdejo Parada (2011) Master 1. Mention BGAE, spécialité BIMP, UM2, Montpellier • Encadrement Ikram Dahmani (2013) Master 2 BIOGECO (Biodiversité, Gestion et Conservation). Faculté des sciences, Université Mohammed V, Rabat, Maroc • Coencadrement Najoua Mghazli. 2015. Master 2 Production Végétale. Faculté des sciences, Université Mohammed V, Rabat, Maroc 8

Thèses • Co-encadrement, pour la partie microbiologie, de la thèse de Doctorat d’Ingénieur du CNRS de Marion Egal (2005-2008). Directrice de thèse : F. Elbaz Poulichet (DR CNRS chimiste à HSM). Encadrement par C. Casiot. Encadrement personnel effectif : 5% • Co-encadrement de thèse d’Aurélie Volant (2009-2012) soutenue le 12/12/12. Ecole Doctorale SIBAGHE. Directeurs thèse : F. Elbaz Poulichet (DR CNRS chimiste, HSM) et P. Bertin (Professeur au laboratoire GMGM, Strasbourg). Encadrement personnel effectif: 90% Publications : Bruneel et al. (2011) Characterization of the active bacterial community involved in natural attenuation processes in arsenic-rich creek sediments. Microbial Ecology. 61, 793-810 Volant et al. (2012) Archaeal diversity: temporal variation in the arsenic-rich creek sediments of Carnoulès Mine, France. Extremophiles. 16, 645-657 Volant et al. (2014) Diversity and spatiotemporal dynamics of bacterial communities: physicochemical and others drivers along an acid mine drainage. FEMS Microbiology Ecology. 90, 247-263

• Co-encadrement thèse Ikram Dahmani. Décembre 2013. Faculté des sciences. Université Mohammed V, Rabat, Maroc. Directeur de thèse : J. Aurag (LMBM, Rabat), co-encadrement avec L. Sbabou (LMBM, Rabat) et E. Navarro (AMPERE, Lyon - LSTM, Montpellier). Encadrement personnel effectif : 60%


ACTIVITES D’ENSEIGNEMENT  Université de Pau et des Pays de l’Adour ; Master 2. Module écologie moléculaire bactérienne. (3 heures/an, de 2004-2006)  Université Montpellier 2 ; DEA SEEC – Etude du rôle des microorganismes dans le transfert de la pollution minière (2 heures/an, 2005-2008)  Université Montpellier 2 ; M2R Fenec, L3Pro GPTP. Sortie terrain sur l’ancien site minier de Carnoulès (Gard) (3 à 9 h/an 2006-2011).  Université Paris VI ; DEA puis M2R Sciences de l’Univers, Ecologie, Environnement – Parcours Hydrologie, Hydrogéologie, Stage terrain et visite de l’ancien site minier de Carnoulès (4 à 8 heures/an, de 2003-2011)  Université Mohamed V de Rabat, Faculté des Sciences, Masters PV & BioGéCo (Module de Microbiologie du sol) (4 à 8 heures/an, 2012-2015)

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IV PUBLICATION ET COMMUNICATION
SYNTHESE DE LA PRODUCTION SCIENTIFIQUE Bibliométrie ISI (mai 2015) Results found Sum of the Times Cited without self-citations Average Citations per Item h-index

Journal The ISME Journal PLoS Genetics Environmental Microbiology Environmental Science and Technology Water Research Geochimica et Cosmochimica Acta Applied and Environmental Microbiology FEMS Microbiol Ecol Chemosphère Vaccine Chemical Geology Microbial Ecology Science of the Total Environment Environmental Chemistry Journal of Applied Microbiology Extremophiles Applied Geochemistry Aquatic Geochemistry Geomicrobiology Journal Environmental Science: Processes and Impacts.

31 690 26 17

Nb d’articles 1 1 1 3 1 2 2 2 1 1 2 1 1 1 1 2 2 1 1 1

IF 2013 9.267 8.167 6.24 5.481 5.323 4.250 3.952 3.875 3.499 3.485 3.482 3.118 3.163 3.035 2.386 2.174 2.021 1.809 1.804

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PUBLICATIONS Revues à Comité de lecture dans des revues indexées (ISI & Pubmed) 1. Bruneel O, Personné J-C, Casiot C, Leblanc M, Elbaz-Poulichet F, Mahler BJ, Le Flèche A, Grimont PAD (2003) Mediation of arsenic oxidation by Thiomonas sp. in acid mine drainage (Carnoulès, France). Journal of Applied Microbiology. 95, 492-499 2. Morin G, Juillot F, Casiot C, Bruneel O, Personné J-C, Elbaz-Poulichet F, Leblanc M, Ildefonse P, and Calas G (2003) Bacterial formation of tooeleite and mixed arsenic(III) or arsenic(V)-Iron(III) gels in the Carnoulès acid mine drainage, France. A XANES, XRD, and SEM study. Environmental Science and Technology. 37, 1705-1712 3. Casiot C, Morin G, Juillot F, Bruneel O, Personné JC, Leblanc M, Duquesne K, Bonnefoy V, Elbaz-Poulichet F (2003) Bacterial immobilization and oxidation of arsenic in acid mine drainage (Carnoulès creek, France). Water Research. 37, 2929-2936 4. Duquesne K, Lebrun S, Casiot C, Bruneel O, Personné J-C, Leblanc M, Elbaz-Poulichet F, Morin G, and Bonnefoy V (2003) Immobilization of arsenite and ferric iron by Acidithiobacillus ferrooxidans in acid mine drainage. Applied and Environmental Microbiology. 69, 6165-6173 5. Casiot C, Leblanc M, Bruneel O, Personné J-C, Koffi K, Elbaz-Poulichet F (2003) Geochemical processes controlling the formation of As-rich waters within a tailings impoundment. Aquatic Geochemistry. 9, 273-290 6. Casiot C, Bruneel O, Personné J-C, Leblanc M, Elbaz-Poulichet F (2004) Arsenic oxidation and bioaccumulation by the acidophilic protozoan, Euglena mutabilis, in acid mine drainage (Carnoulès, France). Science of the Total Environment. 320, 259-267 7. Mévelec MN, Bout D, Desolme B, Marchand H, Magne R, Bruneel O, Buzoni-Gatel D (2005) Evaluation of protective effect of DNA vaccination with genes encoding antigens GRA4 and SAG1 associated with GM-CSF plasmid, against acute, chronical and congenital toxoplasmosis in mice. Vaccine. 23, 4489-4499 8. Casiot C, Lebrun S, Morin G, Bruneel O, Personné JC, Elbaz-Poulichet F (2005) Sorption and redox processes controlling arsenic fate and transport in a stream impacted by acid mine drainage. Science of the Total Environment. 347, 122-30 9. Bruneel O, Duran R, Koffi K, Casiot C, Fourçans A, Elbaz-Poulichet F, Personné J-C (2005) Microbial diversity in a pyrite-rich tailings impoundment (Carnoulès, France). Geomicrobiology Journal. 22, 249 - 257 10. Bruneel O, Duran R, Casiot C, Elbaz-Poulichet F, Personné JC (2006) Diversity of microorganisms in Fe-As-rich acid mine drainage waters of Carnoulès, France. Applied and Environmental Microbiology. 72, 551-556 11. Casiot C, Pedron V, Bruneel O, Duran R, Personné J-C, Grapin G, Drakides C, ElbazPoulichet F (2006) A new bacterial strain mediating As oxidation in the Fe-rich biofilm naturally growing in a groundwater Fe treatment pilot units. Chemosphère. 64, 492-496 12. Bruneel O, Pascault N, Egal M, Bancon-Montigny C, Goni M, Elbaz-Poulichet F, Personné J-C, Duran R (2008) Archaeal diversity in a Fe-As rich acid mine drainage at Carnoulès (France). Extremophiles. 12, 563-571 13. Egal M, Elbaz-Poulichet F, Casiot C, Motelica-Heino M, Negrel P, Bruneel O, Nieto JM, Sarmiento AM (2008) Iron isotopes in acid mine waters and iron-rich solids from the Tinto-Odiel Basin (Iberian Pyrite Belt, Southwest Spain). Chemical Geology. 253, 162–171 11

14. Benzerara K, Morin G, Yoon TH, Miot J, Tyliszczak T, Casiot C, Bruneel O, Farges F, and Brown Jr GE (2008) Nanoscale study of As transformations by bacteria in an acid mine drainage system. Geochimica and Cosmochimica Acta. 72, 3949-3963 15. Casiot C, Egal M, Bruneel O, Cordier M-A, Bancon-Montigny C, Gomez E, Aliaume C, Elbaz-Poulichet F (2009) Hydrological and geochemical controls on metals and arsenic in a Mediterranean river contaminated by acid mine drainage (the Amous River, France); preliminary assessment of impacts on fish (Leuciscus cephalus). Applied Geochemistry. 24, 787-799 16. Egal M, Casiot C, Morin G, Parmentier M, Bruneel O, Lebrun S, Elbaz-Poulichet F (2009) Kinetic control on the formation of tooeleite, schwertmannite and jarosite by Acidithiobacillus ferrooxidans strains in an As(III)-rich acid mine water. Chemical Geology. 265, 432-441 17. Arsène-Ploetze F, Koechler S, Marchal M, Coppee J-Y, Chandler M, Bonnefoy V, Barakat M, Barbe V, Battaglia -Brunet F, Brochier-Armanet C, Bruneel O, G. Bryan C, Cleiss J, Heinrich-Salmeron A, Hommais F, Joulian C, Krin E, Lieutaud A, Lièvremont D, Michel C, Muller D, Ortet P, Proux C, Siguier P, Roche D, Rouy Z, Salvignol G, Slyemi D, Talla E, Weiss S, Weissenbach J, Médigue C, Bertin PN (2010) Structure, function and evolution of the Thiomonas spp. genome inferred from sequencing and comparative analysis. PLoS Genetics. 6 (2) e1000859 18. Egal M, Casiot C, Morin G, Elbaz-Poulichet F, Cordier MA Bruneel O (2010) An updated insight into the natural attenuation of As concentrations in Reigous Creek (southern France). Applied Geochemistry. 25, 1949–1957 19. Bruneel O, Volant A, Gallien S, Chaumande B, Casiot C, Carapito C, Bardil A, Morin G, Brown Jr GE, Personné JC, Le Paslier D, Schaeffer C, Van Dorsselaer A, Bertin PN, Elbaz-Poulichet F, Arsène-Ploetze F (2011) Characterization of the active bacterial community involved in natural attenuation processes in arsenic-rich creek sediments. Microbial Ecology. 61, 793-810 20. Bertin PN, Heinrich-Salmeron A, Pelletier E, Goulhen- Chollet F, Arsène-Ploetze F, Gallien S, Lauga B, Casiot C, Calteau A, Vallenet D, Bonnefoy V, Bruneel O, Chane-WoonMing B, Cleiss-Arnold J, Duran R, Elbaz-Poulichet F, Fonknechten N, Giloteaux L, Halter D, Koechler S, Marchal M, Mornico D, Schaeffer C, Thil Smith AA, Van Dorsselaer A, Weissenbach J, Médigue C and Le Paslier D (2011) Metabolic diversity between main microorganisms inside an arsenic-rich ecosystem revealed by meta- and proteo-genomics. The ISME Journal. 5, 1735-1747. Cet article a fait l’objet d’une note dans la revue Sciences (2011, vol 332, p1128) 21. Casiot C, Egal M, Bruneel O, Verma N, Parmentier M, Elbaz-Poulichet F (2011) Predominance of aqueous Tl(I) species in the river system downstream from the abandoned Carnoulès mine (Southern France). Environmental Science & Technology. 45, 2056-2084 22. Volant A, Desoeuvre A, Casiot C, Lauga B, Delpoux S, Morin G, Personné JC, Héry M, F Elbaz-Poulichet, Bertin P and Bruneel O (2012) Archaeal diversity: temporal variation in the Arsenic-Rich Creek Sediments of Carnoulès Mine, France. Extremophiles. 16, 645-657 23. Giloteaux L, Duran R, Casiot C, Bruneel O, Elbaz-poulichet F and Goñi-urriza M (2013) A survey of sulfate reducing bacteria in a heavily arsenic contaminated acid mine drainage (Carnoulès, France). FEMS Microbiol Ecol. 83 724–737 12

24. Maillot F, Morin G, Juillot F, Bruneel O, Casiot C, Ona-Nguema G, Wang Y, Lebrun S, Aubry E, Vlaic G, Brown GE Jr (2013) Structure and reactivity of As(III)- and As(V)-rich schwertmannites and amorphous ferric arsenate sulfate from the Carnoulès acid mine drainage, France: comparison with biotic and abiotic model compounds and implications for As remediation. Geochimica et Cosmochimica Acta. 104, 310-329 25. Resongles E, Casiot C, Elbaz-Poulichet F, Freydier R, Bruneel O, Piot C, Delpoux S, Volant A, Desoeuvre A (2013) Fate of Sb(V) and Sb(III) species along a gradient of pH and oxygen concentration in the Carnoulès mine waters (Southern France)". Environmental Science: Processes and Impacts. 15, 1536-1544 26. Adra A, Morin G, Ona-Nguema G, Maillot F, Casiot C, Bruneel O, Lebrun S, Juillot F, Brest J (2013) Arsenic Scavenging by Al-Substituted Ferrihydrites in a Circumneutral pH River Impacted by the Acid Mine Drainage of Carnoulès, Gard, France. Environmental Science and Technology. 47, 12784-12792 27 Héry M, Casiot C, Resongles E, Gallice Z, Bruneel O, Desoeuvre O, Delpoux S (2014) Release of arsenite, arsenate and methyl-arsenic species from streambed sediment impacted by acid mine drainage : a microcosm study. Environmental Chemistry. 11, 514-524 28 Volant A, Bruneel O, Desoeuvre A, Héry M, Casiot C, Bru N, Delpoux S, Fahy A, Javerliat F, Bouchez O, Duran R, Bertin PN, Elbaz-Poulichet F and Lauga B (2014) Diversity and spatiotemporal dynamics of bacterial communities: physicochemical and others drivers along an acid mine drainage. FEMS Microbiology Ecology. 90, 247-263 Publications soumises Doumas P, Munoz M, Banni M, Becerra S, Bruneel O, Casiot C, Cleyet-Marel J-C, Gardon J, Noak Y, Sappin-Didier V. Polymetallic pollution from abandoned mines in Mediterranean regions: a multidisciplinary approach of environmental risks. Soumis à Regional Environmental Change Publications en cours de soummission Idir Y, Sbabou L, Bruneel O, Filali-Maltouf A and Aurag J. Characterization of rootnodule bacteria isolated from Hedysarum spinosissimum L, growing in mining sites of Northeastern region of Morocco. Sera soumis à Environmental Science and Pollution Research

Publication dans des revues non indexées Casiot C, Héry M, and Bruneel O (2012) Pollution by mine drainage: towards biological treatment? In: Water at the Heart of Science. IRD Edition, Marseille Benyassine EM, Dekayir A, Héry M, Delpoux S, Desoeuvre A, Bruneel O, Benhassou H, Rouai M, Casiot C (2013) Contrasted arsenic speciation in two alkaline pit lakes from the abandoned Pb mining area of Zeida (Moulouya, Morocco). International Journal Clean-Soil, Air, Water. Special Focus Issue on Emerging Pollutants in Euro-Mediterranean and MENA Countries

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COMMUNICATIONS, CONFERENCES ET POSTER Communication orale (5 dernières années) Bruneel O, Casiot C, Personné J-C, Volant A, Vadapalli VRK, Petrik L, Cowan DA, Morin G, Duran R, and Elbaz-Poulichet F. Impact des microorganismes sur les transformations des métaux et métalloïdes dans des drainages miniers d’Afrique du Sud. Proceeding, réunion de restitution du programme Ec2co. Toulouse, France. 22-26 November 2010 Bertin PN, Heinrich-Salmeron A, Pelletier E, Goulhen- Chollet F, Arsène-Ploetze F, Gallien S, Lauga B, Casiot C, Calteau A, Vallenet D, Bonnefoy V, Bruneel O, Chane-WoonMing B, Cleiss-Arnold J, Duran R, Elbaz-Poulichet F, Fonknechten N, Giloteaux L, Halter D, Koechler S, Marchal M, Mornico D, Schaeffer C, Thil Smith AA, Van Dorsselaer A, Weissenbach J, Médigue C and Le Paslier D. Diversity of metabolic interactions inside an arsenic-rich microbial ecosystem revealed by meta- and proteo-genomics. BAGECO11, 11th Conference on Bacterial Genetics and Ecology. Corfu, Greece. 29 May - 2 June 2011 Morin G, Ona-Nguema G, Juillot F, Maillot F, Wang Y, Egal M, Bruneel O, Casiot C, Elbaz-Poulichet F, Calas G, Brown JR. How biogenic nano-iron oxides can control the fate of pollutants. Goldschmidt. Prague, République Tchèque. 14-19 août 2011 Casiot C, Delpoux S, Desoeuvre A, Volant A, Egal M, Resongles E, Hery M, Freydier R, Elbaz-Poulichet F, Cadot E, Gardon J, Bruneel O. Spéciation et processus de transfert de métaux et métalloïdes dans les eaux minières: exemple du site de Carnoulès dans le Gard. Premières rencontres du Réseau "Environnements Miniers Méditerranéens".Montpellier, France. 14-16 mai 2012 Bruneel O, Desoeuvre A, Volant A, Héry M, Casiot C, Delpoux S, Freydier R, Elbaz – Poulichet F. Impact des microorganismes sur le transfert des contaminants métalliques dans les environnements miniers. Premières rencontres du Réseau "Environnements Miniers Méditerranéens". Montpellier, France. 14-16 mai 2012 Casiot C, Bruneel O, Hery M, Delpoux S, Desoeuvre A, Volant A, Resongles E, Freydier R, Elbaz-Poulichet F. Speciation and transfer processes of metals /metalloids in mining water : exemple of studies at the Carnoulès mining site (Gard). 4th SPECIATION seminar; Biological, environmental and nuclear speciation. Montpellier, France. May 29-31, 2012 Bruneel O, Volant A, Dahmani I, Sbabou L, Navarro I, Héry M, Désœuvre A, Casiot C, Filali-Maltouf A. Study of diversity using next generation sequencing. 4ème Congrès de l'Association Marocaine de Microbiologie (AMM) et 16ème Congrès de l'Association Africaine pour la Fixation Biologique de l'azote (AABNF) sur le thème BIOFERSOL, Biofertilisation des sols et développement durable en Afrique. Maroc, Rabat. 03-07 novembre 2014 Dekayir A, Benyassine M, Casiot C, Hery M, Bruneel O, El Hachimi ML, Rouai M. Contamination des eaux de lacs de carrières de la mine abandonnée de Zeida (Maroc). Colloque SICMED. Tunisie, Tunis. 18-20 novembre 2014 Poster (5 dernières années) Bruneel O, Casiot C, Personné J-C, and Elbaz-Poulichet F. The Carnoulès mine (Gard, France). Generation of as-rich acid mine drainage and natural attenuation processes. 5ème

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Colloque International « Contamination Métallique : Impact sur l’Environnement, la Santé et la Société ». Oruro, Bolivie. 13-15th October 2010 Elbaz-Poulichet F, Casiot C, Bruneel O, Egal M, Morin G, Miot J, Benzerara K, Duran R, Goni-Urriza, M.; Giloteaux, L. Biologie, biominéraux et biotransformations dans les eaux acides minières – 3BIO. Colloque de restitution EC2CO. Toulouse, France. 23-25 novembre 2010 Bertin P.N., Heinrich-Salmeron A., Pelletier E., Goulhen- Chollet F., Arsène-Ploetze F., Gallien S, Lauga B, Casiot C, Calteau A, Vallenet D, Bonnefoy V, Bruneel O, Chane-WoonMing B, Cleiss-Arnold J, Duran R, Elbaz-Poulichet F, Fonknechten N, Giloteaux L, Halter D, Koechler S, Marchal M, Mornico D, Schaeffer C, Thil Smith AA, Van Dorsselaer A, Weissenbach J, Médigue C and Le Paslier D. Diversity of metabolic interactions inside an arsenic-rich microbial ecosystem revealed by meta- and proteo-genomics. Colloque Restitution ANR “Des molécules aux écosystèmes”. Montpellier France, 13-14th September 2011 Lauga B, Volant A, Bruneel O, Fahy A, Laoudi S, Casiot C, Nieto JM and Duran R. MIGRAMD : Microbial biogeography of Acid Mine Drainage: a study of genetic diversity and species diversity from an evolutionary perspective. Colloque FRB "Les Ressources Génétiques face aux nouveaux enjeux environnementaux, économiques et sociétaux". Montpellier, France. 21-22 September 2011 Lauga B, Volant A, Bruneel O, Fahy A, Laoudi S, Casiot C, Nieto M and Duran R. Microbial biogeography of Acid Mine Drainage: a study of specific diversity and molecular diversity, in Colloque Jacques Monod "Génomique écologique intégrative". Roscoff, France. 15-19 octobre 2011 Javerliat F, Volant A, Laoudi S, Bruneel O, Fahy A, Casiot C, Iniguez V, Nieto JM, Duran R and Lauga B. Microbial biogeography of Acid Mine Drainage: a study of genetic diversity and species diversity from an evolutionary perspective, Colloque Génomique Environnementale. Lyon, France. 28-30 November 2011 Volant A, Bruneel O, Desoeuvre A, Casiot C, Bru N, Delpoux S, Héry M, Javerliat F, Fahy A, Elbaz-Poulichet F, Duran R, Bertin P and Lauga B. Spatio-temporal dynamics of bacterial community in the very As-rich creek waters of Carnoulès mine, France. In Ecole Thématique Expert Génomique Environnementale. Aussois, France. 23-27 Avril 2012 Volant A, Bruneel O, Desoeuvre A, Casiot C, Bru N, Delpoux S, Héry M, Javerliat F, Fahy A, Elbaz-Poulichet F, Duran R, Bertin P and Lauga B. Spatiotemporal dynamics of bacterial community in the very As-rich creek waters of Carnoulès mine, France. ISME. Copenhague, Danemark, 19-24 August 2012 Benyassine EM, Dekayir A, Héry M, Delpoux S, Desoeuvre A, Bruneel O, Benhassou H, Rouai M, Casiot C.Contrasted arsenic speciation in two alkaline pit lakes from the abandoned Pb mining area of Zeida (Moulouya, Morocco). International Symposium On Emerging Pollutants in Irrigation Waters: Origins, Fate, Risks, and Mitigation. Tunisia : Hammamet.2528 November 2013

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V ACTIVITE DE RECHERCHE
PREAMBULE Lors de mon stage de DEA, effectué en 1997 au sein du CJF INSERM 93-09, Immunologie des Maladies Infectieuses (Tours), j’ai travaillé sur la vaccination génique contre la toxoplasmose en utilisant le gène SAG1. Suite à ce stage et désirant depuis longtemps faire de la coopération mais n’ayant pas trouvé d’opportunités en biologie, je suis partie 2 ans en tant que professeur des écoles en CE2, à Djibouti, dans le cadre d’une coopération civile d’aide au développement. Cette expatriation ayant été extrêmement enrichissante et afin de pouvoir trouver du travail plus facilement dans la coopération, j’ai entrepris, à mon retour en France en 2000, une formation plus appliquée, un DESS « Diagnostics, Prévention et Traitements en Environnement ». Déjà très intéressée par l’Institut de Recherche pour le Développement, j’ai effectué mon stage de fin d’étude de 6 mois en avril 2002 au laboratoire HydroSciences Montpellier, UMR 5569 (IRD, CNRS, Université de Montpellier 1 et 2). Ce stage a porté sur l’identification des microorganismes présents dans les eaux de drainage de la mine de Carnoulès (Gard) et sur l’isolement d’espèces actives sur l’arsenic et le fer. La finalité de ces travaux était, à terme, d’aider au développement de procédés passifs de bio-réhabilitation des effluents miniers et industriels en utilisant ces microorganismes. Très intéressée par ce sujet et par les potentialités d’application de ce travail, j’ai finalement poursuivi cette étude par une thèse au sein de cette même UMR. Après ma thèse, soutenue en avril 2004, j’ai été recrutée à l’IRD en octobre de la même année pour travailler sur l’implication des microorganismes dans les environnements miniers. Mon programme de recherche s’intitule : «Etude des processus microbiens et géochimiques de transfert des métaux et métalloïdes issus des activités minières».

L'écologie microbienne suscite un engouement très important car les microorganismes, bien qu’invisibles à l’œil nu, sont essentiels à la vie sur terre. Ces microorganismes catalysent en effet les transformations uniques et indispensables aux cycles biogéochimiques de la biosphère de part leurs activités métaboliques. Ils produisent les composants essentiels de la planète et représentent le plus grand réservoir de nutriments terrestre, comme le nitrogène et le phosphore et séquestrent également environ 50% du carbone total des organismes vivants (Whitman et al., 1998). Ils sont également les principaux recycleurs de matières en décomposition, rendant disponible différents types de composés sous forme organique, permettant ainsi la survie et le fonctionnement des écosystèmes (Whitman et al., 1998 ; Falkowski et al., 2008). Parce que les microorganismes sont présents dans les 3 domaines du vivant (Archaea, Bacteria et Eukarya) et qu’ils représentent les groupes les plus diversifiés d’organismes sur Terre, une connaissance de leur diversité est primordiale pour la compréhension du fonctionnement des écosystèmes et des processus planétaires (Pace, 1997 ; Behnke et al., 2011).

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L'exploitation minière est vitale pour l'économie mondiale, mais l'extraction des composés métalliques génère de grandes quantités de déchets. Actuellement, le volume est estimé à plusieurs milliers de millions de tonnes par an, mais est en augmentation exponentielle en raison de la demande qui ne cesse de croître et de l'exploitation de gisements de faibles teneurs (Hudson-Edwards and Dold, 2015). En l’absence d’une gestion extrêmement rigoureuse des sites miniers, ces derniers sont une source de nuisance importante, en raison de la présence de composés très toxiques comme le plomb, l’arsenic ou le mercure Leur accumulation tout au long de la chaîne alimentaire génère des problèmes importants pour la végétation, la santé animale et humaine. Lorsque des minéraux sulfurés sont présents dans ces déchets, ils peuvent former, en présence d’eau et d’oxygène, des effluents acides, riches en métaux et métalloïdes, appelés Drainages Miniers Acides (DMA) (Langmuir, 1997). Ces drainages de mine sont considérés comme l’une des plus importantes et pernicieuses forme de pollution des eaux provenant de l’activité minière à travers le monde et représentent d’importants impacts environnementaux et sociaux économique (Hallberg, 2010) avec des coûts de traitements estimés à plusieurs milliards de dollars. Même s’il est très difficile d’estimer l’impact des DMA à travers le monde, il a été suggéré que plus de 12 000 km de cours d’eau étaient touchés par les DMA rien qu’au Royaume Uni (Hallberg, 2010). Le problème de ces DMA est leur potentiel de menace à long terme, avec une production généralement étalée sur des dizaines, voire des centaines d’années après la fermeture des mines (Younger, 1997 ; Hallberg, 2010). Bien que ces milieux soient très hostiles en raison des conditions extrêmes de vie en termes de pH et de concentration en métaux et métalloïdes toxiques, de nombreux microorganismes (Bactéries, Archaea et Eucaryotes), naturellement présents, sont capables de s’y développer (Baker and Bandfiel, 2003 ; Jonhson and Hallberg, 2003). Ces microorganismes adaptés jouent un rôle essentiel car ils sont impliqués dans les mécanismes biogéochimiques contrôlant le comportement des métaux et métalloïdes, qui sont présents dans l’environnement sous différentes formes chimiques qui n’ont ni la même toxicité, ni la même mobilité. Les réactions d’oxydoréduction ou de méthylation sont généralement très lentes et nécessitent la plupart du temps une catalyse qui est bien souvent assurée par les microorganismes. Par exemple, le rôle clé de l’activité des microorganismes (et notamment ceux qui oxydent le fer) est connu depuis longtemps dans les réactions d’oxydation de la pyrite à l’origine de l’apparition des DMA (Edwards et al., 2000a ; Sand et al., 2001 ; Vera et al., 2013). Selon certains auteurs, l’activité microbienne serait à l’origine d’environ 75% de la production des DMA (Edwards et al., 2000b ; Baker and Banfield, 2003). Ces mêmes organismes qui oxydent le fer sont également susceptibles de promouvoir, dans l’eau, la formation d’oxydes de fer qui favorisent l’immobilisation des métaux en les coprécipitant ou en les adsorbant (Johnson and Hallberg, 2003, 2005 ; Johnson, 2014). Les bactéries sulfato-réductrices sont aussi capables d’immobiliser des métaux en favorisant la précipitation directe de sulfures métalliques généralement insolubles (Johnson and Hallberg, 2005). De plus, certains processus métaboliques vont également modifier la mobilité de l’élément toxique et/ou sa toxicité. Par exemple, la forme oxydée As(V) produite par Thiomonas sp. est considérée comme 60 fois moins toxique pour les organismes supérieurs que la forme réduite As(III) à pH acide. Ces quelques exemples illustrent le rôle des microorganismes dans les processus de

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précipitation, complexation, adsorption, remise en solution et la distribution des différentes formes chimiques en solution. De plus, les stériles miniers sont généralement constitués de particules très fines facilement transportées par la pluie et le vent, polluants les terres agricoles, les cours d’eau ou les puits environnants et générant un problème de santé publique majeur pour les populations alentours (Mendez and Maier, 2008). Depuis une quinzaine d’années, des travaux se sont intéressés à l’utilisation de plantes pour limiter l’impact de cette pollution ; les déchets pouvant être immobilisés par la mise en place d’un couvert végétal (phytostabilisation) ou être accumulés dans les tissus végétaux (phytoextraction, Ma et al., 2011). Alors que l'établissement d'un couvert végétal sur ces déchets minier reste un défi, les microorganismes peuvent fortement accélérer le processus de phytostabilisation en influençant la croissance des plantes grâce à différents mécanismes (fixation d’azote, solubilisation du phosphate, production de phytohormones, etc., Rajkumar et al., 2012). Ils peuvent aussi intervenir directement sur la mobilisation/immobilisation des métaux et métalloïdes dans le sol (production de sidérophores, d’enzymes, etc. ou transformation rédox de ces éléments (Ma et al., 2011 ; Rajkumar et al., 2012). Les microorganismes jouent ainsi un rôle primordial dans ces environnements. Leur connaissance présente donc un intérêt fondamental majeur pour la gestion et la remédiation des sites contaminés. Mon programme de recherche s’inscrit dans le cadre de l’axe 1 (Biogéochimie, Contaminant, Santé) de l’UMR HydroSciences Montpellier qui aborde les questions de pollution et de toxicité pour les écosystèmes aquatiques. Cet axe s’intéresse également aux aspects de bioréhabilitation et de recyclage des eaux. L’étude des pollutions d’origine minière a commencé il y a maintenant une 20aine d’années au laboratoire. D’abord principalement centrée sur les aspects purement géochimiques puis microbiologiques, cette équipe s’intéresse maintenant également à l’impact de ces polluants métalliques sur la santé grâce au recrutement d’un médecin et d’une géographe épidémiologiste. Au sein de cette équipe, je m’intéresse à la partie microbiologie et principalement au rôle des microorganismes dans le transfert des polluants inorganiques. Ce travail inclut à la fois de la microbiologie classique par isolement mais aussi de la biologie moléculaire et maintenant de la génomique. L’équipe de microbiologie comprend actuellement une Assistante Ingénieure depuis 2010 ainsi qu’une maître de conférences recrutée en janvier 2011.

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TRAVAUX ANTERIEURS J’ai commencé ma première activité de recherche en 1997 au sein du CJF INSERM 93-09, Immunologie des Maladies Infectieuses (Tours), à l’occasion de mon stage de DEA sur la vaccination génique contre la toxoplasmose en utilisant le gène SAG1. La toxoplasmose est une maladie infectieuse très répandue qui touche les animaux à sang chaud dont l’Homme en raison de la présence d’un parasite protozoaire, Toxoplasma gondii. Généralement bénigne chez l’homme et asymptomatique dans 90% des cas, ce parasite peut menacer la vie lors d’une immunodépression ou peut avoir de graves conséquences pour le fœtus lors de la contamination d’une femme pendant la grossesse (primo-infection) en raison de la transmission transplacentaire du parasite. Durant mon stage, des essais vaccinaux, utilisant de l’ADN codant une des protéines de Toxoplasma gondii, le gène SAG1 (vaccination à ADN), ont été réalisés chez la souris qui présente des formes de toxoplasmose très proches de la toxoplasmose humaine. Cette étude a montré une bonne réponse du système immunitaire de la souris avec la production d’anticorps mais un taux de survie très faible lors de l’immunisation intramusculaire1.

Depuis mon stage de DESS en avril 2001, je m’intéresse à l’implication des microorganismes dans les biotransformations et processus de transfert des métaux et métalloïdes dans les drainages miniers acides. Ce programme de recherche a pour objectif de mieux comprendre les processus biogéochimiques qui contrôlent les transferts de métaux et métalloïdes, en particulier l’arsenic, et d’étudier de manière pluridisciplinaire et intégrée le fonctionnement de ces environnements extrêmes. Il se situe en effet à l’interface de la microbiologie, de la géochimie, mais également de l’hydrogéologie et de la minéralogie. En microbiologie, pour l’étude du chantier de Carnoulès, ce programme de recherche fédère différentes compétences apportées par plusieurs équipes d’autres laboratoires comme la métagénomique ou la métaprotéomique (collaboration étroite avec l’EEM de Pau (R. Duran, B. Lauga) et le laboratoire GMGM de Strasbourg (P. Bertin, F. Ploetze) ou la minéralogie (partenariat avec G. Morin, IMPMC, IPGP de Paris). Ces recherches incluent également la caractérisation physicochimique approfondie de ces environnements extrêmes par les chimistes du laboratoire (C. Casiot, F. Elbaz-Poulichet, MA. Cordier puis S. Delpoux). Ces approches combinées permettent d’obtenir une vision globale et intégrée des processus complexes qui conditionnent les interactions entre les microorganismes et leur environnement.

1

Mévelec MN, Bout D, Desolme B, Marchand H, Magne R, Bruneel O, Buzoni-Gatel D (2005) Evaluation of protective effect of DNA vaccination with genes encoding antigens GRA4 and SAG1 associated with GM-CSF plasmid, against acute, chronical and congenital toxoplasmosis in mice. Vaccine. 23, 4489-4499

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Introduction à l’étude des drainages miniers acides L’intérêt pour l’étude de ces écosystèmes extrêmes est multiple. Comme nous l’avons vu, ces microorganismes présentent tout d’abord un grand intérêt pour la gestion des déchets miniers et leur connaissance est primordiale pour mieux gérer leurs impacts sur l’environnement et est également critique pour pouvoir continuer l’exploitation des ressources minérales, dont la demande ne cesse de croitre à travers le monde (Hallberg, 2010). Les microorganismes qui peuplent ces écosystèmes extrêmes sont généralement constitués de communautés simplifiées par rapport aux environnements plus hospitaliers (Tyson et al., 2004 ; Denef et al., 2010). Ceci est dû notamment aux pressions de sélection qu’impose l’adaptation des microorganismes à ces environnements, ainsi que par le nombre limité de sources d’énergie disponible dans le milieu (Baker and Banfield, 2003). Ces environnements sont donc colonisés par des espèces dites spécialistes, généralement peu abondantes, ce qui en font d’excellents modèles pour étudier la dynamique des microorganismes dans le temps et/ou l’espace, d’identifier les paramètres qui les gouvernent, d’étudier leurs capacités d’adaptation, de mieux comprendre leurs interactions et d’explorer les fonctions qu’elles exercent (Denef et al., 2010). Les DMA représentent également des habitats fragmentés, qui possèdent chacun des conditions physicochimique (T°, pH, concentration en oxygènes) et/ou des concentrations en métaux et métalloïdes différents, permettant ainsi d’aborder des questions particulières de biogéographie (Hallberg, 2010 ; Kuang et al., 2012). L’étude de la diversité de ces environnements extrêmes suscite également un intérêt important du fait que ces écosystèmes peuvent représenter un réservoir de nouvelles biomolécules ayant un intérêt biotechnologique. Enfin, les similarités qui existent entre la minéralogie de ces environnements, comme celui du Rio Tinto en Espagne, et de la planète Mars (vaste dépôts de sulfates et d’oxydes de fer) ont conduit à l’idée que les propriétés de ces acidophiles pourraient être similaires à ceux susceptibles d’être retrouvés sur Mars (Amils et al., 2007). Parmi les éléments toxiques des DMA, l’arsenic pose un problème particulier parce qu’il est fortement assimilable par les organismes vivants du fait que ses propriétés chimiques sont très voisines de celles du phosphore et du soufre, qui sont des éléments essentiels à la vie (Yammura and Amachi, 2014). Chez l’être humain, il est toxique et induit de nombreuses pathologies dont des cancers et ne devrait pas dépasser 10 µg.l-1 selon l’OMS (Yamanaka et Okada, 1994 ; McClintock et al., 2012 ; Jiang et al., 2013). L’arsenic présent dans l’eau de boisson représente un problème mondial majeur qui touche plusieurs millions de personnes, en particulier au Bangladesh où 35-77 millions de personnes sont concernés (Nordstrom, 2000; Argos et al., 2010 ; Yunus et al., 2011) mais cela touche également de nombreux pays comme les Etats-Unis, la Chine, le Mexique, l’Espagne ou le Canada, etc. (Jiang et al., 2013). Malgré sa faible abondance dans la croûte terrestre (0.0001%), il est largement distribué dans l’environnement où il est souvent associé avec les minerais métalliques sulfurés comme le cuivre, le plomb ou l’or, etc. (Oremland and Stolz, 2003). Dans les sols, il est généralement retrouvé à des concentrations inférieures à 15 mg.kg-1 (Yammura and Amachi, 2014). Bien que l’arsenic existe sous 4 états d’oxydation différents (V, III, 0, -III) avec une multitude de formes organiques et inorganiques, l’arséniate (As(V)) et l’arsénite (As(III) sont les formes inorganiques prédominantes dans l’environnement (Ormeland and Stolz, 2005), avec l’As(III) considéré comme plus toxique que l’As(V) (Lièvremont et al., 2009 ; Yammura 20

and Amachi, 2014). L’As(V) est généralement présent sous forme d’oxyanions chargés négativement (H2AsO4-/ HAsO42-) à pH modéré et a ainsi tendance à être fortement adsorbé sur la surface de nombreux minéraux chargés positivement, comme les oxydes et hydroxydes de fer et d’aluminium. L’As(III) est quand à lui généralement présent sous une forme non chargée (H3AsO30) dans l’environnement et est donc habituellement moins adsorbé et donc plus mobile que l’As(V) (Yammura and Amachi, 2014). Dans les environnements aérobies, l’As(V) est souvent la forme prédominante alors qu’en conditions anoxiques, c’est la forme As(III) qui prédomine. Certains microorganismes ne sont pas seulement résistant à l’As mais le métabolisent activement via des réactions de méthylation, déméthylation, oxydation ou réduction, modifiant ainsi les formes redox de l’As et utilisant certaines de ces étapes pour générer de l’énergie (Oremland and Stolz, 2005 ; Stolz et al., 2010). A ce jour, de nombreux microorganismes, principalement des bactéries capables d’oxyder ou de réduire l’As, ont été isolés d’environnements contaminés par l’arsenic (Oremland and Stolz, 2003 ; Lièvremont et al., 2009). La réduction de l’arséniate comprend une voie de détoxification (gène arsC) ainsi que la respiration (gènes arrA/B). L’organisation de l’opéron ars varie fortement entre les taxons et les gènes de base inclus arsR, arsB et arsC tandis que arsD et arsA peuvent également parfois être trouvés (Oremland and Stolz, 2003). Les gènes arrA/B codent une enzyme réductase active durant la respiration anaérobie, utilisant l’As(V) comme accepteur final d’électron (Costa et al., 2014). L’oxydation microbienne de l’As(III), décrite pour la première fois en 1918, peut être médiée par 2 enzymes distinctes, Aio (comprenant gènes aox, aso et aro) très étudié et Arx récemment décrite par Zargar et al. (2012). L’oxydation aérobie de l’As(III) est catalysée par une arsénite oxidase qui utilise l’O2 comme accepteur terminal d’électrons et qui est codée par les gènes aioB/A (Lett et al., 2012 ; Costa et al., 2014). ArxAB est détectée chez des bactéries oxydant As(III) en conditions anoxiques, où la réduction du nitrate ou du chlorate est couplée à l’oxydation de l’As(III) (Oremland et al., 2009 ; Sun et al., 2010 ; Costa et al., 2014). Certains membres du genre Ectothiorhodospira sont également capables d’utiliser l’As(III) comme donneur d’électrons pour la croissance phototrophe anoxygénique (Kulp et al., 2008). Parce que ces processus de réduction d’As(V) ou d’oxydation d’As(III) affectent directement la spéciation et la mobilité de l’As, l’activité microbienne joue un rôle clé dans les cycles biogéochimiques de ce métalloïde et peuvent être utilisés pour dépolluer les sols et les eaux pollués par l’arsenic (Yammura and Amachi, 2014 ; Costa et al., 2014 ; Sarkar et al., 2014).

L’ancien site minier de Carnoulès a constitué pour le laboratoire HydroSciences un cadre privilégié pour l’étude des interactions entre les microorganismes et les polluants métalliques et notamment l’arsenic (Leblanc et al., 1996). L’intérêt dans ce site réside également dans le fait qu’un système de remédiation naturel est présent où, près de 99% de l’arsenic va précipiter et être piégé dans des minéraux de fer le long des 1,5 km du Reigous, petit ruisseau alimenté par les drainages miniers acides du stérile de Carnoulès (Leblanc et al., 1996). Enfin, la proximité géographique de ce site avec le laboratoire HydroSciences est un facteur non négligeable étant donné les nombreux allers-retours nécessaires pour étudier cet environnement sur le long terme. Ce site atelier est, depuis 2009, un site d’observation de 21

l’Observatoire des Sciences de l’Univers OREME (tâche d’observation intitulé « Suivi des processus hydrobiogéochimiques de transfert des métaux et métalloïdes issus des activités minières sur le site de Carnoulès »). Les connaissances acquises sur ce site avec mes collègues du laboratoire HSM, M. Leblanc, (géologue), J.-C. Personné puis A. Desoeuvre (AI depuis 2010) et M. Héry en 2011 (microbiologistes) ; F. Elbaz-Poulichet et C. Casiot (géochimistes) en association avec G. Morin (minéralogiste à l’IMPMC, Paris) et en collaboration avec 2 laboratoires de microbiologie, l’EEM de Pau (R. Duran, B. Lauga) puis le laboratoire GMGM de Strasbourg (P. Bertin, F. Ploetze) ont permis de mieux comprendre cet écosystème et ont ainsi contribué à fédérer différents groupes de recherches sur ce site.

Description du site minier de Carnoulès La mine de Carnoulès est située dans les Cévennes dans le Sud de la France et a été définitivement fermée en 1962.

Figure 1. Localisation et carte du site minier de Carnoulès. D’après Bruneel et al., 2005 22

Au Sud-Est du Massif Central, le long des Cévennes, un horizon conglomératique de 3 à 5 m d’épaisseur contenant de la marcasite (et/ou de la pyrite), de la galène, de la barytine et accessoirement de la sphalérite, des sulfo-arséniures (proustite, arsénopyrite) et des sulfure d’antimoine (freibergite) est présent au niveau de la mine de Carnoulès (Leblanc et al., 1996). Le gisement de 2.5 Mt contenait 3.5% Pb et 0.8% Zn et a été principalement exploité à ciel ouvert puis définitivement abandonné en 1962. Le stérile actuel, d’environ 1.2 Mt qui est confiné derrière une digue, comporte les déchets d’après traitement qui contiennent encore environ 0.7% de Pb et 10% de sulfure de Fe, (Leblanc et al., 1996).

Figure 2. Schéma simplifié du dépôt de stériles miniers de Carnoulès avec en (a) la localisation du forage instrumenté, des carottages réalisés sur le site (T1, T4) et du système de drainage et en (b) une coupe dans le dépôt montrant les différents horizons, la couverture d’argile en surface, les sables gris fins et riches en pyrite, les sables grossiers et le socle composé de quartzites du Trias (b). D’après Casiot et al., 2003a

Ce stérile a une superficie de 5500 m2 et une épaisseur de 10 à 24 m. Il est recouvert d’une couche d’argile de 0.3 m d’épaisseur. En dessous, il est constitué majoritairement de sables à pyrite contenant 75% de quartz et entre 5 et 15 % de pyrite qui contient de 1 à 4% d’As. Les minéraux secondaires incluent le K-feldspath, la biotite, la barytine et la galène (Alkaaby et al., 1985). Ces matériaux sont généralement très fins (taille moyenne des grains de 30 µm) et peu perméables, excepté près du fond où une couche de 2 à 3 mètres d’épaisseur contient du matériel ferrugineux relativement grossier (200 µm) (Koffi et al., 2003). L’oxydation des sulfures est limitée dans la partie supérieure du dépôt, contrairement à ce qui est généralement constaté dans d’autres stériles miniers et est probablement dû à la présence d’une couverture argileuse peu perméable et à la faible conductivité hydraulique du matériau qui limite l’infiltration des eaux de pluie (Koffi et al., 2003). Dans la partie inférieure du dépôt au contraire, les sulfures sont partiellement oxydés en liaison avec la présence d’un drain et la circulation d’eaux à la base du stock, dans une zone à matériaux plus grossiers très probablement en raison de la présence de sources enterrées présentes sous le stérile (Koffi et 23

al., 2003). Le niveau de l’eau se situe entre 1 et 10 m sous la surface en fonction de la localisation dans le stérile et de la saison. L’eau qui circule dans le stock de déchet donne naissance au ruisseau du Reigous dont la source apparaît à la base de la digue qui retient les déchets. La masse d’arsenic contenu dans ce stock de stériles est estimée à 3000 t. Compte tenu de la masse annuelle d’As rejetée par la source acide (6 t), la durée de vie du système est estimée à au moins 500 ans (Leblanc et al., 2002). Les études physicochimiques ont montré que le débit à la source est relativement faible (0.2 à 1 l.s-1) mais ces eaux coulent toute l’année. Elles sont pratiquement anoxiques à la source mais en quelques dizaines de mètres, on observe une augmentation de la concentration en oxygène. Les flux annuels d’arsenic, calculés au cours de 2 années hydrologiques aux caractéristiques différentes, varient de 2 à 6 t. Les concentrations en As diminuent rapidement en aval, juste avant le confluent avec l’Amous, elles sont en moyenne de 6 mg.l-1 avec de très fortes variations saisonnières (Leblanc et al., 1996). Ces diminutions sont à attribuer en partie à des dilutions avec de petits rus latéraux mais surtout à la précipitation de l’arsenic et à la formation de sédiments riches en fer et en arsenic. Les variations saisonnières du système du Reigous sont fortement marquées : en période d’étiage, les sédiments arséniés s’accumulent mais, en période de fortes pluies (printemps, automne), les sédiments sont érodés et transportés, entraînant une forte augmentation du flux d’arsenic avec un transport essentiellement sous forme particulaire (Leblanc et al., 2002).

A mon arrivée au laboratoire HydroSciences dans le cadre de mon stage de DESS en 2002, les travaux de Leblanc et al. (1996) avaient permis de mettre en évidence à Carnoulès, dans le ruisseau du Reigous qui draine le site, la formation de précipités contenant près de 20% d’arsenic autour de structures bactériennes, mais les processus géochimiques et microbiologiques à l’origine de la formation de ces solides n’étaient pas connus. Durant ce stage, sous l’encadrement de Jean Christian Personné, j’ai isolé une vingtaine de colonies bactériennes dans les eaux du stock de déchets miniers ainsi que dans les eaux le long du Reigous et j’ai commencé leurs études en laboratoire et en particulier, leurs activités sur l’oxydation du fer et de l’arsenic. La grande majorité de ces souches ont été identifiées comme étant des bactéries des genres Thiomonas et Acidithiobacillus ferrooxidans. Ce travail a permis de décrire plusieurs souches de Thiomonas et de montrer pour la première fois que des souches pures de Thiomonas étaient capables d’oxyder l’arsenic2.

Suite à ce travail, j’ai débuté en décembre 2002 une thèse intitulée « Contribution à l'étude des mécanismes couplés géochimiques et bactériologiques de transfert de la pollution minière sur le site de Carnoulès (Gard) » sous l’encadrement de Jean Christian Personné et de François Elbaz Poulichet, ma directrice de thèse. Bien qu’apportant des informations très 2

Bruneel O, Personné J-C, Casiot C, Leblanc M, Elbaz-Poulichet F, Mahler BJ, Le Flèche A, Grimont PAD. (2003) Mediation of arsenic oxidation by Thiomonas sp. in acid mine drainage (Carnoulès, France). Journal of Applied Microbiology. 95, 492-499

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intéressantes sur le métabolisme des souches isolées, les techniques classiques d’isolement de souches pures et la caractérisation de leurs activités en laboratoire ne permettent pas de comprendre un écosystème étant donné que près de 99% des organismes ne peuvent être pour l’instant isolés par des approches culturales (Rappé and Giovannoni, 2003). J’ai donc rapidement été amenée à travailler avec le Laboratoire d’Ecologie Moléculaire (R. Duran, EA 3525, Ecologie Moléculaire Microbiologie de l’Université de Pau) pour mettre en œuvre une approche moléculaire qui n’était pas disponible, à l’époque, au Laboratoire HydroSciences.

Processus de génération du drainage minier acide riche en As de Carnoulès Les eaux de drainage de mines sont générées par l’exposition des minerais sulfurés, telles que la pyrite (FeS2) à l’oxygène et à l’eau (Johnson and Hallberg, 2003 ; Vera et al., 2013). De nombreux métaux sont présents sous forme de minerais sulfurés, comme la galène (PbS) ou la sphalérite et sont également souvent associés à la pyrite qui est le minerai sulfuré le plus commun. Le fer ferrique (Fe(III)) est le principal oxydant des minerais sulfurés (Baker and Banfield, 2003) : FeS2 + 14 Fe3+ + 8 H2O → 15 Fe2+ + 2 SO42− + 16 H+ La régénération du Fe(III), selon l’équation ci-dessous, est l’étape limitante de l’oxydation des minerais et nécessite de l’oxygène (Singer and Stumm, 1970) : 14Fe2+ + 3.5 O2 + 14H+ → 14Fe3+ + 7H2O A pH supérieur à 4, l’oxydation du fer ferreux se produit chimiquement en présence d’oxygène ou biologiquement mais à des pH inférieures à 4, le taux d’oxydation chimique est très lent, voir négligeable et c’est l’activité des microorganismes oxydant le fer qui va avoir un rôle pivot dans la génération des DMA (Baker and Bandfield, 2003 ; Vera et al., 2013). De plus, en raison des faibles pH rencontrés dans ces environnements (jusque -3 comme dans la mine de Richmond aux Etats Unis (Californie, Nordstrom et al 2000), la solubilité des métaux est plus importante et les DMA contiennent donc généralement de très fortes concentrations en métaux et métalloïdes qui vont varier en fonction de la minéralogie de la roche d’origine (Hallberg, 2010). Des études réalisées au sein du piézomètre S5, situé approximativement au centre du stérile minier en 2001 et 2002, ont montré de très fortes variations de la chimie sur une année qui semblaient être liées au niveau de la nappe et aux concentrations en oxygène dissous 3. En période de remontée de la nappe, le niveau d’oxygène est très élevés (7-9 mg.l-1), le pH est acide (1.8), et de très fortes concentrations de fer (proche 20000 mg.l-1) et d’As (jusque 12000 mg.l-1, concentrations parmi les plus importantes au monde) ont été relevées avec les espèces oxydantes qui dominent (As(V) et Fe(III)). Ces teneurs très élevées ont été attribuées à la dissolution de phases secondaires, en particulier des hydroxysulfates de fer contenant jusque 10% d’As, présents dans le stock de déchets. A l’inverse, lorsque le niveau de la nappe diminue et que le milieu devient pratiquement anoxique (DO = 0.5 mg.l-1), le pH remonte autour de 4 et les concentrations en As et en Fe diminuent fortement et se stabilisent (autour 3

Casiot C, Leblanc M, Bruneel O, Personné J-C, Koffi K, Elbaz-Poulichet F (2003) Geochemical processes controlling the formation of As-rich waters within a tailings impoundment. Aquatic Geochemistry. 9, 273-290

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de 3000 mg.l-1 pour Fe et 750 mg.l-1 pour As) avec As et Fe principalement sous forme réduite As(III), Fe(II). Dans le cadre de ma thèse et pour tenter de mieux comprendre la génération de ces eaux acides et riches en métaux ainsi que les variations associées, j’ai initié l’étude des bactéries présentes par des approches moléculaires ciblant l’ARNr 16S par les techniques de clonageséquençage. Ces analyses nous ont permis de mettre en évidence que la diversité était faible comparée à des eaux non polluées avec un total de 5 taxons identifiés ici4. Table 1. Inventaire des fragments d’ADNr 16S des clones présents en octobre 2001 (S5Oct) et janvier 2002 (S5Jan) dans les eaux du stock de déchets miniers, groupés selon l’analyse RFLP et l’analyse phylogénétique. D’après Bruneel et al., 2005

Ce travail a également montré que ce sont curieusement des groupes proches des bactéries sulfato-réductrices (BSR, Desulfosarcina variabilis) qui dominent et ceci principalement lorsque les concentrations en oxygène sont élevées et le pH très bas alors que ces bactéries sont pourtant connues pour préférer les conditions anoxiques. En octobre, quand le taux d’oxygène est faible, on trouve des organismes dont les séquences sont affiliées à Desulfosarcina variabilis (représentant environ 27% du nombre total de clones) associés à des séquences apparentées à Acidithiobacillus ferrooxidans, Thiobacillus et Acidimicrobium alors qu’en janvier, lorsque les conditions sont très oxygénées et le pH très acide, la communauté bactérienne est composée essentiellement de Desulfosarcina variabilis (représentant environ 95%) associée à Acidithiobacillus ferrooxdians et Thiobacillus spp.

4

Bruneel O, Duran R, Koffi K, Casiot C, Fourçans A, Elbaz-Poulichet F, Personné J-C (2005) Microbial diversity in a pyrite-rich tailings impoundment (Carnoulès, France). Geomicrobiology Journal. 22, 249 - 257

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Etude du système de remédiation présent sur le site de Carnoulès Contrairement aux composés organiques qui peuvent être dégradés en composés simples et sans risque pour la santé comme le CO2 ou l’H2O du fait de leur minéralisation, la remédiation des métaux et métalloïdes implique seulement leur retrait de la solution dans le milieu aquatique (Bahar et al 2013). Cette remédiation de l’eau est due à des réactions biotiques et abiotiques qui font que ces composés toxiques deviennent insolubles et précipitent, s’accumulant dans des sédiments composés généralement d’une variété d’(oxyhydr)oxydes et d’hydroxysulfates de fer tel que la jarosite, la schwertmannite ou la ferrihydrite (Johnson and Hallberg, 2005; Johnson, 2014). Ces processus de précipitation résultent en grande partie de l’oxydation et de la précipitation du fer, qui est souvent le principal métal soluble présent dans le DMA, et de l’adsorption d’autres métaux et métalloïdes comme le Pb, l’U ou As sur les minéraux sulfurés formés (Hallberg, 2010). Comme l’oxydation abiotique du Fe(II) est un processus très lent dans les eaux acides, les microorganismes oxydants le fer qui catalysent ces réactions jouent un rôle pivot dans les processus de remédiation (Rowe and Johnson, 2008; Hallberg, 2010; Johnson, 2014). A Carnoulès, les études de Leblanc et al. (1996, 2002) avaient révélé la présence d’un système de remédiation naturel efficace dans les eaux du Reigous qui permettait de limiter les concentration de l’As en aval du système. Pour identifier les processus chimiques et microbiologiques qui influencent le transfert de l’As dans le Reigous, des échantillons d’eau ont été prélevés lors de 8 campagnes de prélèvements en 2001. Les stations de prélèvement étaient situées dans les 30 premiers mètres du ruisseau où aucun apport latéral d’eau n’avait été observé.

Figure 3. Coupe montrant la localisation des stations de prélèvements dans les 30 premiers mètres du ruisseau du Reigous (1, A, C, E, F, 2). Le temps d’écoulement des eaux entre les stations 1 et 2 est d’environ 1 heure. D’après Casiot et al., 2003b

Les analyses physicochimiques réalisées dans le ruisseau du Reigous qui draine le site ont montré que l’arsenic en solution est essentiellement sous forme réduite (As(III)) à la source du Reigous5. Sur les 30 premiers mètres, 20 à 60% de l’arsenic coprécipite en liaison avec 5

Casiot C, Morin G, Juillot F, Bruneel O, Personné JC, Leblanc M et al. (2003b) Bacterial immobilization and oxidation of arsenic in acid mine drainage (Carnoulès creek, France). Water Res. 37, 2929-2936

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l’oxydation du Fe(II) en Fe(III). Les formes méthylées sont absentes. Le taux de précipitation est variable selon les saisons. Il semble plus important pendant la saison humide lorsque la teneur en oxygène dans les eaux à la source est plus élevée. Pour tenter de mieux comprendre ce système de remédiation, des études moléculaires combinées (comprenant des analyses de clonage et séquençage par la méthode de Sanger ainsi que des analyses t-RFLP) ont été réalisées afin d’identifier les communautés bactériennes présentes6. Table 2. Inventaire des fragments d’ADNr 16S des clones présents dans les eaux du ruisseau du Reigous groupés selon l’analyse RFLP et l’analyse phylogénétique. D’après Bruneel et al, 2006

a

abondance relative des clones dans chaque librairies

Ces analyses ont montré, comme au sein du stérile, une diversité faible avec l’identification de 2 à 4 taxons par échantillons. De plus, comme attendu en raison de la chimie de l’eau, les résultats ont mis en évidence que les eaux du ruisseau acide étaient largement dominées par des bactéries impliquées dans le cycle du fer et du soufre. Les séquences affiliées à la bactérie neutrophile qui oxyde le Fe, Gallionella ferruginea, sont largement dominante. Cette bactérie pourrait jouer un rôle important dans la remédiation naturelle observée dans le ruisseau acide en immobilisant l’As par coprécipitation avec le Fe(III). La structure et la spéciation de l’As dans les sédiments du Reigous ont été également caractérisées par des analyses spectroscopiques et minéralogiques (XRD, XANES et SEM)7. Cette étude a mis en évidence des variations spatiales et temporelles des précipités formés dans le ruisseau. Pendant la saison humide, les précipités présents dans les 10 premiers mètres du ruisseau consistent essentiellement en tooéléite (un minéral rare de Fe6(AsO3)4(SO4)(OH)4•4H2O) associée à des précipités amorphes d’As(III)-Fe(III). Pendant la saison sèche, la formation d’un oxyhydroxyde de Fe(III)-As(V) amorphe prédomine.

6

Bruneel O, Duran R, Casiot C, Elbaz-Poulichet F, Personné JC (2006) Diversity of microorganisms in Fe-As-rich acid mine drainage waters of Carnoulès, France. Applied and Environmental Microbiology. 72, 551-556 7 Morin G, Juillot F, Casiot C, Personné JC, Elbaz-Poulichet F, Leblanc M, Ildefonse P, Calas G (2003) Bacterial formation of tooeleite and mixed arsenic(III) or arsenic(V)-iron(III) gels in the Carnoulès Acid Mine Drainage, France. A XANES, XRD, and SEM study. Environmental Science and Technology. 37, 1705-1712

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Dans la poursuite des études réalisées dans le cadre du DESS, le rôle des bactéries isolées (Thiomonas et Acidithiobacillus ferrooxidans) dans les réactions de précipitation de l’As et du Fe a été testé grâces à des études en laboratoire. Six souches (B1 à B6) isolées à partir de l’eau du ruisseau ont été inoculées individuellement dans l’eau de la source. B1, B2, B3 et B6 sont des souches du genre Thiomonas et B4 et B5 sont des Acidithiobacillus ferrooxidans. En parallèle, les précipités formés par les souches B1 à B6 ont été analysés.

Figure 3. Essais en laboratoire présentant le pourcentage d’As total (AsT), de Fe(II) et d’As(III) éliminés après une semaine d’incubation de différentes souches de microorganismes (B1 à B6) isolées à partir de l’eau du Reigous avec les concentration en As(V) en solution en fin d’expérience. S1: eau de la source avant incubation et SA: témoin stérile. D’après Casiot et al., 2003b

Ces études ont montré que 3 souches de Thiomonas ont la capacité d’oxyder l’As(III) dans l’eau du Reigous: B2, B3 et B6. C’est la souche B6, qui du fait de l’oxydation simultanée de l’arsenic et du fer, entraîne le plus grand battement d’As (87%)5. Les précipités du témoin abiotique, tout comme dans ceux des bactéries B1, B2, B3, B4 et B6, sont constitués essentiellement d’hydroxydes sulfates ferriques d’As(V)7. Une souche d’Acidithiobacillus ferrooxidans (bactérie B5) permet la formation de tooéléite nanocristalline associée à un mélange de composés d’oxyhydroxydes d’As(III)/As(V)-Fe(III) amorphes. Des études avec d’autres souches d’Acidithiobacillus ferrooxidans ont également montrées que ce genre était capable de faire précipiter rapidement l’arsenic avec le Fe(III) en milieux synthétiques sous forme de schwertmannite8. La bioremédiation de l’arsenic peut s’appuyer sur l’activité des microorganismes qui ont la capacité de détoxifier, mobiliser ou immobiliser l’As à travers différents processus comme l’oxydation, la réduction, la biométhylation, la sorption ou la complexation (Oremland et al., 2005 ; Bahar et al., 2013). Etant donné que l’As(III) est fortement toxique et mobile dans l’environnement, une stratégie de remédiation intéressante consiste généralement à le convertir en As(V), forme moins toxique et mobile qui a tendance à se fixer sur différents types de matrices (Bahar et al., 2013).

8

Duquesne K, Lebrun S, Casiot C, Bruneel O, Personné J-C, Leblanc M, Elbaz-Poulichet F, Morin G, and Bonnefoy V (2003) Immobilization of arsenite and ferric iron by Acidithiobacillus ferrooxidans in acid mine drainage. Applied and Environmental Microbiology. 69, 6165-6173

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Aux cotés des bactéries, les eucaryotes, présents dans ces drainages miniers acides, ont également développé des stratégies de résistance vis-à-vis de cet élément toxique dans l’environnement. Euglena mutabilis est un protozoaire photosynthétique, communément rencontré dans les eaux minières acides qui semble bien adapté aux conditions extrêmes qui y règnent (Brake et al., 2001). Cet organisme peut jouer un rôle important dans les DMA en contribuant à l’apport d’oxygène par leur activité photosynthétique, en séquestrant le fer et probablement d’autres métaux par précipitation intracellulaire et en apportant de la matière organique (Brake et al., 2001). A Carnoulès, les euglènes sont présentes en grand nombre dans le Reigous et sont visibles grâce à la présence de tapis verts caractéristiques, pouvant atteindre une épaisseur d’environ 1 cm. L’étude de la dynamique saisonnière de ces biofilms a montré qu’elle n’est pas liée aux variations des concentrations en polluants métalliques mais à l’effet de l’érosion mécanique du sédiment du fait des fortes précipitations9. Cultivés en milieu synthétique en présence de 0.2 à 300 mg/l d’As(III), les euglènes issues du site de Carnoulès accumulent l’As à l’intérieur de leurs cellules sous forme d’arsénite et d’arséniate dont les concentrations varient en fonction des concentrations en As(III) du milieu de culture. L’arsenic est également adsorbé à la surface de la cellule sous forme d’As(V).

9

Casiot C, Bruneel O, Personné J-C, Leblanc M, Elbaz-Poulichet F (2004) Arsenic oxidation and bioaccumulation by the acidophilic protozoan, Euglena mutabilis, in acid mine drainage (Carnoulès, France). Science of the Total Environment. 320, 259-267

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L’étude de cet écosystème s’est poursuivie après ma thèse dans le cadre de plusieurs projets de recherche. Une étude sur les Archaea a été réalisée suite aux résultats de l’étude moléculaire réalisée sur les bactéries présentes dans les eaux souterraines au sein du stock de déchets miniers. Historiquement, on pensait en effet que les bactéries représentaient les principaux microorganismes impliqués dans les processus de lixiviation à l’origine de la formation des DMA mais il a été montré depuis plusieurs années maintenant que les Archaea sont elles aussi susceptibles de jouer un rôle majeur, de part de leurs capacités à oxyder le fer dans les processus de génération et/ou de remédiation des DMA (Edwards et al., 2000c ; Baker and Banfield, 2003 ; Bini, 2010). Table 3. Inventaire des fragments d’ADNr 16S des clones présents dans les eaux au sein du stock de déchets miniers et dans le DMA du Reigous. D’après Bruneel et al., 2008

a

abondance relative des clones dans chaque librairie

Cette étude a révélé que l’ensemble des séquences retrouvées était affilié au phylum des Euryarchaeota, tandis que les Crenarchaeota n’étaient pas du tout présentes10. Ce travail a 10

Bruneel O, Pascault N, Egal M, Bancon-Montigny C, Goni M, Elbaz-Poulichet F, Personné J-C, Duran R (2008) Archaeal diversity in a Fe-As rich acid mine drainage at Carnoulès (France). Extremophiles. 12, 563-571

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également montré que la structure des communautés d’Archaea dans l’aquifère au sein du stock de déchet minier était très différente de celle présente dans les eaux du ruisseau du Reigous drainant le site. Au sein de la nappe qui draine le stock de déchets, les séquences majoritaires sont proches de Ferroplasma acidiphilum, un microorganisme acidophile, sans paroi cellulaire, oxydant le fer et connu pour son rôle majeur dans le lessivage (Golyshina and Timmis, 2005). Dans les eaux du Reigous, par contre, ce sont des séquences affiliées à un groupe de Thermoplasmatales non cultivé, le clone YAC1, qui est largement dominant.

Une étude en collaboration avec le laboratoire EEM de Pau s’est également intéressée aux bactéries sulfato-réductrice présentent sur ce site pour essayer de déterminer l’influence des paramètres environnementaux sur la structure de ces communautés par analyse t-RFLP et étude des gènes dsrAB11. Ce travail réalisé sur une période de 3 ans a permis de mettre en évidence la présence prédominante de la famille Desulfobulbaceae dans le système et a montré que la dynamique des bactéries sulfato-réductrices semble être liée aux fluctuations spatio-temporelles du pH, du fer et des formes spécifiques de l’arsenic. Pour tenter de mieux comprendre le fonctionnement du système de remédiation présent dans le drainage minier acide de Carnoulès, les concentrations en arsenic et métaux ont été suivis sur une période de plus de 4 ans sur l’ensemble du ruisseau. Cette étude a mis en évidence que les variations saisonnières semblaient être liées aux précipitations avec une augmentation des concentrations durant les mois secs12. Environ 30% de l’As initialement présent en solution se trouve sous forme d’As(III) qui coprécipite avec le fer dans les 40 premiers mètres du ruisseau. La minéralogie de ces précipités varie spatialement et saisonnièrement. Dans les 40 premiers mètres, on trouve des composés amorphes d’As(V)As(III)-Fe(III) associés à de la tooéléite alors que plus en aval, ces phases d’oxyde de Fe sont remplacées par de la schwertmannite et de la ferrihydrite12. Des travaux en collaboration avec l’IMPMC de Paris, ont permis de montrer que ces minéraux d’arsenic se forment généralement en étroite association avec des cellules bactériennes dans le milieu extracellulaire ou dans le périplasme des cellules ainsi qu’autour d’abondantes vésicules organiques d’origine inconnue13. Les conditions de formation de ces minéraux de fer très riches en As(III) et As(V) et l’implication des bactéries dans ces processus ont été par ailleurs étudiées en laboratoire. Des bactéries du genre Acidithiobacillus ferrooxidans inoculées dans l’eau du Reigous conduisent à la formation d’un assemblage de minéraux (schwertmannite, tooéléite) qui est différent de celui obtenu en conditions abiotiques où l’on trouve généralement de la jarosite. De plus, la proportion des minéraux formés semble différer selon la souche d’Acidithiobacillus 11

Giloteaux L, Duran R, Casiot C, Bruneel O, Elbaz-poulichet F and Goñi-urriza M (2013) A survey of sulfate reducing bacteria in a heavily arsenic contaminated acid mine drainage (Carnoulès, France). FEMS Microbiol Ecol. 83 724–737 12 Egal M, Casiot C, Morin G, Elbaz-Poulichet F, Cordier MA Bruneel O (2010) An updated insight into the natural attenuation of As concentrations in Reigous Creek (southern France). Applied Geochemistry. 25, 1949–1957 13 Benzerara K, Morin G, Yoon TH, Miot J, Tyliszczak T, Casiot C, Bruneel O, Farges F, and Brown Jr GE (2008) Nanoscale study of As transformations by bacteria in an acid mine drainage system. Geochimica et Cosmochimica Acta. 72, 3949-3963

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ferrooxidans et la taille de l’inoculum de départ14. Ces résultats semblent montrer que les bactéries peuvent influencer la composition minéralogique du précipité formé en intervenant sur la cinétique d’oxydation du fer, principalement durant les premiers stades d’incubation. La tooéléite, par exemple, ne semble se former que lorsque la cinétique d’oxydation du fer est lente et que le rapport As(III)/Fe(III) est élevé (≥ 0.8) avec des concentrations en Fe(III) du même ordre de grandeur que celles d’As(III). Pour mieux comprendre l’implication des microorganismes du genre Thiomonas, une collaboration avec le laboratoire GMGM de Strasbourg a permis de séquencer le génome de l’une de ces souches, Thiomonas sp. 3As, ce qui a permis de révéler les adaptations spécifiques de cet organisme lui permettant de survivre et de résister aux concentrations élevées de métaux et métalloïdes dans ces environnements extrêmes15. De plus, 8 souches différentes incluant 5 souches de la même espèce, ont également été comparées par hybridation génomique comparative. Le génome du genre Thiomonas semble avoir évolué à travers le gain ou la perte d’ilots génomiques, comme ceux conférant la résistance à l’As (opéron ars) par exemple. Cette capacité a permis à cette espèce de s’adapter à son environnement et suggère aussi que l’environnement influence l’évolution génomique de ces bactéries. Ces résultats soulignent de plus la variabilité très importante qui peut exister à l’intérieur d’un même groupe taxonomique, élargissant le concept d’espèces.

Etude des sédiments présents dans le DMA du Reigous En raison de la précipitation des éléments toxiques en solution, présent en grande quantité dans ces DMA, les sédiments de ces cours d’eau agissent comme des puits et accumulent de fortes quantités de composés métalliques toxiques. Cependant, ces éléments peuvent également être relargués dans l’eau en fonction de changements dans la chimie des sédiments, de l’évolution du régime hydrologique ou de l’activité microbienne et peuvent ainsi représenter une source potentielle de métaux et de métalloïdes toxiques (Park et al., 2006; Butler, 2011; Héry et al., 2014). Etudier les microorganismes présents et leurs fonctions dans de tels écosystèmes est donc également très important pour comprendre le devenir des polluants. Toujours en collaboration avec le GMGM de Strasbourg (F. Ploetze), une étude s’est intéressée aux populations actives de ces écosystèmes présentes à la fois dans l’eau et les sédiments du ruisseau du Reigous. L’utilisation d’une méthode de clonage-séquençage nous a permis d’identifier les différentes populations présentes et une étude de métaprotéomique

14

Egal M, Casiot C, Morin G, Parmentier M, Bruneel O, Lebrun S, Elbaz-Poulichet F( 2009). Kinetic control on the formation of tooeleite, schwertmannite and jarosite by Acidithiobacillus ferrooxidans strains in an As(III)-rich acid mine water. Chemical Geology. 265, 432-441 15 Arsène-Ploetze F, Koechler S, Marchal M, Coppee J-Y, Chandler M, Bonnefoy V, Barakat M, Barbe V, Battaglia -Brunet F, Brochier-Armanet C, Bruneel O, G. Bryan C, Cleiss J, Heinrich-Salmeron A, Hommais F, Joulian C, Krin E, Lieutaud A, Lièvremont D, Michel C, Muller D, Ortet P, Proux C, Siguier P, Roche D, Rouy Z, Salvignol G, Slyemi D, Talla E, Weiss S, Weissenbach J, Médigue C, Bertin PN (2010) Structure, function and evolution of the Thiomonas spp. genome inferred from sequencing and comparative analysis. PLoS Genetics. 6 (2) e1000859

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nous a permis d’identifier les membres actifs de ces environnements16. Ce travail a été réalisé en partie dans le cadre de la thèse d’Aurélie Volant (2009-2012, bourse environnée) que j’ai principalement encadré, intitulée « Etude des communautés microbiennes (Bactéries, Archaea et Eucaryotes) et de leurs variations spatiotemporelles dans la mine de Carnoulès fortement contaminée en arsenic ».

Table 4. Inventaire des fragments d’ADNr 16S des clones présents dans les eaux de drainage et les sédiments au point COWG, 30 mètres en aval de la source dans le ruisseau du Reigous. D’après Bruneel et al, 2011

Les analyses taxonomiques des banques de gènes codant pour l’ARNr 16S ont permis de montrer que la diversité bactérienne est plus faible dans l’eau que dans les sédiments avec 11 souches identifiées dans l’eau contre 13 souches dans les sédiments. Un total de 17 groupes taxonomiques différents ont été identifiés avec seulement 7 genres présents à la fois dans l’eau et les sédiments. La plupart des ces bactéries étaient affiliées à des β-protéobactéries telles que Gallionella ou Thiomonas mais également à des γ- protéobactéries (tel que Acidithiobacillus ferrooxidans), des α-protéobactéries (Acidiphilium), des δ-protéobactéries (Desulfomonile limimaris), des Nitrospira (Leptospirillum ferrooxidans), des Actinobacteria et des Firmicutes. Il s’agit majoritairement d’espèces trouvées communément dans les DMA avec une majorité impliquée dans les cycles du fer, de l’arsenic et du soufre. Les bactéries impliquées dans l’oxydation de l’As(III) sont affiliées à Thiomonas, celles impliquées dans l’oxydation de Fe(II) sont affiliées à Gallionella, At ferrooxidans, Ferrimicrobium, Leptospirillum, Sideroxydans lithotrophicus, et Ferrovum myxofaciens alors que la réduction 16

Bruneel O, Volant A, Gallien S, Chaumande B, Casiot C, Carapito C, Bardil A, Morin G, Brown Jr GE, Personné JC, Le Paslier D, Schaeffer C, Van Dorsselaer A, Bertin PN, Elbaz-Poulichet F, Arsène-Ploetze F (2011) Characterization of the active bacterial community involved in natural attenuation processes in arsenic-rich creek sediments. Microbial Ecology. 61, 793-810

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du fer a été mise en évidence pour les bactéries des genres Acidiphilium, Desulfuromonas svalbardensis, Acidocella, Rhodoferax ferrireducens, At ferrooxidans et Ferrimicrobium acidiphilum. Concernant le cycle du soufre, des populations capables d’oxyder des composés soufrés inorganiques ont été mis en évidence telles que Thiobacillus, Thiomonas ou At ferrooxidans. Des bactéries sulfato-réductrices comme Desulfomonile limimaris ou Desulfuromonas svalbardensi pourraient être impliquées dans la consommation du sulfate. L'oxydation de l'arsenic associée à l'oxydation du fer et l'oxydation du soufre pourrait contribuer à la co-précipitation de ces éléments et expliquerait l'atténuation de la contamination arséniée constatée dans le Reigous. L’étude par métaprotéomique faite au niveau des sédiments a révélé que les genres oxydants le fer comme Gallionella et Acidithiobacillus et oxydants l’As comme Thiomonas comptent parmi les membres métaboliquement actifs de la communauté procaryote du Reigous. Nous avons également caractérisé la communauté d’Archaea présente dans ces sédiments et avons étudié sa dynamique temporelle en utilisant la technique de clonage-séquençage du gène codant pour l’ARNr16S. Les Archaea restent pour l’instant assez mal connues et peu étudiées en raison notamment de difficultés d’isolement qui font que les connaissances sur leurs métabolismes ne concernent pour l’instant qu’un nombre restreint de souches. Ainsi, la diversité de ces organismes et leurs rôles physiologique au sein des DMA sont assez obscur et les études moléculaires restent indispensables.

35

Figure 4. Arbre phylogénétique basé sur le gène codant pour l'ARNr 16S représentant l'affiliation taxonomique de la communauté des Archaea présente dans les sédiments du ruisseau du Reigous au point COWG. Le nombre entre parenthèses indique le nombre de séquences de clones pour la période d'échantillonnage représenté par un symbole (Avril 2006,
Octobre 2008, Janvier 2009 et  Novembre 2009 ; Volant et al., 2012)

L'affiliation taxonomique des Archaea a montré un faible degré de diversité avec uniquement 2 phylums détectés: les Thaumarchaeota (contenant la grande majorité des séquences) et les Euryarchaeota17. Contrairement aux Archaea retrouvées dans les eaux du 17

Volant A, Desoeuvre A, Casiot C, Lauga B, Delpoux S, Morin G, Personné JC, Héry M, F Elbaz-Poulichet, Bertin P and Bruneel O (2012) Archaeal diversity: temporal variation in the Arsenic-Rich Creek Sediments of Carnoulès Mine, France. Extremophiles. 16, 645-657

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stock de déchet minier et dans les eaux du DMA, nous n’avons pas retrouvé ici de microorganismes directement impliqués dans le cycle du fer ou du soufre. Un grand nombre de séquences sont affiliées à Thermogymnomonas acidicola, une Archaea hétérotrophe retrouvée dans d’autres DMA et qui pourrait jouer un rôle important dans l’écosystème en utilisant les composés organiques qui peuvent être toxiques pour certains autotrophes (Hallberg, 2010 ; Yang et al., 2014). Des microorganismes affiliés à des Archaea méthanogènes, impliquées dans le cycle du carbone, telle que Methanomassiliicoccus luminyensis, ont également été identifiées. Enfin, des séquences apparentées à Candidatus Nitrososphaera viennensis et Candidatus nitrosopumilus sp., des Archaea impliquées dans l’oxydation de l’ammonium, une étape clé du cycle de l’azote, ont été décris. L’ensemble de ces microorganismes pourrait donc contribuer conjointement avec les bactéries au processus de remédiation observé in situ. Cette étude a également permis de mettre en évidence des modifications importantes de la structure et de la composition de la communauté d’Archaea au cours du temps qui sont probablement liées à des modifications de l’environnement.

Une étude, en collaboration avec l’IMPMC de Paris (G. Morin), s’est également intéressée aux conditions de formation des minéraux de fer riches en arsénite As(III) et arséniate As(V) identifiés sur le site, tel que la schwertmannite qui joue un rôle très important dans la rétention de l’As et la remédiation de ce métalloïde. Ce travail a montré que l’oxydation bactérienne de l’arsenic, en favorisant la formation d’As(V)-schwertmannite ou d’arséniate ferrique, améliore grandement l’immobilisation de l’As dans la phase solide18. Une autre étude avec l’IMPMC de Paris s’est également intéressée à la structure de la ferrihydrite, un oxyhydroxyde de fer qui est également impliqué dans la rétention de l’As. C’est la phase minérale prédominante présente dans les sédiments de la rivière Amous (pH 6−7) qui se forme, après la confluence, après neutralisation avec les DMA du Reigous. Ces travaux montrent que cet oxyhydroxyde de fer pourrait également jouer un rôle important dans la séquestration de l’As dans les environnements miniers19. Des études géochimiques ont également porté sur le thallium et ont montré que la forme réduite du thallium Tl(I) est largement prédominante dans le DMA de Carnoulès et est peu adsorbé sur les particules de ferrihydrite, qui se forment dans la rivière Amous en aval du Reigous, impliquant une forte mobilité du thallium dans l’hydrosystème aval20.

18

Maillot F, Morin G, Juillot F, Bruneel O, Casiot C, Ona-Nguema G, Wang Y, Lebrun S, Aubry E, Vlaic G, Brown GE Jr (2013) Structure and reactivity of As(III)- and As(V)-rich schwertmannites and amorphous ferric arsenate sulfate from the Carnoulès acid mine drainage, France: comparison with biotic and abiotic model compounds and implications for As remediation. Geochimica et Cosmochimica Acta. 104, 310-329 19 Adra A, Morin G, Ona-Nguema G, Maillot F, Casiot C, Bruneel O, Lebrun S, Juillot F, Brest J (2013) Arsenic Scavenging by Al-Substituted Ferrihydrites in a Circumneutral pH River Impacted by the Acid Mine Drainage of Carnoulès, Gard, France. Environmental Science and Technology. 47, 12784-12792 20 Casiot C, Egal M, Bruneel O, Verma N, Parmentier M, Elbaz-Poulichet F (2011) Predominance of aqueous Tl(I) species in the river system downstream from the abandoned Carnoulès mine (Southern France). Environmental Science & Technology. 45, 2056-2084

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Etude de la diversité fonctionnelle des communautés du Reigous par métagénomique La diversité fonctionnelle des microorganismes présents au sein du drainage minier acide de Carnoulès a été étudiée dans le cadre du projet ANR RARE initié par P. Bertin (GMGM de Strasbourg). Au départ prévu sur l’eau, le manque de matériel biologique a conduit la réalisation de cette étude dans les sédiments de surface au point COWG. Le séquençage massif et le réassemblage de l’ADN, réalisé par le Génoscope d’Evry, ont conduit à la reconstruction de 7 pseudo-génomes microbiens (CARN1 à CARN7) présents dans cet environnement21. Tableau 5. Analyse phylogénétique des pseudogénomes présents dans le sédiment de la mine de Carnoulès réalisée à l’aide de 27 marqueurs universels ou du gène de l’ARNr 16S avec RDP. D’après Bertin et al., 2011

(

1) Pour le 16S, l’organisme le plus proche a été obtenu par recherche à l’aide du logiciel BLAST sur la base de donnée NCBI nr. Seuls les microorganismes ayant un pourcentage de similarité >90 sont indiqués. La recherche des 27 marqueurs universels a été réalisé selon Ciccarelli et al., (2006). (2) Absence du gène de l’ARNr 16S

Cette analyse a confirmé la présence de souches identifiées par les études antérieures réalisées par PCR/Clonage/séquençage comme Thiomonas, Acidithiobacillus ferrooxidans, Thiobacillus sp. ou Gallionella. L’utilisation conjointe de la métagénomique et de la métaprotéomique a également permis de mettre en évidence les relations entre les microorganismes ainsi que les fonctions importantes dans cet environnement. 21

Bertin PN, Heinrich-Salmeron A, Pelletier E, Goulhen- Chollet F, Arsène-Ploetze F, Gallien S, Lauga B, Casiot C, Calteau A, Vallenet D, Bonnefoy V, Bruneel O, Chane-Woon-Ming B, Cleiss-Arnold J, Duran R, Elbaz-Poulichet F, Fonknechten N, Giloteaux L, Halter D, Koechler S, Marchal M, Mornico D, Schaeffer C, Thil Smith AA, Van Dorsselaer A, Weissenbach J, Médigue C and Le Paslier D (2011) Metabolic diversity between main microorganisms inside an arsenic-rich ecosystem revealed by meta- and proteo-genomics. The ISME Journal. 5, 1735-1747. Cet article a fait l’objet d’une note dans la revue Sciences (2011, vol 332, p1128)

38

Figure 5. Modèle de la communauté bactérienne de Carnoulès mettant en évidence les fonctions majeures identifiées par le séquençage du métagénome et la métaprotéomique présentes au sein du sédiment de COWG. Les interactions entre les organismes et les composés biologiques ou chimiques sont indiquées par des flèches. Les microorganismes CARN sont numérotés de 1 à 7.

Ce travail a permis de mettre en évidence différentes activités et interactions au sein de cette communauté comme la capacité de certains microorganismes à fixer l’azote (particulièrement peu abondant dans ce type d’environnement) et le carbone inorganique par les microorganismes autotrophes permettant le développement des microorganismes hétérotrophes. La capacité de formation de biofilms, connue pour apporter une meilleure résistance face aux différents stress environnementaux (Harrison et al., 2007, Marchal et al., 2012), a été révélée ainsi que la présence de flagelles et de capsules. Les mécanismes énergétiques impliquants l’arsenic, le fer et le soufre ont été identifiés ainsi que le recyclage et le transport de la matière organiques : acides aminés, vitamines et nucléosides. En particulier, ces études ont permis l’identification d'un nouveau phylum, ‘Candidatus Fodinabacter comunificans’ qui pourrait exercer à Carnoulès un rôle indirect mais important en participant au recyclage de la matière organique comme les acides aminés ou les nucléosides provenant notamment de microorganismes eucaryotes retrouvés sur le site (Halter et al., 2012a). Ces approches génomiques ont ainsi permis de mieux comprendre le rôle des microorganismes dans l’atténuation naturelle de l’arsenic sur ce site et d’attribuer à des organismes spécifiques, dont des organismes non encore cultivés, des fonctions importantes.

39

Utilisation des nouvelles technologies de séquençage pour l’étude des DMA Depuis quelques années, les avancées dans le domaine des techniques de séquençage haut débit, encore appelé séquençage massif ou de nouvelle génération, ont révolutionné la biologie moléculaire et ont ouvert une nouvelle aire dans les recherches concernant les études sur la biodiversité (Sogin et al., 2006; Behnke et al., 2011). En raison de la rapidité d’obtention et du coût relativement faible (et qui ne cesse de diminuer) pour produire des millions de séquences, il est maintenant possible d’explorer en profondeur la diversité et la complexité des communautés microbiennes. Dans les études de diversité, ces techniques apparaissent comme essentielles car elles permettent d’avoir une profondeur de séquençage et une vue quasi exhaustive des microorganismes présents. Ces techniques permettent donc de s’intéresser également aux populations minoritaires qui peuvent malgré tout jouer un rôle crucial dans les processus biogéochimiques alors que l’on ne pouvait que très difficilement les étudier avant selon les méthodes traditionnelles de biologie moléculaire comme le clonageséquençage (Behnke et al., 2011). C’est ce type d’analyses qui a été utilisé dans le cadre de 2 études qui se sont intéressées aux microorganismes (bactéries et eucaryotes) présents dans les sédiments miniers de la mine de Carnoulès. Comme nous l’avons vu précédemment, des études antérieures principalement basées sur des souches isolées, ont suggéré un rôle déterminant de l’activité bactérienne dans la coprécipitation de l’As avec le Fe(III) et le sulfate et la formation de phases amorphes d'oxyhydroxydes associées à des minéraux comme la tooéléite, la schwertmannite ou la ferrihydrite. Cette étude a permis l’analyse de la diversité bactérienne présente dans différents types de sédiments le long des 1500 m du Reigous, en utilisant, pour la première fois une approche de pyroséquençage 454 ciblant le gène codant pour l’ARNr 16S. Le but était d’identifier les communautés bactériennes présentes et d’étudier leurs dynamiques spatiales en fonction de la structure minéralogique des sédiments (comprenant notamment des sites très riches en tooéléite et en schwertmannite) permettant de comprendre si la dynamique de ces communautés est liée aux changements dans les sédiments. Cette approche a permis de générer un total de 53075 séquences de bonne qualité après normalisation, conduisant à l'identification de 966 OTU, mettant en évidence une diversité beaucoup plus importante que précédemment observé. Il est également à noter qu’une grande majorité de cette diversité est du à la présence d’OTUs rares (371, encore appelés singletons) et observés une seule fois pour l’ensemble des séquences. Ceci suggère qu’une part importante de la diversité observée se réfère à des taxons présents à une très faible abondance donnant naissance au concept de biosphère rare (Pedrós-Alió, 2007). En dépit de l’importance de cette biosphère rare dans de nombreuses études, son rôle écologique et fonctionnel reste mal compris actuellement (Galand et al., 2009). Pour certains auteurs, ces organismes pourraient devenir dominants et actifs suite à des modifications des conditions environnementales et pourraient permettre aux processus biogéochimiques d’être maintenus limitant ainsi les effets des modifications de l’environnement (Sogin et al, 2006 ; Behnke et al., 2011 ; Bachy and Worden, 2014). D'autres études s’interrogent également sur l'exactitude des estimations de la richesse en OTUs générée par le séquençage à haut débit, qui pourrait correspondre à des erreurs de séquençage (Huse et al., 2010). 40

450 400

Number of OTUs

350 300

S1

250

COWG

200

GALm

150

GAL

100

CONF

50 0 0

2000

4000

6000

8000

10000 12000

Number of sequences Figure 6. Courbes de raréfaction des séquences bactériennes des gènes codants pour l'ARNr 16S présents dans les sédiments de la mine de Carnoulès et basé sur le nombre d’OTU calculés à 97% d'identité. Le nombre total de séquences analysées est tracé en fonction du nombre d’OTU observé.

Les courbes de raréfaction ont tendance à atteindre une asymptote pour la plupart des échantillons, ce qui suggère que la majorité des phylotypes bactériens présents ont été identifiés, ce qui est confirmé par la couverture très élevée (de 98 à 100%) pour tous les échantillons. Table 6. Estimation de la richesse en OTU, des indices de diversité et de la couverture estimée pour les 5 échantillons de sédiments. Les résultats sont présentés pour les données normalisées, rééchantillonnées au hasard pour avoir une taille d’échantillon égale entre les sites.

a

Les OTUs ont été définis à 97% d’identités Somme des probabilités des classes observées calculées comme suit (1 - (n / N)), où n est le nombre de séquences uniques (singletons) et N est le nombre total de séquences c Prend en compte le nombre et la régularité des espèces Les valeurs entre parenthèses sont des intervalles de confiance à 95% b

Au total, 15 phylums ont pu être identifiés ici pour l’ensemble des échantillons, ce qui est bien plus important que ceux retrouvés dans les analyses antérieures obtenues par clonageséquençage qui n’excédaient généralement pas 5 phylums. L'analyse phylogénétique a révélé que la grande majorité des séquences (65%) appartenaient au phylum des Proteobacteria avec 41

une prédominance des bactéries oxydant de fer, représentées principalement par des séquences proches de Gallionella ou Acidithiobacillus ferrooxidans. Cette analyse quasi exhaustive des taxons présents a également révélé la présence de genres abondants encore jamais détectés auparavant par les analyses de clonage/séquençage, comme les membres des Comamonas, Stenotrophomonas ou Pseudoxanthomonas avec certains d'entre eux impliqués dans l'oxydation de l’As, un métabolisme importante impliqué dans la précipitation de As. Cependant, aucun paramètre évident ne semble lier les communautés à la structure des sédiments. Ce travail devrait être prochainement soumis dans le journal FEMS Microbiology Ecology. Une seconde étude s’est intéressée aux communautés eucaryotes. Les communautés de bactéries des DMA ont été extensivement étudiées depuis plusieurs 10aines d’années avec les premières études de diversité qui remontent au milieu des années 1990 (Goebel et Stackebrandt, 1994 ; Kuang et al., 2012). Paradoxalement, les communautés eucaryotes de ces environnements ont été très peu étudiées bien qu’un intérêt croissant leur soit porté de part leur rôle écologique potentiellement important dans ces écosystèmes. Certains sont par exemple susceptibles de modifier l’abondance, la composition et l’activité des communautés microbiennes procaryotes par de nombreux mécanismes comme la prédation (Baker et al., 2004, 2009; Gadanho et al., 2006). D’autres sont connus pour jouer un rôle important dans le cycle du carbone et le recyclage des nutriments ce qui est primordiale dans ces environnements oligotrophes (Baker et al., 2004). Certains peuvent également apporter de l’oxygène au milieu par leurs activités photosynthétiques ou encore séquestrer des polluants métalliques dans les matrices extracellulaires ou à l’intérieur de la cellule (Brake et al., 2001). Concernant la mine de Carnoulès, aucune analyse de diversité n’avait encore été réalisée sur la communauté eucaryotes au niveau moléculaire bien que des études précédentes se soient intéressées au protozoaire photosynthétique Euglena mutabilis9 (Halter et al., 2012a, 2012b). L’objectif de ce travail était d’identifier les communautés eucaryotes présentes dans les sédiments du Reigous et d’étudier leur distribution spatiale le long du ruisseau par pyroséquençage 454 des gènes codant pour l’ARNr 18S.

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Table 7. Répartition taxonomiques des séquences eucaryotes présentes dans les sédiments de la mine de Carnoulès. Le chiffre entre parenthèses représente l'abondance relative (%) des taxons.

*Calculé par rapport au nombre total de séquences présentes dans cette étude. Autres champignons corresponds aux Blastocladiomycota et à des champignons non classés

Les analyses phylogénétiques ont révélé la présence de 14 taxons essentiellement dominés par 6 groupes (représentant 91 % des séquences totales) affiliés aux phyla des Ascomycètes, Basidiomycètes, Alveolates, Stramenopiles, Streptophytes et Chlorophytes. Parmi ces groupes, les champignons constituaient à eux seuls près de 60 % des séquences et sont apparus être le groupe majoritaire sur l’ensemble des sédiments prélevés (ce qui est en accord avec les résultats obtenus par Baker et al. (2009)), suivis dans une moindre mesure par les Alveolates et les Stramenopiles. La majorité des séquences obtenues dans cette étude se sont révélées être apparentées à des taxons trouvés précédemment dans d’autres DMA tels que les Chlorophytes, les Streptophytes ou les Champignons, etc. (Amaral-Zettler et al., 2002, 2011). Le pyroséquençage a également permis de mettre en évidence de nouveaux taxons non détectés auparavant dans ce type de milieu tels que les Apusozoaires, les Centroheliozoaires et les Jakobides. Ces travaux ont également permis de mettre en évidence une structuration spatiale des communautés eucaryotes qui semble être liée en partie à la physicochimie de l’eau (arsénite, fer et potentiel redox). Ce travail devrait être prochainement soumis à la revue Environmental Microbiology.

Projet MIGRAMD et analyse de biogéographie (France, Bolivie et Espagne) Le projet FRB, MIGRAMD, intitulé : « Microbial biogeography of Acid Mine Drainage: a study of genetic diversity and species diversity from an evolutionary perspective », porté par l’EEM de Pau (B. Lauga) nous a permis d’aborder une nouvelle notion, celle de biogéographie. L’objectif de ce projet était d’évaluer la diversité spécifique des microorganismes présents dans les DMA de 4 pays (Espagne, Portugal, France et Bolivie) plus ou moins riches en arsenic et séparés géographiquement pour mieux comprendre leurs organisations spatiales et leurs répartitions afin d’appréhender les processus qui les mettent en 43

place. Parallèlement à cette approche spatiale, la dynamique spatiotemporelle des communautés bactériennes a été étudiée dans les eaux le long du continuum du DMA de Carnoulès afin d’identifier les paramètres physicochimiques structurant l’assemblage des bactéries. C’est dans le cadre de cette dernière partie que s’est focalisé le travail de thèse d’Aurélie Volant. La configuration du DMA de Carnoulès est en effet telle que la contamination du Reigous (qui prend sa source au sein du stock de déchet minier) s'atténue le long du continuum, mettant en évidence un important gradient spatial des conditions physicochimiques. De plus, les fortes contraintes physico-chimiques qui s'exercent sur ces écosystèmes donnent l'opportunité d'étudier l'effet des pressions de sélection sur la biodiversité. Les méthodes de séquençages haut-débit, de part la profondeur de séquençage qu’elles permettent semblaient ici un outil de choix pour aborder ces problématiques. Concernant l’approche spatiale, douze DMA (eau et sédiments) ont ainsi été échantillonnés dans 3 régions du monde, l’Amérique du Sud (Bolivie), la péninsule Ibérique (Espagne et Portugal) et la France (DMA du Reigous à Carnoulès). Leurs principaux paramètres physicochimiques (pH, température, conductivité, concentrations en éléments métalliques et sulfates, etc) ont été caractérisés et la spéciation a été réalisée pour As et Fe). Les gènes codant pour l'ARNr 16S des bactéries et des Archaea ont été amplifiés par PCR puis séquencés sur pyroséquençage Roche 454 à la plateforme de génomique de Toulouse. Ce travail, s’est fait également en association avec l’équipe « Instituto de Biologıa Molecular y Biotecnologıa, Universidad Mayor de San Andres » de La Paz en Bolivie. Cette partie de l’étude est en cours d’analyse par l’EEM de Pau. Concernant l’étude spatio-temporelle de Carnoulès, 6 campagnes de prélèvement ont été réalisées de novembre 2007 à janvier 2010 au niveau de 5 points de prélèvements, soit 30 échantillons au total22. Les paramètres physico-chimiques ont été caractérisés et l’étude à été réalisé en combinant une technique à empreinte moléculaire, la T-RFLP et le pyroséquençage 454 à la plateforme de génomique de Toulouse. Les analyses physico-chimiques ont montré qu’en moyenne 60% des concentrations en sulfate, 96% de celles en fer et 99% de celles en arsenic étaient précipitées le long des 1500 mètres du ruisseau du Reigous. Le pyroséquençage a permis de générer un total de 66016 séquences qui ont permis l’identification de 6801 OTUs incluant 4629 singletons représentant 68% des séquences. Vingt trois phylums bactériens ont été identifiés sur l’ensemble des échantillons analysés et le phylum largement majoritaire (68%) est celui des Protéobactéries. Les 3 OTUs majoritairement présents sont apparentés aux espèces trouvées précédemment comme Gallionella ferruginea, Acidithiobacillus ferrooxidans et Thiobacillus sp. et confortent ainsi les études antérieures. Cette étude a également permis de mettre en évidence des genres jamais identifiés jusqu’à présent à Carnoulès comme Ignavibacterium, Ralstonia ou Paludibacter, etc.

22

Volant A, Bruneel O, Desoeuvre A, Héry M, Casiot C, Bru N, Delpoux S, Fahy A, Javerliat F, Bouchez O, Duran R, Bertin PN, Elbaz-Poulichet F and Lauga B (2014) Diversity and spatiotemporal dynamics of bacterial communities: physicochemical and others drivers along an acid mine drainage. FEMS Microbiology Ecology. 90, 247-263

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Figure 7. Analyse Canonique par Correspondance (ACC) corrélant la structure des communautés bactériennes avec les paramètres physicochimiques présents dans les différents sites incluant l’arsenic (As), le fer (Fe), la conductivité (Cond), la température (T), l’oxygène dissous (DO), le potentiel redox (Eh), le pH et le sulfate. La structure des communautés correspond à l’abondance des OTUs obtenus à partir des données de T-RFLP (a) ou du pyroséquençage (b). Les principaux clusters ont été entourés. D’après Volant et al., 2014

Une séparation spatiale a également pu être clairement mise en évidence par les données de pyroséquençage et une analyse canonique des correspondances a identifié 3 paramètres physicochimiques (la concentration en arsenic, la température et le potentiel redox) comme des facteurs potentiellement responsables de cette structuration.

Conclusion sur l’étude des drainages miniers acides En conclusion sur cette partie, de nombreuses questions de recherche ont été abordées et les résultats ont permis une amélioration notable des connaissances acquises sur ce site, comme le souligne la vingtaine de publications issues des travaux de notre équipe et de ses partenaires citées dans les paragraphes précédents. Cela démontre également l’intérêt de ces travaux pluridisciplinaires qui ont permis d’obtenir une vision globale et intégrée des processus complexes qui conditionnent les interactions entre les microorganismes et leur environnement. La combinaison d’études de terrain et d’expériences en laboratoire a permis des avancées importantes dans la compréhension des processus d’oxydation et de précipitation de Fe et As et le rôle des microorganismes dans ces processus est désormais mieux compris. L’aptitude de souches, isolées du site, comme Acidithiobacillus ferrooxidans et Thiomonas à oxyder le fer ou l’arsenic a été montré en laboratoire, ainsi que leurs rôles dans la formation de minéraux particuliers. Ces résultats démontrent également qu’en dépit des conditions extrêmes qui règnent à Carnoulès, des communautés microbiennes complexes (Bactéries, Archaea et Eucaryotes) coexistent, interagissent et influencent directement ou indirectement le cycle de 45

certains métaux et métalloïdes et en particulier l’arsenic. Les résultats obtenus soulignent également l’intérêt de l’utilisation des nouvelles techniques de séquençage permettant de mettre en évidence une diversité majoritairement sous estimée par les techniques classiques de clonage-séquençage mais ouvre aussi la voie à de nombreuses interrogations concernant par exemple le rôle écologique des nombreux taxons rares mis en évidence. Un Projet ANR ECO-TS IngECOST-DMA, « Ingénierie écologique appliquée à la gestion intégrée de stériles et DMA riches en arsenic » a été accepté sur Carnoulès en 2014 pour une durée de 4 ans. Il a pour but la mise en place et l’étude d’un système de bioremédiation (intégrant un système utilisant la capacité des bactéries qui oxydent le fer à précipiter les polluants associé à un système utilisant la capacité des bactéries sulfato-réductrices à former des sulfures de métaux insolubles) qui pourra s’appuyer sur les connaissances déjà acquises sur ce site et qui permet d’aborder ici des études de remédiation appliquées.

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TRAVAUX ACTUELS Depuis mon expatriation en février 2012 au sein du Laboratoire de Microbiologie et de Biologie Moléculaire de l’Université Mohammed V de Rabat au Maroc dirigé par le professeur Karim Filali-Maltouf, je m’intéresse à une thématique un peu différente qui est l’étude des interactions plantes-microorganismes dans la mise en place d’un couvert végétal. Ce travail a été initié à l’origine dans le cadre du Laboratoire Mixte International « Biotechnologie Végétale et Microbienne (Directeurs K. Filali-Maltouf et G. Béna) » dans l’axe thématique «Identification de plantes et microorganismes tolérants aux polluants métalliques dans les sites miniers marocains». Ce travail a été réalisé en grande partie dans le cadre d’un projet Ec2co (2012-2013) sur l’«Etude des interactions plantes-microorganismes dans un contexte de réhabilitation de sites minier: mécanismes adaptatifs et effets sur le devenir des polluants métalliques» dont je suis porteur. Comme nous l’avons vu, les activités minières sont très polluantes et ont un impact important sur l'environnement et la santé que ce soit lors de l’extraction du minerai, de sa transformation ou du fait de la production de milliers de tonnes de déchets. Ces déchets sont généralement composés de particules très fines et souvent riches en divers composés toxiques. L'activité minière a été l'un des piliers de l'économie marocaine et a entrainé l’accumulation de milliers de tonnes de résidus pour la plupart abandonnés à l'air libre. Les conditions climatiques du bassin méditerranéen (vents violents et périodes de pluies intenses qui succèdent à des périodes très sèches) favorisent le lessivage et la dissémination des polluants et rendent difficile l’installation d’un couvert végétale. Plusieurs technologies ont été développées pour dépolluer les sols contaminés par les polluants métalliques comme leur extraction par des moyens chimiques ou physiques ou encore l’élimination physique du sol qui est confiné dans des sites d'enfouissement. Mais ces techniques sont souvent très coûteuses à la fois d’un point de vue économique et environnemental et peuvent fortement altérer les qualités physiques, chimiques et biologiques des sols (Glick, 2010). Depuis une quinzaine d’années, des travaux se sont intéressés à l’utilisation de plantes pour dépolluer ces sols. Les polluants peuvent en effet être soit stabilisés dans le sol pour les rendre moins bioassimilables (phytostabilisation), soit être accumulés dans les tissus végétaux (phytoextraction) ou encore être transformés en formes volatiles (phytovolatilisation) (Khan, 2005 ; Kavamura and Esposito, 2010). Le principal obstacle à ces techniques est dû au fait que la plupart des résidus miniers sont de mauvais substrats pour la croissance des plantes en raison à la fois de la présence de métaux toxiques en concentrations élevées, de la présence parfois de pH acides, de la salinité souvent élevée, du manque de matière organique et de nutriments essentiels, de la mauvaise structure du sol et d’une mauvaise rétention de l’eau (Kid et al., 2009 ; de-Bashan et al., 2010). Ces résidus restent généralement dépourvus de couverture végétale pendant des décennies ou plus (Mendez and Maier, 2008 ; de-Bashan et al., 2010). Pour remédier ces environnements extrêmes et en raison des concentrations élevées en polluants métalliques, c’est la phytostabilisation qui est généralement préférée, c'est-à-dire la création d’une couverture végétale qui va limiter l’érosion éolienne et hydrique en stabilisant et précipitant les éléments métalliques au niveau des racines tout en limitant leur accumulation dans les feuilles (de-Bashan et al., 2010, Bolan et al., 2014). Alors que l'établissement d'un couvert végétal sur des sols contaminés par des polluants chimiques reste un défi, les microorganismes peuvent fortement accélérer le processus de 47

phytostabilisation (de-Bashan et al., 2010, Ma et al., 2011). La croissance des plantes est en effet fortement influencée par les microorganismes qui peuvent intervenir à plusieurs niveaux (fixation d’azote, solubilisation du phosphate, production de phytohormones ou d’antibiotiques, etc.). Certains microorganismes ont de plus la capacité à agir sur la mobilisation/immobilisation des métaux et métalloïdes dans le sol par la production de sidérophores, d’enzymes, ou d’acides organiques, etc. composés qui peuvent modifier ces éléments par acidification, chélation, précipitation, oxydoréduction ou méthylation, etc. (Rajkumar et al., 2012). De nombreux microorganismes sont en effet connus pour favoriser la croissance des plantes (effet PGPB, Plant Growth Promoting Bacteria, de-Bashan et al., 2010, Das et al., 2014). Plusieurs études ont ainsi montré que des rhizobactéries appartenant aux genres Achromobacter, Arthrobacter, Azotobacter, Bacillus, Pseudomonas, ou Serratia favorisaient la croissance des plantes dans des environnements contaminés par des métaux et métalloïdes (Ma et al., 2011). Parmi ces microorganismes, on peut distinguer les microorganismes telluriques, présents dans le sol; les rhizobactéries localisées à proximité immédiate des racines et les bactéries endophytes qui colonisent les tissus internes des plantes sans causer d’infections. Contrairement à la pollution par les mines dans les régions tempérées, il n’existe que très peu d'études sur l'impact environnemental des activités minières dans les régions arides et semi-arides (González et al., 2011). Les sites que nous étudions dans le cadre de ce projet se situent dans le district minier de la ville d’Oujda, au Nord-Est du Maroc près de la frontière algérienne.

Figure 8. Situation géographique des régions étudiées et localisation des stations de prélèvements. D’après Smouni et al., 2010

Les sites d’études comprennent les digues de lavage des mines abandonnées de Pb et Zn de Touissit et Boubker ainsi que les scories de l’ancienne fonderie de Oued El Heimer. Ces déchets qui représentent plusieurs millions de tonnes constituent des digues de très grande superficie.

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A

B

C

Figure 9. Description des sites de Oued El Heimer, Touissit et Boubker. A) Scories plombifères déposées sur de grandes surfaces aux abords de la fonderie. B) Digue de sable aux abords du village de Touissit. C) Digue de sable à proximité d’un champ de blé dans la région de Boubker. D’après Smouni et al., 2010 Malgré un climat austère et une forte teneur en polluants, une flore tolérante parvient à s’y développer. Ces plantes, ainsi que les microorganismes associés sont à priori adaptés aux conditions édapho-climatiques de ces régions et présentent donc une ressource pour le développement de stratégies de réhabilitation, notamment par la phytostabilisation et la mise en place d’un couvert végétal qui limiterait l’érosion éolienne et hydrique. L’intérêt pour cette région est multiple. D’une part, le périmètre étudié est fortement impacté par une pollution polymétallique aussi bien au niveau des terres agricoles que des cours d’eau et des puits (Smouni et al., 2010). L’index de pollution des échantillons prélevés dans ces environnements est généralement très élevé du fait de la présence simultanée de plusieurs polluants (As, Cd, Cu, Ni, Pb et Zn) avec de très importantes teneurs en Pb, Zn et As (respectivement jusque 7 g/kg, 2 g/kg et 187 mg/kg) (Smouni et al., 2010). Enfin, la présence de sites divers et originaux (stériles couverts et digues nues, revégétalisés ou non, de façon naturelle ou par action humaine) permet de comparer leurs impacts sur l’association plantes49

microorganismes qui les a colonisés sur une échelle de temps variée. Cette situation constitue ainsi une source d’une incroyable diversité floristique et microbienne. L’objectif de ce projet de recherche consiste à étudier à la fois les plantes et les microorganismes associés et doit permettre : (i) d’étudier les mécanismes de résistance et d’accumulation notamment pour le Pb et le Zn de 2 plantes endémiques (une plante hyperaccumulatrice de plomb, Hirschfeldia incana et une légumineuse Hedysarum spinosissimum) (ii) d’identifier les communautés microbiennes capables de se développer sur ces différents environnements et de mieux comprendre leurs mécanismes de résistance et d’adaptation et enfin (iii) d’isoler de nouveaux microorganismes à la fois rhizosphériques et symbiotiques (présents dans les nodules de H spinosissimum) et de mieux appréhender leurs mécanismes d’action sur la croissance des plantes et la mobilisation/immobilisation des métaux et métalloïdes. Cette étude combinée des plantes et des microorganismes devrait permettre à terme de proposer une collection de plantes et de microorganismes résistants à ces polluants et susceptibles d’être des outils efficaces pour établir un programme de phytoremédiation. Elle pourrait ainsi avoir un impact sociétal important en accélérant significativement les processus de réhabilitation de ces zones contaminées. C’est un travail pluridisciplinaire qui associe à la fois des végétalistes, des microbiologistes et une géochimiste (P. Moulin, Ingénieur IRD, US IMAGO). Il a été réalisé en collaborations avec des laboratoires marocains : le Laboratoire de Microbiologie et Biologie Moléculaire (LMBM, L. Sbabou et J. Aurag) dans lequel s’effectue actuellement mon expatriation ainsi que le Laboratoire de Physiologie et Biotechnologie Végétale (LPBV, A. Smouni, M. Fahr) de l’Université de Rabat. Ce projet comprend également l’implication de partenaires français: le Laboratoire des Symbioses Tropicales et Méditerranéennes (AMPERE-LSTM, E. Navarro) ainsi que le laboratoire de Biochimie et Physiologie Moléculaire des Plantes de Montpellier (BPMP, P. Doumas, F. Auguy). Ce travail s’inscrit également dans le cadre du réseau SICMED «Environnements Miniers Méditerranéens » coordonné par P. Doumas (BPMP, Montpellier). Dans le cadre de ce projet de recherche, mon travail a essentiellement porté sur l’étude de la diversité des microorganismes et sur leur rôle dans le transfert des métaux et métalloïdes dans ces environnements extrêmes. Ce travail est réalisé dans le cadre de la thèse de I. Dahmani qui a débutée en décembre 2013 et que je coordonne avec 2 encadrants marocains, J. Aurag, L. Sbabou ainsi que E. Navarro. Ces travaux comprennent l’utilisation de nouvelles techniques de séquençage associant études taxonomiques et études fonctionnelles. L’analyse des données de pyroséquençage réalisée sur 24 sols miniers en triplicat (associant sols nus et sols rhizosphériques) est en cours par bioinformatique à l’aide du logiciel Mothur (http://www.mothur.org/wiki). Cette technique de pyroséquençage haut débit, permet d'appréhender de manière la plus exhaustive possible la diversité microbienne globale et nous permet également de pouvoir accéder à la biosphère “rare” qui semble jouer un rôle important dans l’adaptation à ces environnements pollués.

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L’étude fonctionnelle par métagénomique (travail en collaboration avec E. Navarro, AMPERE-LSTM) nous permettra d’étudier la résistance des microorganismes et les mécanismes importants impliqués dans de tels écosystèmes, comme la fixation du CO2 atmosphérique ou le métabolisme de l’azote, etc. La comparaison des métagénomes issus de divers environnements permettra une analyse de type fonctionnel (présence/absence/diversité de gènes impliqués dans les fonctions du sol). Les échantillons de l’analyse métagénomique ont été choisis parmi les 24 échantillons utilisés pour le pyroséquençage et comprennent l’étude des sols qui font l’objet d’isolements pour l’étude des bactéries PGPB (travail effectué par des membres de l’équipe LMBM) afin de pouvoir comparer l’activité des bactéries isolées à celles de l’analyse fonctionnelle. L’analyse des données du pyroséquençage a commencé a donné ses premiers résultats. Un des soucis rencontré lors de cette étude a été la génération d’un fichier conséquent (près de 5 Go pour le fichier ssh) qui n’a pas permis de réaliser l’ensemble des opérations sur ordinateur et il a fallu l’utilisation d’un serveur à distance au niveau du laboratoire de Montpellier pour finaliser les analyses. Les séquences brutes générées par la technique 454 GS-FLX Titanium auprès de la plateforme de séquence MR DNA (Molecular Research LP, Texas, EU, http://mrdnalab.com) ont été analysées en utilisant la version 1.33.2 du logiciel mothur, (http://www.mothur.org) (Schloss et al., 2009). Ces séquences ont été traitées par la commande "shhh.flows" en utilisant l'algorithme PyroNoise (Quince et al. 2009, 2011). Le prétraitement des séquences non alignées a inclus la suppression des codes barres, des deux amorces, de toutes les séquences ambigües (contenant au moins un nucléotide «N», ainsi que toutes celles qui contenaient plus de 8 homopolymères). Les séquences identiques (100%) ont ensuite été regroupées pour accélérer le traitement des données et les séquences représentatives ont été alignées sur la base de données de référence SILVA (bactéries et archées) en utilisant l'algorithme de Needleman-Wunsch (Needleman & Wunsch, 1970). Les séquences mal alignées ont ensuite été éliminées. Une autre étape de criblage (pré-cluster) a été appliquée pour réduire les erreurs dues au pyroséquençage, par regroupement des séquences qui ne présentent qu’une base de différence sur 100 pb par rapport à une séquence de référence présente en plus grand nombre dans le groupe (Huse et al., 2010). Les séquences chimériques ont été détectées et supprimées en utilisant le programme Uchime Chimera (Edgar et al., 2011) et les séquences d’Archaea ou les organites des organismes eucaryotes comme les chloroplastes ont également été retirés de l'ensemble de données. Ces analyses sont en cours et je ne m’étendrai donc pas trop dessus. Les premiers résultats montrent que l’étude des 72 échantillons de sols (24 sites en triplicat) a permis d’obtenir un total de 1545801 séquences brutes ayant une longueur moyenne d’environ 400 pb. Après le nettoyage et l’ensemble des traitements, 743501 séquences de bonne qualité (d’environ 172 pb) ont été récupérées. Après normalisation, 101 016 séquences correspondant à 6966 OTUS dont 3640 OTUs rares (représentant 52% des séquences) ont pu être identifiés.

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Table 8. Estimation de la richesse en OTUs, des indices de diversité et de la couverture estimée pour les 5 échantillons de sédiments. Les résultats sont présentés pour les données normalisées, rééchantillonnées au hasard pour avoir une taille d’échantillon égale entre les sites. Sampling stations

N° reads after quality filtering

N° of N° of a normalized OTU reads

Singletons

Good's b coverage

Chao1 Richness

Shannon c diversity

MINE DE BOUBKER OMF12BoGrRh1a OMF12ToGrRh1b OMF12ToGrRh1c OMF12BoGrRh3a OMF12BoGrRh3b OMF12BoGrRh3c OMF12BoGrNu4a OMF12BoGrNu4b OMF12BoGrNu4c OMF12BoGHRh5a OMF12BoGHRh5b OMF12BoGHRh5c OMF12BoGHNu6a OMF12BoGHNu6b OMF12BoGHNu6c OMF12BoHeRh13a OMF12BoHeRh13b OMF12BoHeRh13c OMF12BoHeRh15a OMF12BoHeRh15b OMF12BoHeRh15c

16966 15417 16215 16543 9265 6182 5796 10148 5781 15933 17654 6858 1479 2548 1403 12336 9130 16533 16622 4431 8442

1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403

428 397 433 396 362 368 132 147 123 363 390 362 10 27 26 291 280 273 336 326 322

62 40 62 43 33 25 13 18 13 43 50 31 1 2 10 27 32 26 45 36 32

82% 85% 82% 84% 87% 87% 98% 97% 98% 85% 84% 86% 100% 100% 99% 88% 89% 89% 86% 88% 88%

934 (785; 1146) 715 (617; 857) 855 (732; 1028) 769 (655; 933) 617 (535; 737) 623 (540; 745) 178 (151; 240) 198 (169; 266) 170 (141; 248) 663 (569;800) 761 (648;923) 624 (541; 746) 12 (10; 25) 33 (28;66) 92 (48; 223) 697 (550; 927) 514 (431; 642) 526 (434; 669) 760 (618;973) 555 (477;673) 534 (463; 642)

5.14 (5.06; 5.23) 5.06 (4.98; 5.15) 5.18 (5.09; 5.26) 4.92 (4.83; 5.02) 4.86 (4.77; 4.95) 4.99 (4.90; 5.07) 4.23 (4.17; 4.28) 4.36 (4.31; 4.42) 4.27 (4.22; 4.32) 4.77 (4.68; 4.86) 4.92 (4.84; 5.01) 4.83 (4.74; 4.91) 1.39 (1.36; 1.43) 2.79 (2.75; 2.83) 2.20 (2.15; 2.24) 4.56 (4.48; 4.64) 4.42 (4.33; 4.51) 4.40 (4.31; 4.49) 4.70 (4.61; 4.78 4.75 (4.66; 4.83) 4.66 (4.57; 4.74)

MINE DE TOUISSIT OMF12ToGrRh17a OMF12ToGrRh17b OMF12ToGrRh17c OMF12ToGrNu18a OMF12ToGrNu18b OMF12ToGrNu18c OMF12ToGrRh19a OMF12ToGrRh19b OMF12ToGrRh19c OMF12ToGrNu20a OMF12ToGrNu20b OMF12ToGrNu20c OMF12ToHeRh21a OMF12ToHeRh21b OMF12ToHeRh21c OMF12ToHeNu22a OMF12ToHeNu22b OMF12ToHeNu22c OMF12ToHeRh23a OMF12ToHeRh23b OMF12ToHeRh23c OMF12ToGrRh25a OMF12ToGrRh25b

13495 9853 5823 14943 15623 5824 11327 10389 9623 11811 11922 8779 13553 11746 11950 5971 15394 12936 4035 9998 7476 1775 3785

1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403

426 443 407 213 233 211 444 408 429 307 310 309 465 449 444 449 440 443 532 552 552 385 375

39 48 35 39 42 28 50 36 46 45 43 51 75 80 73 49 54 56 58 70 61 28 28

82% 82% 84% 92% 91% 93% 82% 85% 84% 88% 88% 88% 77% 80% 81% 81% 81% 81% 78% 78% 78% 86% 87%

862 (734; 1043) 901 (768; 1088) 760 (653; 913) 396 (323; 517) 441 (361; 573) 322 (277; 399) 815 (708; 965) 728 (629; 870) 740 (647; 873) 641 (526; 818) 656 (536; 839) 595 (497; 746) 1312 (1071; 1650) 1019 (857; 1246) 864 (744; 1032) 863 (745; 1028) 1026 (853; 1271) 954 (807; 1162) 1067 (923; 1264) 967 (858; 1115) 975 (864; 1126) 681 (585; 821) 576 (512; 669)

5.04 (4.95; 5.13) 5.10 (5.01; 5.19) 4.96 (4.87; 5.06) 3.93 (3.84; 4.01) 4.01 (3.92; 4.10) 4.00 (3.92; 4.09) 5.12 (5.03; 5.21) 5.12 (5.03; 5.21) 5.20 (5.12; 5.29) 4.48 (4.39; 4.57) 4.48 (4.39; 4.57) 4.48 (4.38; 4.57) 4.92 (4.82; 5.02) 4.92 (4.82; 5.02) 4.99 (4.90; 5.09) 5.20 (5.12; 5.29) 5.11 (5.02; 5.19) 5.11 (5.02; 5.20) 5.62 (5.55; 5.69) 5.72 (5.65; 5.79) 5.69 (5.62; 5.76) 4.98 (4.89; 5.07) 4.87 (4.78; 4.96)

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3707 11614 10035 8394 13447 6646 19157

1403 1403 1403 1403 1403 1403 1403

414 448 434 430 445 415 458

44 53 47 50 74 51 62

84% 82% 83% 83% 82% 84% 81%

773 (665; 929) 931 (787; 1136) 750 (658; 881) 924 (774; 1140) 792 (693; 929) 697 (613; 816) 905 (779; 1081)

5.09 (5.01; 5.18) 5.28 (5.20; 5.36) 5.18 (5.10; 5.27) 5.14 (5.06; 5.23) 5.08 (4.99; 5.17) 5.02 (4.93; 5.11) 5.13 (5.04; 5.22)

SITE DE OUED EL HEIMER OMF12OhGrRh29a 18557 OMF12OhGrRh29b 6486 OMF12OhGrRh29c 14358 OMF12OhGrNu30a 6869 OMF12OhGrNu30b 7341 OMF12OhGrNu30c 5523. OMF12OhGrRh31a 7651 OMF12OhGrRh31b 12625 OMF12OhGrRh31c 9757 OMF12OhHeRh33a 14507 OMF12OhHeRh33b 19202 OMF12OhHeRh33c 19009 OMF12OhHeNu34a 8970 OMF12OhHeNu34b 9217 OMF12OhHeNu34c 16679 OMF12OhHeRh35a 5205 OMF12OhHeRh35b 16874 OMF12OhHeRh35c 16636 OMF12OhHeNu36a 1904 OMF12OhHeNu36b 4089 OMF12OhHeNu36c 5329

1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403 1403

243 270 292 106 174 112 541 565 556 586 589 572 475 485 510 492 536 527 404 464 425

26 25 27 4 27 13 105 119 108 110 113 107 67 86 91 68 100 126 57 63 39

91% 89% 88% 96% 93% 96% 74% 73% 74% 73% 72% 74% 80% 79% 78% 80% 75% 75% 86% 82% 85%

457 (374; 594) 523 (431; 666) 576 (477; 728) 212 (157; 327) 368 (285; 513) 245 (175; 392) 1350 (1136; 1641) 1370 (1164; 1646) 1345 (1141; 1619) 1377 (1177; 1644) 1363 (1169; 1621) 1371 (1164; 1651) 1007 (856; 1217) 1003 (860; 1201) 1053 (905; 1255) 869 (766; 1009) 1238 (1056; 1485) 1260 (1065; 1525) 637 (565; 742) 838 (732; 986) 661 (590; 762)

4.40 (4.33; 4.48) 4.49 (4.41; 5.57) 4.56 (4.48; 4.64) 2.43 (2.33; 2.53) 2.86 (2.75; 2.98) 2.25 (2.13; 2.36) 5.31 (5.22; 5.41) 5.42 (5.33; 5.51) 5.37 (5.27; 5.46) 5.68 (5.60; 5.76) 5.66 (5.58; 5.74) 5.64 (5.56; 5.72) 5.38 (5.30; 5.45) 5.37 (5.29; 5.45) 5.49 (5.41; 5.57) 5.44 (5.36; 5.51) 5.46 (5.38; 5.54) 5.49 (5.41; 5.57) 5.34 (5.27; 5.41) 5.45 (5.38; 5.52) 5.35 (5.28; 5.42

OMF12ToGrRh25c OMF12ToGrNu26a OMF12ToGrNu26b OMF12ToGrNu26c OMF12ToGrRh27a OMF12ToGrRh27b OMF12ToGrRh27c

a

OTUs définis avec un seuil de 97% de similarités entre les séquences Somme des probabilités des classes observées calculées selon (1 - (n/N)), où n représente le nombre de singleton et N est le nombre total de séquences c Prend en compte le nombre et la régularité des espèces Les valeurs entre parenthèses représentent les intervalles de confiance à 95% b

L’indice de diversité de Shannon varie fortement entre les échantillons et est compris entre 1.39 et 5.72 et le taux de couverture est compris entre 72 et 100%.

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Figure 10. Composition des différents phylums basés sur la classification des séquences des gènes codants pour les ARNr16S des bactéries présents dans les 3 sites étudiés. L'affiliation des séquences est basée sur la classification RDP.

Soixante dix-sept pourcent des séquences ont pu être classées au niveau du phylum et 17 phylums ont pu être identifiés. Les Actinobacteria et les Protéobactéria sont les phylums les plus importants représentant respectivement environ 35 et 25% de l’ensemble des séquences suivi par les Bactéroidetes (7%), les Acidobactéria (5%), les Gemmatimonadetes (3%) et le groupe TM7 (environ 2%). Le reste des phylums représente moins de 1%. Les 5 genres les plus abondants sont Sphingomonas, Arthrobacter, Rubrobacter, Nocardioides et Pseudonocardia. Les genres Sphingomonas et Arthrobacter ont déjà été détectés dans des stériles miniers (Schippers et al., 2010, Chen et al., 2013). Le genre Sphingomonas est souvent retrouvé dans la phyllosphere de différentes plantes et pourrait être impliqué dans la protection de plantes comme Arabidopsis thaliana contre certains pathogènes (Innerebner et al., 2011). Plusieurs études ont également montrées l’effet bénéfique du genre Arthrobacter sur la croissance des plantes dans des environnements contaminés par des métaux et métalloïdes (Ma et al., 2011). Un important travail d'analyses statistiques et bioinformatiques bioinformatiques est maintenant nécessaire afin de décrire la diversité spécifique de chaque site, de comparer les assemblages microbiens entre les sites, de révéler les relations inter-spécifiques et d’identifier les facteurs environnementaux déterminant la composition de la communauté.

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VI. PROJET DE RECHERCHE Ces thématiques sur lesquelles j'ai acquis aujourd'hui certaines connaissances vont définir le cadre de mes recherches pour les années à venir. Je souhaite développer 3 grands volets dans le cadre de l’étude sur les environnements miniers: - Caractériser la diversité taxonomique et fonctionnelle en utilisant les nouvelles technologies de séquençages associées à des méthodes tels que la métagénomique ou la métatranscriptomique afin d’explorer la structure et la dynamique des communautés microbiennes (Bactéries, Archaea et Eucaryotes) et obtenir ainsi une vue d'ensemble de leurs potentiels métaboliques dans le but de mieux comprendre le fonctionnement de ces écosystèmes particuliers, - Continuer l’étude des interactions plantes-microorganismes initiée lors de mon expatriation qui permettent d’aider à la mise en place de solutions pratiques dans le cas de la mise en place d’un couvert végétal, - Poursuivre l’isolement de microorganismes afin de pouvoir les étudier en laboratoire ce qui permet d’avoir une meilleure connaissance de leurs réelles capacités métaboliques.

Caractérisation de la diversité taxonomique et fonctionnelle Ces dernières années, les nouvelles technologies de séquençage ont fortement accélérées les recherches en biologie et microbiologie et ont permis la production de très grands volumes de séquences en diminuant fortement les prix, comparées aux méthodes de séquençage traditionnelles (Knief et al., 2014). Ces développements récents permettent maintenant de répondre à des questions qui n’étaient pas concevables il y a seulement quelques années en raison essentiellement des limitations techniques et financières comme par exemple : qu’elles sont les communautés microbiennes présentes, que font elles, comment arrivent t’elles à se développer dans ces environnements, comment évoluent t’elles en fonction des perturbations et des changements de leurs environnements, comment interagissent elles entre elles et avec leur environnement, comment peuvent elles affecter le développement des plantes (Knief et al., 2014)? Le recours aux disciplines « méta-omiques », permet en effet d’avoir une meilleure compréhension de l'écologie microbienne. La métagénomique est par exemple devenue une des disciplines scientifiques les plus actives. Cette approche permet désormais l’analyse de communautés microbiennes qui semblaient largement hors de portée il y a encore quelques années comme les organismes non cultivés et permet d'obtenir une vue d'ensemble du potentiel métabolique des communautés présentes. Des études comme la métatranscriptomique basées sur l'expression des gènes sont également très intéressantes pour apporter de nouvelles connaissances sur la dynamique fonctionnelle des communautés microbiennes, mieux identifier les facteurs environnements qui régulent leurs activités et mettre en exergue les fonctions phares essentielles pour le fonctionnement de la communauté (Gifford et al., 2011 ; Carvalhais et al., 2012). Cependant, il faut malgré tout bien garder à l’esprit que, comme la plupart des techniques de biologie, ces technologies ne sont pas non plus exempts de biais. Concernant les études de diversité par les techniques de séquençage à haut débit (pyroséquençage ou technologie 55

Illumina, etc.), il est à noter par exemple la faible taille des amplicons générés pour l’instant ainsi que le taux important d’erreurs de séquençage, que l’utilisation de nouveaux algorithmes tente de corriger (Huse et al., 2010 ; Knief, 2014). Il reste également les biais inhérents à la biologie moléculaires comme ceux au niveau de l’extraction de l’ADN ou ceux générés lors de l’étape de PCR. L’utilisation des séquenceurs de 3ème générations permettront peut être de limiter ce dernier biais dans les prochaines années. Concernant la métagénomique par exemple, même un séquençage « en profondeur » d’un environnement ne permet d’accéder qu’à une petite fraction de la variabilité génétique réellement présente en identifiant principalement les membres les plus abondants (Gilbert and Dupont, 2011). Je souhaite, dans la poursuite de mes travaux, continuer à m’investir dans l’étude des drainages miniers acides. Comme déjà présenté précédemment, les conditions de vie extrêmes de ces environnements (pH acides, concentrations élevés en métaux et métalloïdes toxiques qui diffèrent d’un site à un autre) et les communautés simplifiées qui les caractérisent permettent d’aborder un certain nombre de questions fondamentales et contribuent à mieux comprendre la structure des communautés microbiennes et leurs profils de diversité. Mais c’est surtout l’aspect appliqué qui m’intéresse en raison de l’implication de ces organismes dans les processus de génération et/ou de remédiation de ces DMA qui peuvent avoir des applications concrètes dans de nombreux pays du Sud, en accord avec les objectifs de l’IRD. Une meilleure caractérisation de la diversité génétique mais aussi fonctionnelle de ces communautés microbiennes ainsi que l’étude de leurs interactions entre elles et avec leur environnement est en effet une étape essentielle à la compréhension du fonctionnement de ces écosystèmes pour pouvoir développer à terme des stratégies pour remédier à ces pollutions. Pour ce faire, il est également indispensable de prendre en compte l’ensemble de la communauté microbienne comprenant les organismes procaryotes et eucaryotes car, jusqu’à présent, la majorité des études réalisées sur ces écosystèmes se sont focalisées sur les bactéries. L’ancien site minier de Carnoulès, par ses caractéristiques comme les concentrations exceptionnelles en As ainsi que par la présence d’un gradient spatial de pollution résultant de processus naturels de remédiation demeurera un site d’étude important pour mes travaux, notamment dans le cadre de projets comme l’ANR ECO-TS IngECOST-DMA ou au travers de l’observatoire OSU OREME. Les projets de recherche que je souhaite développer au cours des prochaines années concerneront surtout les pays du Sud avec par exemple le Maroc, en continuation avec les travaux lancés depuis 3 ans maintenant dans le cadre de mon expatriation et pays avec lequel je souhaite poursuivre les collaborations dans le futur. L’étude des DMA va se faire par exemple dans le cadre d’un projet débuté récemment concernant les drainages de mine non pérennes présents dans un nouveau chantier, la mine de Kettara au Maroc qui se fait en association avec l’équipe de recherche E2G (R. Hakkou) de la Faculté des Sciences et Techniques de Guéliz à Marrakech. La mine de Kettara, située à environ 30 km au nord-est de Marrakech a été exploitée pour sa pyrrhotite de 1964 à 1981 et a produit 5.2 Mt de pyrrhotite concentré contenant une 56

moyenne de 29% en poids de sulfures ce qui a généré d’importants stériles miniers répartis, sans aucune protection, sur de très grande surfaces autour de la mine (Lghoul et al., 2014). C’est l’une des mines qui pose le plus de problèmes autour de Marrakech en raison notamment de la présence de ces DMA qui se forment à chaque pluie importante et qui expose directement la population du village minier de Kettara avoisinant, qui comprends environ 2000 habitants. Le climat est semi aride avec une moyenne de 250 mm de pluies annuelles qui surviennent généralement sur de courtes périodes et avec une forte intensité.

Figure 10. Présentation de la mine de Kettara: (a) localisation, (b) effluent de DMA, and (c) minéraux secondaires, (d) vue panoramique. D’après Lghoul et al. 2014

Cette mine a été extensivement étudiée comme en atteste les nombreuses publications depuis quelques années (Hakkou et al., 2008a, 2008b, 2009 ; Lghoul et al., 2014 et références citées). Ces travaux ont été réalisés en grande partie dans le cadre d’une chaire de recherche IDRC maroco-canadienne, entre l’équipe de recherche E2G (R. Hakkou) de la Faculté des Sciences et Techniques de Marrakech et l’Institut de recherche sur les mines et l’environnement (UQAT) situé à Québec au Canada. Cette étude microbiologique, se fait en partenariat avec l’équipe de recherche E2G à Marrakech dans le cadre du Master 2 de N. Mghazli qui vient de débuter (co-encadrement avec L. Sbabou du LMBM de Rabat) et qui a pour but d’identifier les communautés procaryotes (Bactéries et Archaea) présentes dans ces déchets miniers pour tenter d’identifier les communautés responsables de la génération de ces drainages miniers acides. Les prélèvements ont été réalisés sur 9 points répartis sur l’ensemble du site et une analyse par séquençage Illumina est en cours. 57

Un autre aspect de la mobilisation des métaux et métalloïdes concerne le cas particulier de l’As qui fait actuellement peser une lourde menace sur la santé de nombreuses personnes à travers le monde et ce, principalement dans les pays du Sud, où plusieurs millions de personnes consomment des eaux de boisson contaminées par ce toxique (Nordstrom, 2000 ; Jiang et al., 2013). Comme nous l’avons vu, les microorganismes sont fortement impliqués dans les processus de transfert de ce polluant dans l’environnement. Des travaux sur l’étude des transferts de l’As (d’origine minière ou géogénique, présent naturellement dans la roche) vers le milieu aquatique et les impacts sanitaires associés sont traités dans le cadre du LMI Picass-Eau (« Prédire l’Impact du Climat et des usAges sur les reSSources en Eau en Afrique SUbsaharienne"). Ce projet prévoit notamment d’aborder la question de la mobilisation de l’arsenic vers la ressource en eau sur le bassin du Nakambé au Burkina Faso. Il s’agit de déterminer les facteurs qui influencent la variabilité spatiale de l’arsenic (facteurs géologiques, hydrogéologiques, physico-chimiques et microbiologiques) dans les aquifères de la région de Ouahigouya dans le Nord du Burkina Faso et d’étudier l’implication des microorganismes dans ces systèmes et l’impact sur la santé des populations exposés. Ces travaux de recherche seront développés dans le cadre de l’ANR BALWASA (Basement aquifers for a local water service in Africa), si elle est acceptée. Cet ANR a été déposé cette année par P. Genthon, un hydrogéologue de HydroSciences. Ces travaux se feront plus spécifiquement dans le cadre du Work Package n° 3 intitulé « Arsenic contamination and health near Ouahigouya » en collaboration notamment avec F. Lalanne de l’Institut International d’Ingénierie de l’Eau et de l’Environnement et de P. Genthon.

Etude des interactions plantes–microorganismes dans un contexte de phytoremediation et de réhabilitation des environnements miniers au Maroc Le travail initié dans le cadre du projet Ec2co va se poursuivre dans les prochains mois avec un volet important concernant l’analyse métagénomique des populations bactériennes présentes dans ces environnements et se fera dans le cadre de la thèse de Ikram Dahmani en collaboration avec Isabelle Navarro (AMPERE, Lyon-LSTM, Montpellier). Cette nouvelle approche permettra de mieux comprendre comment les communautés bactériennes s’adaptent à leur environnement et interagissent avec lui (identification des gènes de résistance ou d’oxydation à l’arsenic, etc.) et comment elles peuvent affecter le développement des plantes (fixation d’azote par exemple, etc.). D’autres études sur la revégétalisation pourront également se mettre en place, par exemple sur la mine de Kettara, dans le cadre d’un projet de recouvrement de ces déchets utilisant des déchets de mines de phosphates, basiques, qui est à l’étude actuellement (Lghoul et al. 2014) afin de limiter les infiltrations d’eau et la formation de DMA. Si ce revêtement est mis en place sur l’ensemble du site, ce qui est prévu dans le cadre de la chaire, une couverture végétale devra être apportée sur le long terme. Des études de diversité et de métagénomiques permettraient d’identifier les communautés de microorganismes présentes et de mieux comprendre leurs interactions avec les plantes. Ce travail est à combiner également avec l’isolement de souches bactériennes pour étudier leurs activités bénéfiques sur les plantes naturellement présentes (solubilisation du phosphate, production de sidérophores ou d’auxine, 58

fixation d’N, etc.) afin de pouvoir proposer à terme une collection de plantes et de microorganismes résistants à ces polluants et susceptibles d’être des outils efficaces pour établir un programme de phytoremédiation.

Isolement de microorganismes et étude en laboratoire de leurs capacités métaboliques Bien que les méthodes moléculaires apportent des informations indispensables du fait qu’un faible pourcentage de microorganismes de l’environnement peuvent actuellement être cultivés en laboratoire, les méthodes culturales restent indispensables pour une meilleure connaissance des organismes et de leurs interactions réelles avec l’environnement en utilisant des études physiologiques. Des études d’isolement réalisées à Carnoulès sur les sédiments du Reigous (Delavat et al., 2012), ont par exemple souligné l’importance du maintient des méthodes culturales pour l’identification précise et la compréhension du rôle fonctionnel des microorganismes dans leurs environnements. Les études réalisées sur les souches de Thiomonas et d’Aciditiobacillus ferrooxidans ont également bien montré l’intérêt de ces travaux pour la compréhension de leur rôle réel dans l’environnement et le système de remédiation présent à Carnoulès. De plus, les méthodes culturales permettent de contourner certains biais inhérents aux approches moléculaires comme la résistance de certaines bactéries à la lyse cellulaire ou bien la difficulté à détecter les microorganismes appartenant à la biosphère rare. Dans le cadre d’une collaboration avec le laboratoire GMGM de Starsboug (P. Bertin), un projet Ec2co devrait être soumis cette année qui va spécifiquement s’intéresser, entre autre, à l’étude des microorganismes difficiles à cultiver. Ces travaux vont se focaliser plus spécifiquement sur des organismes comme Gallionella ferruginea que nous n’avons pas pu isoler pour l’instant malgré de nombreux essais ou encore pour tenter de cultiver le pseudogénome CARN1 qui semble avoir un rôle important au sein de l’écosystème et qui est retrouvé en assez grand nombre dans l’eau et les sédiments et détecté depuis l’utilisation des méthodes de séquençage à haut débit. Ce projet à pour but de trier par cytométrie les microorganismes selon des critères taxonomiques et/ou fonctionnels avant d’en séquencer le génome afin d’étudier le métabolisme de ces microorganismes ; d’isoler par des approches de culture in situ des populations non cultivées et enfin de déterminer la dynamique et l'activité des populations microbiennes en fonction des variations contrôlées des paramètres physicochimiques.

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VIII ANNEXES : SELECTION DE 5 PUBLICATIONS Bruneel O, Duran R, Casiot C, Elbaz-Poulichet F, Personné JC (200) Diversity of microorganisms in Fe-As-rich acid mine drainage waters of Carnoulès, France. Applied and Environmental Microbiology. 72, 551-556 Bruneel O, Pascault N, Egal M, Bancon-Montigny C, Goni M, Elbaz-Poulichet F, Personné J-C, Duran R (2008) Archaeal diversity in a Fe-As rich acid mine drainage at Carnoulès (France). Extremophiles. 12, 563-571 Bruneel O, Volant A, Gallien S, Chaumande B, Casiot C, Carapito C, Bardil A, Morin G, Brown Jr GE, Personné JC, Le Paslier D, Schaeffer C, Van Dorsselaer A, Bertin PN, Elbaz-Poulichet F, Arsène-Ploetze F (2011) Characterization of the active bacterial community involved in natural attenuation processes in arsenic-rich creek sediments. Microbial Ecology. 61, 793-810 Volant A, Desoeuvre A, Casiot C, Lauga B, Delpoux S, Morin G, Personné JC, Héry M, Elbaz-Poulichet F, Bertin P and Bruneel O (2012) Archaeal diversity: temporal variation in the Arsenic-Rich Creek Sediments of Carnoulès Mine, France. Extremophiles. 16, 645-657 Volant A, Bruneel O, Desoeuvre A, Héry M, Casiot C, Bru N, Delpoux S, Fahy A, Javerliat F, Bouchez O, Duran R, Bertin PN, Elbaz-Poulichet F and Lauga B (2014) Diversity and spatiotemporal dynamics of bacterial communities: physicochemical and others drivers along an acid mine drainage. FEMS Microbiology Ecology. 90, 247-263

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APPLIED AND ENVIRONMENTAL MICROBIOLOGY, Jan. 2006, p. 551–556 0099-2240/06/$08.00⫹0 doi:10.1128/AEM.72.1.551–556.2006 Copyright © 2006, American Society for Microbiology. All Rights Reserved.

Vol. 72, No. 1

Diversity of Microorganisms in Fe-As-Rich Acid Mine Drainage Waters of Carnoule`s, France O. Bruneel,1* R. Duran,2 C. Casiot,1 F. Elbaz-Poulichet,1 and J.-C. Personne´1 Laboratoire Hydrosciences Montpellier, UMR5569, Universite´ Montpellier 2, Place E. Bataillon, Case MSE, 34095 Montpellier cedex 05,1 and Laboratoire d’Ecologie Mole´culaire-Microbiologie, EA 3525, Universite´ de Pau et des Pays de l’Adour, Avenue de l’Universite´, IBEAS, BP 1155, F-64013 Pau cedex,2 France Received 14 March 2005/Accepted 28 September 2005

The acid waters (pH 2.7 to 3.4) originating from the Carnoule`s mine tailings contain high concentrations of dissolved arsenic (80 to 350 mg · literⴚ1), iron (750 to 2,700 mg · literⴚ1), and sulfate (2,000 to 7,500 mg · literⴚ1). During the first 30 m of downflow in Reigous creek issuing from the mine tailings, 20 to 60% of the dissolved arsenic is removed by coprecipitation with Fe(III). The microbial communities along the creek have been characterized using terminal-restriction fragment length polymorphism (T-RFLP) and 16S rRNA gene library analyses. The results indicate a low bacterial diversity in comparison with unpolluted water. Eighty percent of the sequences obtained are related to sequences from uncultured, newly described organisms or recently associated with acid mine drainage. As expected owing to the water chemistry, the sequences recovered are mainly related to bacteria involved in the geochemical Fe and S cycles. Among them, sequences related to uncultured TrefC4 affiliated with Gallionella ferruginea, a neutrophilic Fe-oxidizing bacterium, are dominant. The description of the bacterial community structure and its dynamics lead to a better understanding of the natural remediation processes occurring at this site. toxic, bacteria in acid mine waters may be useful in AMD bioremediation or that of some other industrial effluents. In order to develop remediation processes or optimize them, further knowledge of the bacteria living in the extreme environment of AMD is required. This study aims to investigate the microbial community of a small creek (the Reigous, present at Carnoule`s, France). The Carnoule`s mine (Fig. 1) has been inactive since 1962. Its exploitation has left about 1.5 megatons of tailings containing 0.7% Pb, 10% FeS2, and 0.2% As. The tailings are contained behind a dam. Water percolating through the tailings emerges at the base of the dam, forming the head of the Reigous creek. The head waters of the creek are characterized by low pH (2.7 to 3.4) and high concentrations of As (100 to 350 mg · liter⫺1), Fe (750 to 2,700 mg · liter⫺1), and SO42⫺ (2,000 to 7,500 mg · liter⫺1). The As and Fe behavior in creek water has been intensively studied (8, 22, 23, 24). As(III) is the dominant As type, whereas Fe occurs as Fe(II). Along the first 30 m of the creek (about 1 h of residence time), the bacterially mediated oxidation of Fe(II) leads to the coprecipitation of 20 to 60% of the dissolved As. The precipitate which contains up to 22% of As is mainly composed of As(III)-Fe(III) oxy-hydroxide in the wet season while As(V)-Fe(III) oxy-hydroxide compounds predominate in the dry season. Several phenotypes of Acidithiobacillus ferrooxidans have been isolated, and their role in the oxidation of Fe(II) and the coprecipitation of As has been demonstrated in laboratory experiments (8, 11). Additionally, Bruneel et al. (7) isolated at this site three different strains of Thiomonas spp. closely related to Thiomonas sp. strain Ynys1 able to promote As oxidation in laboratory conditions. The present study combines terminal-restriction fragment

The processing of sulfide-rich ores in the recovery of base metals, such as copper, lead, zinc, and gold, has produced large quantities of pyrite wastes (20). When exposed to rain, this material generates acid mine drainage (AMD) which contains large amounts of sulfate, iron, arsenic, and heavy metals. Despite their toxicity, such waters host organisms, both prokaryotes and eukaryotes, which are able to cope with the pollution (2, 33). Some of them have the capacity to modify the physicochemical conditions of the water either by detoxification or by metabolic exploitation. For example, efficient oxidation of As by bacteria has been reported in AMD or in chemically somewhat similar waters like those from hot springs (3, 7, 21, 25, 30). Because of their elevated Fe concentration, the development of iron-oxidizing bacteria is favored in AMD (16) where Acidithiobacillus ferrooxidans and Leptospirillum ferrooxidans are often observed (2). Owing to its ability to oxidize Fe, the bacterial consortium in AMD plays a major role in the immobilization of the elements that exhibit a strong affinity for solid Fe oxide phases such as Sr, Cs, Pb, U (14), and As (8, 24). In addition, the ability of several bacterial strains in AMD to oxidize As further contributes to reduction of its toxicity in water, because As(III) is considered to be more toxic than As(V) (28) and because arsenate adsorbs more strongly than arsenite to Fe(III) oxides and hydroxides at acidic pH (5, 26). Owing to their tolerance of heavy metals and the ability of some to promote transformations that make some metals less * Corresponding author. Mailing address: Laboratoire Hydrosciences Montpellier, UMR5569, Universite´ Montpellier 2, Place E. Bataillon, Case MSE, 34095 Montpellier cedex 05, France. Phone: 33-4-67-14-36-59. Fax: 33-4-67-14-47-74. E-mail: [email protected] -montp2.fr. 551

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FIG. 1. Map of the Carnoule`s mining site and location of sampling stations. Sampling stations were Reigous spring (S1), 3 m downstream of the spring (COWA), and 30 m downstream of the spring (COWG).

length polymorphism (T-RFLP) analysis in order to investigate the dynamics of the bacterial communities and 16S rRNA gene library analysis to identify the dominant bacterial group. MATERIALS AND METHODS Sampling procedure and physicochemical determinations in situ. Water samples for molecular analysis of microbial populations were collected in October 2002 and January 2003 in the spring and at two other locations in the creek over a distance of 30 m (Fig. 1). A volume of 200 ml of water was filtered through a sterile 0.22-␮m nucleopore filter. These filters were then transferred to a tube, frozen in liquid nitrogen, and stored at ⫺20°C until further analysis. DNA isolation. Genomic DNA was extracted from filtered water using the UltraClean Soil DNA Isolation kit according to the recommendation of the manufacturer (MoBio Laboratories, Inc.). All extracted genomic DNA samples were stored at ⫺20°C until further processing. T-RFLP analysis. Primers 8F (5⬘-AGAGTTTGATCCTGGCTCAG-3⬘) and 1489R (5⬘-TACCTTGTTACGACTTCA-3⬘) (19, 31) were used for T-RFLP analysis to assess the bacterial community structures. Forward (8F) and reverse (1489R) primers were fluorescently labeled with tetrachlorofluorescein phosphoramidite and hexachlorofluorescein phosphoramidite (E.S.G.S. Cybergene Group), respectively. The PCR amplification mixture contained 12.5 ␮l Hot Start Taq polymerase master mix (QIAGEN), 0.5 ␮l of each primer (20 ␮M), and 10 ng of DNA template. A final volume of 50 ␮l was adjusted with distilled water. 16S rRNA gene amplification reactions were cycled in a PTC200 thermocycler (MJ Research) with a hot start step at 94°C for 15 min followed by 35 cycles of 94°C for 1 min, 52°C for 1.5 min, and 72°C for 1 min, with a final extension step at 72°C for 10 min. The amount of PCR product was determined by comparison to known concentrations by the “dots method” (Smartlader; Eurogentec) after migration on agarose gel. PCR products were purified with the GFX PCR DNA purification kit (Amersham-Pharmacia).

APPL. ENVIRON. MICROBIOL. Purified PCR products (600 to 700 ng) were digested with 12 U of enzyme HaeIII or HinfI (New England Biolabs). The lengths of terminal-restriction fragments (T-RFs) from the digested PCR products were determined by capillary electrophoresis on an ABI prism 310 (Applied Biosystems). About 50 ng of the digested DNA from each sample was mixed with 10 ␮l of deionized formamide and 0.25 ␮l of 6-carboxytetramethylrhodamine size standard, denatured at 94°C for 2 min, and immediately chilled on ice prior to electrophoresis. After an injection step of 10 s, electrophoresis was carried out for up to 30 min, applying a voltage of 15 kV. T-RFLP profiles were performed using GeneScan software (ABI). Dominant operational taxonomic units represent T-RFs whose fluorescence was higher than 100 fluorescence units for at least one sample. Predictive digestions were made on the RDP web site (http://rdp.cme.msu.edu/html/index.html) using the T-RFLP Analysis Program. Cloning and restriction analysis. To further characterize the bacterial populations inhabiting the creek in each sampling period and sampling point, the bacterial diversity was analyzed by cloning PCR amplified 16S rRNA genes. For S1 and COWG, libraries were constructed for each sampling period. For COWA, a library was constructed only for October, since the comparison between October and January T-RFLP profiles showed mainly a disappearance of T-RFs in January. Bacterial 16S rRNA genes were amplified with unlabeled 8F and 1489R primers. These PCR products were cloned in Escherichia coli TOP10 using the pCR2.1 Topo TA cloning kit (Invitrogen, Inc.). Cloned 16S rRNA gene fragments were amplified using the primers TOP1 (5⬘-GTGTGCTGGAATTCGCC CTT-3⬘) and TOP2 (5⬘-TATCTGCAGAATTCGCCCTT-3⬘), located on the vector and surrounding the inserted PCR fragment, and then were digested with the enzyme HaeIII or HinfI. Restriction profiles were analyzed using 2.5% agarose gel electrophoresis (small-fragment resolution agarose; QA agarose; QBioge`ne, Inc.). Sixty clones from each library were analyzed and grouped according to their RFLP patterns (HaeIII and HinfI digestion). Only sequences from dominant groups were determined 16S rRNA gene sequencing. Partial sequences of the 16S rRNA gene (from 8 to 336 according to E. coli numbering) were determined by the dideoxy nucleotide chain termination method using a BigDye cycle sequencing kit (Applied Biosystems) on an ABI PRISM 310 Genetic analyzer (Applied Biosystems). DNA sequence analyses were performed via the infobiogen server (http://www .infobiogen.fr) by using the FASTA, BLAST, ALIGNN, and CLUSTALW programs (1, 13, 29). Phylogenetic trees were constructed by using the PHYLIP computer package (13). The confidence level of the phylogenetic tree topology was evaluated by performing 100 bootstrap replications with the SEQBOOK program.

RESULTS Bacterial community structures. The results of the T-RFLP analysis of bacterial community structure are presented in Fig. 2. The average T-RF number was relatively small (about 10) both in October and January, reflecting low bacterial diversity. The bacterial population characterized by a 216-bp (⫾ 2 bp) T-RF was generally the most abundant, except at station S1 in October. Abundance of this 216-bp T-RF generally increased between October and January, except at station COWG, where the variations were minor. Composition of bacterial communities. The most representative sequences of the dominant clones are summarized in Table 1, and the phylogenetic analysis of all the obtained sequences are presented in Fig. 3 to 5. The most abundant sequence types are positioned within the beta subdivision of the Proteobacteria (Table 1). They were recovered at all stations during both sampling periods, accounting for 5 to 28% of the clones in October and more than 65% in January. Numerous clone sequences of this group displayed around 95% homology with a sequence isolated from an acid- and iron-rich stream in the United Kingdom (GenBank accession no. AY766002) (unpublished data). The phylogenetic analyses (Fig. 3) did not allow affiliation of the clone sequences with any representative of the subdivision. The clos-

FIG. 2. Seasonal comparison of bacterial community T-RFLP fingerprints from the AMD of Carnoule`s, France, in October and January samples.

FIG. 3. Phylogenetic analysis of 16S rRNA gene sequences affiliated with the Gallionella division from the AMD of Carnoule`s, France. Clone names in boldface correspond to sequences found in October (Oct) and January (Jan) within the three stations along the Reigous Creek, S1, COWA, and COWG. 553

c

b

a

COWG

S1

COWG

S1Oct9 S1Oct7 S1Oct43 S1Oct11 COWAOct18 COWAOct77 COWGOct61 COWGOct52 S1Jan1 S1Jan50 COWGJan9 COWGJan29 COWGJan20 COWGJan58

Clone

Closest relative (postulated metabolism)

Desulfobacterium indolicum (sulfate reduction) A. ferrooxidans (sulfide/iron oxidation and iron reduction) Actinomycetales spp. (sulfide/iron oxidation) Gallionella ferruginea (iron oxidation) Gallionella ferruginea (iron oxidation) Desulfobacterium indolicum (sulfate reduction) Gallionella ferruginea (iron oxidation) Desulfobacterium indolicum (sulfate reduction) Gallionella ferruginea (iron oxidation) Desulfobacterium indolicum (sulfate reduction) Gallionella ferruginea (iron oxidation) Thiobacillus plumbophilus (sulfide oxidation) A. ferrooxidans (sulfide/iron oxidation and iron reduction) Desulfomonile tiedjei (sulfate reduction)

Phylogenetic group

␦-Proteobacteria ␥-Proteobacteria Actinobacteria ␤-Proteobacteria ␤-Proteobacteria ␦-Proteobacteria ␤-Proteobacteria ␦-Proteobacteria ␤-Proteobacteria ␦-Proteobacteria ␤-Proteobacteria ␤-Proteobacteria ␥-Proteobacteria ␦-Proteobacteria

Accession no.

AJ877944 AJ877952 AJ877956 AJ877924 AJ877926 AJ877946 AJ877929 AJ877947 AJ877934 AJ877949 AJ877935 AJ877957 AJ877953 AJ877951

Corresponds to the relative abundance of clones for each library. T-RFs correspond to expected terminal fragments with HaeIII predictive digestion. The phylogenetic group, closest relatives, and postulated metabolism and relative abundance of clones are indicated.

January

S1

October

COWA

Station

Sampling period

96 99 94 94 95 94 94 91 97 93 95 91 95 91

% Similarity

10 8 8 5 28 8 22 5 66 5 70 5 4 1

Relative abundance of clones (%)a

202 251–197 160 217 217 202 217 202 217 202 217 219 250–197 202

T-RFs (bp)b

TABLE 1. Most representative sequences of bacterial clones found in October in the three stations of the Reigous Creek (S1, COWA, and COWG) and in two stations in January (S1 and COWG)c

554 BRUNEEL ET AL. APPL. ENVIRON. MICROBIOL.

FIG. 4. Phylogenetic analysis of 16S rRNA gene sequences affiliated with the Desulfobacterium division from the AMD of Carnoule`s, France. Clone names in boldface correspond to sequences found in October (Oct) and January (Jan) within the three stations along the Reigous Creek, S1, COWA, and COWG.

est relative (91%) is Gallionella ferruginea, a neutrophilic ironoxidizing bacterium. The sequences representing the second-most abundant type are positioned within the delta subdivision of the Proteobacteria (Table 1, Fig. 4). These sequences were more abundant in October, representing 10, 8, and 5% of the clones at S1, COWA, and COWG, respectively, than in January, with 5 and 1% at S1 and COWG. In October, all the clones were similar (more than 90% similarity) to clones found in an AMD at Iron Mountain (4). In contrast, the clones of January were similar (94% similarity) to those found in a forested wetland impacted by sulfate-rich waters from coal piles (6). As for the main sequence, the phylogenetic analyses did not allow the affilia-

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The next most abundant sequence types, representing 8% of the clones at S1 in October and 4% at COWG in January (Table 1), were firmly positioned in the Acidithiobacillus ferrooxidans group (Fig. 5). Three sequences are related (99% similarity) to uncultured A. ferrooxidans KF/GS-JG36-22 (27) isolated in waste piles of a uranium mine, and one sequence was related to A. ferrooxidans DSM 2392 (Fig. 5). The next group, representing 8% of the clones at S1 in October, was associated with the Actinobacteria group, with 94% similarity with sequences recovered in forested wetland exposed to coal effluent (6). The phylogenetic analysis could not affiliate the sequence with any isolated bacterium (data not shown). The last sequence found, detected only in January at COWG, representing 5% of the clones, was firmly positioned in the Thiobacillus group with 91% similarity with T. plumbophilus DSM 6690. These strains were isolated from a uranium mine, and they grew by oxidation of H2S, galena (PbS), and H2 (10). Finally, sequences closely related to 16S rRNA genes from a chloroplast of Euglena spp. were also detected (data not shown). This was not surprising, since the 16S rRNA gene of chloroplasts is closely related to the bacterial 16S rRNA gene and therefore can be amplified by primers 8F and 1489R. Moreover, this is consistent with previous work indicating that these organisms are able to accumulate and oxidize As in the cell (9). DISCUSSION

FIG. 5. Phylogenetic analysis of 16S rRNA gene sequences affiliated with the Acidithiobacillus division from the AMD of Carnoule`s, France. Clone names in boldface correspond to sequences found in October (Oct) and January (Jan) within the three stations along the Reigous Creek, S1, COWA, and COWG. Strains in boldface (CC1, B5, B4, and B9) represent the bacteria isolated in the Carnoule`s Creek.

tion of the clone sequences with any representative of the subdivision. The closest relative was Desulfobacterium indolicum, a sulfate-reducing bacterium (18). For the clone from COWG in January that was phylogenetically distant from the others (Fig. 4), the closest relative is Desulfomonile tiedjei, a sulfate-reducing bacterium (12).

In the Reigous creek, the low bacterial diversity as revealed by molecular-based methods is consistent with the results of Baker and Banfield (2) in a similar environment. This may reflect the limited number of different electron donors and acceptors available in AMD and the toxicity of heavy metals and low pH. Numerous sequences in the libraries are related to sequences previously found in AMD, indicating that the clone libraries were not contaminated. Nevertheless, 80% of the sequences could not be closely related to cultured organisms, suggesting that they may constitute new taxa. As long as the bacterial strains were not isolated, their physiological role in the creek ecology will remain uncertain. Both molecular methods revealed that the dominant population (216-bp [⫾2 bp] T-RF) can be related to Gallionella ferruginea sequences, as indicated by predictive digestion (217 bp) and 16S rRNA gene library analyses. Gallionella ferruginea is a neutrophilic bacterium that oxidizes Fe. It has been shown to efficiently remove Fe, As(III), and As(V) in water (17). It is possible that an acid-tolerant relative of this bacterium has the ability to oxidize iron under acid pH conditions. In the creek, the abundance of this population was much more significant in January (more than 65%) than in October (less than 30%). Such variations are consistent with the occurrence of higher Fe and As precipitation rates in the rainy seasons than in other seasons, as reported by Casiot et al. (8). In addition to the Gallionella ferruginea sequences, the library analyses show the presence of other uncultured bacterial groups related to the Fe cycle, such as the Actinobacteria group. Members of this group, previously reported in AMD, are iron-oxidizing, heterotrophic,

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acidophilic bacteria capable of autotrophic growth. Some of them may play a synergistic role, removing organic carbon (4). Finally, A. ferrooxidans constituted a minor group in the Feoxidizing bacterial population contrary to expectations from previous findings based on isolation and culturing techniques (8). With respect to bacteria involved in S cycling, the sequences recovered, in addition to A. ferrooxidans, are related to members of the Desulfobacterium genera, which contains sulfatereducing bacteria (18). As the water of the Carnoule`s creek is fully oxygenated, the presence of bacteria from this group, which is characterized by anaerobic respiration, may be surprising. Nevertheless, this is in agreement with several studies that have recently reported sulfate- and iron-reducing bacteria under acidic conditions (15, 32). Considering the small population, sequence analyses indicate the presence of bacteria from the ␤ subdivision of the Proteobacteria affiliated with the Thiobacillus group. A member of this group was recently described as a galena and hydrogen oxidizer (11). A Thiomonas sp., which has been isolated and shown to be very active in the oxidation of As (7), was not detected by molecular techniques, probably reflecting its low abundance. Analyses of the most abundant clones strongly indicate that further efforts have to be exerted to fully understand AMD systems. They include isolation and identification of the organisms represented by these clones in order to define their ecophysiological roles.

APPL. ENVIRON. MICROBIOL.

10. 11.

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19. 20. 21. 22.

ACKNOWLEDGMENTS This study was financed by the project GEOMEX from the CNRS, the project Environnement Vie et Socie´te´s (CNRS-INSU), the ACIEcologie Quantitative, and the ACI-ECCODYN (French Ministry of Research). REFERENCES 1. Altschul, S. F., W. Gish, W. Miller, E. W. Myers, and D. J. Lipman. 1990. Basic local alignment search tool. J. Mol. Biol. 215:403–410. 2. Baker, B. J., and J. F. Banfield. 2003. Microbial communities in acid mine drainage. FEMS Microbiol. Ecol. 44:139–152. 3. Battaglia-Brunet, F., M.-C. Dictor, F. Garrido, C. Crouzet, D. Morin, K. Dekeyser, M. Clarens, and P. Baranger. 2002. An arsenic(III)-oxidizing bacterial population: selection, characterization, and performance in reactors. J. Appl. Microbiol. 93:656–667. 4. Bond, P. L., S. P. Smriga, and J. F. Banfield. 2000. Phylogeny of microoorgansims populating a thick, subaerial, predominantly lithotrophic biofilm at an extreme acid mine drainage site. Appl. Environ. Microbiol. 66:3842–3849. 5. Bowell, R. J. 1994. Sorption of arsenic by iron oxides and oxyhydroxides in soils. Appl. Geochem. 9:279–286. 6. Brofft, J. E., J. V. McArthur, and L. J. Shimkets. 2002. Recovery of novel bacterial diversity from a forested wetland impacted by reject coal. Environ. Microbiol. 4:764–769. 7. Bruneel, O., J.-C. Personne´, C. Casiot, M. Leblanc, F. Elbaz-Poulichet, B. J. Mahler, A. Le Fle`che, and P. A. D. Grimont. 2003. Mediation of arsenic oxidation by Thiomonas sp. in acid mine drainage (Carnoule`s, France). J. Appl. Microbiol. 95:492–499. 8. Casiot, C., G. Morin, F. Juillot, O. Bruneel, J. C. Personne´, M. Leblanc, K. Duquesne, V. Bonnefoy, and F. Elbaz-Poulichet. 2003. Bacterial immobilization of arsenic in acid mine drainage (Carnoule`s creek, France). Water Res. 37:2929–2936. 9. Casiot, C., O. Bruneel, J.-C. Personne´, M. Leblanc, and F. Elbaz-Poulichet. 2003. Arsenic oxidation and bioaccumulation by the acidophilic protozoan,

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Extremophiles DOI 10.1007/s00792-008-0160-z

ORIGINAL PAPER

Archaeal diversity in a Fe–As rich acid mine drainage at Carnoule`s (France) O. Bruneel Æ N. Pascault Æ M. Egal Æ C. Bancon-Montigny Æ M. S. Gon˜i-Urriza Æ F. Elbaz-Poulichet Æ J.-C. Personne´ Æ R. Duran

Received: 26 November 2007 / Accepted: 9 March 2008 Ó Springer 2008

Abstract The acid waters (pH = 2.73–3.4) that originate from the Carnoule`s mine tailings (France) are known for their very high concentrations of As (up to 10,000 mg l-1) and Fe (up to 20,000 mg l-1). To analyze the composition of the archaeal community, (their temporal variation inside the tailing and spatial variations all along the Reigous Creek, which drains the site), seven 16S rRNA gene libraries were constructed. Clone analysis revealed that all the sequences were affiliated to the phylum Euryarchaeota, while Crenarchaeota were not represented. The study showed that the structure of the archaeal community of the aquifer of the tailing stock is different to that of the Reigous Creek. Irrespective of the time of sampling, the most abundant sequences found inside the tailing stock were related to Ferroplasma acidiphilum, an acidophilic and ferrous-iron oxidizing Archaea well known for its role in bioleaching. Inversely, in Reigous Creek, a sequence affiliated to the uncultured Thermoplasmatales archaeon, clone YAC1, was largely dominant. This study provides a better understanding of the microbial community associated with an acid mine drainage rich in arsenic.

Communicated by J.N. Reeve. O. Bruneel (&)
N. Pascault
M. Egal
C. Bancon-Montigny
F. Elbaz-Poulichet
J.-C.Personne´ Laboratoire Hydrosciences Montpellier, UMR 5569, IRD, CNRS, Universite´s Montpellier 1 et 2, Universite´ Montpellier 2, Place E. Bataillon, Case MSE, 34095 Montpellier Cedex 05, France e-mail: [email protected] M. S. Gon˜i-Urriza
R. Duran Equipe Environnement et Microbiologie UMR CNRS 5254, IPREM, EEM, Universite´ de Pau et des Pays de l’Adour, Avenue de l’Universite´, IBEAS, BP 1155, 64013 Pau Cedex, France

Keywords Microbial diversity
Arsenic
Acid mine drainage
Mine tailings

Introduction The processing of sulfide-rich ores in the recovery of base metals such as copper, lead, zinc, and gold, has produced large quantities of pyrite wastes (Langmuir 1997). When exposed to rain, this material generates acid mine drainage (AMD) which contains large quantities of sulfate, iron, arsenic and heavy metals. Despite their toxicity, these waters are colonized by iron- and sulfur-oxidizing prokaryotes and form stable microbial communities with obligate acidophilic eukaryotes (fungi, yeasts, algae and protozoa; Johnson 1998; Zettler et al. 2002). The metabolic activities of such communities lead to solubilization (leaching) of the heavy metals from the sulfidic ores and pollution of surface and subsurface waters fed by the runoff. For several decades, bacteria-like Acidithiobacillus or Leptospirillum have been considered to be the principal acidophilic sulfur- and iron-oxidizing microorganisms in AMD. They were believed to be responsible for pyrite oxidation and for the release of associated metals. However, during the last 10 years, several studies have evidenced the presence of archaeal communities in acidic waters (Edwards et al. 2000; Dopson et al. 2004). Previously, Archaea were renowned for their ability to inhabit extreme environments and specialized niches but their widespread presence in non-extreme environments, such as marine and terrestrial soils, was also recently revealed (Chaban et al. 2006). Archaeal communities are often better adapted to low pH, high concentrations of total and ferrous iron and other

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metals, and moderately elevated temperatures than classical bioleaching mesophilic bacteria (Acidithiobacillus spp. and Leptospirillum spp.). Archaea were seen as numerically significant members in these environments (Bond et al. 2000; Edwards et al. 2000; Johnson and Hallberg 2003). Furthermore, it has been suggested that Archaea could play a major role in the generation of AMD (Baker and Banfield 2003) with oxidation of iron. Some members of the Archaea that respire As(V) like Pyrobaculum aerophilum and Pyrobaculum arsenaticum have been discovered (Huber et al. 2000; Oremland and Stolz 2003). Furthermore, Pyrobaculum arsenaticum, forms realgar (As2S2) as a precipitate under organotrophic conditions in the presence of thiosulfate and arsenate. These findings suggest that Archaea may play a significant role in the biogeochemical cycling of arsenic (Huber et al. 2000; Chaban et al. 2006). Highly acidic environments are relatively scarce worldwide and are generally associated with mining activities. The oxidation by meteoric water of the pyrite-rich wastes from the abandoned Pb–Zn Carnoule`s mine generates low pH (2.7–3.4) water containing high concentrations of As and Fe, up to 10,000 and up to 20,000 mg l-1, respectively (Casiot et al. 2003a). We previously characterized the bacterial communities and showed that populations related to sulfate-reducing bacteria and Gallionella ferruginea seem to play a key role in AMD functioning (Bruneel et al. 2005, 2006). To know how a system is structured and how it functions, we first have to address the diversity of the whole community. We used a molecular phylogenetic approach to characterize the microbial structure and infer a corresponding ecosystem function where appropriate. The aim of the present study was to investigate the archaeal community in water samples from an AMD very rich in As, to improve our understanding of the implication of these microorganisms in AMD functioning. This is the first molecular analysis of the archaeal community present in the Carnoule`s mine system.

The source of the Reigous Creek, now located at the foot of the dike retaining the mining spoil, is acid (pH 2.7–3.4) and very rich in dissolved arsenic and iron (80–350 and 750–2,700 mg l-1 respectively, Leblanc et al. 2002) predominantly in their reduced forms: As(III) and Fe(II). The water discharge is comprised between 0.8 and 1.7 l s-1. In the Reigous Creek, As(III) is the dominant As species whereas Fe occurs as Fe(II). Along the first 30 m of the creek (about 1 h residence time), the microbial mediated oxidation of Fe(II) leads to the coprecipitation of 20–60% of the dissolved As. As-rich (up to 20%) yellow sediments cover the bottom of the creek. The precipitate is mainly composed of amorphous Fe(III)–As(III) associated with tooeleite, a rare nanocrystal mineral of Fe(III)–As(III) during the winter period and with amorphous Fe(III)– As(V) the rest of the year (Casiot et al. 2003b; Morin et al. 2003). Bacteria play an essential role in the oxidation of Fe and As (Casiot et al 2003b). Bacterial diversity is lower than in unpolluted water. Sequences related to G. ferruginea, a neutrophilic Fe-oxidizing bacterium, are dominant (Bruneel et al. 2006). The biogeochemical processes that occur in the Carnoule`s spoil heaps are more complex than those in the creek. The general hydrochemistry and aquifer hydrodynamics have already been broadly characterized (Koffi et al. 2003; Casiot et al. 2003a). The spoil heaps are covered by an impermeable layer of clay which prevents rainwater percolation from the surface towards the unsaturated zone. The aquifer originates from former natural springs that were buried under the tailings (Koffi et al. 2003). Therefore, the primary region of oxidation is located at the base of the tailing, where the oxygen rich rainwater can penetrate directly. The dominant organisms (27–65%) are related to Desulfosarcina variabilis a sulfate-reducing bacterium. Acidithiobacillus ferrooxidans represent the second most important group (8–14%). Cultivable bacterial strains of A. ferrooxidans and Thiomonas (shown to be very active in the oxidation of As) were identified both in the tailing stock and in the Reigous Creek (Bruneel et al. 2003).

Materials and methods Sampling and analysis Description of the study site The lead and zinc mine of Carnoule`s, which has been abandoned since 1963, produced 1.2 MT of spoil material containing sand, sulfide minerals, heavy metals (Pb, Zn, Tl) and metalloids (As, Sb). The material is deposited in the middle of and across the upstream part of a creek (the Reigous) at the site of its natural spring. The Reigous collects downstream seepage waters from the surroundings before joining, at 1.5 km, the relatively pristine Amous river.

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Three surveys were carried out in November 2004, April 2005, and September 2005 in the tailing stock. Groundwaters were collected in a borehole (S5, between 10 and 12 m deep) located in the center of the tailings. Samples were also taken along the Reigous Creek, (collecting downstream seepage waters from the surroundings) in November 2005, at the spring (S1), 30 m downstream from the spring (station COWG), 150 m downstream (COWS), and 1,500 m (CONF) upstream from the confluence between the Reigous and the Amous river. Water samples

Extremophiles

(300 ml) were filtered through sterile 0.22 lm Nuclepore filters that were then transferred to cryotubes, frozen in liquid nitrogen, and stored at -80°C until further analysis. The main physicochemical parameters [pH, T°C, dissolved oxygen (DO), etc.] were measured at the sampling points. Measurements of pH and water temperature were made in the field with an Ultrameter Model 6P (Myron L 125 Company, Camlab, Cambridge). Water samples were immediately filtered through 0.22 lm Millipore membranes fitted on Sartorius polycarbonate filter holders. Samples for total Fe and As determination were acidified to pH = 1 with HNO3 (14.5 M), and stored at 4°C in polyethylene bottles until analysis. The samples for Fe and As speciation and sulfate determination were stored in the dark and analyzed within 24 h. DNA isolation Genomic DNA was extracted from filtered water using the UltraClean Soil DNA Isolation Kit according to the recommendations of the manufacturer (MoBio Laboratories Inc., USA). All the extracted genomic DNA samples were stored at -20°C until further processing. PCR amplification Amplification of archaeal 16S rRNA genes was obtained using primers Arch21F (50 -TTCCGGTTGATCCYGCCG GA-30 ) and Arch958R (50 -YCCGGCGTTGAMTCCAA TT-30 ) (Delong 1992). The PCR amplifications were performed as previously described (Bruneel et al. 2006). The amount of PCR product was determined by comparison to known concentrations after migration on agarose gel. Archaeal 16S rRNA gene library analysis Archaeal 16S rRNA gene libraries were constructed to characterize the archaeal populations. Archaeal 16S rRNA genes were amplified with Arch21F and Arch958R primers. These PCR products were cloned in E. coli TOP 10 using the pCR2.1 Topo TA cloning kit (Invitrogen, Inc.), according to the manufacturer’s instructions. Cloned 16S rRNA gene fragments were reamplified using the primers TOP1 (50 -GTGTGCTGGAATTCGCCCTT-30 ) and TOP2 (50 -TATCTGCAGAATTCGCCCTT-30 ) located on the vector and surrounding the inserted PCR fragment, and then digested with the enzymes HaeIII or HinfI. Restriction profiles were analyzed using 2.5% agarose gel electrophoresis (small-fragment resolution agarose; QA agarose, QBioge`ne, Inc.). Around 60–70 clones from each library were analyzed and grouped according to their RFLP patterns (HaeIII and HinfI digestion). The sequences of clones from dominant groups were determined.

16S rRNA gene sequencing Partial sequences of the 16S rRNA gene were determined by the dideoxy nucleotide chain-termination method using the BigDye 3.1 kit (Applied Biosystems) on an ABI PRISM 3730XL Genetic analyzer (Applied Biosystems). Sequences were checked for chimeras using the CHIMERA CHECK function of the Ribosomal Database Project II (Maidak et al. 2001). DNA sequence analyses were performed using the BLAST, ALIGNN, and CLUSTALW programs (Altschul et al. 1990; Felsenstein 1993; Thompson et al. 1994). A phylogenetic tree was constructed using the PHYLIP computer package (Felsenstein 1993). The confidence level of the phylogenetic tree topology was evaluated by performing 100 bootstrap replications with the SEQBOOK program. All the sequences obtained were submitted to the EMBL databases under accession numbers AM765808 to AM765809 and AM778965 to AM778977. Chemical analysis The determination of total dissolved As was performed by hydride generation atomic fluorescence spectrometry (HGAFS). Analyses of As species were carried out using coupled anion-exchange chromatography–HG-AFS. This method, described by Bohari et al. (2001), has a detection limit of 2.3 nM for As(III) and 6.1 nM for As(V). The precision is better than 5%. Total dissolved Fe was determined by flame atomic absorption spectrometry. Fe(II) was determined using colorimetry at 510 nm after complexation with 1,10-phenanthrolinium chloride solution in buffered samples (pH 4.5) (Rodier et al. 1996). The detection limit is 0.2 lM and the precision better than 5%. The sulfate concentration was determined after precipitation of BaSO4 with BaCl2 and spectrophotometric measurement at 650 nm. Rarefaction analysis, diversity index, and coverage values PAST (PAleontological STatistics v 1.19) software from the website http://folk.uio.no/ohammer/past/ was used for different diversity indices (Rarefaction analysis, Taxa, Total clones, Singletons, Dominance, Coverage, Shannon, Equitability, and Simpson) for each clone library. To perform rarefaction analysis, the total number of clones obtained compared with the number of clones representing each unique phylotype was used to produce the rarefaction curves. Coverage values were calculated to determine how efficiently the libraries described the complexity of a theoretical community like an original archaeal community. The coverage (Good 1953) value is given as

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Results

and 20,000 mg l-1 for As and Fe, respectively) in the tailing stock (Casiot et al. 2003a) and from 80 to 350 mg l-1 for As, 750 to 2,700 mg l-1 for Fe, and 2,000 to 7,500 mg l-1 for sulfate in the head waters of the Reigous creek (Leblanc et al. 2002).

Aqueous chemistry

Composition of archaeal communities

The physicochemical composition of the water is presented in Table 1. The pH inside the piezometer was between 3.73 and 5.78. The temperature varied from 15.5 to 20.6°C and was relatively stable throughout the year (Koffi et al. 2003). The DO was quite low particularly in April 2005 (between 0.1 and 0.2 mg l-1). The concentration of As inside the tailing stock varied greatly. As(III) was predominant, comprised between 78 and 277 mg l-1, and As(V) varied between 42 and 66 mg l-1. The concentration of Fe(II) (Fe(III) not detected, data not shown) varied greatly, i.e. between 778 and 1,299, and sulfate between 3,264 and 4,195 mg l-1. The concentrations of As(III), Fe and SO42- were highest in November 2004. In the Reigous creek, the 2.5 pH at the spring increased along the creek to reach 3.43 at COWS and 3.25 just before the confluence with the Amous (CONF), 1.5 km away. The DO content was 1 mg l-1 in the spring but it increased along the creek to reach 5–6 at COWS and 3–4 mg l-1 at CONF. Dissolved As and Fe concentrations decreased at varying degrees along the course of the creek, (30 mg l-1 for As(III), 39 mg l-1 for As(V), 879 mg l-1 for Fe(II) and 4,388 mg l-1 for sulfate at the spring station (S1) but only 0.53 for As(III and V), 25 mg l-1 for Fe(II) and 749 for sulfate at the CONF station. These elements are removed by coprecipitation with Fe(III). This process results from bacterially mediated As- and Fe-oxidation (Casiot et al. 2003b). Furthermore, the increase in pH as a result of dilution by unpolluted tributaries after COWG also contributes to an increase in As and Fe precipitation. During this sampling period, the concentrations of As, Fe and SO42- were not particularly high in comparison to the concentrations usually found in these waters (up to 10,000

16S rRNA gene library analyses were performed to identify the dominant groups of archaeal populations. The most representative sequences of the dominant clones are summarized in Table 2 and the phylogenetic filiations of the sequences obtained are presented in Fig. 1. DNA could be extracted from all sampling sites except the S5 borehole in November 2005. In the Carnoule`s mine drainage, numerous sequences in the libraries are related to sequences previously found in AMD, showing that the clone libraries were not contaminated. Clones analysis revealed that all the sequences were affiliated to the phylum Euryarchaeota, while Crenarchaeota were not represented. The most abundant sequence types present in the water of the tailing (S5) displayed from 99 to 100% homology with Ferroplasma acidiphilum strain DR1, that was detected in microbial consortia from AMD and in industrial bioleaching environments (Dopson et al. 2004, AY22042). They were recovered in the groundwater in November 2004 and April 2005, representing a large majority of the clones (65–72%). The second most abundant group (9% in November 2004 but 65% in September 2005) was similar (99–100%) to the uncultured archaeon clone ant h4 (Table 2, Fig. 1) found in two anaerobic sludges (DQ462728, unpublished). The sequences representing the second most abundant type in April 2005 (15%) were similar (91%) to clones of the uncultured archaeon clone YAC1 (Table 2, Fig. 1) found in communities of different hot springs (DQ237924, unpublished). In September 2005, the second most important group (20%), (Table 2), was related to the uncultured archaeon clone ASL1 found in AMD (Baker and Banfield 2003; AF544224).

C = 1 - (n1/N) where n1 is the number of clones that occurred only once in the library.

Table 1 Physico-chemical characteristics of the water (mg l-1) during the sampling in S5, S1, COWG, COWS and CONF Sampling station

Sampling period

pH (±SD)

T (°C)

DO (±SD)

As(III) (±SD)

As(V) (±SD)

Fe (II) (±SD)

SO42- (±SD)

Tailing stock

November 2004

5.78 (±0.05)

15.5

2

277 (±14)

42 (±2)

1299 (±104)

4195 (±420)

Reigous Creek

S5

S1

April 2005

4.05 (±0.05)

17.3

0.1–0.2

128 (±6)

66 (±3)

784 (±62)

3264 (±326)

September 2005

3.73 (±0.05)

20.6

4–5

78 (±4)

53 (±3)

778 (±62)

3629 (±363) 4388 (±441)

2.5 (±0.05)

14.6

1

30.0 (±0.8)

39 (±2)

879 (±70)

COWG

November 2005

2.74 (±0.05)

10.6

5–6

22.0 (±0.8)

22.0 (±0.8)

501 (±40)

1785 (±182)

COWS

3.43 (±0.05)

7.2

5–6

4.5 (±0.2)

1.50 (±0.08)

95 (±8)

902 (±90)

CONF

3.25 (±0.05)

6.7

3–4

0.53 (±0.02)

0.53 (±0.02)

25 (±2)

749 (±75)

SD Standard deviation

123

Extremophiles Table 2 Archaeal clones found in Carnoule`s mine drainage with closest match organism or clone name, percent similarity, phylogenetic group, closest relative and percent number of each group compared to the total number of clones Sampling station

Tailing stock

S5

Sampling period

Clones

Phylum

Closest relative (accession number)

Number of bp identical and % similarity

Relative abundance of clones (%)a

November 2004

S5Nov04 73

Euryarchaeota

100

72

S5Nov04 82

Euryarchaeota

100

9

S5Apr05 12

Euryarchaeota

F. acidiphilum strain DR1 (AY222042) Uncultured archaeon clone ant h4 (DQ303256) F. acidiphilum strain DR1 (AY222042)

99

65

S5Apr05 47 S5Apr05 45

Euryarchaeota

99 91

15

S5Sep05 53

Euryarchaeota

99

65

S5Sep05 56

Euryarchaeota

97

20

S1Nov05 90

Euryarchaeota

99

54

S1Nov05 58

Euryarchaeota

93

21

CGNov05 19

Euryarchaeota

93

59

CGNov05 94 CGNov05 32

Euryarchaeota

93 100

4

CSNov05 10

Euryarchaeota

92

93

CSNov05 20

Euryarchaeota

99

6

CFNov05 6

Euryarchaeota

94

74

April 2005

September 2005

Reigous Creek

S1

COWG

COWS

CONF

a

November 2005

Uncultured archaeon clone YAC1 (DQ237924) Uncultured archaeon clone ant h4 (DQ303256) Uncultured archaeon clone ASL1 (AF544224) F. acidiphilum strain DR1 (AY222042) Uncultured archaeon clone YAC1 (DQ237924) Uncultured archaeon clone YAC1 (DQ237924) F. acidiphilum strain DR1 (AY222042) Uncultured archaeon clone YAC1 (DQ237924) Uncultured archaeon clone ant g10 (DQ303253) Uncultured archaeon clone YAC1 (DQ237924)

The abundance of clones was calculated for each library

In the Reigous creek during the sampling campaign in November 2005, the most abundant group (21% at the spring S1, 59% at COWG, 93% at COWS and 74% at CONF) was related (92–94%) to the uncultured archaeon clone YAC1. These clones were found in low abundance (15%) in the groundwater and only in April 2005. The second most abundant group in the creek was similar (99– 100%) to F. acidiphilum, also numerically significant members in Carnoule`s tailing stock. The abundance of this group decreased along the creek, representing 54% of the clones at the spring S1, but only 4% at COWG and was undetected at COWS and CONF. The least abundant sequences (6%) found only at the COWS station was

related (99% similarity) to the uncultured archaeon clone ant g10 isolated in macroscopic filaments from an extremely acidic environment, Tinto River (DQ303253, unpublished). Phylogenetic analyses (Fig. 1) did not enable affiliation of the clone sequences with any representative of the subdivision. The closest relative (91%) was Thermoplasma sp. SO2 (AB262009, unpublished). Rarefaction analysis, diversity index and coverage values of the clone libraries analyzed Table 3 shows Dominance, Shannon, Equitability, Simpson index and Coverage values calculated for each library.

123

Extremophiles Fig.1 Phylogenetic analysis of 16S rRNA gene sequences affiliated with Archaea members from the AMD of Carnoule`s (France). Clone names in bold correspond to sequences found in the Carnoule`s mine drainage

S5Apr05 12 (AM778965) S1Nov05 90 (AM778970) CGNov05 32 (AM778974) Ferroplasma acidiphilum strain DR1 (AY222042) Ferroplasma acidiphilum strain YT DSM 12658T (AJ224936) Uncultured archaeon ASL32 (AF544222) 57

S5Nov04 73 (AM765808) Uncultured archaeon ant c8 (DQ303251) S5Apr05 47 (AM778966) Ferroplasma acidarmanus (AF145441)

76

Uncultured archaeon ant c7 (DQ303250) Ferroplasma sp. MT17 (AF513710) Uncultured archaeon ant h10 (DQ303255) S5Sep05 53 (AM778968)

97 63

S5Nov04 82 (AM765809) Uncultured archaeon ant h4 (DQ303256)

Ferroplasma sp. JTC3 (AY830840) 76 71

Uncultured archaeon MS14 (AF232925) Ferroplasma cyprexacervatum (AY907888)

Thermoplasma volcanium (AF339746) Thermoplasma sp. S02 (AB262009) Uncultured archaeon ASL1 (AF544224)

29 75 29

38

Uncultured archaeon ARCP1-28 (AF523940) Uncultured archaeon ant g4 (DQ303254) S5Sep05 56 (AM778969)

17

Uncultured archaeon ant g10 (DQ303253) CSNov05 20 (AM778976)

65 99

Uncultured archaeon AS1 (AF544219) Uncultured archaeon ant b7 (DQ303249)

Unidentified archaeon pISA42 (AB019742)

53

Uncultured euryarchaeote pLM14A-1 (AB247822) Uncultured Thermoplasmatales archaeon OPPD020 (AY861955) Uncultured archaeon YAC1 (DQ237924) 50 66

CFNov05 6 (AM778977)

49

CGNov05 94 (AM778973) 95

S1Nov05 58 (AM778971) CGNov05 19 (AM778972)

37

8

S5Apr05 45 (AM778967)

16

CSNov05 10 (AM778975)

Archaeoglobus fulgidus strain VC-16 (X05567) Sulfolobus solfataricus (D26490) Sulfurisphaera ohwakuensis DSM 1242T (D85507)

50 96 76 53 61

Metallosphaera hakonensis (D86414) Acidianus infernus DSM 3191T (D85505) Acidianus ambivalens DSM 3772T (D85506)

Uncultured archaeon PMA5 (DQ399817) Uncultured archaeon ZAR100 (AY341269) Acidithiobacillus caldus (X72851) 0.05

To estimate diversity coverage and to determine whether a sufficient number of clones from each library had been sequenced, rarefaction analysis was performed. The generated curves were near saturation (data not shown), consistent with the high coverage values (between 0.82 and

123

0.93). In November 2005, the COWS library showed lower diversity indices (Shannon: 0.5704; Simpson: 0.2397) than the other libraries (Shannon ranging from 1.151 to 1.604; Simpson from 0.4488 to 0.6545). Inversely, in November 2005, the COWS library presented a higher Dominance

Extremophiles Table 3 Diversity indices calculated for the seven clone libraries from different stations in Carnoule`s mine drainage Clone library S5 November 2004

Taxa

Total clones

Singletons

Dominance

Coverage(C)

Shannon (H)

Equitability

Simpson (1-D)

9

66

5

0.4913

92

1.151

0.5241

0.5087

S5 April 2005

11

66

6

0.4564

90

1.277

0.5323

0.5436

S5 September 2005

10

61

6

0.4512

90

1.234

0.5361

0.5488

S1 November 2005

14

57

10

0.3456

82

1.604

0.6077

0.6545

COWG November 2005

13

69

9

0.3989

86

1.424

0.5552

0.6011

COWS November 2005 CONF November 05

6

61

4

0.7603

93

0.5704

0.3183

0.2397

12

61

6

0.5512

90

1.189

0.4785

0.4488

index (0.7603) than the other libraries (from 0.3456 to 0.5512).

Discussion In the AMD site of Carnoule`s, more than 65% of the archaeal sequences could not be closely related to cultured organisms, suggesting that they may constitute new taxa. Only sequences close to F. acidiphilum were related to cultured organisms. Rarefaction data and percent coverage calculations suggested that the archaeal 16S rRNA gene libraries reach saturation. Whatever the sampling period, the water of S5 inside the tailing stock, where intensive pyrite oxidation takes place, was numerically dominated by sequences clearly related to F. acidiphilum, or to the uncultured clone ant h4 which showed more than 98% similarity with F. acidiphilum. This isolate was an acidophilic, mesophilic, ferrous-iron oxidizing, cell-wall lacking microbe that became the basis of a new archaeal lineage: the new genus Ferroplasma within the new family Ferroplasmaceae, in the order Thermoplasmatales, which includes the families Thermoplasmaceae and Picrophilaceae (Golyshina and Timmis 2005). These two populations represented 81% of clones in November 2004, 65% in April 2005, and 65% in September 2005. Previous analysis of the bacterial community in the Carnoule`s tailing showed that the dominant population was related to the sulfate-reducing bacteria Desulfosarcina variabilis (Bruneel et al. 2005). This population could not clearly explain the leaching of the Carnoule`s tailing as it is well known that it was mostly acidophilic ferrous iron-oxidizing microorganisms that were found to be involved in the production of acid mine drainage (Baker and Bandfield 2003). Iron oxidizing bacteria like A. ferrooxidans and Sulfobacillus spp. were also present in the Carnoule`s mine tailing but represented a minor population (Bruneel et al. 2005). Thus, F. acidiphilum could explain the intensive leaching observed in the Carnoule`s tailing and the high concentration of As, up to 10,000 mg l-1, one of the highest concentrations reported

in the world. Furthermore, some strains of this genus like Ferroplasma acidarmanus Fer1 was shown to be an arsenic-hypertolerant acidophilic archaeon (Gihring et al. 2003; Baker-Austin et al. 2007). This strain, isolated from the Iron Mountain mine, California, was able to grow with up to 10 g arsenate per litre but his growth was reduced with 5 and 10 g of arsenite per litre. This population, which is more acid-resistant than iron- and sulfur-oxidizing bacteria, is in fact known to mobilize metals from sulfide ores, e.g. pyrite, arsenopyrite and copper-containing sulfides. According to Golyshina and Timmis (2005) Ferroplasma spp. are probably the major players in the biogeochemical cycling of sulfur and sulfide metals in highly acidic environments, and may have considerable potential for biotechnological applications such as biomining and biocatalysis under extreme conditions. These results are consistent with those of Edwards et al. (2000) at the Iron Mountain acid-generating site (United State), where the microbial community is dominated (85%) by an archaeon of the genus Ferroplasma. For these authors, the presence of this population and other closely related Thermoplasmatales suggests that these acidophiles are important contributors to acid mine drainage and may substantially impact iron and sulfur cycles. The growth of F. acidiphilum occurs between 20 and 45°C with an optimum at 35°C and at pH 1.3–2.2 with an optimum at pH 1.7 (Golyshina et al. 2000). Surprisingly, we detected this population in a less acidic environment (3.73–5.7). Isolation and characterization of members of this population are needed to determine their physiological capabilities especially at the pH range found in Carnoule`s waters. The clone sequences from the Reigous Creek were related to the same groups detected in the tailing S5 but the abundance of each varied. The dominant population in the Reigous Creek (21% of total clones at the spring S1, 59% at COWG, 93% at COWS and around 74% CONF) was related to the uncultured archaeon clone YAC1 found in communities in different hot springs. Phylogenetic analyses (Fig. 1) did not enable affiliation of the clone sequences with any cultured representative of the subdivision and this clone could thus represent a new species. The closest

123

Extremophiles

relative (91%) was the uncultured Thermoplasmatales archaeon found in the Yellowstone geothermal ecosystem (Spear et al. 2005). The order Thermoplasmatales includes the families Ferroplasmaceae, Thermoplasmaceae and Picrophilaceae (Golyshina and Timmis 2005). The known members of the Thermoplasmales are all acidophilic. Some groups, like the family Ferroplasmacea within this order, are capable of iron oxidation (Edwards et al. 2000; Golyshina and Timmis 2005). A previous study of bacterial populations in the Carnoule`s creek showed that the dominant bacterial population was related to G. ferruginea, a neutrophilic bacterium that oxidizes Fe (Bruneel et al. 2006). Consistent with previous observations demonstrating that G. ferruginea efficiently remove As (III and V) in water by coprecipitation with Fe (Katsoyiannis and Zouboulis 2004), this population may play a key role in the remediation process observed in the Reigous creek (Casiot et al. 2003b). If the uncultured archaeon clone YAC1 oxidizes Fe, this population could play a role in the natural remediation processes occurring in the Reigous Creek in association with G. ferruginea, but until the archaeal strains are isolated, their physiological role in the creek ecology will remain uncertain. Environmental genome data like those obtain with analysis of assembled random shotgun sequence data can also provide detailed insight into the metabolic potential of uncultivated organisms (Tyson et al. 2005). Our study demonstrated the existence of a complex prokaryotic community in the Carnoule`s AMD where bacterial and archaeal populations are present. Both phylotype communities were significantly altered in terms of size and structure with microhabitats varying inside the AMD particularly in underground water from the tailing and in the Reigous and the small creek draining the site. The occurrence of different dominant communities is likely associated with the formation of environmental gradients of temperature, pH, oxidation–reduction potential, etc. Other methods such as fluorescence in situ hybridization (FISH) will help to clearly assess the relative proportion of population. However, this method has not been widely applied to samples of thermophilic archaea and may be limited by cross-hybridization. Furthermore, methods such as metagenomic research (study of the entire genetic composition of communities of an environment) could help to study the total diversity, physiology, ecology and phylogeny of microbial population but all of the approaches that are available today have advantages and limitations (Pontes et al. 2007). Only, the isolation of archaeal strains at the Carnoule`s mine will extend our understanding of the ubiquity of archaea in such environments, and help elucidate the microbial component driving the biogeochemical processes present in this and other extreme AMD sites.

123

Acknowledgments The study was financed by the EC2CO programme (Institut National des Sciences de l’Univers, CNRS). We thank Marjorie Cloez for identification of the archaeal population in the site, and Marie Ange Cordier for assistance in analysis of physical–chemical parameters.

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Microb Ecol (2011) 61:793–810 DOI 10.1007/s00248-011-9808-9

ENVIRONMENTAL MICROBIOLOGY

Characterization of the Active Bacterial Community Involved in Natural Attenuation Processes in Arsenic-Rich Creek Sediments Odile Bruneel & Aurélie Volant & Sébastien Gallien & Bertrand Chaumande & Corinne Casiot & Christine Carapito & Amélie Bardil & Guillaume Morin & Gordon E. Brown Jr & Christian J. Personné & Denis Le Paslier & Christine Schaeffer & Alain Van Dorsselaer & Philippe N. Bertin & Françoise Elbaz-Poulichet & Florence Arsène-Ploetze

Received: 7 August 2010 / Accepted: 20 January 2011 / Published online: 12 February 2011 # Springer Science+Business Media, LLC 2011

Abstract Acid mine drainage of the Carnoulès mine (France) is characterized by acid waters containing high concentrations of arsenic and iron. In the first 30 m along the Reigous, a small creek draining the site, more than 38% of the dissolved arsenic was removed by co-precipitation

with Fe(III), in agreement with previous studies, which suggest a role of microbial activities in the co-precipitation of As(III) and As(V) with Fe(III) and sulfate. To investigate how this particular ecosystem functions, the bacterial community was characterized in water and sediments by

Electronic supplementary material The online version of this article (doi:10.1007/s00248-011-9808-9) contains supplementary material, which is available to authorized users. O. Bruneel (*) : A. Volant : C. Casiot : A. Bardil : C. J. Personné : F. Elbaz-Poulichet Laboratoire HydroSciences Montpellier, UMR5569 (CNRS-IRD-Universités Montpellier I et II), Université Montpellier II, CC MSE, Place Eugène Bataillon, 34095 Montpellier Cedex 05, France e-mail: [email protected]

G. E. Brown Jr Surface and Aqueous Geochemistry Group, Department of Geological and Environmental Sciences, Stanford University, Stanford, CA 94305-2115, USA

B. Chaumande : P. N. Bertin : F. Arsène-Ploetze Génétique Moléculaire, Génomique Microbiologie, UMR7156, Université de Strasbourg/CNRS, 28 rue Goethe, 67083 Strasbourg Cedex, France

G. E. Brown Jr Stanford Synchrotron Radiation Laboratory, SLAC, 2575 23 Sand Hill Road, MS 69, Menlo Park, CA 94025, USA

S. Gallien : C. Carapito : C. Schaeffer : A. Van Dorsselaer Laboratoire de Spectrométrie de Masse Bio-organique, Institut Pluridisciplinaire Hubert Curien, UMR7178 (CNRS-Université de Strasbourg), 25 rue Becquerel, 67087 Strasbourg, France

D. Le Paslier Génomique Métabolique, UMR8030, CNRS, 2 rue Gaston Crémieux, 91057 Evry Cedex, France

G. Morin Institut de Minéralogie et de Physique des Milieux Condensés (IMPMC), UMR7590 (CNRS - Universités Paris 6&7 - IPGP), 140, rue de Lourmel, 75015 Paris, France

D. Le Paslier Commissariat à l’Energie Atomique (CEA), Direction des Sciences du Vivant, Institut de Génomique, Genoscope, Laboratoire de Génomique Comparative, 2 rue Gaston Crémieux, 91057 Evry Cedex, France

794

16S rRNA encoding gene library analysis. Based on the results obtained using a metaproteomic approach on sediments combined with high-sensitivity HPLC-chip spectrometry, several GroEL orthologs expressed by the community were characterized, and the active members of the prokaryotic community inhabiting the creek sediments were identified. Many of these bacteria are β-proteobacteria such as Gallionella and Thiomonas, but γ-proteobacteria such as Acidithiobacillus ferrooxidans and α-proteobacteria such as Acidiphilium, Actinobacteria, and Firmicutes were also detected.

Introduction Acid Mine Drainage (AMD) is one of the most serious forms of water pollution in industrial and post-industrial areas worldwide [38]. AMD is generated when the wastes from the mining and processing of sulfide ores (such as pyrite or arsenopyrite) come into contact with oxygenated water [5]. AMD is often characterized by pH values of 2–4. Such waters generally contain high levels of iron, toxic metals (such as aluminum, manganese, lead, cadmium, and zinc), and metalloids (arsenic) [5, 32, 48]. AMD can still occur hundreds of years after mine closure and tens of thousands of kilometers of groundwater, streams, lakes, and estuaries throughout the world have been directly impacted [40]. In several cases of AMD, natural remediation has been observed, as for example at the Carnoulès site in France and the Rio Tinto site in Spain [18, 53]. In such AMD, toxic compounds are accumulated in sediments consisting of a variety of iron (oxyhydr)oxides and hydroxysulfates such as jarosite, schwertmannite, and ferrihydrite [48]. Natural remediation of metal pollutants is generally due to the occurrence of abiotic reactions and/or microbial activities that make these toxic compounds insoluble and lead them to accumulate in sediments [32, 40]. This toxic compound precipitation processes mainly involve the oxidation and precipitation of iron, which is often the main soluble metal present in AMD, and the adsorption of other metals and metalloids by the ferric minerals formed [32, 51]. Indeed, many elements such as Sr, Cs, Pb, U, and As show a strong affinity for solid iron oxide [18, 27, 48]. Abiotic oxidation of Fe(II) proceeds very slowly in acidic (pH 3.5) waters [51]. In contrast, iron-oxidizing bacteria catalyze the reaction and thus accelerate the formation of solid iron oxide [32, 41, 51]. In addition, several bacteria contribute to the immobilization of arsenic via their ability to oxidize this metalloid [6, 14, 18, 22, 48], arsenate (As(V)) being adsorbed more strongly than arsenite (As(III)) by Fe(III) oxides and hydroxides at acidic pH levels [10]. Thiomonas strains show a high arsenite oxidation capacity, and these metabolic activities have been extensively analyzed under laboratory conditions [6, 14, 22].

O. Bruneel et al.

However, to be able to develop remediation processes and/or optimize existing processes, further knowledge is required about how these bacteria function in situ. In particular, it is of crucial importance to determine which bacteria are viable and active in such ecosystems. The AMD of Carnoulès mine in Southern France is a highly suitable site for analyzing how microorganisms contribute to the transformation of metals and metalloids in situ, since efficient natural remediation processes are known to occur at this site [12, 18]. This former mine generated around 1.2 Mt of tailings containing 0.7% Pb, 10% FeS2, and 0.2% As. Water percolating through the tailings forms the head of the Reigous creek. This creek is acidic (pH around 3) and highly contaminated with As (100 to 350 mg L−1). The behavior of As and Fe in the Reigous creek has been intensively studied [18, 23, 48]. In the creek spring, As(III) is the main As species present and Fe occurs in the form of Fe(II) [18]. Along the first 30 m of the creek (about 1 h residence time), the oxidation of Fe(II) leads to the co-precipitation of more than 38% of the dissolved As [18, 23]. Arsenic accounts for up to 22% of the total dry weight of the sediments formed along the first 10 m along the creek. In the wet season, approximately 30 m downstream of the spring, these sediments are mainly composed of As(III)–Fe(III) oxyhydroxysulfates, whereas As(V)–Fe (III) oxyhydroxysulfates compounds predominate during the dry season [48]. Because of the very high molar As/Fe ratio (up to 0.3) existing in the dissolved phase of the Carnoulès creek, the mineralogical content of the sediments differs significantly from that classically observed at most AMD [47], especially along the first 50 m of the creek. Several strains of Thiomonas and Acidithiobacillus ferrooxidans have been isolated from Reigous creek waters, and based on the results of laboratory experiments, it has been suggested that these bacteria may contribute to the oxidation of Fe(II) and the co-precipitation of As [14, 18, 21–23, 48]. Preliminary analyses have shown that the DNAs of both bacteria are present in the Reigous creek, as well as that of Gallionella sp., Thiobacillus sp., and some sulfate-reducing bacteria [12]. Archaea have also been found to occur in the Reigous creek (Ferroplasma acidiphilum and sequences affiliated to uncultured Thermoplasmatales archaeon) as well as a eukaryotic microorganism, Euglena mutabilis [12, 13, 15]. However, the bacterial population inhabiting the As-rich Reigous sediments has never been characterized so far. It, therefore, seemed to be necessary not only to identify the bacteria present in this creek but also to determine which members of this community are viable and, therefore, perform metabolic activities in situ. The aim of this study was to describe the bacterial populations occurring in both the sediments and waters at the disused Carnoulès site and to identify the bacteria at work. For this purpose, three complementary approaches

Active Bacteria in Arsenic-Rich Sediments

were used. First, chemical and mineralogical studies were performed in order to determine the arsenic species present. A 16S rRNA encoding gene library was then analyzed in order to identify the bacterial population present in the creek sediments and waters. Lastly, based on the findings obtained using a metaproteomic approach combined with high-sensitivity mass spectrometry methods, the active species inhabiting the sediments were identified.

Methods Sampling and Analysis Samples were collected from Reigous creek in April 2006 at COWG station located 30 m downstream from the spring. This sampling was part of a long-term monitoring of the physicochemistry of the Reigous Creek water [23]. The main physicochemical parameters (pH, temperature, and dissolved oxygen concentrations) were measured in situ at this sampling point. The 5-cm deep sediments on the bottom of the creek and a thin column (less than 10 cm) of running water covering the sediments were sampled. Solid samples were removed with a sterile spatula from the surface of the sediments. Water samples (300 ml) were immediately filtered through 0.22 μm Millipore membranes fitted on Sartorius polycarbonate filter holders (for water chemical analysis) or through sterile 0.22-μm Nucleopore filters that were then transferred to a collection tube (Nunc), frozen in liquid nitrogen, and stored at −80°C until DNA extraction (for 16S rRNA encoding gene analysis). Sampling was repeated three times. For total Fe and As determination, filtered water was acidified to pH=1 with HNO3 (14.5 M) and stored at 4°C in polyethylene bottles until analysis. For As and Fe speciation, a 10 μl aliquot of filtered sample water was added to either 0.5 ml of 5% (v/v) 0.25 M EDTA solution for As speciation [7] or a mixture of 0.5 ml acetate buffer (pH 4.5) and 1 ml of 1,10phenanthrolinium chloride solution for Fe speciation [50]. The vials were completed to 10 ml with deionized water. The samples used for arsenic speciation and Fe(II) and sulfate determination were stored in the dark and analyzed within 24 h. Chemical Analysis The determination of total dissolved As was performed by ICP-MS using Thermo X7 series with a conventional external calibration procedure. Indium was used as internal standard to correct for instrumental drift and possible matrix effects. It was not necessary to correct interference with chloride because of the extremely high As levels present. Certified reference material SLRS-4 (freshwater

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samples) was used to check analytical accuracy and precision. The results showed that the recovery rate obtained was within ±5%. Analyses of inorganic arsenic species (As(III), As(V)) were carried out using anion-exchange chromatography (25 cm×4.1 mm i.d. Hamilton PRP-X100 column with Varian ProStar gradient solvent delivery system) coupled to a hydride generation (VGS 200, FISONS, France) with an atomic fluorescence spectrometry detector (Excalibur, PSAnalytical, GB) [17]. The detection limit obtained was 172 ng L−1 for As(III) and 458 ng L−1 for As(V), with a precision better than 5%. Total dissolved Fe was determined by flame atomic absorption spectrometry. Fe(II) concentration was determined using colorimetry at 510 nm after complexation with 1,10-phenanthrolinium chloride solution in buffered samples (pH 4.5) [50] (detection limit: 11 μg L−1; precision better than 5%). Sulfate concentration was determined after precipitation of BaSO4 with BaCl2 and spectrophotometric measurement at 650 nm [50]. Solid Sample Characterization XAFS data were gathered on the laboratory samples and the sample taken at COWG on April 2006, at 10 K in transmission mode on a bending magnet D44 at the LURE synchrotron (Orsay, France), and in fluorescence mode on the 11-2 wiggler beamline at SSRL (Stanford, CA), respectively. Experiments and data reduction were previously reported [48, 49]. DNA Isolation, 16S rRNA Encoding Gene Cloning, Restriction Analysis, and Sequencing Genomic DNA was extracted in triplicate from filtered water and sediments using the UltraClean Soil DNA Isolation Kit according to the manufacturer’s recommendations (MoBio Laboratories Inc., USA). These triplicates were pooled before PCR amplification. All the genomic DNA samples extracted were stored at −20°C until further processing. Bacterial diversity was analyzed by cloning PCR amplified 16S rRNA encoding genes. Bacterial 16S rRNA encoding genes were amplified with 8F (5′-AGAGTTTGA TCCTGGCTCAG-3′) and 1489R primers (5′-TACCTTGT TACGACTTCA-3′) [43, 57], as previously described [12]. These PCR products were cloned into Escherichia coli TOP 10 strain using the pCR2.1 Topo TA cloning kit (Invitrogen, Inc.). Cloned 16S rRNA encoding gene fragments were reamplified using the primers TOP1 (5′-GTGTGCT GGAATTCGCCCTT-3′) and TOP2 (5′-TATCTGCAGA ATTCGCCCTT-3′) that anneal to the vector and surround the inserted PCR fragment and then digested with HaeIII or HinfI enzymes. Restriction profiles were analyzed using 2.5% agarose gel electrophoresis (small fragment resolution

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agarose; QA agarose, QBiogène, Inc.). Around 200 clones from each library were analyzed and grouped according to the RFLP patterns obtained. PAST (Paleontological STatistics v 1.19) software from the website http://folk. uio.no/ohammer/past/ was used to calculate different diversity indices (rarefaction analysis, taxa, total clones, singletons, dominance, coverage, shannon, equitability, and simpson, Table 1) for each clone library. The total number of clones obtained compared with the number of clones representing each unique phylotype was used to produce the rarefaction curves. Coverage values were calculated to determine how efficiently the libraries described the complexity of a theoretical community such as an original bacterial community. The coverage [29] value is given as C= 1—(n1/N) where n1 is the number of clones that occurred only once in the library. Rarefaction analysis showed that the curves generated were near saturation (data not shown) and consistent with the high coverage values of the two clone libraries (97.8 for the sediment and 98.6 for the water). This indicated that the clone libraries were sufficiently sampled. Partial sequences of the clones from dominant groups were determined by the dideoxy nucleotide chaintermination method using the BigDye 3.1 kit (Applied Biosystems) on an ABI PRISM 3730XL Genetic analyzer (Applied Biosystems). The PINTAIL program [4] was used to check the presence of chimerae. Sequences were also examined manually for chimerae, which were excluded from further analyses. These sequences were compared with known sequences (NCBI database) using the BLAST, ALIGN, and CLUSTALW programs [1, 26, 55]. All sequence data obtained were submitted to the EMBL databases under accession numbers (FR676963-FR677013; AM988784-AM988794; AM988796; AM988798; AM988801-AM988805; AM988807-AM988809). Preparation of Protein Extracts and Gel Electrophoresis Analysis Prokaryotes were separated from sediments and eukaryotes using a Nycodenz density gradient. It should be noted that the main population determined from the DNA directly extracted from sediments was similar to that identified after Nycodenz treatment (data not shown), which suggests that this treatment did not result in enrichment of the sample by any particular microorganisms. Ten grams of sediments

were washed in 10 mL of saline buffer and agitated overnight at 4°C. After 10 min of decantation, 7.5 mL of supernatant were added without mixing to 17.5 mL of Nycodenz solution (Axis-Shield, Dundee, Scotland), and then centrifuged for 30 min at 10,000×g. The cellular fraction (nycodenz/sample interface) was removed and washed by adding two volumes of NaCl 0.9% and centrifuged for 15 min at 10,000×g at 4°C. Proteins were extracted from this cellular fraction as previously described [58], further purified using the 2-D Clean-up kit (GE Healthcare), and resuspended in rehydration buffer (364 g L−1 thiourea, 1,000 g L−1 urea; 25 g L−1 CHAPS, 0.6% v/v IPG buffer Pharmalyte, 10 g L−1 of DTT, and 0.01% bromophenol blue). Protein concentrations were quantified using the 2-D Quant kit (GE Healthcare). These proteins were separated by 2-D gel electrophoresis as previously described [58] and finally stained with silver nitrate. Gels were analyzed using an Image Scanner, LabScan v 3.0 (GE Healthcare), and the ImageMaster 2D platinum software program (v. 6.01, GE Healthcare). The spots selected were cut out of the 2-D gels and stored at −20°C. Eighty-one spots were analyzed by performing nanoLC-Chip-MS/MS. In-Gel Digestion, Mass Spectrometry Analysis, and Protein Identification Unless otherwise specified, all chemicals were obtained from Sigma (St. Louis, MO, USA). In-gel digestion of gel spots was performed as previously described [58]. The resulting peptides were analyzed by performing nanoLC-MS/MS on an Agilent 1100 Series HPLC-Chip/MS system (Agilent Technologies, Palo Alto, USA) coupled to an HCT Ultra ion trap (Bruker Daltonics, Bremen, Germany). The MS/MS data were analyzed using the MASCOT 2.2.0 algorithm giving a maximum of one missed cleavage, with a mass tolerance of 0.5 Da for MS and MS/MS data and carbamidomethylation of cysteines and oxidation of methionines were specified as the variable modifications. MS/MS data searches were performed against two in-house generated databases. The first database was composed of the protein sequences of all the organisms related to the groups identified by performing 16S rRNA encoding gene analysis on the Reigous creek sediments and water (α-, β-, δ-, and γ-proteobacteria, Bacilli, Clostridia, Actinobacteria,

Table 1 Diversity indices calculated from the two clone libraries in sediment and water at the Carnoulès mine drainage creek Clone library Sediments Water

Taxa

Total no. of clones

Singletons

Dominance (D)

Coverage (C)

Shannon (H)

Equitability

Simpson (1-D)

15 18

229 221

5 3

0.5503 0.2551

97.8 98.6

1.146 1.949

0.4231 0.6744

0.4497 0.7449

Active Bacteria in Arsenic-Rich Sediments

Nitrospira), as well as unclassified bacteria from http://beta. uniprot.org/, Thiomonas sp. from http://www.genoscope.cns. fr/ (FP475956–FP475957), Euglenozoa, and Viridiplantae. The second database included all bacterial and archaeal GroEL chaperonins (12501 and 291 sequences, respectively) extracted from the Uniprot database (http://www.uniprot.org/ uniprot). To assess the false positive rate in the protein identification, a target-decoy database search was performed [25]. With this approach, peptides are matched against a database consisting of the native protein sequences detected in the database (target) and the sequence-reversed entries (decoy). Protein identification was confirmed when at least two peptides with a minimum Mascot ion score of 30 were detected. In the case of one-peptide hits, the score of the unique peptide had to be greater than the 95% significance Mascot threshold level. All the proteins identified were added to the “InPact” proteomic database developed at our laboratory (http://inpact.u-strasbg.fr/~db/) [8]. Phylogenetic Analyses A search for GroEL homologs and 16S rRNA encoding sequences was carried out in the Uniprot and NCBI databases, respectively. A total number of 530 reviewed GroEL bacterial sequences were retrieved from the RefSeq database. These sequences were 500–550 amino acids in length. Only one sequence representative of each genus (259 sequences in all) was kept. GroEL and 16S rRNA encoding sequences were aligned using ClustalW [55]. Alignments were checked by hand and positions with more than 1% of gaps were automatically removed. Neighborjoining trees were constructed with 185 amino acids in the case of the GroEL sequences and with 310 nt in that of the 16S rRNA encoding sequences. Trees were drawn up using the iTOL website (http://itol.embl.de/) [44].

Results and Discussion Physical and Chemical Characteristics of Samples The physicochemistry of the Reigous Creek water at the time of sampling was typical of that revealed during the long-term monitoring study [23]. The water sample was acid (pH=3.28) and moderately oxygenated (dissolved oxygen concentration= 3.5± 0.5 mg L−1); it contained extremely high concentrations of SO 4 2− (2700 ± 300 mg L−1), Fe (620±30 mg L−1), and As (140± 4 mg L−1), with a large predominance of Fe(II) (90±10% of total Fe concentration) and equal proportion of As(III) and As(V). The removal of As during the course of the Reigous Creek from its source to the sampling station

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COWG reached 38%, corroborating the typical removal rates measured during the long-term monitoring study [23]. The pale-yellow loosely packed sediments previously observed during the dry season at the sampling point chosen in this study (COWG ~30 m downstream of the spring), consisted of an amorphous Fe(III)–As(V) hydroxysulfate mineral with an As/Fe molar ratio of 0.5 to 0.6 [48]. However, various other biominerals may be formed from dissolved Fe(II) and As(III) [47, 48]. The exact nature and structure of the sediment sample studied was, therefore, further investigated. X-ray powder diffraction (data not shown) and X-ray absorption spectroscopy data obtained at the As–K edge (Fig. 1) showed that arsenic was present in these samples in an amorphous Fe(III)–As (V) hydroxysulfate phase as previously observed [48]. These analyses showed that despite the presence of a minor As(III) impurity, the oxidized arsenic form As(V) predominates in this sediment (Fig. 1a). In a previous study, it has been shown that the catalytic oxidation of As(III) by Thiomonas sp. strains accelerates such As–Fe precipitation process [48]. Therefore, using extended X-ray absorption fine structure analysis at the As–K edge (Fig. 1b), the structure observed in our samples was compared with that of the minerals obtained after As(III) oxidation by the Thiomonas sp. strain B2 in bioassays in which sterilized Carnoulès Creek water was used [48]. These comparisons (Fig. 1b, c) showed that the molecular structure of the amorphous Fe(III)–As(V) hydroxysulfate phase observed in these sediments was similar to that of the Fe(III)–As(V) hydroxysulfate obtained in the presence of Thiomonas, further supporting its role in situ. Composition of Bacterial Communities in Reigous Creek Water and Sediments Two 16S rRNA encoding gene libraries were constructed (Table 2), containing 229 clones in the sediment library and 221 in that of the water library. The Shannon index (see “Methods”) and equitability values were greater in the water library than in the sediment library (Table 1), which suggests that the bacterial diversity was lower in the sediment than in the water samples. Eleven different species were identified in the sediments and 13 in the water (Table 2, Fig. 2). Several of the bacteria identified in the present study in both the waters and the sediments have been previously detected in the Reigous waters [12, 14, 15, 18, 21, 22]. Classified first by abundance order, several sequences were affiliated to Thiobacillus sp. ML2-16. This bacterium has been frequently reported to occur in AMD [5]. The presence of several strains affiliated to this proteobacteria is in agreement with the results of previous studies and shows that these bacteria persist in this

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Figure 1 X-ray absorption spectra at the As–K edge of the sample, (COWG April 11, 2006,) showing similarities with the X-ray amorphous Fe(III)–As(V) hydroxysulfate phases obtained after incubating sterilized Carnoulès water with the Thiomonas sp. strain B2 isolated at the site [48]. These phases reached a molar As/Fe ratio of 0.8, as described in [48]. a Linear least-squares fitting of XANES data showed that the largest arsenic fraction (90±2%) was in the As(V) oxidation state. A small arsenic fraction (10±2%) was in the As(III) oxidation state, which resulted in a slight decrease in the amplitude in the EXAFS spectrum. b Shell by shell fit of the EXAFS spectra in k-

space for the COWG sediment sample and the Thiomonas sp. strain B2 precipitate sample. c Corresponding Fourier transforms of the experimental and fit curves. Dotted lines experimental; solid lines fitting curves. The local structure of both the COWG and the laboratory Thiomonas sp. samples includes bidentate arsenate– oxygen–iron complexes characterized by ~1.5–2.0 Fe atoms at an As–Fe distance of 3.31±0.02 Å. A small arsenic fraction (10±2%) was in the As(III) oxidation state, which resulted in a slight decrease in the amplitude in b the EXAFS spectrum and in c the corresponding Fourier transform

ecosystem [12]. Secondly, bacteria affiliated to Gallionella capsiferriformans were detected in both the water and sediments. G. capsiferriformans is an oxygen-dependent ferrous iron-oxidizing bacterium that grows at circumneutral pH [59]. Relatives of Gallionella, such as G. ferruginea in particular, have often been detected, sometimes as the dominant group in microbial mine water communities, including Carnoulès [12, 33–35]. Bacteria related to At. ferrooxidans as well as Thiomonas strains have been previously isolated from this site [14, 18, 21, 22]. At. ferrooxidans, which was the first microorganism to be isolated from an acidic leaching environment, occurs ubiquitously in AMD, as does Thiomonas [32]. In addition to these groups, other species that have not previously been described at this site were detected in this study. Some of these species were found to occur in both sediments and water. For example, bacteria affiliated to the Firmicutes Alicyclobacillus sp. BRG 73 were identified. This genus, found in AMD [5], is characterized by moderately thermophilic, acidophilic, strictly aerobic, and endosporeforming bacilli [30]. Likewise, bacteria related to “Ferrovum myxofaciens” PSTR were detected in both the waters and sediments. “Ferrovum myxofaciens” is an autotrophic ironoxidizer which predominates in some AMD and is able to grow litho-autotrophically, using ferrous iron as an electron

donor [32]. Lastly, bacteria affiliated to Leptospirillum ferrooxidans, an iron-oxidizing member of the Nitrospirae [36], were also present. This bacterium has been found to occur in several acidic environments and in biofilms originating from AMD [5, 9, 32]. Other newly characterized groups were identified only in sediments (Table 2). The presence in acidic mine waters of Acidocella sp., a non-iron-oxidizing heterotrophic acidophile is quite common in AMD [33, 35]. Ferrimicrobium is an iron-oxidizing heterotroph that can also use iron as an electron acceptor [20]. Other prokaryotes detected in sediments were affiliated to Acidiphilium sp. CCP3, a non-iron-oxidizing heterotrophic acidophile that is also quite common in AMD [33] and Dokdonella koreensis, a γ-proteobacteria. Six newly characterized groups were identified only in water. Some of these bacteria were related to Sideroxydans lithotrophicus LD-1, an oxygen-dependent ferrous ironoxidizing bacterium that grows at circumneutral pH [59]; Rhodoferax ferrireducens, a psychrotolerant, facultative anaerobic bacterium which is able to oxidize acetate with the reduction of Fe(III) [28]; and an Acidobacteriaceae bacterium, CH1. Members of Acidobacteria have previously been reported in AMD [5, 32]. Finally, three sulfate-reducing bacteria were related to strain JHA1, Desulfomonile limimaris,

Gallionella capsiferriformans ES-2 (DQ386262) Acidithiobacillus ferrooxidans BGR:110 (GU168011) Acidithiobacillus ferrooxidans DSM 2392 (AJ459800) Alicyclobacillus sp. BGR 73 (GU167996)

ß-Proteobacteria γ-Proteobacteria Firmicutes ß-Proteobacteria ß-Proteobacteria ß-Proteobacteria Nitrospirae ß-Proteobacteria Acidobacteria δ-Proteobacteria δ-Proteobacteria

CGA6Wt11a, 29c, 78c

CGA6Wt3a, 8c CGA6Wt86b CGA6Wt15a

CGA6Wt51b CGA6Wt61b

CGA6Wt42c CGA6Wt30a CGA6Wt10a

82 87 82

98–99 94 94 99 96

“Ferrovum myxofaciens” PSTR (EF133508) Thiomonas sp. PK44 (AY455806) Leptospirillum ferrooxidans (AB510912) Rhodoferax ferrireducens T118 (CP000267) Acidobacteriaceae bacterium CH1 (DQ355184) Sulfate-reducing bacterium JHA1 (EF442984) Desulfomonile limimaris (NR_025079) Desulfuromonas svalbardensis 60 (AY835390)

94–97

Sideroxydans lithotrophicus LD-1 (DQ386859)

89–97 100 91–92 91–99

96 99 99–100 99 92 99 99 92–99 99 100 94–96

95–96

Percentage of similarity

3 3 1

4 3 3 3 3

8

8

18 10

21 10 8 6 5 3 3 3 2 2 26

31

Relative abundance of clones (%)

Sequences closely related to 16S rRNA genes from Euglena spp. chloroplast were also detected (data not shown). The 16S rRNA encoding gene of chloroplasts is closely related to the bacterial 16S rRNA encoding gene and can therefore be amplified by primers 8F and 1489R

Water

Gallionella capsiferriformans ES-2 (DQ386262) Acidithiobacillus ferrooxidans DX-1 (EU084695) Acidocella sp. M21 (AY765998) Thiomonas sp. PK44 (AY455806) Dokdonella koreensis NML 01–0233 (EF589679) Ferrimicrobium sp. BGR 49 (GU167992) Acidiphilium sp. CCP3 (AY766000) Alicyclobacillus sp. BGR 73 (GU167996) Leptospirillum ferrooxidans Sy (AF356839) “Ferrovum myxofaciens” PSTR (EF133508) Thiobacillus sp. ML2-16 (DQ145970)

ß-Proteobacteria γ-Proteobacteria α-Proteobacteria ß-Proteobacteria γ-Proteobacteria Actinobacteria α-Proteobacteria Firmicutes Nitrospirae ß-Proteobacteria ß-Proteobacteria

Thiobacillus sp. ML2-16 (DQ145970)

ß-Proteobacteria

CGA6Sd1a, 5a, 10b, 13c, 23c, 34c, 59b, 89c, 92c

CGA6Sd4b, 36c, 48c CGA6Sd13a CGA6Sd10a, 37a CGA6Sd31c, 36a CGA6Sd6b, 18a, 27b CGA6Sd32a CGA6Sd38c CGA6Sd20a, 76c CGA6Sd58b CGA6Sd51c CGA6Wt4c, 7a, 15c, 20a, 21b, 22b, 23a, 31b, 32a, 33c, 45b, 54c, 63b, 73c CGA6Wt7c, 17b, 21a, 23c, 27b, 35b, 36b, 67c, 80c, 86c CGA6Wt25c, 56b CGA6Wt5a, 48c, 79b CGA6Wt9a, 19a, 27a, 9b, 61c

Closest isolated relative (accession number)

Sediment

Phylogenetic group

Clones

Sampling

Table 2 Bacterial clones detected at the Carnoulès mine drainage with their phylogenetic group, the closest isolated relative and the relative abundance of each group versus the total number of clones (100%)

Active Bacteria in Arsenic-Rich Sediments 799

800

an anaerobic dehalogenating bacterium from marine sediments [54] and Desulfuromonas svalbardensis 60, a psychrophilic, Fe(III)-reducing bacterium isolated from Arctic sediments [56] (Table 2). All in all, 17 species of bacteria were identified in the water and sediments sampled at the Reigous creek. Only seven genera were found to be present in both phases, six were found only in water, and four only in the sediments (Table 2). Most of these species are common residents of AMD [5, 32]. This quite low bacterial diversity was probably due to the high concentration of toxic compounds in this AMD and was consistent with previous observations showing that the biodiversity of acidic, metal-rich mine waters is mainly restricted to specialized prokaryotes and some eukaryotes such as Euglena [15, 52], which has been detected in this study (data not shown). In the Reigous system, in both sediments and water, the populations observed were mainly involved in the Fe, As, and S cycles. The populations involved in Fe(II) oxidation were related to Gallionella, At. ferrooxidans, Ferrimicrobium, Leptospirillum, Sideroxydans lithotrophicus, or “Ferrovum myxofaciens” [32, 59], whereas ferric iron reduction has been described for populations like Acidiphilium spp., Acidocella, Desulfuromonas svalbardensis, Rhodoferax ferrireducens, or even At. ferrooxidans and Ferrimicrobium acidiphilum [20, 28, 56]. Since the Carnoulès creek spring contains mainly Fe(II) and As(III) in the form of dissolved species [18], the Fe(III) and As(V) may be formed as the result of microbial oxidation processes via the activity of acidophilic iron- and arsenite-oxidizing bacteria [24, 48]. In other words, the large amounts of soft pale-yellow As(V)–Fe (III) hydroxysulfate sediments analyzed here (Fig. 1) were probably formed by the joint activities of iron-oxidizing (e.g., At. ferrooxidans or Gallionella) and arsenic-oxidizing (e.g., Thiomonas sp.) microorganisms. Concerning S cycling, we found populations able to oxidize the reduced inorganic sulfur compounds, like Thiobacillus, Thiomonas, or At. ferrooxidans [32, 42, 46]. Sulfate-reducing bacteria such as Desulfomonile limimaris or Desulfuromonas svalbardensis were also found to be present in sediments and may be involved in sulfate consumption [54, 56]. Among these prokaryotes, some bacteria may be present but not functionally active, and it was, therefore, crucial to differentiate between dead or inactive cells and functional cells. To determine which organisms play a significant role in the natural remediation processes such as the Fe(II) oxidation processes observed at the study site, a metaproteomic approach was used to list the bacterial population expressing proteins, i.e., those which were active. The metaproteomic approach was possible with sediments but failed with the water samples because larger numbers of bacterial cells were recovered from sediments than from water (data not shown).

O. Bruneel et al. Figure 2 Phylogenetic tree based on 16S rRNA-encoding sequences. Sequences were aligned using ClustalW. Alignments were checked by hand and positions with more than 1% of gaps were automatically removed. Neighbor-joining trees were drawn up with 310 nt using ITOL (http://itol.embl.de/) [44]. Accession numbers: see supplementary data. In red: bacteria identified based on the metaproteomic (GroEL identifications) approach; in blue: bacteria identified using the 16S rRNA encoding gene library; in black: sequences detected in NCBI databases which are closely related to the bacteria present in the Reigous sediment

Characterization of the Main Proteins Expressed by the Sediment Community Proteins expressed by this community were liable to correspond to orthologs originating from diverse prokaryotes and to have similar amino acid sequences. For those reasons and to improve their characterization, proteins were separated by performing 2-D gel electrophoresis (supplementary Fig. 1). A total number of 89 proteins were identified, 44% of which (39 proteins, Table 3) originated from bacteria and 39% (35 proteins) from protists, while 15 proteins originated from higher plants, probably from decomposed plant debris present at the Reigous creek. One third of the proteins originated from protists, mainly consisting of E. mutabilis detected in our samples (data not shown) and could not be completely removed using the Nycodenz Gradient. E. mutabilis is a common inhabitant of AMD [2, 11, 15, 39] and was also present at the surface of sediments. These Euglena proteins are involved in various metabolic processes, suggesting that this eukaryote may play a relevant role in this ecosystem, in agreement with recent results (Gouhlen-Chollet and Bertin, unpublished data). Only proteins originating from bacteria were further analyzed in this study. The 2-D gel electrophoresis approach used here allowed identifying from a single sample only the most abundant cytoplasmic proteins. Therefore, some relevant proteins that might be expressed in this environment, such as rusticyanin from At. ferrooxidans, which is known to be involved in Fe(II) oxidation and was previously thought to possibly play a functional role at this site [21, 24, 48], were not detected in this study. This membrane protein may not be resolved in the 2-D gel, or it may not be abundant at the sampling point. In addition, the majority of the bacteria forming the Carnoulès community have never been grown and studied in vitro so far. Their genome sequences, and hence their protein sequences, which are required for MS identification purposes, may not be available in public databases, except for those of At. ferrooxidans, Thiomonas, and Gallionella strains. All these hypotheses may explain why so few bacterial proteins were identified in this study. The bacterial proteins identified originated from Aquificae were Actinobacteria, Deinococcus, Synergistetes, Firmicutes, Bacteroidetes, and α-, β-, and γ-proteobacteria. Among the

b

Active Bacteria in Arsenic-Rich Sediments

801

-proteobacteria

Actinobacteria

-proteobacteria

Synergistetes

-proteobacteria

Firmicutes

-proteobacteria

Acidobacteria

Nitrospirae

Deinococcus/Thermus

Proteobacteria α-proteobacteria, Rhizobiales;

Species or subspecies

Species

Species

Genus or below

C7IKN8

60 kDa chaperoninsa

Genus or

60 kDa chaperoninsa

ATP synthase; beta subunit

Order

Arthrobacter, Janibacter, Clavibacter or Kineococcus Sinorhizobium medicae

A6UH06

A0JY64, A1R7V3, A3TGD9, A5CQ60, A6W7G9

D2BBD1

60 kDa chaperoninsa

Family

Streptosporangium roseum

C4DUC7

60 kDa chaperoninsa

Suborder or below

A5JUG8

60 kDa chaperoninsa

Stackebrandtia nassauensis

A0M6J2

Phosphoglycerate kinase

Species

Propionibacterium freudenreichii

A0M791

ATP synthase; beta subunit

60 kDa chaperoninsa

A5I723, A7FYP3, A7GIN3, B1IFD4, B1L1K0, C1FLV5, C3KUC8, B1Q9U6, B1QI57 B6FW06

60 kDa chaperoninsa

O50305, A8VUQ6, D3FSF9

A9LHR1

A6TLJ1, A8HJ57

a

Q70BV2, Q70BV5

D1B621

A1YUK7

C1CZP1

60 kDa chaperoninsa

60 kDa chaperonins

60 kDa chaperonins

a

60 kDa chaperoninsa

Subspecies

a

60 kDa chaperoninsa

60 kDa chaperonins

a

60 kDa chaperonins

Family or below Species

Protein accession numbers

Putative uncharacterized protein A7WFJ8

Genus or below

Species

Species

Species

Level of Protein name discrimination

Gramella forsetii (strain Species KT0803)

Clostridium papyrosolvens

Clostridia; Clostridiales; Clostridiaceae; Clostridium

Flavobacteria; Flavobacteriales; Flavobacteriaceae; Gramella

Clostridium hiranonis

Lactobacillus delbrueckii subsp. Indicus or delbrueckii Virgibacillus pantothenticus Bacillus halodurans, pseudofirmus or selenitireducens Alkaliphilus metalliredigens or ormlandii Clostridium botulinum

Clostridia; Clostridiales; Clostridiaceae; Clostridium

Clostridia; Clostridiales; Clostridiaceae; Clostridium

Clostridia; Clostridiales; Clostridiaceae; Alkaliphilus

Bacilli; Bacillales; Bacillaceae; Bacillus

Bacilli; Bacillales; Bacillaceae

Bacilli; Lactobacillales; Lactobacillaceae

Actinobacteria Actinobacteria (class); Actinobacteridae; Actinomycetales; Propionibacterineae; Propionibacteriaceae Actinobacteria (class); Actinobacteridae; Actinomycetales; Glycomycineae; Glycomycetaceae; Stackebrandtia Actinobacteria (class); Actinobacteridae; Actinomycetales; Streptosporangineae; Streptosporangiaceae; Streptosporangium Actinobacteria (class); Actinobacteridae; Actinomycetales

Bacteroidetes

Firmicutes

Synergistetes

Thermanaerovibrio acidaminovorans

Deinococcus sp. A62

Deinococci; Deinococcales; Deinococcaceae; Deinococcus Synergistia; Synergistales; Synergistaceae; Thermanaerovibrio

DeinococcusThermus

Hydrogenobaculum sp. Y04AAS1 Deinococcus deserti

Aquificae (class); Aquificales; Aquificaceae; Hydrogenobaculum Deinococci; Deinococcales; Deinococcaceae; Deinococcus

Aquificae

Organism

Class, Family, Genus

Phylum

Table 3 Bacterial proteins identified in the Reigous sediment’s microbial community b

2, 4

10, 31, 32, 33, 38

4

6

4, 5, 6

13, 20

11

4, 6

4, 5, 6

4

6

2

4, 5, 6

4, 5

4

2

4, 6

25

Spot number

LVAAGMNPMDLK

IGLFGGAGVGK

VALSALTMAEYFR

DVQNQDVLLFIDNIFR

GTFTSVAVK

APGFGDR

GMNALADAVK

NVTAGANPIELK

LGDIYVNDAFGTAHR

MPSAVGYQPTLATEMGAMQER

FGSPTITNDGVTIAK

APGFGDR

TNDIAGDGTTTATVLAQAIIR

VGAATEVEMK

KALEEPLR

APGFGDR

LGIDIIR

APGFGDR

LSGGVAVIQVGAATETELK

NVTSGANPMVIR

AVEVAVK

YGAPTITNDGVTIAK

APGFGDR

FGSPTITNDGVTIAK

IAQVASISANDK

AVLVAIEEIK

QLVFDEAAR

APGFGDR

IGAAVIGR

Peptide sequence

802 O. Bruneel et al.

Phylum

Acidovorax avenae

Bordetella petrii

Bordetella avium (strain 197 N) Herminiimonas arsenicoxydans

β-proteobacteria, Burkholderiales; Comamonadaceae; Acidovorax

β-proteobacteria, Burkholderiales; Alcaligenaceae; Bordetella

β-proteobacteria

β-proteobacteria; Burkholderiales; Oxalobacteraceae; Herminiimonas

Leptothrix cholodnii or β-proteobacteria, Burkholderiales; Thiomonas unclassified Burkholderiales; intermedia Burkholderiales Genera incertaesedis

Rhodobacterales bacterium HTCC2083

Acidiphilium cryptum

Organism

α-proteobacteria, Rhodobacterales; unclassified Rhodobacterales

Rhizobiaceae; Sinorhizobium/ Ensifergroup; Sinorhizobium α-proteobacteria, Rhodospirillales; Acetobacteraceae; Acidiphilium

Class, Family, Genus

Table 3 (continued)

Genus

Species

Species

Species

Species

Family or below

Genus or below

below a

Q2L2M6

A9I685

A1TKQ5, D1STJ1

B6AWC8

A5G1G2

Protein accession numbers

60 kDa chaperoninsa

B1XXY9, C7HZY6

A4G6P6 Glutathione-dependent formaldehyde dehydrogenase (alcohol dehydrogenase class III), HEAR2039 A4G6Q5 Glutathione-independent formaldehyde dehydrogenase, HEAR2048

50S ribosomal protein L7/L12

60 kDa chaperoninsa

60 kDa chaperoninsa

60 kDa chaperoninsa

60 kDa chaperonins

Level of Protein name discrimination

b

2, 3, 4, 5, 36, 60

NC3, NC11

NC12

NC14

2, 4, 5

4

4, 5

5, 6

Spot number

IQIEEATSDYDR

VEDALHATR

IQIEEATSDYDREK

VTLADLGQAK

YVAAGMNPMDLK

VIAEEVGLTLEK

VGAATEVEMK

EGVITVEDGK

LQNMGAQMVK

APGFGDR

YVAAGMNPMDLKR

SFGAPTVTK

FPELITPQGK

GMTMGHEMTGEVIEVGSDVEVVK

VIDYVGVDCR

LEDAPAAYK

TNLCVAVR

IIAIDTNPAK

DLVDGAPKPVK

AEILDAIAGMTVLELSELIK

VQIEEATSDYDR

VEDALHATR

DLLPVLEQVAK

VQIEEATSDYDREK

EGVITVEDGK

VGAATEVEMK

AVEEPLR

APGFGDR

AAVEEGIVAGGGVALLR

VTLADLGQAK

AVTALVAELKK

VGAATEVEMK

APGFGDR

SVAAGMNPMDLK

EIELADPFENMGAQLVK

APGFGDR

ENTTIVEGAGK

AGIIDPTK

AVAAGMNPMDLK

AAVEEGIVPGGGVALAR

APGFGDR

AAVEEGIVAGGGVALLR

Peptide sequence

Active Bacteria in Arsenic-Rich Sediments 803

Phylum

Limnobacter sp. MED105

Methylibium petroleiphilum

Ralstonia pickettii

Verminephrobacter eiseniae

Methylotenera mobilis

β-proteobacteria, Burkholderiales; unclassified Burkholderiales; Burkholderiales Genera incertaesedis; Methylibium

β-proteobacteria, Burkholderiales; Burkholderiaceae; Ralstonia

β-proteobacteria, Burkholderiales; Comamonadaceae; Verminephrobacter

β-proteobacteria, Methylophilales; Methylophilaceae; Methylotenera

Genus or below

Genus

Subspecies

Genus or below

Genus or below

Genus

Thiomonas 3As

60 kDa chaperoninsa

60 kDa chaperoninsa

60 kDa chaperoninsa

60 kDa chaperoninsa

60 kDa chaperoninsa

50S ribosomal protein L1; THI3722

Level of Protein name discrimination

Organism

β-proteobacteria, Burkholderiales; Burkholderiaceae; Limnobacter

Class, Family, Genus

Table 3 (continued)

C6WTL6

A1WL05

B2U6M6

A2SCV1

A6GTE5

FP475956

Protein accession numbers

5, 6

2, 4

4

2, 4

4

38

Spot number

b

SVAAGMNPMDLK

AMLEDIAILTGGK

VQIEEATSDYDR

VEDALHATR

VTLADLGQAK

AVTALVAELKK

VQIEEATSDYDREK

VIAEEVGLTLEK

EGVITVEDGK

VGAATEVEMK

EVVFGGEAR

APGFGDR

AAVEEGIVAGGGVALLR

DLLPILEQVAK

VGAATEVEMK

APGFGDR

AMLEDIAILTGGK

VQIEEATSDYDR

VQIEEATSDYDR

AAVEEGIVAGGGVALLR

VEDALHATR

VTLADLGQAK

YVAAGMNPMDLK

VIAEEVGLTLEK

EGVITVEDGK

VGAATEVEMK

LQNMGAQMVK

VQIEEATSDYDREK

APGFGDR

YVAAGMNPMDLKR

SFGAPTVTK

GVNILANAVK

VGAATEVEMK

APGFGDR

VDTATVNAAVAGQ

VAVSSTMGIGVR

AAVEEGIVAGGGVALLR

AMLEDIAILTGGK

Peptide sequence

804 O. Bruneel et al.

Methylococcus capsulatus

Pseudomonas

Gammaproteobacterium Group or HTCC2207 clade

γ-proteobacteria, Methylococcales; Methylococcaceae; Methylococcus

γ-proteobacteria; Pseudomonadales; Pseudomonadaceae

γ-proteobacteria, unclassified Gammaproteobacteria; OMG group; SAR92 clade δ-proteobacteria, Myxococcales; Nannocystineae; Haliangiaceae; Haliangium Several Proteobacteria

Phylum

Haliangium ochraceum Order or below

Genus

Order or below

Species

Succinyl-CoA synthetase; beta subunit

60 kDa chaperonins

a

60 kDa chaperoninsa

Outer membrane lipoprotein OprI

60 kDa chaperoninsa

60 kDa chaperoninsa

60 kDa chaperoninsa

b

QIVANAGDEPSVVLNK

VEDALHATR

VGAATEVEMK

APGFGDR

LESTTLADLGQAK

AMLEDMAILTGGR

VEDALHATR

VVSEEIGMK

GVNVLADAVK

AVIAGMNPMDLK

HALEGFK

APGFGDR

VEDALHATR

DLLPVLEQVAK

GYLSPYFINNQDR

VGAATEVEMK

TNDIAGDGTTTATVLAQAIIR

Peptide sequence

4, 6

NC1, NC3, NC11

Q3KFU6c

5

Spots from 1 to 65 originated from a pH 4 to 7 gradient gel (Supplementary Fig. 1), spots from NC1 to NC14 originated from a pH 3 to 10 gradient gel (data not shown)

LEGNNAELGAK

GYLSPYFVTDSER

VGAATEVEMK

APGFGDR

AQIEDTSSDYDR

SVAAGMNPMDLK

4, 15, 17, 19, 22, 26– LTATEDAAAR 27, 40, 44, 49, 55, KADEALAAAQK 60, 62, 64–65, ADEALAAAQK NC7-NC10 ITATEDAAAR

2, 3, 4

2, 3

2

Spot number

D0LRR3

Q1YSA6

A2VC34, A4XVE5, O85409085430-O85432-O85437, O85439-O85444, Q3K906, Q48K14, Q883S8

Q60AY0

B5EN19, B7J561

C5V7N1

Protein accession numbers

MS/MS data were searched against an in-house database including all the bacterial and archaeal GroEL sequences obtained from Uniprot

Proteobacteria

Acidithiobacillus ferrooxidans

γ-proteobacteria, Acidithiobacillales; Acidithiobacillaceae; Acidithiobacillus

Genus or below

Gallionella ferruginea

β-proteobacteria, Gallionellales; Gallionellaceae; Gallionella

Level of Protein name discrimination

Organism

Class, Family, Genus

Several proteins may correspond to this identification: Q3KFU6, A1A8Y0, A1FGM7, A1JRB6, A1KTM6, A2UEB0, A3HHN5, A3M887, A4TNT8, A4W879, A4XV90, A5W114, A5WC33, A6BTC9, A6T6F6, A6V7K5, A7FKR4, A7MQX5, A7ZJA8, A7ZXY8, A8AJ84, A8GB83, P0A836, P0A837, P0A838, P0A839, P53593, P66869, P66870, Q02K73, Q0T6W6, Q0TJW6, Q1CAG1, Q1CFM0, Q1I7L3, Q1REJ8, Q21IW6, Q2NUM2, Q2SD35, Q324I4, Q32IK3, Q3Z476, Q48K68, Q4FVH9, Q4KFY6, Q4ZUW7, Q57RL3, Q5F878, Q5PCM7, Q66DA0, Q6D7G2, Q6F8L4, Q7N6V5, Q7NZ47, Q883Z4, Q88FB2, Q8ZH00, Q9JUT0, Q9JZP4

c

b

a

Phylum

Table 3 (continued)

Active Bacteria in Arsenic-Rich Sediments 805

806

39 bacterial proteins detected, there were two distinct ATP synthases, two distinct 50 S ribosomal proteins, one phosphoglycerate kinase, and one succinyl-CoA synthetase, which are involved in energy metabolism, translation, glycolysis, and TCA cycle, respectively (Table 3). These proteins may not play a specific role in this environment since they are known to be housekeeping proteins in bacteria. Among the other proteins, one outer protein OrpI, one uncharacterized protein with an unknown function, one glutathione-dependent, and one glutathione-independent formaldehyde dehydrogenases were identified. The latter two proteins belong to the formaldehyde detoxification pathway. Although no correlation with the environmental conditions might explain the functional specificities of these proteins, it has been reported that the arsenite-oxidizing bacteria H. arsenicoxydans synthesizes alcohol dehydrogenase and glutathione-dependent formaldehyde dehydrogenase when grown in the presence of arsenic [58]. It is worth noting that more than half of the identified bacterial proteins were similar to the 60-kDa GroEL chaperonin. These data suggest that multiple chaperonins of various genetic origins are expressed by the Reigous creek community. GroEL is known to be ubiquitously present in Bacteria and Archaea. These proteins are generally abundantly expressed in bacterial cells, especially under stress conditions such as those occurring in this particularly toxic environment [3]. The groEL gene is conserved in prokaryotes, and has been found to be present in one copy in the majority of sequenced genomes, except in the case of some pathogens [45, 60]. Because of its conservation properties (supplementary Fig. 2), this gene is often used as a phylogenetic marker [31]. In addition, it has been previously established that some of the amino acids stretch occurring in GroEL are specific to one genus or family of bacteria. These peptide sequences can therefore be used as the signature of a specific phylogenetic group. These GroEL identifications (Table 3, Fig. 3) were, therefore, considered for use as a possible taxonomic tool in addition to the 16S rRNA-based taxonomic approach. To determine which bacteria in the whole community were active, i.e., able to express proteins, the organisms identified using the 16S rRNA encoding gene library- and GroELbased approaches (Fig. 2) were compared. Most of the bacteria identified based on GroEL belonged to five phyla divisions. Bacteria belonging to Deinococcus and Synergistetes did not feature among those identified based on the 16S rRNA encoding gene. One possible explanation for this discrepancy may be that a PCR or cloning bias may have prevented those bacteria from being detected with this method. These findings suggest that metaproteomic methods used as taxonomic tools can provide a useful complementary tool in addition to the 16S rRNA encoding gene approach. Interestingly, Thiomonas, At. ferrooxidans, Acidiphilium, and Gallionella, expressed proteins and were, therefore, active.

O. Bruneel et al.

16S rRNA-encoding gene analysis showed that these bacteria abound in this ecosystem. Bacteria affiliated to At. ferrooxidans and Gallionella are able to oxidize iron. In addition, many strains of the Thiomonas genus are able to oxidize As(III) into As(V) under laboratory conditions [6, 14, 22]. The fact that their proteins were detected shows that these bacteria were viable and metabolically active. This finding supports the hypothesis that the oxidation of Fe(II) to Fe(III) catalyzed by iron-oxidizing microorganism such as At. ferrooxidans and Gallionella and oxidation of As(III) into As(V) by As(III) oxidizers such as Thiomonas, probably leads to the precipitation of the more or less ordered iron oxy-hydroxides (Fe(III)–As(V) hydroxysulfate) detected in this study (Fig. 1) [48]. This finding is in agreement with previous data showing that Gallionella ferruginea efficiently remove Fe, As(III), and As(V) in water [41]. The present data show for the first time that this bacterium is active and probably plays a functional role in the sediments of the Reigous creek. Some heterotrophic bacteria such as Acidiphilium were also found to be active in this AMD, suggesting that they could cope with the low amount of organic carbon (dissolved organic carbon concentration 1.7±0.4 mg/L [16]) of Reigous creek water. It has previously been suggested that these acidophilic heterotrophic bacteria may be involved in organic carbon turnover processes [32]. Interestingly, these four bacteria (At. ferrooxidans, Thiomonas, Gallionella, and Acidiphilium) found to be active members of this AMD community have been previously identified in AMD, but some of them were thought to have different optimum pH levels. Indeed, G. ferruginea is a neutrophilic bacterium which oxidizes Fe, but relatives of Gallionella, have often been detected in AMD [12, 33–35]. The strain occurring at Carnoulès showed less than 97% homology with G. capsiferriformans and its physiological characteristics are probably different. It seems probable that an acid-tolerant relative of this bacterium is able to oxidize iron under acid pH conditions. In addition to the bacteria belonging to these four genera, other bacteria were also found to be active, but a discrepancy was again observed between the bacteria identified based on the results of 16S rRNA encoding gene analysis and the metaproteomic approach. The GroEL protein sequences of some bacteria identified using the 16S rRNA encoding gene library were not available in the Uniprot database, which might explain this discrepancy. However, phylogenetic comparisons between the 16S rRNA and metaproteomic data obtained (Fig. 2) suggested which of the bacteria present in this ecosystem may express a GroEL identified in the metaproteomic study. Based on these comparisons, it seems likely that in addition to Thiomonas, At. ferrooxidans, Acidiphilium, and Gallionella, clones related to β-, γ-, and δ-proteobacteria, such as Limnobacter or Methylococcus (At. ferrooxidans DSM

Active Bacteria in Arsenic-Rich Sediments

807

A. avenae subsp. avenae A. avenae subsp. citrulli A. ferrooxidans ATCC53993 A. ferrooxidans ATCC23270T A. cryptum A. metalliredigens A. oremlandii B. halodurans B. pseudofirmus B. selenitireducens B. petrii C. botulinum C. hiranonis C. papyrosolvens D. desertii D. sp. A62 G. ferruginea Gamma-proteobacterium HTCC2207 H. ochraceum L. delbrueckii subsp. delbrueckii L. delbrueckii subsp. indicus L. cholodnii Limnobacter sp. MED105 M. petroleiphilum M. capsulatus M. mobilis P. freudenreichii R. picketii Rhodobacterales bacterium HTCC2083 S. medicae S. nassauensis S. roseum T. acidaminovorans Thiomonas 3As T. intermedia V. eiseniae V. pantothenticus

A. avenae subsp. avenae A. avenae subsp. citrulli A. ferrooxidans ATCC53993 A. ferrooxidans ATCC23270T A. cryptum A. metalliredigens A. oremlandii B. halodurans B. pseudofirmus B. selenitireducens B. petrii C. botulinum C. hiranonis C. papyrosolvens D. desertii D. sp. A62 G. ferruginea Gamma-proteobacterium HTCC2207 H. ochraceum L. delbrueckii subsp. delbrueckii L. delbrueckii subsp. indicus L. cholodnii Limnobacter sp. MED105 M. petroleiphilum M. capsulatus M. mobilis P. freudenreichii R. picketii Rhodobacterales bacterium HTCC2083 S. medicae S. nassauensis S. roseum T. acidaminovorans Thiomonas 3As T. intermedia V. eiseniae V. pantothenticus

Figure 3 Alignment of the amino acid sequences of 60 kDa chaperonins. Thirty-six sequences matched the MS results: 29 Proteins were identified in Table 3: 22 of them unambiguously matched one protein (the bacterial name of which is given in orange), whereas fifteen identifications matched at least two proteins (22 bacterial names given in black). Thiomonas sp. 3As data were added for the sake of comparison (in blue). Thirty-seven sequences in all were aligned. These sequences were compared with ClustalW2 using the default parameters (http://www.ebi.ac.uk/Tools/clustalw2/index.html). Alignment was performed using the Jalview software program [19]. The blue highlighted letters correspond to identical residues among the 37 orthologs (BLOSUM62 score option). Highlighted letters corresponding to the peptide sequences identified by MS allowed distinguishing several orthologs. First, 23 proteins were identified because at least one identified peptide matched only this GroEL: these peptides (labeled in red) corresponding to signature sequences specific to one species, genus, or family of bacteria are located in the same homology regions but differed from other peptides by at least one amino acid substitution. Secondly, 13 of the proteins identified were confirmed, since several identified peptides (labeled in green) matched this GroEL. Each of these individual peptides matched several proteins; however, only one protein detected in Uniprot contained all these amino-acid sequences, which suggests that a relative of this protein was probably present in this extract. Since the full amino-acid sequences of almost all the

chaperonins expressed by the bacteria present at the study site are unknown, the possibility cannot be ruled out that two identified peptides were erroneously assigned to two distinct chaperonins, whereas these peptides may in fact have originated from one protein, the amino acid sequence of which has not yet been included in the databases. Nevertheless, because of the high level of conservation observed in GroEL proteins (Supplementary Fig. 2), the proteins identified may be expressed by a close relative of the organism identified using the Uniprot database. GroEL originated from Acidiphilium cryptum; Acidithiobacillus ferrooxidans ATCC23270T; Acidithiobacillus ferrooxidans ATCC53993; Acidovorax avenae subsp. avenae; Acidovorax avenae subsp. citrulli; Alkaliphilus metalliredigens; Alkaliphilus oremlandii; Bacillus halodurans; Bacillus pseudofirmus; Bacillus selenitireducens; Bordetella petrii; Clostridium botulinum; Clostridium hiranonis; Clostridium papyrosolvens; Deinococcus desertii; Deinococcus sp. A62; Gallionella ferruginea; Haliangium ochraceum; Lactobacillus delbrueckii subsp. delbrueckii; Lactobacillus delbrueckii subsp. indicus; Leptothrix cholodnii; Limnobacter sp. MED105; Methylibium petroleiphilum; Methylococcus capsulatus; Methylotenera mobilis; Propionibacterium freudenreichii; Ralstonia picketii; Rhodobacterales bacterium HTCC2083; Sinorhizobium medicae; Stackebrandtia nassauensis; Streptosporangium roseum; Thermanaerovibrio acidaminovorans; Thiomonas 3As; Thiomonas intermedia; Verminephrobacter eiseniae; Virgibacillus pantothenticus; and Gammaproteobacterium HTCC2207

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A. avenae subsp. avenae A. avenae subsp. citrulli A. ferrooxidans ATCC53993 A. ferrooxidans ATCC23270T A. cryptum A. metalliredigens A. oremlandii B. halodurans B. pseudofirmus B. selenitireducens B. petrii C. botulinum C. hiranonis C. papyrosolvens D. desertii D. sp. A62 G. ferruginea Gamma-proteobacterium HTCC2207 H. ochraceum L. delbrueckii subsp. delbrueckii L. delbrueckii subsp. indicus L. cholodnii Limnobacter sp. MED105 M. petroleiphilum M. capsulatus M. mobilis P. freudenreichii R. picketii Rhodobacterales bacterium HTCC2083 S. medicae S. nassauensis S. roseum T. acidaminovorans Thiomonas 3As T. intermedia V. eiseniae V. pantothenticus

A. avenae subsp. avenae A. avenae subsp. citrulli A. ferrooxidans ATCC53993 A. ferrooxidans ATCC23270T A. cryptum A. metalliredigens A. oremlandii B. halodurans B. pseudofirmus B. selenitireducens B. petrii C. botulinum C. hiranonis C. papyrosolvens D. desertii D. sp. A62 G. ferruginea Gamma-proteobacterium HTCC2207 H. ochraceum L. delbrueckii subsp. delbrueckii L. delbrueckii subsp. indicus L. cholodnii Limnobacter sp. MED105 M. petroleiphilum M. capsulatus M. mobilis P. freudenreichii R. picketii Rhodobacterales bacterium HTCC2083 S. medicae S. nassauensis S. roseum T. acidaminovorans Thiomonas 3As T. intermedia V. eiseniae V. pantothenticus

Figure 3 (continued)

2392 affiliated bacteria), Methylotenera (Thiobacillusrelated clones), D. koreensis (which is affiliated to the γ-proteobacteria HTCC2207), Ferrimicrobium-like bacteria (which are related to the Actinobacteria S. nassauensis and S. roseum), and Haliangium (clones affiliated to sulfatereducing bacteria JHA1, D. limimaris and D. svalbardensis) may play a role in this ecosystem. All in all, the data obtained here show that Firmicutes, which could be affiliated to Alicyclobacillus ferrooxidans, are also active. These bacteria are able to oxidize ferrous iron [37] and may, therefore, participate in the transformation of the iron present in high concentrations in these waters. The active population as a whole was not only composed of several ironoxidizers in addition to At. ferrooxidans but also contained iron reducers, one known arsenite-oxidizer, sulfate-reducing, and sulfur compound oxidizers, and both autotrophic and heterotrophic bacteria. All these bacteria

may contribute importantly to the remediation process observed in situ. In Conclusion The active bacterial species inhabiting Carnoulès AMD ecosystem were identified in this study using highsensitivity nanoLC-chip-MS/MS methods combined with a 16S rRNA based phylogenetic approach. The metaproteomic data obtained here show for the first time that Gallionella, Thiomonas, At. ferrooxidans, and Acidiphilium actively express proteins in situ. Previous hypotheses based on experiments performed under laboratory conditions [14, 18, 21, 22, 24, 48] suggest that microbial activity may contribute to the arsenite oxidation and As immobilization occurring in the heavily contaminated AMD at the Carnoulès mine via iron oxidation processes.

Active Bacteria in Arsenic-Rich Sediments

Since these bacteria were found to be active and to express proteins which are among the most abundant proteins encountered at this site, it seems likely that the large amounts of pale-yellow As(V)–Fe(III) hydroxysulfate sediments forming at Carnoulès, which were characterized here, may result from the conjugate activities of ironoxidizing microorganisms (such as At. ferrooxidans, Alicyclobacillus ferrooxydans, Ferrimicrobium, or Gallionella) and arsenic-oxidizing microorganisms (such as Thiomonas sp.). Several bacteria may be responsible in situ for changing the ratio between the oxidized and reduced forms of iron, arsenic, and sulfur compounds, promoting the formation of the Fe (III)–As(V) hydroxysulfate precipitates detected in this study. These bacteria are therefore of prime importance in the partial but efficient natural process of remediation undergone by the contaminated Carnoulès ecosystem. In addition, autotrophic iron, arsenic, and sulfur oxidizers may provide the organic carbon sources required by the functional heterotrophs such as Acidiphilium present in this ecosystem. All in all, the present findings provide evidence that the functional genomics approach provides a useful means of describing bacterial communities such as those inhabiting the Reigous creek and determining their contribution to natural attenuation processes. It is now proposed to use approaches of this kind in future studies to complete this picture of the functional processes at work in this ecosystem, as well as to investigate the role played by the less abundant active bacteria identified in this study. Acknowledgements The study was financed by the EC2CO program (“Institut National des Sciences de l’Univers,” CNRS), the “Observatoire de Recherche Méditerranéen en Environnement” (OSU-OREME), and by the ANR 07-BLANC-0118 project (“Agence Nationale de la Recherche”). Sébastien Gallien and Aurélie Volant were supported by a grant from the French Ministry of Education and Research. This work was performed in the framework of the “Groupement de recherche: Métabolisme de l’Arsenic chez les Microorganismes” (GDR2909-CNRS).

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Author's personal copy Extremophiles (2012) 16:645–657 DOI 10.1007/s00792-012-0466-8

ORIGINAL PAPER

Archaeal diversity: temporal variation in the arsenic-rich creek sediments of Carnoule`s Mine, France A. Volant • A. Desoeuvre • C. Casiot • B. Lauga • S. Delpoux G. Morin • J. C. Personne´ • M. He´ry • F. Elbaz-Poulichet • P. N. Bertin • O. Bruneel

•

Received: 16 February 2012 / Accepted: 3 May 2012 / Published online: 20 June 2012 Ó Springer 2012

Abstract The Carnoule`s mine is an extreme environment located in the South of France. It is an unusual ecosystem due to its acidic pH (2–3), high concentration of heavy metals, iron, and sulfate, but mainly due to its very high concentration of arsenic (up to 10 g L-1 in the tailing stock pore water, and 100–350 mg L-1 in Reigous Creek, which collects the acid mine drainage). Here, we present a survey of the archaeal community in the sediment and its temporal variation using a culture-independent approach by cloning of 16S rRNA encoding genes. The taxonomic affiliation of Archaea showed

Communicated by F. Robb.

Electronic supplementary material The online version of this article (doi:10.1007/s00792-012-0466-8) contains supplementary material, which is available to authorized users. A. Volant  A. Desoeuvre  C. Casiot  S. Delpoux  J. C. Personne´  M. He´ry  F. Elbaz-Poulichet  O. Bruneel (&) Laboratoire HydroSciences Montpellier, HSM, UMR 5569 (IRD, CNRS, Universite´s Montpellier 1 et 2), Universite´ Montpellier 2, Place E. Bataillon, CC MSE, 34095 Montpellier, France e-mail: [email protected] B. Lauga Equipe Environnement et Microbiologie, EEM, UMR 5254 (IPREM, CNRS), Universite´ de Pau et des Pays de l’Adour, BP 1155, 64013 Pau, France G. Morin Institut de Mine´ralogie et de Physique des Milieux Condense´s, IMPMC, UMR 7590 (CNRS, Universite´ Pierre et marie curie/Paris 6), 4 place Jussieu, 75252 Paris, France P. N. Bertin Laboratoire de Ge´ne´tique Mole´culaire, Ge´nomique, Microbiologie, GMGM, UMR 7156 (Universite´ de Strasbourg, CNRS), De´partement Microorganismes, Ge´nomes, Environnement, 28 Rue Goethe, 67083 Strasbourg, France

a low degree of biodiversity with two different phyla: Euryarchaeota and Thaumarchaeota. The archaeal community varied in composition and richness throughout the sampling campaigns. Many sequences were phylogenetically related to the order Thermoplasmatales represented by aerobic or facultatively anaerobic, thermoacidophilic autotrophic or heterotrophic organisms like the organotrophic genus Thermogymnomonas. Some members of Thermoplasmatales can also derive energy from sulfur/iron oxidation or reduction. We also found microorganisms affiliated with methanogenic Archaea (Methanomassiliicoccus luminyensis), which are involved in the carbon cycle. Some sequences affiliated with ammonia oxidizers, involved in the first and rate-limiting step in nitrification, a key process in the nitrogen cycle were also observed, including Candidatus Nitrososphaera viennensis and Candidatus nitrosopumilus sp. These results suggest that Archaea may be important players in the Reigous sediments through their participation in the biochemical cycles of elements, including those of carbon and nitrogen. Keywords Archaea  Diversity  Arsenic  Acid mine drainage  Lead and zinc mine

Introduction Acid mine drainage (AMD) water is a worldwide environmental problem caused by active and abandoned mines (Johnson and Hallberg 2003). Mining and processing of sulfide-rich ores produce large amounts of pyrite-rich waste. In contact with meteoric water, oxidation of this material generates AMD. These effluents are generally characterized by a low pH and contain significant quantities of sulfates, metals and metalloids including arsenic. AMD generation is mainly mediated by acidophilic iron-oxidizing microorganisms

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(Edwards et al. 1999). Natural remediation of AMD can be observed at the Carnoule`s site (France) or at Rio Tinto (Spain) (Casiot et al. 2003; Sa´nchez Espan˜a et al. 2005). This natural remediation of metal pollutants is generally due to the occurrence of abiotic reactions and/or microbial activities that make these toxic compounds insoluble and lead to their accumulation in sediments (Hallberg 2010). These precipitations mainly involve the oxidation and precipitation of iron and the adsorption of other metals and metalloids by the resulting ferric minerals. Sulfate-reducing bacteria also have the ability to reduce sulfate to sulfide, which then reacts with certain dissolved metals to form insoluble precipitates (Hallberg 2010). In addition, several bacteria contribute to the immobilization of arsenic, thanks to their ability to oxidize this metalloid, arsenate As(V) being less soluble than arsenite As(III) (Bowell 1994). The microbiology of AMD streams has been the subject of numerous studies. While a large amount of information is available on acidophilic bacteria indigenous to AMD, little is known about Archaea (Hallberg 2010). Several studies evidenced the presence of archaeal communities in acidic waters (Edwards et al. 2000; Dopson et al. 2004). The Archaea reported in AMD systems include groups of sulfur and/or iron-oxidizers, such as Sulfolobus, Acidianus, Metallosphaera, Sulfurisphaera, and Ferroplasma (Edwards et al. 2000; Golyshina et al. 2000; Baker and Banfield 2003). It has consequently been suggested that Archaea could also play a major role in the generation and remediation of AMD via oxidation of iron (Baker and Banfield 2003). Archaea may also play a role in the biogeochemical cycling of arsenic, for example, through the presence of Archaea that respire As(V) like Pyrobaculum aerophilum and Pyrobaculum arsenaticum (Huber et al. 2000; Oremland and Stolz 2003). In a previous study, Bruneel et al. (2008) investigated the archaeal community in water samples from Carnoule`s, an AMD very rich in metallic elements and especially arsenic compared to many others AMD. This study reported the presence of Ferroplasma acidiphilum and sequences affiliated to uncultured Thermoplasmatales archaeon. However, the archaeal population that inhabits the arsenic-rich Reigous sediments has never been characterized. Thus, to improve our understanding of AMD functioning, we characterized the archaeal communities present in sediment samples from the arsenic-rich AMD of the Carnoule`s mine (France) and their temporal variations using a 16S rRNA encoding gene library.

Materials and methods Description of the study site The Pb-Zn Carnoule`s mine, located in southern France, was closed in 1962. The mining extraction left about 1.2 Mt of

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solid sulfidic wastes containing 0.7 wt% lead, 10 wt% iron and 0.2 wt% arsenic, which are stored behind a 6 m high dam on the uppermost course of Reigous Creek. The seepage water, which percolates through the wastes, emerges at the base of the tailings dam, and is the initial source of Reigous Creek. The water is acidic (2 \ pH \ 3) and rich in dissolved sulfate, iron and arsenic (2000–7700, 500–1000 and 50–350 mg L-1, respectively) the later being predominantly in reduced forms: Fe(II) and As(III) (Casiot et al. 2003). The arsenic concentration decreases within the first 30 m of the creek mainly due to bacterial iron oxidation which leads to the coprecipitation of 20–60 % of dissolved arsenic (Casiot et al. 2003). Although the arsenic level remains high, its concentration subsequently decreases by around 95 % between the source of Reigous Creek and its confluence with the Amous River, 1.5 km downstream. The precipitates, which form around stromatolitic-like bacterial structures, are mainly composed of Fe(III)–As(III) in winter in the first 10 m and of amorphous Fe(III)–As(V) during the rest of the year (Casiot et al. 2003; Morin et al. 2003). Many studies (including culture-dependent and independent) have been conducted on the bacterial communities inhabiting the Carnoule`s mine. Two of them focused specifically on sediment. The active bacterial species were identified in the sediments in the April 2006 library using high sensitivity nanoLC-chip-MS/MS methods combined with a 16S rRNA based phylogenetic approach (Bruneel et al. 2011). This study showed that Gallionella, Thiomonas, Acidithiobacillus ferrooxidans, and Acidiphilium actively expressed proteins in situ. Meta- and proteo-genomics approaches were also used on sediments in the May 2007 library and allowed reconstruction of seven bacterial strains (Bertin et al. 2011). These studies and previous results (Casiot et al. 2003; Morin et al. 2003) suggest that the large amounts of As(V)– Fe(III) hydroxysulfate sediments forming at Carnoule`s may result from the combined activities of iron-oxidizing microorganisms (such as At. ferrooxidans, Alicyclobacillus ferrooxidans, Ferrimicrobium, or Gallionella) and arsenicoxidizing microorganisms (such as Thiomonas sp.). Sampling procedure and measurement of physicochemical properties Four sampling campaigns were carried out in April 2006, October 2008, January 2009 and November 2009. Samples were collected at the station called COWG (Carnoule`s Oxidizing Wetland, point G) located 30 m downstream of the spring (Bruneel et al. 2003). 5 cm deep pale yellow loosely packed sediments were collected at the bottom of the creek using a sterile spatula and pooled [global positioning system (GPS) coordinates: 44107001.8000N/ 4100006.9000E]. This sampling was done in three replicates. Solid phases were harvested by centrifugation and

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dried under vacuum before mineralogical and spectroscopic analyses. The main physicochemical parameters (pH, T °C, and dissolved oxygen concentration) of the running water at the sampling point were measured in the field. pH and water temperature were measured with an Ultrameter Model 6P (Myron L 125 Company, Camlab, Cambridge). Water samples (500 ml) were immediately filtered through 0.22 lm Millipore membranes fitted on Sartorius polycarbonate filter holders. For total iron and arsenic determination, the filtered water was acidified to pH 1 with HNO3 (14.5 M) and stored at 4 °C in polyethylene bottles until analysis. For arsenic and iron speciation, a 20 ll aliquot of filtered water sample was added to either a mixture of acetic acid and EDTA (Samanta and Clifford 2005) for arsenic speciation or to a mixture of 0.5 ml acetate buffer (pH 4.5) and 1 ml of 1,10-phenanthrolinium chloride solution (Rodier et al. 1996) for Fe(II) determination. The vials were completed to 10 ml with deionized water. The samples for iron and arsenic speciation and sulfate determination were stored in the dark and analyzed within 24 h. Chemical analysis were carried out as previously described (Bruneel et al. 2011). Solid sample characterization The mineralogical composition of the solid samples collected at COWG was qualitatively determined using powder X-ray diffraction analysis (XRD). Data were collected with Co K-alpha radiation on an X’Pert PRO P analytical diffractometer equipped with an X’Celerator detector, in continuous mode and a counting time of 4 h per sample. X-ray absorption spectroscopy data were collected on the solid phases sampled at COWG in October 2008, January 2009, and November 2009. X-ray absorption near edge structure (XANES) and extended X-ray absorption fine structure (EXAFS) spectra were recorded at a temperature 10–15 K in fluorescence mode on the FAME BM30B bending magnet beamline at ESRF (Grenoble, France). Data for the April 2006 COWG sample were previously collected at the 11-2 wiggler beamline at SSRL (Stanford, CA) and analyzed in Bruneel et al. (2011). Experimental details and data reduction procedures are reported in previous studies (Morin et al. 2003; Ona-Nguema et al. 2005; Hohmann et al. 2011). XANES and EXAFS data were interpreted by linear combination fitting using a set of model compound spectra. This set includes As(V)- and As(III)–Fe(III) oxyhydroxides and oxyhydroxysulfates synthesized via biotic and abiotic pathways (Morin et al. 2003; Maillot 2011). DNA isolation Triplicate genomic DNA was extracted from sediments using the UltraClean Soil DNA Isolation Kit according to

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the manufacturer’s recommendations (MoBio Laboratories Inc., Carlsbad, CA, USA). These triplicates were pooled before PCR amplification. All extracted genomic DNA samples were stored at -20 °C until further analysis. PCR amplification Amplification of archaeal 16S rRNA genes was obtained by PCR using primers Arch21F (50 -TTCCGGTTGATCC YGCCGGA-30 ) and Arch958R (50 -YCCGGCGTTGAMTC CAATT-30 ) (Delong 1992). Two PCR protocols were used due to major amplification difficulties. The first PCR amplification mixture contained 2 ll of DNA template, 2 ll of both primers (20 lM), 25 ll of PCR Master Mix Ampli Taq Gold 360 (Applied Biosystems, Foster City, CA, USA). Sterile distilled water was added to reach a final volume of 50 ll. The PCR conditions were as follows, an initial denaturation step of 95 °C for 7 min followed by 35 denaturation cycles at 95 °C for 1 min, an annealing cycle at 55 °C for 45 s and an extension cycle at 72 °C for 1 min. Final extension was at 72 °C for 10 min. As amplification of the January 2009 sample failed with this protocol, another enzyme was used, the PCR Extender Polymerase Mix (5Prime, Hamburg, Deutschland) as well as for a part of the November 2009 sample, which was also very difficult to amplify. The second PCR amplification mixture contained 2 ll of DNA template, 2 ll of both primers (20 lM), 2.5 ll of dNTPs 10 mM, 5 ll reaction Tunning buffer 910 and 0.5 ll of PCR Extender Polymerase Mix (5Prime, Hamburg, Deutschland). Sterile distilled water was added to reach a final volume of 50 ll. The PCR conditions were as follows: initial denaturation step at 94 °C for 3 min followed by 35 denaturation cycles at 94 °C for 1 min, an annealing cycle at 55 °C for 1 min, and an extension cycle at 72 °C for 1.5 min. Final extension was at 72 °C for 10 min. PCR products were purified with the GFX PCR DNA purification kit (AmershamPharmacia). The PCR Extender polymerase mix creates blunt ended products. For TA CloningÒ, 30 A-overhangs are needed on these PCR products, which are obtained with a different Taq polymerase. To 25 ll of purified PCR product, 2.5 ll of buffer 109, 0.5 ll of dATPs 10 mM, and 0.5 ll of Taq DNA polymerase (EurobiotaqÒ, Eurobio, France) were added. The PCR amplification mixture was then incubated at 72 °C for 20 min. Cloning and 16S rRNA gene sequencing The PCR products were cloned in E. coli TOP 10 strain using the pCR2.1 Topo TA cloning kit (Invitrogen, Inc., Carlsbad, CA, USA). Cloned 16S rRNA gene fragments were re-amplified using the primers TOP1 (50 -GTGTGCT GGAATTCGCCCTT-30 ) and TOP2 (50 -TATCTGCAGAA

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TTCGCCCTT-30 ) that anneal to the vector and flank the inserted PCR fragment. A total of 340 clones from the four libraries were sequenced. Partial sequences of the clones were determined by the dideoxy nucleotide chain-termination method using the BigDye 3.1 kit (Applied Biosystems) on an ABI PRISM 3730XL Genetic analyzer (Applied Biosystems). The MALLARD program (Ashelford et al. 2006) was used to detect and then remove chimera. Sequences were also examined manually for chimera, which were excluded from further analyses. Sequences were then aligned in Mothur (http://www.mothur.org) (Schloss et al. 2009) using the SILVA archaeal database as reference alignment. The same program was used to calculate a neighbor-joining (NJ) (Saitou and Nei 1987) distance matrix using the Jukes-Cantor (JC) correction. The matrix was then used to assign sequences to operational taxonomic units (OTUs) defined at 97 (species level) and 85 % (class level) cutoff using the furthest-neighbor algorithm. Sequences were compared with the available databases NCBI and Greengenes (http://greengenes.lbl.gov) by BLAST online searches (Altschul et al. 1990) and Mothur to identify their taxonomic identities. Representative sequences for each OTU defined at 97 % cutoff were identified using the tool implemented in Mothur and were submitted to the EMBL databases under accession numbers (HE653775–HE653816). Phylogenetic analysis Archaeal 16S rRNA gene homologs were collected from the database at NCBI using the BLAST program with default parameters; one representative of each OTU was selected, giving a dataset of 99 sequences for final analysis. Multiple sequence alignment of partial prokaryotic sequences was performed using Clustal W (Thompson et al. 2000). A maximum likelihood phylogenetic reconstruction was obtained using the PhyML program (Guindon and Gascuel 2003) with the GTR model, four evolutionary rates, a calculated proportion of invariant sites and calculated nucleotide frequencies (default parameters). Statistical likelihood at nodes was calculated via a likelihood-ratio test (Anisimova and Gascuel 2006). Statistical analysis of diversity and comparison of archaeal libraries The Mothur software package was also used to generate diversity indices and statistics (OTUs, total clones, singletons, Chao1, Shannon, evenness, coverage) for each clone library as sequence similarity with a 97 % cutoff. The total number of clones obtained compared with the number of clones representing each unique phylotype was used to produce the rarefaction curves at the 85 % level. Coverage

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values were calculated to determine how efficiently the libraries described the complexity of a theoretical community like an original archaeal community. The coverage (Good 1953) value is given as C = 1 - (n1/N) where n1 is the number of clones that occurred only once in the library. To determine the significance of differences between archaeal libraries, a LIBSHUFF statistical analysis was performed in Mothur following Singleton et al.’s (2001) method. A LIBSHUFF comparison of libraries yielded the following formula using the Bonferroni correction: 0.05 = 1-(1 - a)k(k - 1), where a is the critical P value and k is the number of libraries. The critical P value is 0.0042 when four libraries are compared. If any comparison of two libraries has a P value below or equal to 0.0042, then there is 95 % confidence to believe that the two libraries concerned differ significantly in community composition. Jaccard and Yue & Clayton theta tree clustering analysis (Yue and Clayton 2005) were also performed in Mothur to identify community membership and structure relationships between the libraries.

Results Physical and chemical characteristics of samples The physicochemical characteristics of the waters are listed in Table 1. The physicochemistry of Reigous Creek water at these sampling periods was typical of that observed during a previous long-term monitoring study (Egal et al. 2010). The water samples were acid (pH = 2.91–3.28) and very rich in sulfate (1830–3400 mg L-1), iron (510–1735 mg L-1), and arsenic (70–194 mg L-1), with predominance of the reduced forms Fe(II) and As(III). Dissolved oxygen concentrations ranged from 3.5 to 7.86 mg L-1. The January 2009 sample showed the lowest iron, arsenic, and sulfate concentrations. The nature and structure of the sediment samples were investigated using mineralogical and spectroscopic methods. XANES analyses at the arsenic K-edge showed that, despite the presence of an As(III) component equal to 12–34 ± 5 % of total arsenic, the oxidized arsenic form As(V) predominated in all the sediments (Fig. S1). EXAFS data (Fig. S2) showed that As(V) was mainly present in the samples in an amorphous Fe(III)–As(V) hydroxysulfate phase, as previously observed (Morin et al. 2003; Bruneel et al. 2011), As(III) being likely sorbed to poorly ordered schwertmannite. For January 2009, there was not enough time exposure to X-ray beam in EXAFS analysis to record this sample, however, based on the XANES data we can assume that this sample should be similar to the others. XRD analyses (Fig. S3) showed that these arsenic-bearing phases were mixed with sandy components (quartz,

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Table 1 Physico-chemical characteristics of the water (mg L-1) during sampling at COWG Sampling period

pH (±SD)

T (°C)

DO (±SD)

As(III) (±SD)

As(V) (±SD)

Fe (total) (±SD)

Fe(II) (±SD)

SO42- (±SD)

April 2006

3.28 (±0.05)

12.9

3.5 (±0.5)

69 (±3)

71 (±4)

620 (±30)

560 (±28)

2700 (±300)

October 2008

3.13 (±0.05)

14.3

5.7 (±0.1)

133 (±7)

20 (±1)

1250 (±62)

1220 (±61)

3400 (±340)

January 2009

2.91 (±0.05)

9.4

5.5 (±0.5)

43 (±2)

27 (±1)

510 (±25)

540 (±27)

1830 (±183)

November 2009

3.26 (±0.05)

13.1

7.9 (±0.1)

161 (±8)

33 (±2)

1735 (±87)

1440 (±72)

3300 (±330)

SD standard deviation

K-feldspar and micas) and that pyrite was only detected after October 2008. Diversity analysis A total of 340 clones obtained from the four independent 16S rRNA gene libraries were fully sequenced and phylogenetically analyzed. Thirteen sequences were identified as likely chimeras and excluded from further analyses. Sequencing and phylogenetic analysis of the 327 remaining cloned sequences led to the identification of 9 and 42 OTUs defined at two different levels of identity (85 and 97 %, respectively). Rarefaction curves calculated at the class level (85 % identity, the rank usually used for representing the microbial community) were near saturation (Fig. 1). Table 2 shows the Shannon, evenness, and Chao1 indices and the coverage values calculated for each library at 97 % identity. The coverage values of the four clone libraries (90, 88, 96 and 92, respectively, for April 2006, October 2008, January 2009, and November 2009) indicate that the clone libraries were sufficiently sampled. The estimations of the diversity indices show that the structure and membership composition of the archaeal community changed over the sampling period. The Shannon diversity (H) and Chao1 richness indices ranged from 1.37 to 2.57 and 6.5 to 30.5, respectively. The diversity (H = 1.37) and richness (Chao1 = 6.5) were significantly lower in January 2009 whereas November 2009 displayed the highest values (H = 2.57; Chao1 = 30.5), which is consistent with the rarefaction curves. Comparison of archaeal community The overall community structure was analyzed for each sample using the Mothur software package. LIBSHUFF analysis was performed to compare the OTU compositions of each clone library revealing a high degree of variation between individuals and showing that with Bonferroni correction, each library differed significantly from all others (Table 3). The resulting dendrograms of Jaccard and Yue & Clayton theta similarity coefficient analysis (Fig. 2) identified one major cluster and one outlier (January 2009). The similarity in community membership (Jaccard index,

Fig. 1 Rarefaction curves of the archaeal 16S rRNA sequences from Carnoule`s mine sediments at 85 % identity. The total number of sequenced clones is plotted against the number of OTUs observed in the same library

Fig. 2a) showed that April 2006 and November 2009 were more related to each other in this respect, whereas April 2006 and October 2008 were more related to each other in terms of community structure (Yue & Clayton index, Fig. 2b). Phylogenetic analysis of archaeal community Four 16S rRNA encoding gene libraries were constructed each containing a distinct archaeal community, which varied in composition and richness throughout the sampling campaigns. In April 2006, the 16S rRNA phylogenetic reconstruction (Fig. 3) showed that all the sequences corresponding to 17 OTUs (OTUs 1–17) were affiliated to the phylum Euryarchaeota, as previously observed in the water samples from Carnoule`s (Bruneel et al. 2008). The most abundant OTU (OTU 1, 53 clones representing around 61 % of the sample) was affiliated to the order Thermoplasmatales which contained 97 % of the sequences grouped in 15 OTUs. Within this order, the majority of the OTUs were closely related to uncultured clones from an acidic environment such as acidic mine water and sediments (Fig. 3).

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Table 2 Diversity indices and statistics calculated for the four clone libraries from COWG station at different sampling periods Clone library

No. of sequences

No. of OTUsa

Singletons

Good’s coverageb

Shannon diversityc

Chao1 richness

April 2006

87

17

9

90

1.63

24.2

October 2008

80

20

10

88

1.96

27.5

January 2009

47

6

2

96

1.37

6.5

113

25

9

92

2.57

30.5

November 2009 a

OTUs were defined at 97 % cutoff

b

Coverage: sum of probabilities of observed classes calculated as (1 - (n/N)), where n is the number of singleton sequences and N is the total number of sequences

c

Takes into account the number and evenness of species

Table 3 Community comparison using LIBSHUFF Y library Apr-06

Oct-08

Jan-09

Nov-09

X library Apr-06

\0.0001*

0.1529

\0.0001*

0.0001*

\0.0001*

–

0.2222

\0.0001*

\0.0001*

–

–

0.0260

Oct-08

0.0001*

Jan-09

\0.0001*

Nov-09

\0.0001*

–

* Significant difference. Bonferroni correction P value = 0.0042 – Not compared

The BLAST affiliation (Table 4) showed that some of these OTUs displayed 89–94 % similarity with Thermogymnomonas acidicola, a moderately thermophilic, acidophilic, strictly aerobic heterotroph that uses yeast extract, as well as glucose and mannose (in the presence of yeast extract) as carbon and energy sources (Itoh et al. 2007). Additionally, OTU 15 related to the uncultured clone ORCMO 26 retrieved from a copper mine drainage (Rowe et al. 2007, Fig. 3) was found. This OTU was assigned to methanogenic lineage (Methanomicrobia, Fig. 3) with the closest relative Methanomassiliicoccus luminyensis, a methanogenic Archaea recently isolated from human faeces (Dridi et al. 2011). However, the Greengenes classification (Table 4) assigned this OTU to the order Thermoplasmatales. Lastly, an unknown group belonging to the Euryarchaeota and represented by OTU 8 was detected. This group formed an independent branch that was distantly related to the identified groups and showed low similarity with the uncultured archaeon clone hfm29 isolated from an iron-rich microbial mat (Kato et al. in press). Twenty OTUs were retrieved from the October 2008 library, 18 of which belonged to the Euryarchaeota and two to the Thaumarchaeota (Fig. 3). Like in April 2006, most of the Euryarchaeota sequences were affiliated with the Thermoplasmatales (OTUs 1, 6, 9, 11, 12, 17, 19, 20,

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Fig. 2 Similarities in archaeal community membership (Jaccard a) and in community structure (Yue & Clayton b) between samples. Values are based on 0.03 distances

22–27, and 31) which accounted for 86 % of the total archaeal clones including the same most abundant OTU (OTU1; around 54 %, Fig. 3). The BLAST affiliation (Table 4) also revealed similarity of some OTUs with Thermogymnomonas acidicola. Three OTUs (18, 21, and 28) affiliated with uncultured clones isolated from acidic environments (clone SALE1B1 and clone anta6) and from a forested wetland impacted by reject coal (clone ARCP212) (Brofft et al. 2002; Garcı´a-Moyano et al. 2007, Fig. 3), respectively, were assigned to Methanomicrobia. The remaining OTUs (OTUs 29 and 30) were affiliated with environmental sequences originating from acidic soil and acidic hot springs, which likely represent uncultured lineages of Thaumarchaeota. A significant change in the archaeal community appeared in the January 2009 library, when diversity decreased and no cultured species were identified. Indeed, almost all the sequences (96 %) clustered in five OTUs (OTUs 8, 32, 33, 34, and 35, Fig. 3) were related to the uncultured archaeon clone hfmA029 previously found in April 2006. This group formed an independent branch that was far away from the remaining groups. This clone displayed around 97 % similarity with Methanothermobacter thermautotrophicus, an autotrophic thermophilic methanogen recovered from an anaerobic sewage sludge digester (Zeikus and Wolee 1972). Remaining sequences grouped

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Fig. 3 Maximum likelihood tree of 16S rRNA gene homologs from the archaeal clones (in bold) along with a selection of representatives of archaeal diversity. Numbers at nodes indicate a LTR (approximate likelihood ratio test) branch support as computed by PhyML. The

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scale bar gives the average number of substitutions per site. The number in parenthesis indicates the number of clones for the sampling period which is represented by a symbol (star April 2006, square October 2008, circle January 2009 and diamond November 2009)

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Table 4 Identification number of the OTUs retrieved from the Reigous Creek sediment of Carnoule`s mine, taxonomic affiliation and representative sequence for each OTU OTU ID

Number of sequences

Representative sequence

Taxonomic affiliation Phylum

Class

Order

1

132

ArCMSdO8D35

Euryarchaeota

Thermoplasmata

Thermoplasmatales

Aciduliprofundum sp. EPR07-39 (85 %)

2

15

ArCMSdA6A12

Euryarchaeota

Thermoplasmata

Thermoplasmatales

Thermogymnomonas acidicola JCM 13583 (89 %)

3

2

ArCMSdA6A86

Euryarchaeota

Thermoplasmata

Thermoplasmatales

Aciduliprofundum sp. EPR07-39 (85 %)

4

4

ArCMSdA6A46

Euryarchaeota

Thermoplasmata

Thermoplasmatales

Thermogymnomonas acidicola JCM 13583 (90 %)

5

1

ArCMSdA6A17

Euryarchaeota

Thermoplasmata

Thermoplasmatales

Thermogymnomonas acidicola JCM 13583 (91 %)

6

16

ArCMSdA6A67

Euryarchaeota

Thermoplasmata

Thermoplasmatales

Thermogymnomonas acidicola JCM 13583 (92 %)

7

3

ArCoSdN9H63

Euryarchaeota

Thermoplasmata

Thermoplasmatales

Thermogymnomonas acidicola JCM 13583 (93 %)

8

24

ArCMSdJ9B78

Euryarchaeota

–

–

Clone hfmA029 (86 %)

9

4

ArCMSdA6A30

Euryarchaeota

Thermoplasmata

Thermoplasmatales

Thermogymnomonas acidicola JCM 13583 (88 %)

10

3

ArCoSdN9D80

Euryarchaeota

Thermoplasmata

Thermoplasmatales

Thermogymnomonas acidicola JCM 13583 (94 %)

11

7

ArCMSdO8B50

Euryarchaeota

Thermoplasmata

Thermoplasmatales

Thermogymnomonas acidicola JCM 13583 (94 %)

12

4

ArCMSdO8B53

Euryarchaeota

Thermoplasmata

Thermoplasmatales

Thermogymnomonas acidicola JCM 13583 (90 %)

13

1

ArCMSdA6A52

Euryarchaeota

Thermoplasmata

Thermoplasmatales

Thermoplasma volcanium (84 %)

14

2

ArCMSdA6A84

Euryarchaeota

Thermoplasmata

Thermoplasmatales

Thermogymnomonas acidicola JCM 13583 (90 %)

15

3

ArCoSdN9H35

Euryarchaeota

Thermoplasmata

–

Methanomassiliicoccus luminyensis B10 (80 %)

16

1

ArCMSdA6A92

Euryarchaeota

Thermoplasmata

Thermoplasmatales

Thermogymnomonas acidicola JCM 13583 (91 %)

17

4

ArCoSdN9H43

Euryarchaeota

Thermoplasmata

Thermoplasmatales

Thermogymnomonas acidicola JCM 13583 (88 %)

18

5

ArCMSdO8A3

Euryarchaeota

Thermoplasmata

–

Methanomassiliicoccus luminyensis B10 (82 %)

19

1

ArCMSdO8A13

Euryarchaeota

Thermoplasmata

Thermoplasmatales

Thermogymnomonas acidicola JCM 13583 (89 %)

20

1

ArCMSdO8A16

Euryarchaeota

Thermoplasmata

Thermoplasmatales

21

2

ArCoSdN9H67

Euryarchaeota

Thermoplasmata

–

Thermogymnomonas acidicola JCM 13583 (87 %) Methanomassiliicoccus luminyensis B10 (83 %)

22

1

ArCMSdO8A24

Euryarchaeota

Thermoplasmata

Thermoplasmatales

Thermogymnomonas acidicola JCM 13583 (88 %)

23

2

ArCMSdO8A56

Euryarchaeota

Thermoplasmata

Thermoplasmatales

24

4

ArCMSdO8A49

Euryarchaeota

Thermoplasmata

Thermoplasmatales

Thermogymnomonas acidicola JCM 13583 (89 %) Thermoplasma volcanium GSS1 (89 %)

25

1

ArCMSdO8A54

Euryarchaeota

Thermoplasmata

Thermoplasmatales

Thermogymnomonas acidicola JCM 13583 (90 %)

26

3

ArCMSdO8A74

Euryarchaeota

Thermoplasmata

Thermoplasmatales

27

1

ArCMSdO8A85

Euryarchaeota

Thermoplasmata

Thermoplasmatales

Thermogymnomonas acidicola JCM 13583 (99 %) Thermogymnomonas acidicola JCM 13583 (93 %)

123

Closest relative (% of identity)

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653

Table 4 continued OTU ID

Number of sequences

Representative sequence

Taxonomic affiliation

Closest relative (% of identity)

Phylum

Class

Order

28

1

ArCMSdO8A89

Euryarchaeota

Thermoplasmata

–

Methanomassiliicoccus luminyensis B10 (85 %)

29

5

ArCMSdJ9A29

–

–

–

Candidatus Nitrosocaldus yellowstonii HL72 (84 %)

30

2

ArCMSdO8C25

–

–

–

Candidatus Nitrososphaera gargensis (83 %)

31

1

ArCMSdO8E23

Euryarchaeota

Thermoplasmata

Thermoplasmatales

Thermogymnomonas acidicola JCM 13583 (92 %)

32

15

ArCMSdJ9C75

Euryarchaeota

–

–

Clone SVB_Fis_02_pl37c09 (86 %)

33

16

ArCMSdJ9C68

Euryarchaeota

–

–

Clone hfmA029 (85 %)

34

1

ArCMSdJ9C55

Euryarchaeota

Methanomicrobia

Methanomicrobiales

Clone hfmA029 (84 %)

35

2

ArCoSdN9A45

Euryarchaeota

–

–

Clone hfmA029 (85 %)

36

15

ArCoSdN9B9

Thaumarchaeota

No class

Nitrososphaerales

Candidatus Nitrososphaera sp. EN76 (96 %)

37

6

ArCoSdN9F14

Thaumarchaeota

No class

Cenarchaeales

Candidatus Nitrosopumilus sp. NM25 (93 %)

38

11

ArCoSdN9D53

Euryarchaeota

–

–

Clone TG_FD0.2_SA043 (100 %)

39

2

ArCoSdN9H79

Euryarchaeota

Thermoplasmata

Thermoplasmatales

Thermogymnomonas acidicola JCM 13583 (90 %)

40

1

ArCoSdN9E14

Euryarchaeota

Thermoplasmata

Thermoplasmatales

Thermogymnomonas acidicola JCM 13583 (88 %)

41

1

ArCoSdN9G7

Euryarchaeota

Thermoplasmata

Thermoplasmatales

Thermogymnomonas acidicola JCM 13583 (93 %)

42

1

ArCoSdN9H80

Euryarchaeota

Thermoplasmata

Thermoplasmatales

Thermogymnomonas acidicola JCM 13583 (92 %)

OTU definition and taxonomic identification of representative sequences were done using mothur (Schloss et al. 2009; see ‘‘Materials and methods’’ for details). Only taxonomic affiliations with 100 % similarity are shown. The closest relative was obtained by BLAST search on NCBI nr database

in a single OTU (OTU 29) belonged to an unknown group of Thaumarchaeota previously found in October 2008 and were affiliated with clone GBX-A-COQ1-158 isolated from an acidic hot spring (Fig. 3). An increase in archaeal diversity was observed in the November 2009 library, with 25 OTUs belonging to the Euryarchaeota (69 clones corresponding to 61 % of the sample) and to the Thaumarchaeota (22 clones corresponding to 19 % of the sample, Fig. 3). The sequences from the Euryarchaeota were distributed in 22 OTUs. Fifteen were related to the order Thermoplasmatales, 11 of which (OTUs 1, 2, 4, 6, 7, 9, 10, 11, 17, 24, 26) were previously found in the April 2006 and October 2008 libraries (Fig. 3). As in the results observed in these two sampling periods, OTU 1 was also the most abundant group in the sample in November 2009 (32 %). Additionally, OTUs 15 and 21, also found in the two first libraries, were assigned to the order Methanomicrobia. The remaining five OTUs (8, 32, 33, 35, and 38), were not shown to be related to any known species and formed

unknown groups of the Euryarchaeota (Fig. 3). Among these, the most abundant sequences belonging to OTU 38, displayed a strong similarity (99 %) with an uncultured archaeon clone LC15_L00B08 isolated from the monimolimnion of a stratified lake (Gregersen et al. 2009). The four other OTUs (8, 32, 33, and 35) were affiliated with the uncultured archaeon clones hfmA029 mainly present in the January 2009 library. The Thaumarchaeota detected in this study fell into different lineages clustered in three OTUs. The first (OTU 36) belonged to Thaumarchaeota group I.1b and the 15 sequences within this OTU showed from 95 to 96 % similarity with Candidatus Nitrososphaera viennensis a chemolithoautotrophic ammonia-oxidizing archaeon (Tourna et al. 2011). The second (OTU 37) was assigned to Thaumarchaeota group I.1a and the sequences displayed 92–93 % similarity with Candidatus Nitrosopumilus sp., another ammonia-oxidizing prokaryote (Matsutani et al. 2011). The last OTU (OTU 29), previously found in October 2008 could not be related to any known species.

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Discussion Archaeal 16S rRNA gene analysis of the sediment sampled at the Reigous Creek showed that the Carnoule`s archaeal community includes the phylum Euryarchaeota and Thaumarchaeota. The relatively low archaeal diversity revealed by molecular-based methods is consistent with the results of studies in similar environments (Bond et al. 2000; Baker and Banfield 2003; Bruneel et al. 2008; Sa´nchezAndrea et al. 2011). This may reflect the limited number of different electron donors and acceptors available in this AMD and the high concentration of toxic compounds along with the low pH. Most of the phylotypes identified in this study were related to genera and species usually found in extreme environments (hot springs, acidic springs, hydrothermal vents, etc.) and showed similarities with sequences obtained in previous studies of Tinto River and other AMD (Sa´nchez-Andrea et al. 2011; Garcı´a-Moyano et al. 2007; Rowe et al. 2007, Fig. 3). Regarding the dynamics of the archaeal community, our study showed that significant modifications in this community occurred throughout the sampling period. All the sampling periods showed differences in community structure and membership although April 2006 and October 2008 were more similar in terms of community structure. Similarity coefficient analysis showed that January 2009 was very different from all the other sampling periods. In January 2009, the archaeal community changed and diversity decreased. Almost all the sequences were related to an uncultured archaeon clone hfmA029 affiliated with methanogenic lineage (Methanothermobacter thermautotrophicus). This clone, hfmA029, previously found in April 2006 (OTU 8) in only 2 % of the sample became the dominant population in January 2009. The differences in the archaeal community observed in January 2009 may result from a modification in the composition of the sediment, although the physicochemical analysis of the sediments appeared to be similar throughout the sampling period, and consisted mainly of an amorphous Fe(III)– As(V) hydroxysulfate mineral. Indeed, XRD analyses revealed that pyrite first appeared in October 2008. Likewise, since late 2007, a leakage of fine grey sulfide-reach sands out of the tailings pile has been observed after the rainfall events that generally occur in September and October. This is probably due to the corrosion of the drains at the bottom of the tailing stock that are responsible for the water discharge inside the mine tailing. In January 2009, the sulfide sands, originated from the tailings stock, formed a very thick layer (around 3 cm deep) in the bottom of the creek which could explain the change in the archaeal community. In the Reigous sediment, most of the sequences were phylogenetically related to the order Thermoplasmatales,

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although none of the clones could be identified with high similarity ([97 %) as belonging to any cultured species. This order is represented by thermoacidophilic organisms (Reysenbach 2001), which often derive energy from sulfur oxidation or reduction. So far, the order contains three families, each represented by one genus: the Thermoplasmataecae, the Picrophilaceae and the Ferroplasmaceae (Itoh et al. 2007). The Thermoplasmataecae comprises species like Tp. acidophilum that couple the oxidation of organic carbon with reduction of elemental sulfur, whereas members of the Ferroplasmaceae are strict iron-oxidizing chemolithotrophs such as Ferroplasma acidiphilum (Itoh et al. 2007). Microorganisms affiliated with methanogenic Archaea such as Methanomassiliicoccus luminyensis were also identified. Methanogenic communities play an important role in the global carbon cycle, completing the conversion of organic carbon into methane gas by utilizing the metabolic products of bacteria (CO2, H2, acetate, and formate) and other simple methyl compounds available in the environment (Sanz et al. 2011). Lastly, we found microorganisms involved in ammonia oxidation, a key step in the nitrogen cycle (Brochier-Armanet et al. 2011), with presence of sequences affiliated to Candidatus Nitrososphaera viennensis and Candidatus Nitrosopumilus sp. Until recently, ammonia oxidation, the first nitrification step of the nitrogen cycle was thought to be carried out only by autotrophic ammonia-oxidizing bacteria (AOB) belonging to the Beta- and Gammaproteobacteria lineages (Purkhold et al. 2000) occasionally supported by heterotrophic nitrifiers in soil environments (De Boer and Kowalchuk 2001). Ammonia-oxidizing Archaea (AOA) are members of the proposed novel Phylum Thaumarchaeota, and are currently being indentified in almost all environments (Brochier-Armanet et al. 2008). These Archaea may thus play a major role in the nitrogen cycle in the Carnoule`s sediments. Previous studies focused on the bacterial communities inhabiting the Carnoule`s AMD sediment. These studies showed that the active population of bacteria also contained iron reducers, sulfate-reducing, and sulfur compound oxidizers, and both autotrophic and heterotrophic bacteria (Bruneel et al. 2011). Statistical analysis of genomic and proteomic data demonstrated that both metabolic specificity and partnerships can co-exist in this arsenic-rich sediment (Bertin et al. 2011). These processes include the fixation of inorganic carbon and nitrogen by several strains, in particular those belonging to the Thiomonas, Acidithiobacillus, and Gallionella related genera. However, this study did not find evidence for the presence of archaeal species among the dominant organisms, suggesting that they may represent a small proportion of the microbial community in the sediment. Despite the fact that we cannot really infer the implication of the Archaea

Author's personal copy Extremophiles (2012) 16:645–657

detected in most of these metabolic pathways because most of them could not be affiliated to cultured species, we can point to their probable implication in a specific metabolism currently unknown in bacteria (Forterre et al. 2002), methanogenesis. Archaea are also involved in the nitrogen cycle (Candidatus Nitrososphaera viennensis and Candidatus Nitrosopumilus sp.) and some of them may also be involved in the sulfur and iron cycles (Thermoplasmatales). All these microorganisms may contribute to the remediation process observed in situ and could also be involved in the stability of this sediment by changing the ratio between oxidized and reduced forms of iron, arsenic, and sulfur compounds, promoting the formation and/or dissolution of the Fe(III)–As(V) hydroxysulfate precipitates. Because isolation and phenotypic characterization of many environmental Archaea are currently not possible, the physiological features and ecological significance of some Archaea detected in this AMD remain difficult to assess. Moreover, the fact that most of the archaeal sequences were only distantly related (\94 % similarity) to known archaeal species suggests that other taxa may exist. Additionally, the contradictions observed in the taxonomic affiliation resulting from the 16S rRNA phylogenetic reconstruction (Fig. 3) and the Greengenes classification (Table 4) suggest that there is still a lack of information making the taxonomic identification difficult to assess. Indeed, almost half of the 16S rRNA gene sequences archived in GenBank database lacks clear taxonomic information (DeSantis et al. 2006). As a consequence, different authors use different names for uncultured clusters which lead to conflicting nomenclatures. Recently developed high-throughput techniques (metagenomics, metaproteomics, and microarrays) may help link the identity of AMD-promoting prokaryotes to their function in mining environments (Mohapatra et al. 2011; Bertin et al. 2011) in the absence of laboratory culture. In the future, these new genomic tools should provide a more precise assessment of the archaeal diversity that will probably lead to substantial changes in current archaeal phylogeny and taxonomy (Brochier-Armanet et al. 2008; Schleper et al. 2005) and to a better understanding of the evolution and metabolic capacities of uncultured Archaea. In conclusion, to increase our insight into the functioning of these highly acidic environments and to elucidate the role of these microorganisms, both improving culture strategies for further physiological and metabolic characterization of newly detected species and a greater sequencing effort are still needed. Acknowledgments The French CRG is gratefully acknowledged for provision of beamtime on the FAME BM30B beamline. This work was supported by EC2CO CNRS/INSU program, by ACI/FNS Grant

655 #3033 and by SESAME IdF Grant #1775. Part of the field chemical data was acquired through the OSU OREME.

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RESEARCH ARTICLE

Diversity and spatiotemporal dynamics of bacterial communities: physicochemical and other drivers along an acid mine drainage
lie Volant1, Odile Bruneel1, Ange
lique Desoeuvre1, Marina He
ry1, Corinne Casiot1, Noe €lle Bru2, Aure 1 3 3 4 3 Sophie Delpoux , Anne Fahy , Fabien Javerliat , Olivier Bouchez , Robert Duran , Philippe N.
atrice Lauga3 Bertin5, Francßoise Elbaz-Poulichet1 & Be
Montpellier 2, Montpellier, Laboratoire HydroSciences Montpellier, HSM, UMR 5569 (IRD, CNRS, Universit
es Montpellier 1 et 2), Universite e de Pau et des Pays de l’Adour, Pau, France; France; 2Laboratoire de Math
ematiques et de leurs Applications, UMR 5142 (CNRS), Universit
3
Equipe Environnement et Microbiologie, EEM, UMR 5254 (IPREM, CNRS), Universit
e de Pau et des Pays de l’Adour, Pau, France; 4INRA Auzeville, 5

Plateforme Genomique Chemin de Borde Rouge, Castanet-Tolosan, France; and Departement Microorganismes, G
enomes, Environnement, Laboratoire de G
en
etique Mol
eculaire, G
enomique, Microbiologie, GMGM, UMR 7156 (Universit
e de Strasbourg, CNRS), Strasbourg, France 1

Correspondence: Odile Bruneel, Laboratoire HydroSciences Montpellier, UMR5569, Universit
e Montpellier 2, Place E. Bataillon, CC MSE, 34095 Montpellier, France. Tel.: (+33)4 67 14 36 59; fax: (+33)4 67 14 47 74; e-mail: [email protected]

MICROBIOLOGY ECOLOGY

Received 16 April 2014; revised 10 July 2014; accepted 16 July 2014. DOI: 10.1111/1574-6941.12394 Editor: Tillmann Lueders Keywords spatial and temporal dynamics; bacterial diversity; acid mine drainage; arsenic.

Abstract Deciphering the biotic and abiotic factors that control microbial community structure over time and along an environmental gradient is a pivotal question in microbial ecology. Carnoules mine (France), which is characterized by acid waters and very high concentrations of arsenic, iron, and sulfate, provides an excellent opportunity to study these factors along the pollution gradient of Reigous Creek. To this end, biodiversity and spatiotemporal distribution of bacterial communities were characterized using T-RFLP fingerprinting and high-throughput sequencing. Patterns of spatial and temporal variations in bacterial community composition linked to changes in the physicochemical conditions suggested that species-sorting processes were at work in the acid mine drainage. Arsenic, temperature, and sulfate appeared to be the most important factors that drove the composition of bacterial communities along this continuum. Time series investigation along the pollution gradient also highlighted habitat specialization for some major members of the community (Acidithiobacillus and Thiomonas), dispersal for Acidithiobacillus, and evidence of extinction/ re-thriving processes for Gallionella. Finally, pyrosequencing revealed a broader phylogenetic range of taxa than previous clone library-based diversity. Overall, our findings suggest that in addition to environmental filtering processes, additional forces (dispersal, birth/death events) could operate in AMD community.

Introduction Acid mine drainage (AMD) is one of the most pernicious forms of pollution in the world and is widely recognized as having costly environmental and socioeconomic impacts (Hallberg, 2010). AMD occurs when waste from the extraction and processing of sulfide ore comes into contact with oxygenated water. Drainages are typically acidic and usually contain high concentrations of sulfate, metals and metalloids including arsenic. Although perceived as extreme environments hostile to life, a variety of microorganisms are able to thrive in it. For some of them, their role in the oxidation of sulfide minerals, FEMS Microbiol Ecol && (2014) 1–17

which leads to bioleaching, is well known, as is their role in natural attenuation of such polluted waters (Edwards et al., 2000; Hallberg, 2010; Johnson, 2012). Despite the central role of microorganisms in such ecosystem functioning, our understanding of the mechanisms shaping microbial community structure and diversity in AMD remains limited. As pointed out by Miller et al. (2009), deciphering how microbial communities are patterned along environmental gradients is a pivotal question in microbial ecology. Although AMD is characterized by changing conditions over time and space, few studies were interested in comparing the microbial communities along such environmental gradients. The AMD of ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

2

Carnoules in southern France provides an excellent opportunity to investigate these fundamental questions of microbial ecology. This site is characterized by an acid pH (2–4) and high levels of metal and metalloids, in particular As (up to 10 g L
1 in the tailings stock pore water, and 100–350 mg L
1 at the source of Reigous Creek), and natural attenuation processes result in a strong spatial pollution gradient along the drainage. Indeed, nearly 95% of the arsenic in solution is removed between the source of Reigous Creek, which emerges from the mine tailings, and its confluence with the Amous River, 1.5 km downstream. To our knowledge, this AMD is one of the most As-rich AMDs reported to date (Morin & Calas, 2006). It is an outstanding example of adaptation to life in an extreme environment. In this study, we used a combination of molecular approaches to investigate the spatial and temporal dynamics of bacterial communities in relation to the physicochemical parameters in Carnoules acid mine drainage. Using 16S rRNA gene pyrosequencing and terminal restriction fragment length polymorphism (T-RFLP), our aim was (1) to characterize the spatial dynamics of the structure and composition of the bacterial communities along an environmental gradient, (2) to evaluate the temporal changes in the composition of the communities, and (3) to determine whether their dynamics could be linked to variations of environmental conditions.

Materials and methods Description of the study site

The Pb–Zn Carnoules mine, located in southern France, produced 1.2 Mt of solid wastes that are stored behind a dam and contain 0.7% Pb, 10% Fe, and 0.2% As. The aquifer is not fed by vertical percolation of rainwater through the tailings, but rather originates from natural springs that were buried under the tailings (Koffi et al., 2003). The water table is 1–10 m below the surface of the tailings stock, depending on the season and location. With the exception of temperature, which is almost constant with average values around 15 °C, the physicochemical parameters of the groundwater vary as a function of the hydrological conditions (Casiot et al., 2003b). In 2001, the groundwater below the tailings contained extremely high levels of arsenic: up to 10 000 mg L
1 (Casiot et al., 2003b). The water emerges at the bottom of the dam, forming the source of the Reigous Creek. This AMD is acid (pH ≤ 3), with high concentrations of sulfate (2000–7700 mg L
1), iron (500–1000 mg L
1), and arsenic (50–350 mg L
1). Iron and arsenic are mainly present in their reduced forms Fe(II) and As(III) (Casiot et al., 2003a). The natural attenuation of As is the ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

A. Volant et al.

result of microbiologically mediated As–Fe coprecipitation (Morin et al., 2003; Bruneel et al., 2006). 10–47% of Fe, and 20–60% of As are removed from the aqueous phase within the first 30 m of the creek. Beyond this point (COWG sampling site, located 30 m downstream from the spring, Fig. 1), the Reigous receives water from quarries and mine galleries, especially after rainfall events, which strongly influence its acidity and metal content (Egal et al., 2010). Sampling procedure and measurement of physicochemical properties

Six sampling campaigns were carried out in November 2007, February 2008, October 2008, March 2009, November 2009, and January 2010 at five sampling sites, resulting in a set of 30 samples. Groundwater was collected from a borehole (S5, between 10 and 12 m deep) located within the tailings. Water samples were also taken at four sites along Reigous Creek (collecting downstream seepage water from the surroundings) at the spring (S1), 30 m downstream from the spring (COWG), 150 m downstream (GAL), and 1500 m downstream (CONF), just before the confluence between Reigous Creek and the Amous River (Fig. 1). Water samples (300 mL) were immediately filtered through sterile 0.22 lm Nuclepore filters, which were transferred to a collection tube (Nunc), frozen in liquid nitrogen, and stored at
80 °C until DNA extraction. This sampling was carried out in triplicate. Measurements of water conductivity, temperature, redox potential, pH, and dissolved oxygen concentration were carried out as previously described (Bruneel et al., 2011). For chemical analyses, 500 mL water samples were immediately filtered through 0.22 lm Millipore membranes fitted on Sartorius polycarbonate filter holders. For total Fe and As determination, the filtered water was acidified to pH 1 with HNO3 (14.5 M) and stored at 4 °C in polyethylene bottles until analysis. A 20 lL aliquot of the filtered water sample was added either to a mixture of acetic acid and EDTA (Samanta & Clifford, 2005) for As speciation or to a mixture of 0.5 mL acetate buffer (pH 4.5) and 1 mL of 1,10-phenanthrolinium chloride solution (Rodier et al., 1996) for Fe(II) determination. The vials were filled to 10 mL with deionized water. Samples destined for Fe and As speciation and sulfate determination were stored in the dark and analyzed within 24 h. Chemical analyses were carried out as previously described (Bruneel et al., 2011). DNA isolation

Genomic DNA was extracted in triplicate from filtered water using the UltraClean Soil DNA Isolation Kit FEMS Microbiol Ecol && (2014) 1–17

3

Spatiotemporal dynamics of bacterial communities

Fig. 1. Map of Carnoules mine and location of sampling sites.

(MoBio Laboratories Inc., Carlsbad, CA) according to the manufacturer’s recommendations. These triplicate extractions were pooled before PCR amplification. All genomic DNA extracts were stored at
20 °C until further analysis. Terminal restriction fragment length polymorphism

The 16S rRNA genes were amplified by PCR, and the bacterial community structure was identified by T-RFLP. The fluorescent labeled primers HEX 357F (50 -hexachloro-fluorescein-phosphoramidite-CCTACGGGAGGCA GCAG-30 ) (Lane, 1991) and 926R (50 -CCGTCAATTCMT TTRAGT-30 ) (Muyzer & Ramsing, 1995), described as universal within the bacterial domain, were used. Triplicate PCR amplifications were performed on each sample. The reaction mixture contained 1 lL of DNA template, 1 lL of both primers (10 lM), and 12.5 lL of PCR Master Mix Ampli Taq Gold 360 (Applied Biosystems, Foster City, CA). Sterile distilled water was added to obtain a final volume of 25 lL. PCR conditions were as follows: one cycle at 95 °C for 10 min, 35 cycles at 95 °C for 45 s, 55 °C for 45 s, and 72 °C for 45 s, followed by 10 min at 72 °C. The 90 PCR products were purified with Illustra GFXTM PCR DNA and the Gel Band Purification Kit (GE Healthcare, Munich, Germany). The concentration of PCR product was determined by comparison with molecular markers (Smartlader, Eurogentec) after migration on agarose gel. Approximately 100 ng of purified amplicon was digested in 10 lL reaction with 0.3 U of enzyme HpaII or AluI (New England Biolabs Inc., Ipswich, MA) at 37 °C for 3 h. Terminal restriction frag-

FEMS Microbiol Ecol && (2014) 1–17

ment (T-RF) profiles were obtained from the digested amplicons by suspending 1 lL aliquots in 8.75 lL formamide with 0.25 lL of Genescan ROX 500 size standard (Applied Biosystems). T-RFs were separated on an ABI PRISM 3130xl Genetic Analyser (Applied Biosystems). Data were collected and analyzed using GENEMAPPER software (version 1.4, Applied Biosystem). To increase stringency for the T-RF profiles of 16S rRNA genes, T-RFs outside the range of the size standard (35–500 bp) were discarded, and the background noise level was set at 30 fluorescence units. T-ALIGN software (Smith et al., 2005) was used to compare replicate profiles and to generate consensus profiles containing only T-RFs that occurred in replicate reactions. Consensus profiles were then aligned on the basis of the length of the T-RFs and individual peak areas as previously described by Smith et al. (2005) with the confidence interval set at 0.5, resulting in the generation of data sets of aligned T-RFs that gave individual relative peak areas as a percentage of the overall profile. T-RFs were included in the subsequent analysis if they represented > 1% of the cumulative peak height for the sample. Construction of the libraries, 454pyrosequencing, and sequence quality control

The 16S rRNA genes were also amplified by PCR for multiplex pyrosequencing using barcoded primers. The primer pairs used, targeting the V3 to V5 variable regions of the 16S rRNA gene, were 357F (50 -AxxxCCTA CGGGAGGCAGCAG-30 ) and 926R (50 -BxxxCCGTCAAT TCMTTTRAGT-30 ). A and B represent the two FLX Titanium adapters (A adapter sequence: 50 -CGTATCGCCTC CCTCGCGCCATCAG-30 ; B adapter sequence: 50 -CTAT

ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

4

GCGCCTTGCCAGCCCGCTCAG-30 ), and xxx represent the sample-specific barcode sequence. PCR was performed using 30–35 cycles under conditions identical to those described above for T-RFLP. The number of cycles was varied with the samples to obtain a strong band with a minimum number of cycles to respect the initial abundances of bacterial communities. The 90 PCR products with a proximal length of 569 bp were excised from 1% agarose gel and purified with the QIAquick Gel Extraction Kit (QIAGEN Inc., Valencia, CA). To minimize random PCR bias, triplicates were pooled in equimolar ratios prior to pyrosequencing. Pyrosequencing of the 30 amplicon libraries was performed on a GS-FLX-Titanium sequencer (Roche 454 Life Sciences) at the GenoToul genomic platform in Toulouse (France) using four separate 1/8 region of a plate. Processing of pyrosequencing data and taxonomic classification

Preliminary quality checks, sorting, and trimming of the 454 reads were carried out using the NG6 pipeline (http://vm-bioinfo.toulouse.inra.fr/ng6/). Tags were extracted from the 454 reads using the sff file (Roche software), and three kinds of analysis were performed as described by Ueno et al. (2010): (1) BLAST search for E. coli, phage, and yeast contaminants, (2) read quality analysis, and (3) removal of sequences that were too long or too short (sequences with more or less than two standard deviations from the mean), sequences containing more than 4% of N, low-complexity sequences and duplicated reads, using Pyrocleaner. The sequences were then analyzed with the software Mothur version 1.30 (Schloss et al., 2009). Preprocessing of unaligned sequences included removing sequences < 450 bp, all sequences containing ambiguous characters, and sequences with more than eight homopolymers. We also removed sequences that did not align over the same span of nucleotide positions. Identical sequences were grouped, and representative sequences were aligned against the SILVA bacterial and archaeal reference database using the Needleman–Wunsch algorithm (Needleman & Wunsch, 1970). Chimeric sequences were detected and removed using the implementation of Chimera Uchime. A further screening step (precluster) was carried out to reduce sequencing noise by clustering reads differing by only one base every 100 bases (Huse et al., 2010). The remaining high-quality reads were used to generate a distance matrix and were clustered into operational taxonomic units (OTUs) defined at 97% cutoff using the average neighbor algorithm. Next, the OTUs were phylogenetically classified to genus level using the naive Bayesian classifier (80% confidence ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

A. Volant et al.

threshold) trained on the RDP taxonomic outline implemented in Mothur and a modified bacterial database. In silico T-RF prediction of the 16S rRNA gene sequences obtained in this study was performed using the program TRiFLE (Junier et al., 2008), and predicted T-RFs were linked to measured T-RFs from the microbial community profiles. Estimation of diversity and statistical analysis

Diversity indices Nonparametric Chao1 and Shannon alpha diversity estimates, as well as coverage and rarefaction curves, were calculated with MOTHUR v.1.30 for each sample. Analysis of variance (ANOVA) was performed with Tukey’s tests to identify differences between sampling sites. Cluster analysis To compare community composition based on T-RFLP and 454-pyrosequencing data, normalized OTUs abundances were square-root-transformed and pairwise dissimilarities among samples were calculated using the relative abundance-based Bray–Curtis index (BC). Nonmetric multidimensional scaling (nMDS) analysis was performed on the dissimilarity matrices to visualize patterns of community composition. Using the 454-pyrosequencing data, we carried out a random sampling procedure to make equal the number of sequences per sample (486 sequences) and we removed singleton OTUs (sequences that only occurred once) to reduce the influence of rare OTUs. One-way analysis of similarity (ANOSIM) and multiple pairwise comparisons were used to test whether there were significant differences in community composition in space. R-values > 0.75 are commonly interpreted as well-separated bacterial compositions; R > 0.5 as overlapping, but clearly different; and R < 0.25 as practically not separable. CCA Canonical correspondence analyses (CCAs) were used to explore variations in the bacterial communities under the constraint of our set of environmental variables. Explanatory variables were log(x + 1)-transformed where necessary to approximate normal distribution. This model was tested with Monte Carlo permutation tests (499 randomized runs) to determine significance, and each environmental parameter was tested by stepwise analysis to detect significant predictors. All statistical analyses were performed with R 3.0.1 (R Development Core Team, 2012) including the VEGAN package. FEMS Microbiol Ecol && (2014) 1–17

5

Spatiotemporal dynamics of bacterial communities

Results Spatial and temporal analyses of the environmental data set

The physicochemical characteristics of the water samples were determined for six sampling dates and at five different sites in a borehole and along Reigous Creek (Fig. 1; Supporting Information, Table S1). With the exception of pH, the environmental variables measured differed significantly between sites (ANOVA, P < 0.05). A significant decrease (Tukey’s test, P < 0.01) in temperature was observed in Reigous Creek, where the influence of air temperature causes a larger range of values (Fig. 2a) in contrast to the temperature of the water in the borehole (S5) and at the source of the Reigous (S1), which did not differ significantly (13.3  1.4 °C and 13.6  1 °C, respectively, and Tukey’s test, P = 0.99). All samples were characterized by low pH (≤ 3.7). No significant variations in pH (ANOVA, P = 0.49) were observed between the sampling sites located downstream from the source (COWG, GAL and CONF; Fig. 2b). Dissolved oxygen (DO) concentrations in the water at the upstream sites presented a mean of 1.0  1.0 mg L
1 for S5 and 0.8  0.6 mg L
1 for S1, denoting generally suboxic conditions at these sites. DO increased sharply between S1 and COWG (mean of 6.1  1.8 mg L
1) (Fig. 2c) and continued to increase slightly all along the creek, to reach a mean of 10.5  1.3 mg L
1 at CONF. The redox potential (Eh) showed average values of 558  85 mV at S5. Eh increased along Reigous Creek from 512  39 mV at S1 to 635  99 mV at CONF (Fig. 2d). In contrast, average conductivity decreased from 7588  5203 lS cm
1 at S5 to 5121  631 lS cm
1 at S1 and reached minimum (1612  97 lS cm
1) at CONF (Fig. 2e). Sulfate (SO42
) concentrations were maximum in the groundwater at S5 with a mean of 14 080  10 630 mg L
1. After a sharp decrease at S1 (average values of 2682  1180 mg L
1), concentrations gradually decreased along Reigous Creek (Fig. 2f). Dissolved Fe concentrations in the groundwater at S5 exhibited average values of 4474  2855 mg L
1. Fe concentrations decreased from the source (S1, average values of 1317  383 mg L
1) to CONF, where Fe remained below 82 mg L
1 (Fig. 2g). The proportion of Fe(III) (difference between Fe(total) and Fe(II)) was generally negligible except at some sampling dates at S5 and CONF (Table S1). At S5, concentrations of dissolved arsenic (As) exhibited an average value of 440  184 mg L
1 (Fig. 2h). Along Reigous Creek, As concentrations decreased with increasing distance from the source (average value of 175  71 mg L
1), to values below 6 mg L
1 at CONF (Fig. 2h), with predominance of the reduced form As(III). An average of 65% of sulfate, FEMS Microbiol Ecol && (2014) 1–17

96% of iron, and 99% of arsenic were removed from the aqueous phase between S1 and CONF sampling sites. Diversity and species richness estimators of bacterial communities

Hex-labeled PCR products were digested separately with two restriction enzymes. HpaII that produced the largest numbers of T-RFs (data not shown) was used to assess the differences in the microbial communities. T-RFLP profiles generated showed a total of 43 different T-RFs for the five sites, and the number of T-RFs detected in each sample varied from 2 to 17 (Fig. 3). Average T-RF richness (number of T-RFs) and average Shannon diversity indices calculated from relative peak intensity data were highest at S1 and COWG (H = 2.03  0.3 and H = 1.96  0.3, respectively), while the lowest values were observed at GAL (H = 1.26  0.4; Fig. 4a). Values at CONF were intermediate (H = 1.67  0.7). Although bacterial community diversity varied among the sampling sites, the differences were not significant (ANOVA, F = 2.46, P = 0.071). For each site, the bacterial community showed variations over time, but no particular trend could be identified. Some T-RFs were found in the majority of the profiles (e.g. T-RF 150), where they usually accounted for a high proportion of the total T-RFs (Fig. 3). Between one and three site-specific T-RFs were identified in all the sites (in red in Fig. 3). A total of 99 441 sequence reads were generated in a single run of 454-pyrosequencing from 30 independent 16S rRNA gene libraries. Note that pyrosequencing of two samples taken in February 2008 (S5 and S1) failed and were thus excluded from analysis. After trimming and processing with Mothur, 63 442 reads remained with an average length of 530 bp. Clustering of the remaining sequences led to the identification of 6613 OTUs (including 4510 singletons) defined at 97% identity. Although singletons represented 68% of the total number of OTUs, they only accounted for 7% of the total DNA sequences. The results of rarefaction analysis along with the Chao1 and the Shannon indexes and coverage values are listed in Table 1. In the resampled data set, Good’s coverage ranged from 69% to 97% with an average value of 85%, indicating that the majority of bacterial phylotypes were recovered. Species richness (Chao1 index) of the bacterial communities presented significant variations along Reigous Creek (ANOVA, P = 0.001, F = 6.66) (Fig. 4b). The nonparametric estimators Chao1 ranged between 52 and 495 estimated OTUs for all the sites considered (Table 1). The highest average OTU richness was found at CONF and S1 (Chao1 = 364  145 and 296  32, respectively), suggesting that an important number of OTUs were not revealed by the analysis of these two sites. Situated ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

6

A. Volant et al.

(a)

(b)

(c)

(d)

Fig. 2. Variations in the main physicochemical parameters over the course of the study and boxplot of each variable per sampling site. Arrows indicate sampling dates for T-RFLP and pyrosequencing analysis. Note that some data are missing, as shown by the gaps in the curves. DO, dissolved oxygen; Eh, redox potential.

ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

FEMS Microbiol Ecol && (2014) 1–17

Spatiotemporal dynamics of bacterial communities

7

(e)

(f)

(g)

(h)

Fig. 2. Continued

FEMS Microbiol Ecol && (2014) 1–17

ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

8

A. Volant et al.

Fig. 3. Relative abundance of terminal restriction fragments (T-RFs) derived from bacterial communities. Single T-RFs per sampling site are in red. Dominant T-RFs are in bold. Taxonomic affiliation of T-RFs was carried out by in silico T-RFLP analysis. T-RF 91 and 100 could not be assigned to any phylogenetic group; T-RF 125 represented Armatimonadetes gp4 and Chlorobi; T-RF 150 was mainly related to Deinococcus-Thermus, Spirochaetes and Actinobacteria; T-RF 162 was mainly related to A. ferrooxidans but could be assigned to other proteobacterial phylotypes detected in the AMD. N7: November 2007; O8: October 2008; M9: March 2009; N9: November 2009; J10: January 2010.

(a)

(b)

Fig. 4. Average diversity and species richness index per group  standard deviation calculated based on (a) T-RFLP profiles and (b) 454 pyrosequencing reads of the reduced data set based on the 16S rRNA genes.

ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

FEMS Microbiol Ecol && (2014) 1–17

FEMS Microbiol Ecol && (2014) 1–17

79 32 52 92 70

138 131 127 137 181

121 105 98 146 112 50

91 65 93 107 110 83

239 62 191 84 233 180

486 486 486 486 486

486 486 486 486 486 486

486 486 486 486 486 486

486 486 486 486 486 486

Obs. OTUs*

486 486 486 486 486

No. of reads

492 186 335 202 477 495

144 224 253 239 227 201

193 201 206 382 349 88

266 289 270 315 342

116 52 89 142 102 368) 422) 392) 455) 449)

(400; (115; (279; (142; (390; (367;

(117; (135; (172; (178; (171; (140; 635) 352) 426) 323) 612) 711)

200) 430) 418) 354) 334) 331)

(159; 256) (154; 295) (152; 312) (279; 565) (232; 578) (65; 148)

(209; (217; (204; (237; (277;

(95; 163) (38; 98) (67; 146) (115; 199) (82; 150)

Chao1

5.07 1.46 4.40 1.87 4.82 4.06

2.28 1.33 2.57 2.36 2.60 2.05

3.75 3.16 2.90 3.87 3.00 1.44

3.86 3.93 3.82 3.48 4.48

3.18 1.66 2.14 3.31 3.40

(4.97; (1.27; (4.25; (1.66; (4.69; (3.89;

(2.08; (1.14; (2.39; (2.14; (2.39; (1.85;

(3.61; (2.99; (2.72; (3.72; (2.81; (1.26,

(3.71; (3.80; (3.68; (3.30; (4.35;

(3.04; (1.52; (1.99; (3.17; (3.29;

Shannon†

5.18) 1.65) 4.55) 2.07) 4.95) 4.23)

2.49) 1.52) 2.75) 2.57) 2.82) 2.25)

3.89) 3.33) 3.07) 4.01) 3.18) 1.62)

4.01) 4.05) 3.95) 3.65) 4.61)

3.32) 1.80) 2.29) 3.46) 3.51)

70 91 77 88 69 74

90 90 87 85 86 88

87 87 87 79 84 94

83 83 84 81 78

92 97 94 91 94

Coverage‡

3256 1768 1731 527 1994 5718

1638 1679 2093 2489 1682 2246

688 2160 2119 2756 1317 1827

2719 3422 2057 2021 4573

2089 2523 2838 1086 2354

No. of reads

Full data set

933 240 548 125 699 1343

223 177 236 356 285 271

194 305 255 511 201 136

436 727 365 392 845

216 87 177 159 195

Obs. OTUs*

1995 972 1163 462 1708 3763

543 665 614 1070 715 862

367 835 1025 1710 624 472

1329 2396 1068 1040 2158

576 258 381 481 598

810) 465) 520) 751) 908)

734) 1030) 839) 1403) 934) 1183) (1764; 2290) (692; 1428) (1004; 1377) (306; 751) (1467; 2026) (3330; 4289)

(423; (456; (473; (843; (570; (654;

(301; 474) (659; 1099) (715; 1544) (1364; 2196) (455; 907) (311; 781)

(1051; 1773) (1994; 2925) (844; 1397) (848; 1313) (1859; 2544)

(435; (165; (298; (334; (423;

Chao1

5.92 1.94 5.02 2.28 5.45 4.79

2.23 1.56 2.64 2.49 2.65 2.12

4.06 3.21 2.82 4.11 2.80 1.51

3.88 4.59 3.97 3.53 4.81

3.16 1.49 2.20 3.22 3.41

(5.87; (1.82; (4.93; (2.07; (5.37; (4.71;

(2.10; (1.44; (2.54; (2.37; (2.51; (2.01;

(3.93; (3.11; (2.72; (4.02; (2.67; (1.41;

(3.79; (4.52; (3.89; (3.41; (4.75;

(3.07; (1.42; (2.13; (3.11; (3.35;

Shannon†

*OTUs were defined at 97% cutoff. † Takes into account the number and evenness of species. ‡ Coverage: sum of probabilities of observed classes calculated as (1
(n/N)), where n is the number of singleton sequences and N is the total number of sequences. Values in brackets are 95% confidence intervals.

S5 S5N7 S5O8 S5M9 S5N9 S5J10 S1 S1N7 S1O8 S1M9 S1N9 S1J10 COWG CGN7 CGF8 CGO8 CGM9 CGN9 CGJ10 GAL GLN7 GLF8 GLO8 GLM9 GLN9 GLJ10 CONF CFN7 CFF8 CFO8 CFM9 CFN9 CFJ10

Sampling sites

Reduced data set

5.98) 2.06) 5.12) 2.50) 5.53) 4.86)

2.35) 1.68) 2.74) 2.60) 2.78) 2.23)

4.19) 3.30) 2.92) 4.19) 2.93) 1.62)

3.96) 4.66) 4.06) 3.64) 4.88)

3.24) 1.56) 2.28) 3.34) 3.48)

84 89 80 81 77 84

91 92 93 90 88 91

82 90 92 87 89 95

90 85 88 86 88

93 98 96 91 95

Coverage‡

Table 1. Estimated OTU richness, diversity indices, and estimated sample coverage for each 16S rRNA gene library. Results are presented for full data set reads (full data set) and for reduced data sets without singletons and randomly resampled to make the sample size equal (reduced data set)

Spatiotemporal dynamics of bacterial communities

9

ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

10

between these two sites, COWG and GAL exhibited intermediate richness estimates (Chao1 = 236  110 and 215  39, respectively). The lowest richness was observed in the tailing groundwater at S5 (Chao1 = 100  33). Bacterial OTU diversity, estimated by the Shannon index, also differed significantly between sites (ANOVA, F = 3.01, P = 0.039), with values ranging from 1.33 to 5.07 (Table 1). In agreement with T-RFLP data analysis (Fig. 4a), the highest average diversity value was found at S1 (H = 3.91  0.36) and the lowest value at GAL (H = 2.20  0.47) (Fig. 4b). As predictable, average T-RF diversity is lower than OTU diversity (c. 50%); indeed, taxon-specific resolution of pyrosequencing is much higher than fingerprinting (Pilloni et al., 2012). Again, no seasonal trend was observed. The same richness and diversity patterns were observed in both the full and resampled data sets, although the richness estimator and Shannon index were higher in the full data set, due to the larger number of sequences (data not shown). Taxonomic assignment of bacterial pyrosequencing reads and T-RFs

At a confidence threshold of 80%, we were able to assign 56 426 of 63 442 qualified reads (that is, 89%) to a known phylum (Table S2) and 76% to a known order (Supporting Information, Fig. S1). Most of the unclassified reads (55% representing 9.6% to 37% of the qualified reads of each sample) were associated with samples collected at S1. Altogether, 23 bacterial phyla were recovered from our samples, with 4–8 different phyla found in samples collected at S5, 12–13 at S1, 9–14 at COWG, 10–13 at GAL, and 9–20 at CONF (Table S2). Most of the bacterial sequences (86%) belonged to phyla that are most often encountered in acid mine drainages worldwide (Proteobacteria, Actinobacteria, Firmicutes, Acidobacteria, Bacteroidetes, and Nitrospirae). In addition, microorganisms representing 0.5% of the total sequences were related to CARN1, ‘Candidatus Fodinabacter communificans’. Proteobacteria was the most abundant phylum in all the samples, accounting for 69.6% of all sequences retrieved. This phylum was represented by bacteria belonging to the Alphaproteobacteria, Betaproteobacteria, Gammaproteobacteria, Deltaproteobacteria, and Epsilonproteobacteria. The most abundant classes in nearly all the samples were Betaproteobacteria and Gammaproteobacteria (average values of 63.4% and 30.4% of the pyrosequencing reads, respectively). There were dominated by Gallionellales and Acidithiobacillales, respectively (Fig. S1a). Three other phyla, Actinobacteria represented mainly by Acidimicrobiales and Actinomycetales, Firmicutes (principally Clostridiales and Bacilliales), and Acidobacteria, were also abundant but their proportion varied depending on the ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

A. Volant et al.

sample analyzed (Fig. S1b–d). Most of the sequences associated with Acidobacteria could not be classified to the order level except for Acidobacteriales and Holophagales. As can be seen in Fig. S2, a relatively small number of OTUs dominated at all sites (> 1% in total abundance per sample). The most abundant OTUs were phylogenetically related to Gallionella ferruginea (Gallionellales), Acidithiobacillus ferrooxidans (Acidithiobacillales), and Thiobacillus sp. (Hydrogenophilales), collectively accounting for 41% of all the sequences. When possible, T-RFs were assigned to a taxon or a group of taxon by in silico restriction of 16S rRNA gene sequences. Among the five dominant T-RFs (91, 100, 125, 150, and 162 bp in size), T-RFs 91 and 100 could not be assigned to any specific phylogenetic group. Armatimonadetes gp4 and Chlorobi were represented by T-RF 125, and T-RF 150 was mainly related to Deinococcus-Thermus, Spirochaetes, and Actinobacteria. While T-RF 162 was mainly related to A. ferrooxidans, it could be assigned to other proteobacterial phylotype detected in this AMD. Spatial and temporal variations in bacterial community structure

Spatiotemporal dynamics of bacterial populations were identified by T-RFLP analysis and 454-pyrosequencing of 16S rRNA genes (Fig. S3). Although samples formed overlapping clusters on the nMDS plot of the T-RFLP profiles, weak but significantly different bacterial communities at the five sites were revealed (ANOSIM Global R = 0.2819, P < 0.001). S5 differed significantly from the other sites, with some overlapping communities (pairwise tests: r-values ranging from 0.45 to 0.61, P < 0.05). These results highlighted changes in the structure of the bacterial communities between the tailing groundwater (S5) and the water in Reigous Creek. The high dissimilarity observed within each site revealed variations in community structure over time, especially at S5, GAL, and CONF (Fig. S3a). These variations may have masked a spatial pattern. nMDS analyses of 454-pyrosequencing data also showed that the composition of the bacterial communities differed significantly along the spatial gradient from the sterile (S5) to the confluence (CONF) (Fig. S3b). Furthermore, an ANOSIM test corroborated the nMDS plot data, revealing significantly different bacterial compositions in water as a function of the spatial location (Global R = 0.6192, P < 0.001), except at GAL and COWG which did not differ significantly (ANOSIM pairwise comparison r = 0.206, P = 0.37). Higher temporal variation at CONF was highlighted by the large cluster on the nMDS plot. The marked temporal variations in the bacterial community at S5 and CONF highlighted by the two data sets FEMS Microbiol Ecol && (2014) 1–17

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Spatiotemporal dynamics of bacterial communities

may be linked to the stronger seasonal fluctuation of some physicochemical parameters at these sites, particularly temperature at CONF (Fig. 2a) and pH, Eh, sulfate, Fe, and As at S5 (Fig. 2b, d, f, g and h). We investigated the four most abundant phyla to get a global view of the variations of bacterial communities along the creek (Fig. S1). Proteobacteria distribution varied between samples, with a relative predominance of Acidithiobacillales in samples from S5 and S1, followed by the dominance of Gallionellales in the majority of other samples (Fig. S1a). A general increase in Betaproteobacteria was observed in the downstream direction of Reigous Creek. Among Actinobacteria, the Acidimicrobiales were present in all samples except those collected at CONF where almost equal proportions of Acidimicrobiales and Actinomycetales were retrieved (Fig. S1b). The Firmicutes phylum revealed the dominance of Clostridiales in samples from S5, whereas Bacillales were dominant at the other sites, again except CONF. Different orders were dominant at CONF over time, including Lactobacillales and Selenomonadales (Fig. S1c). No Acidobacteria were retrieved at S5 in October 2008 (Fig. S1d). We also assessed the dynamics of the dominant genera (> 5% in total abundance per sample) (Fig. 5). The relative abundance of genera at each site varied over the sampling period. While the relative abundance of Gallionella was almost constant in COWG and GAL, there was an important temporal variation in the other sites. This was evident in S5 where this genus was extinct and re-thrived over time (Fig. 5a). Although Gallionella was present in almost all sites for a sampling date, there was no clear relationship between sites. Indeed, GAL and COWG exhibited a relatively high proportion of Gallionella at almost all the sampling dates (as much as 85% of all pyrosequencing reads at GAL) without any link with the upstream sites S5 and S1 (Fig. 5b). In contrast, Acidithiobacillus represented a minor fraction of the bacterial community, except at S5 where this OTU was dominant (24–72% of the pyrosequencing reads). The relative abundance of Acidithiobacillus showed a decreasing trend along the continuum for each sampling date (Fig. 5b). This genus also exhibited an increase in October 2008 and March 2009 for S5 and S1 (Fig. 5a). Members of the Thiobacillus genus showed higher proportion in COWG at each sampling date independently of the other sites (Fig. 5b). The temporal variation of this genus was minor except an important increase at GAL in October 2008 (Fig. 5a). T-RFLP profiles from the 30 samples were investigated to assess the dynamics of T-RFs (Fig. 3). Among the five dominant T-RFs, T-RFs 91 and 100 represented a large proportion of the T-RFLP profiles in almost all samples except those from S5. T-RF 125 related to Armatimonadetes gp4 and Chlorobi was more abundant in samples from FEMS Microbiol Ecol && (2014) 1–17

S5 and S1 than in downstream samples. T-RF 150 (Deinococcus-Thermus, Spirochaetes, and Actinobacteria – related) was the most abundant phylotype in the tailings groundwater (S5), accounting for up to 70% of the TRFLP profiles. It was relatively abundant along the creek especially at GAL. T-RF 162 (related to A. ferrooxidans but also to other proteobacterial phylotype) was not dominant at S5 and represented a minor fraction of the bacterial community along the creek. Linking bacterial community structure to environmental variables

Canonical correspondence analysis (CCA) was performed to elucidate the main relationships between physicochemical variables and bacterial community structure and composition (Fig. 6). Samples were plotted in different areas of the diagram depending on their environmental characteristics. The resolution of 454-pyrosequencing allowed to account for more variation than T-RFLP (36.4% and 20.5%, respectively) in the species–environment relationship across the first two canonical axes. CCA axis 1 based on T-RFLP data only separated the samples into two clusters, one containing the tailings site (S5) and the other grouping the sites along the creek (S1, COWG, GAL, and CONF), with sulfate, DO, and pH being the strongest determinants of bacterial community structure (Fig. 6a). In contrast, a higher resolution was observed with CCA axis 1 based on 454-pyrosequencing data, which was most closely correlated with iron, arsenic, and conductivity and separated the sampling sites into three clusters (CONF, GAL+COWG, and S1+S5) as a function of the pollution gradient (Fig. 6b). The upstream site S5 was highly polluted and little oxygenated, whereas the downstream site CONF was less polluted and characterized by a higher redox potential (Eh). CCA axis 2 separated samples according to water temperature. After the Monte Carlo permutation test, the environmental variables significantly correlated with the canonical axes based on 454-pyrosequencing data were arsenic (F-ratio = 1.9, P = 0.01), temperature (F-ratio = 1.4, P = 0.01), and sulfate (Fratio = 1.4, P = 0.01). The differences between the two data sets were probably due to the power of 454-pyrosequencing over T-RFLP for taxon resolution. Focusing on 454-pyrosequencing data, the influence of environmental variables on dominant OTUs (> 5% of total abundance per sample) was also investigated (Fig. S4). Nineteen of the 23 dominant OTUs showed a strong correlation with the physicochemical parameters. Five OTUs (15, 16, 28, 32, and 52) were strongly correlated with elevated DO and Eh and 14 with high temperatures and high concentrations of As, Fe, and sulfate. As indicated by the position of OTUs 1, 3, 4, and 11 on the graph, near the origin of the ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

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A. Volant et al.

(a)

(b)

Fig. 5. Relative abundance of the dominant genera (> 5% in total abundance per sample) presented by (a) sampling sites and (b) sampling date. N7: November 2007; O8: October 2008; M9: March 2009; N9: November 2009; J10: January 2010.

axes, none of the environmental variables measured in the study could explain their distribution and thus their niche. At the least polluted site (CONF), Gallionella, Ferrovum, and Acidiferrobacter were the main genera detected, whereas, at the most polluted sites (S5 and S1), a higher number of genera were codominant (Acidithiobacillus, Ignavibacterium, Ralstonia, Leptospirillum, Gallionella, Ferrovum, etc.).

ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

Discussion This study combined a classical fingerprinting method (T-RFLP) and a high-throughput barcoded pyrosequencing of 16S rRNA genes to investigate the diversity, spatial distribution, and seasonal variation of bacterial communities in Carnoules AMD (France), which is heavily contaminated with As.

FEMS Microbiol Ecol && (2014) 1–17

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Spatiotemporal dynamics of bacterial communities

(a)

(b)

Fig. 6. Canonical correspondence analysis (CCA) correlating the bacterial community structure at each sampling site with arsenic (As), iron (Fe), conductivity (Cond), temperature (T), dissolved oxygen (DO), redox (Eh), pH and sulfate. The bacterial community structures correspond to OTU abundances from (a) T-RFLP data and (b) pyrosequencing data. The main clusters are highlighted.

Spatial and temporal variations in the environmental data set and in the bacterial community

Monitoring the physicochemical parameters of Reigous Creek confirmed previous results (Casiot et al., 2003a; Egal et al., 2010), showing a significant decrease in concentrations of dissolved As, Fe, and sulfate with increasing distance from the source: 72% of sulfate, 96% of iron, and 99% of arsenic had been removed by the time Reigous Creek flowed into the River Amous (Table S1). In addition, the concentrations of As and Fe in the water from the tailings stock were much lower in 2007– 2010 (average values of 440  184 mg L
1 and 4474  2855 mg L
1, respectively), than those measured in 2001 (up to 10 g L
1 for As and around 20 g L
1 for Fe, Casiot et al., 2003b), although these concentrations are still very high compared to other AMDs. Both molecular methods highlighted a higher bacterial diversity than expected in this extreme habitat. T-RFLP profiles showed for the five sites a total of 43 T-RFs ranging from 2 to 17 T-RFs per sampling site (Fig. 3). For pyrosequencing data, a total of 63 442 reads led to the identification of 6613 OTUs, including 4510 singletons representing 68% of the total number of OTUs. As expected, a larger number of phylotypes were identified using the pyrosequencing method leading to a significant increase in resolution. Average Good’s coverage was over 89%, suggesting that the 16S rRNA gene sequences into each sample represented the majority of the bacterial FEMS Microbiol Ecol && (2014) 1–17

phylotypes present. Nonetheless, additional sequencing effort would be required to exhaustively characterize the bacterial community, particularly for samples from the least polluted site CONF, as shown by the lower coverage values and the lack of asymptote in the rarefaction curves (data not shown). nMDS analyses revealed significant differences in the composition of the bacterial communities in the five sites along the AMD (Fig. S3). However, different clustering patterns were obtained based on T-RFLP or pyrosequencing data. With pyrosequencing, individual sequences can be classified at the genus level. In contrast, one T-RF can correspond to several different bacterial phylotypes (belonging to different genera or even different higher taxonomic levels). Such differences in the resolution of the two methods may explain the differences obtained in the cluster analyses (Hwang et al., 2012). Nevertheless, changes in bacterial community structure between the tailings groundwater (S5) and the Reigous Creek were revealed by the two sets of data, reflecting important differences in ecological conditions between the two habitats. According to both methods, S1 was the most diverse bacterial community, while GAL was the least diverse. Therefore, bacterial diversity varied independently of the sampling site, suggesting that globally upstream communities do not influence downstream communities. The apparent minimum effect of immigration suggests that species-sorting processes best describe bacterial community structure in these connected environments, with local environmental factors driving the composition of the ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

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A. Volant et al.

bacterial community at each site. Temporal variations of the bacterial communities could also be observed at each site although no particular trend could be identified. However, the important temporal variation of the bacterial community observed at S5 and CONF may be due to a higher seasonal fluctuation in physicochemical parameters at these two sites, especially temperature at CONF, and pH, Eh, sulfate, Fe, and As at S5. However, our fine-scale investigation at the genus level of the bacterial communities along the Reigous Creek over time provided some important data and allowed to establish some hypothesis about community composition. Indeed, Gallionella in contrast to Acidithiobacillus do not seem to benefit from the seed bank provided by the most upstream sites (S5 and S1). This suggests that Gallionella, under a process that still need to be elucidated, extinct/ re-thrived at each site over time. In contrast, Acidithiobacillus that is preferentially encountered upstream of the Reigous Creek or Thiobacillus that thrived at COWG could be found at these sites, under conditions that reflect their preferential habitats. The presence of these organisms downstream of the sites would instead reflect dispersal from upstream sites.

Gallionella-like organisms may be more tolerant to acid and metal than currently thought (Fabisch et al., 2013). In accordance with our results, temperature has been previously suggested as a primary factor controlling the structure and dynamics of microbial communities in AMD (Edwards et al., 1999) and in various natural environments like hot springs (Ward et al., 1998; Miller et al., 2009) or marine environments (Fuhrman et al., 2008). Nevertheless, sulfate and arsenic concentrations have not previously been shown to be significantly correlated with bacterial diversity in AMDs. Earlier studies identified different environmental predictors of microbial populations in AMD including conductivity and rainfall (Edwards et al., 1999), pH (Lear et al., 2009), oxygen gradient (Gonz
alez-Toril et al., 2011), and season (Streten-Joyce et al., 2013), which may result in site-specific physicochemical and geochemical characteristics (Kuang et al., 2012). Furthermore, while many studies highlighted pH as the most important factor structuring AMD communities (Kuang et al., 2012; Chen et al., 2013), our study produced no evidence of the influence of this parameter, probably due to the limited variation in pH among our samples (average values of 2.5  0.8–3.2  0.3).

Physicochemical parameters shape the composition of the bacterial community

Composition of the bacterial communities

This work highlighted a spatial gradient of physicochemical conditions linked to a significant shift in bacterial community composition along the continuum. Indeed, canonical correspondence analysis of the whole pyrosequencing data set indicated that arsenic, temperature, and sulfate were the factors that most influence the composition of the bacterial communities (Fig. 6b). The level of pollution affects also some dominant bacterial populations (> 5% of relative abundance). Gallionella, Ferrovum, and Acidiferrobacter were the dominant genera in water sampled at the least polluted site (CONF) and were correlated with high DO and Eh, whereas in water from the most polluted sites (S5 and S1), a larger number of dominant genera were detected (Acidithiobacillus, Ignavibacterium, Ralstonia, Leptospirillum, Gallionella, and Ferrovum) whose relative abundance was correlated with higher temperature and high concentrations of As, Fe, and sulfate (Fig. S4). Thus, different members of a given genus such as Gallionella (OTUs 19, 15 and 1) or Ferrovum (OTUs 25 and 28) were correlated with different environmental parameters, suggesting that these OTUs correspond to bacterial phylotypes with some specificity explaining these different behaviors. Furthermore, the high abundance of Gallionella-related sequences in these acidic ecosystems characterized by contrasted levels of pollution is consistent with results of a previous study suggesting that ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

In this study, we were able to identify a wider phylogenetic range of taxa than in any previous clone librarybased diversity survey of the Carnoules AMD, including sequences of several previously undetected taxa. These new taxa include members of the Bacteroidetes, Chlorobi, Chloroflexi, Elusimicrobia, Chlamydiae, Cyanobacteria, Deinococcus-Thermus, Spirochaetes, Fibrobacteres, Fusobacteria, Gemmatimonadetes, Plantctomycetes, Verrumicrobia, and of the uncultured OD1-PO11-TM7 clade. The majority of phyla that were not previously detected on clone libraries accounted only for < 1% of the pyrosequencing data, explaining why they were missed with the clone library approach. The high rate of low-abundance populations (68% of singletons) increased the phylogenetic bacterial diversity. However, despite the preponderance of this rare biosphere in most studies, its ecological and functional roles remain largely unexplored (Galand et al., 2009). Recent studies indicated that such organisms may be at a dormant or a spore stage, but in favorable conditions they may become active and even dominant (Delavat et al., 2012). Thus, these taxa may play an important role in extreme habitats like AMD, buffering the effects of important environmental shifts (Sogin et al., 2006; Monchy et al., 2011). However, further investigations will be needed to determine whether they play a role in this ecosystem and/or whether they reflect allochthonous input from surrounding environments. Moreover, the highFEMS Microbiol Ecol && (2014) 1–17

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Spatiotemporal dynamics of bacterial communities

throughput sequencing also questions the accuracy of OTU richness estimates, as sequencing errors and inadequate clustering algorithms can lead to overestimates of community richness (Huse et al., 2010). The majority of the most abundant taxa detected in this study were related to orders commonly encountered in AMD, most of which are known to be involved in Fe, As, and S cycles: namely Gallionellales (Betaproteobacteria), Acidithiobacilliales (Gammaproteobacteria), Acidimicrobiales (Actinobacteria), Hydrogenophilales (Betaproteobacteria), Burkholderiales (Betaproteobacteria), Nitrospiralles (Nitrospirae), Desulforomonadales (Deltaproteobacteria), and Desulfobacterales (Deltaproteobacteria). The ecological role of previously detected taxa has been widely characterized (Bruneel et al., 2005, 2006, 2011; Bertin et al., 2011) in this ecosystem. A relatively small number of OTUs dominated at each sampling site (Fig. S2) and the majority of them were phylogenetically related to taxa previously found in AMD (Gallionella ferruginea, Acidithiobacillus ferrooxidans, and Thiobacillus sp.), as well in Carnoules revealing their persistence in such ecosystems (Baker & Banfield, 2003; Bruneel et al., 2006, 2011; Hallberg et al., 2006; Heinzel et al., 2009; Hallberg, 2010). These three genera varied in their relative abundance over the sampling period. Gallionella was present in high proportions in almost all samples, mainly at GAL and COWG. In contrast, except at S5 where this genus was dominant, Acidithiobacillus accounted for a minor fraction of the bacterial community (Fig. 5). Furthermore, our study confirmed the presence of relatives of a novel bacterial phylum, ‘Candidatus Fodinabacter communificans’ detected by a recent metagenomic investigation of Carnoules AMD and prominent in the active COWG community (Bertin et al., 2011; Fahy et al., unpublished data). The relatively high number of unclassified bacteria per sample (0.3–37%) supports the fact that many bacteria remain to be cultured. These results thus corroborate the main observations made in previous studies, except for the predominance of organisms related to sulfate reducing bacteria (SRB) identified in water from the tailings by Bruneel et al. (2005) using a cloning–sequencing approach. Instead, our results revealed the dominance of Acidithiobacillales over SRB in these samples. The very low proportion of SRB populations in our study (on average 0.1% of total abundance per sample) could be partly due to differences in the physicochemical variables of the water, to the choice of a stringent similarity cutoff but also to the different primers used for PCR amplification. Furthermore, relatives of Thiomonas belonging to the Burkholderiales order were retrieved and accounted for < 1% of the total sequences (Fig. S1a). Despite their low abundance, several strains of Thiomonas sp. have been previously isolated and shown to be active in the FEMS Microbiol Ecol && (2014) 1–17

oxidation of As (Bruneel et al. 2003). A metaproteomic approach also showed that Gallionella, Thiomonas, and A. ferrooxidans actively express proteins in situ, thus probably playing a functional role in this AMD (Bruneel et al., 2011). These populations could play an important role in the efficient remediation process observed along this creek by favoring the oxidation of Fe(II) and the co-precipitation of As (Casiot et al., 2003a; Bruneel et al., 2011). This work has increased our knowledge of bacterial diversity and dynamics in acid mine drainage. Bacterial diversity in Carnoules AMD was revealed to be much higher than previously evidenced using clone library techniques (Bruneel et al., 2011), as suggested by culture-dependent methods (Delavat et al., 2012). Our study revealed complex patterns of spatial and temporal variations in bacterial community composition, suggesting that community composition reflects changes in physicochemical conditions. This investigation provided a first step to the study of spatial and temporal structure of bacterial communities and the factors that control it. To improve our understanding of the functioning of this ecosystem, future efforts should be oriented toward active communities and how they fluctuate in response to environmental changes. Such knowledge will help to determine their roles in the functioning of the AMD ecosystems and explain important assembly processes in microbial ecology.

Acknowledgements This study was financed by the FRB (Fondation pour la recherche sur la Biodiversite) program blanc AAP-IN-2009039, the « Observatoire de Recherche Mediterraneen de l’ Environnement » (OSU-OREME). A.V. was supported by a grant from the French Ministry of Education and Research and F.J. by a grant from the Direction G
en
erale de l’Armement (DGA). This work was performed within the framework of the Groupement de recherche: Metabolisme de l’Arsenic chez les Microorganismes (GDR2909CNRS).

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ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

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Supporting Information Additional Supporting Information may be found in the online version of this article: Fig. S1. Composition of different phyla based on classification of 16S rRNA gene sequences of bacteria from each sample using RDP Classifier: (a) Proteobacteria orders, (b) Actinobacteria orders, (c) Firmicutes orders, and (d) Acidobacteria orders. Fig. S2. Histogram of the relative abundance of dominant OTUs at the Carnoules sampling sites (G. ferruginea subsp. capsiferriformans ES-2: NC_014394; A. ferrooxidans strain HL1: JF815535; Thiobacillus sp. ML2-16: DQ145970; Pseudomonas migulae: AY605698; A. ferrivorans SS3: NR_074660; Actinobacterium BGR 105: GU168008; Acidobacteriaceae bacterium CH1: DQ355184; Ferrimicrobium sp. Py-F2: KC208496; Metallibacterium sp. 911: HE858262; Alicyclobacillaceae bacterium Feo-D4-16CH: FN870323; Acidisphaera sp. nju-AMDS1: FJ915153; Betaproteobacterium OYT1: AB720115. Fig. S3. Nonmetric multidimensional scaling analysis of the composition of the bacterial community estimated by (a) T-RFLP and (b) 454 pyrosequencing based on 16S rRNA genes. Fig. S4. (a) Ordination plot of CCA based on pyrosequencing data showing OTUs with relative abundance >5%. (b) Abundant OTUs and their correlation with environmental variables and phylogenetic affiliation determined by BLAST search. Table S1. Physicochemical characteristics of the water at each sampling site and sampling date. Table S2. Relative abundance (in %) of total sequences of bacterial 16S rRNA genes from each sample assigned to different phyla.

ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved