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Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine 1053

Selection of Resistance at very low Antibiotic Concentrations ERIK GULLBERG

ACTA UNIVERSITATIS UPSALIENSIS UPPSALA 2014

ISSN 1651-6206 ISBN 978-91-554-9101-7 urn:nbn:se:uu:diva-235225

Dissertation presented at Uppsala University to be publicly examined in A1:111a, BMC, Husargatan 3, Uppsala, Wednesday, 17 December 2014 at 09:00 for the degree of Doctor of Philosophy (Faculty of Medicine). The examination will be conducted in English. Faculty examiner: Professor Laura Piddock (University of Birmingham, Institute of Microbiology and Infection). Abstract Gullberg, E. 2014. Selection of Resistance at very low Antibiotic Concentrations. Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine 1053. 86 pp. Uppsala: Acta Universitatis Upsaliensis. ISBN 978-91-554-9101-7. The extensive medical and agricultural use and misuse of antibiotics during the last 70 years has caused an enrichment of resistant pathogenic bacteria that now severely threatens our capacity to efficiently treat bacterial infections. While is has been known for a long time that high concentrations of antibiotics can select for resistant mutants, less is known about the lower limit at which antibiotics can be selective and enrich for resistant bacteria. In this thesis we investigated the role of low concentrations of antibiotics and heavy metals in the enrichment and evolution of antibiotic resistance. Selection was studied using Escherichia coli and Salmonella enterica serovar Typhimurium LT2 with different resistance mutations, different chromosomal resistance genes as well as large conjugative multidrug resistance plasmids. Using very sensitive competition experiments, we showed that antibiotic and heavy metal levels more than several hundred-fold below the minimal inhibitory concentration of susceptible bacteria can enrich for resistant bacteria. Additionally, we demonstrated that subinhibitory levels of antibiotics can select for de novo resistant mutants, and that these conditions can select for a new spectrum of low-cost resistance mutations. The combinatorial effects of antibiotics and heavy metals can cause an enrichment of a multidrug resistance plasmid, even if the concentration of each compound individually is not high enough to cause selection. These results indicate that environments contaminated with low levels of antibiotics and heavy metals such as, for example, sewage water or soil fertilized with sludge or manure, could provide a setting for selection, enrichment and transfer of antibiotic resistance genes. This selection could be a critical step in the transfer of resistance genes from environmental bacteria to human pathogens. Keywords: Antibiotic resistance, Selection, Antibiotic resistant bacteria, Minimal inhibitory concentration, Heavy metals, Conjugative plasmid, ESBL Erik Gullberg, Department of Medical Biochemistry and Microbiology, Box 582, Uppsala University, SE-75123 Uppsala, Sweden. © Erik Gullberg 2014 ISSN 1651-6206 ISBN 978-91-554-9101-7 urn:nbn:se:uu:diva-235225 (http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-235225)

“We are at the very beginning of time for the human race. It is not unreasonable that we grapple with problems. But there are tens of thousands of years in the future. Our responsibility is to do what we can, learn what we can, improve the solutions, and pass them on.” - Richard P Feynman

To my family

Members of the committee

Opponent Professor Laura Piddock Institute of Microbiology and Infection University of Birmingham, UK Members of the evaluation committee Professor Staffan Svärd Department of Cell and Molecular Biology Uppsala University, Sweden Professor Bengt Guss Department of Microbiology Swedish University of Agricultural Sciences Docent Björn Bengtsson Department of Animal Health and Antimicrobial Strategies National Veterinary Institute (SVA)

List of Papers

This thesis is based on the following papers, which are referred to in the text by their Roman numerals. I

II

III

IV

Koskiniemi, S., Pränting, M., Gullberg, E., Näsvall, J., & Andersson, D. I. (2011). Activation of Cryptic Aminoglycoside Resistance in Salmonella enterica. Molecular Microbiology, 80(6), 1464–1478. doi:10.1111/j.1365-2958.2011.07657.x Gullberg, E., Cao, S., Berg, O. G., Ilbäck, C., Sandegren, L., Hughes, D., & Andersson, D. I. (2011). Selection of Resistant Bacteria at Very Low Antibiotic Concentrations. PLoS Pathogens, 7(7), e1002158. doi:10.1371/journal.ppat.1002158 Gullberg, E., Albrecht, L. M., Karlsson, C., Sandegren, L., & Andersson, D. I. (2014) Selection of a Multidrug Resistance Plasmid by Sublethal Levels of Antibiotics and Heavy Metals. mBio, 5(5), e01918-14. doi:10.1128/mBio.01918-14 Gullberg, E., Hjort, K., Sandegren, L., & Andersson, D. I. (2014) Evolution of Resistance at Non-Lethal (Sub-MIC) Levels of Antibiotics. (Manuscript)

Work not included in thesis: •

• •

Mezger, A., Gullberg, E., Göransson, J., Zorzet, A., Herthnek, D., Tano, E., Nilsson, M., & Andersson, D.I. (2014) A General Method to Rapidly Determine Antibiotic Susceptibility and Species in Bacterial Infections. (Submitted) Liljeruhm, J., Gullberg, E., & Forster, A. C. (2014) Synthetic Biology: A Lab Manual. Singapore: World Scientific Gynnå, A. H., Gullberg, E., & Forster, A. C. (2014) Generalizable Tailoring of Inhibition and Fitness Costs of Artificial Small RNAs in E. coli. (Submitted)

Reprints were made with permission from the respective publishers.

Contents

Introduction ................................................................................................... 13 Antibiotics ................................................................................................ 14 The history of antibiotics ..................................................................... 14 The role of antibiotics in nature ........................................................... 15 Different classes of antibiotics ............................................................. 16 Antibiotic resistance ................................................................................. 22 Intrinsic antibiotic resistance ............................................................... 22 Acquired resistance .............................................................................. 25 Heavy metals ............................................................................................ 28 Toxicity ................................................................................................ 28 Resistance mechanisms ........................................................................ 28 The role of horizontal gene transfer ......................................................... 29 Origin of resistance genes .................................................................... 30 Mobile genetic elements ...................................................................... 30 Vectors of HGT.................................................................................... 34 Barriers to HGT ................................................................................... 35 The pUUH239.2 plasmid ..................................................................... 36 Fitness costs .............................................................................................. 38 Selection of resistance .............................................................................. 39 The dynamics of the resistome ............................................................ 39 The mutant selective window hypothesis ............................................ 39 Sub-MIC selection of resistance .......................................................... 40 Antibiotics and heavy metals in the environment .................................... 41 Use in agriculture ................................................................................. 42 Antibiotics in wastewater ..................................................................... 47 Other sources ....................................................................................... 50 Present investigations .................................................................................... 52 Paper I ....................................................................................................... 52 Activation of cryptic aminoglycoside resistance in Salmonella enterica ............................................................................. 52 Paper II ..................................................................................................... 54 Selection of resistant bacteria at very low antibiotic concentrations ... 54 Paper III .................................................................................................... 56 Selection for a multidrug resistance plasmid by sublethal levels of antibiotics and heavy metals ................................................................ 56

Paper IV .................................................................................................... 58 Evolution of resistance at non-lethal (sub-MIC) levels of antibiotics ............................................................................................. 58 Concluding remarks ...................................................................................... 61 Svensk sammanfattning................................................................................. 64 Acknowledgements ....................................................................................... 67 References ..................................................................................................... 70

Abbreviations

BFP bp CFP CRISPR DHFR DHPS DNA E. coli ECDC ESBL FACS HGT IM IS kb LPS Mb MIC MRSA MSC NADH OM PG PBP ppGpp QAC RBS RNA SCV S. typhimurium Tn VRE WGS WWTP YFP

Blue fluorescent protein Base pair Cyan fluorescent protein Clustered Regularly Interspaced Short Palindromic Repeats Dihydrofolate reductase Dihydropteroate synthetase Deoxyribonucleic acid Escherichia coli European Centre for Disease Prevention and Control Extended spectrum beta-lactamase Fluorescence-activated cell sorting Horizontal gene transfer Inner membrane Insertion sequence Kilo base pair Lipopolysaccharide Mega base pair Minimal inhibitory concentration Methicillin-resistant Staphylococcus aureus Minimal selective concentration Nicotinamide adenine dinucleotide (reduced form) Outer membrane Peptidoglycan Penicillin binding protein Guanosine tetraphosphate Quaternary ammonium compound Ribosome binding site Ribonucleic acid Small colony variant Salmonella enterica (Var. Typhimurium LT2) Transposon Vancomycin-resistant enterococci Whole genome sequencing Wastewater treatment plant Yellow fluorescent protein

Introduction

“It seems reasonable to anticipate that within some measurable time, such as 100 years, all the major infections will have disappeared.” - Aidan Cockburn, epidemiologist at Johns Hopkins University, 1964 (Cockburn 1964)

The discovery of antibiotics is without a doubt one of the most important steps forward in the treatment of infectious disease mankind has ever taken. Before there were antibiotics, many people died of bacterial infections before they reached adulthood (Guyer et al. 2000). When penicillin was introduced in the 1940-ies it was a wonder drug, more potent than the antiseptics of the time, and at the same time almost completely nontoxic to humans (Hewitt 1967). Not only did antibiotics provide a cure for many previously potentially lethal diseases, it indirectly had a massive effect on society as a whole by drastically increasing the average lifetime of the population (Lederberg 2000). Between 1937 and 1952 the mortality rate in the US due to infectious disease fell by 8.2% per year, from 283 deaths per 100 000 persons to 75 (G. L. Armstrong et al. 1999). During the ”golden age” of antibiotics in the 1950s and 1960s, several new classes of antibiotics were brought to the clinic, and in the seventies the arsenal of antibiotics was larger than ever (Bérdy 2012). During this time of optimism some infectious diseases almost disappeared, and WHO experts spoke of ”eradication of infectious diseases”, much like smallpox was eradicated through vaccination in 1979 (Snowden 2008). Many leading researchers in the field believed that humanity might be close to “solving the problem” with bacterial infections. This view unfortunately influenced the priorities of pharmaceutical research and development. Since the problem with bacterial infections was considered solved, the focus could shift towards developing drugs targeting cancer, cardio-vascular diseases, diabetes and various other diseases. This shift caused an ”innovation gap”, a period of almost 40 years between 1962 and 2000 where no new classes of antibiotics were introduced in the clinic (Fischbach & Walsh 2009). Unfortunately, the widespread use and misuse of antibiotics during the last 70 years has put an enormous selective pressure on bacteria to evolve resistance, and today many of the pathogenic bacteria found in the clinic are resistant to multiple antibiotics. If this trend of increasing antibiotic resistance would continue and humanity would fail to develop new antibiotics, the level of medical care we take for granted today might be lost forever. 13

Antibiotics “In order to pursue chemotherapy successfully we must look for substances which possess a high affinity and high lethal potency in relation to the parasites, but have a low toxicity in relation to the body, so that it becomes possible to kill the parasites without damaging the body to any great extent.” - Paul Ehrlich, 1909 (Holmstedt & Liljestrand 1963)

The history of antibiotics Already in the beginning of the twentieth century, microbiologist Paul Ehrlich speculated that it should be possible to find chemical “magic bullets”, substances with selective toxicity that would kill bacteria or other parasites without harming the human host. By screening different synthetic compounds he discovered in 1909 that “compound 606”, arsphenamine, could kill the bacteria causing syphilis, and that it was well tolerated by humans. Arsphenamine became the first real antimicrobial, and sold under the name Salvarsan it was a great improvement in the treatment of syphilis (Zaffiri et al. 2012). In the late twenties, Bayer Laboratories in Germany started testing different synthetic dyes for antibacterial activities, and in 1932 they discovered the first sulfonamide antimicrobial, Prontosil. The sulfa drugs were widely used until the end of World War II, when the first antibiotic derived from a natural source, penicillin, could be produced in large enough quantities (Debabov 2013). Alexander Fleming had discovered penicillin in 1928, when he observed a mold growing on his agar plates that could inhibit the growth of Staphylococcus aureus (Fleming 1929). Despite his systematic investigation of the antibacterial properties of this new substance, it was not until 1941 the first patient could be treated with penicillin through the work of Walter Florey and Ernst Boris Chain, and even longer until large-scale production was possible (Ligon 2004). The following 20 years saw the discovery of many new classes of antibiotics, and even more semisynthetic derivatives of the natural substances with improved spectrum and pharmacokinetic properties (Debabov 2013; Hewitt 1967). The newly discovered antibiotics were not only used in human medicine; it was soon discovered that adding low doses of antibiotics such as penicillin or tetracycline to animal feed increased the growth rate of the animals. This quickly became big business for the pharmaceutical industry, and already in 1964 the amounts of penicillin used in livestock were almost as large as those used to treat patients (Hewitt 1967). Since then this use of antibiotics has increased dramatically, and some estimate that eight times more antibiotics are used in agriculture than in human medicine (Marshall & S. B. Levy 2011; FDA 2009).

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The role of antibiotics in nature Most of the natural antibiotics discovered are produced by soil microbes, such as bacteria of the genera streptomyces and actinomyces (Aminov 2009; Fischbach & Walsh 2009). The native biological roles of antibiotics are not completely understood, but many believe that they are weapons in microbial “chemical warfare”, where they would give the producer a growth advantage by inhibiting growth of their competitors. Some theorize that antibiotic production in nature is part of a complex interplay between organisms where the benefit of producing antibiotics to inhibit your neighbor constantly must be balanced against the metabolic burden of this production. This dynamic can be compared to a game of rock-paper-scissors, with antibiotic producers competing against sensitive and resistant (non producing) bacteria. In this game, an antibiotic producing strain can outcompete a sensitive strain, since the growth of the sensitive strain will be inhibited. A resistant strain can outcompete an antibiotic producing strain, since producing antibiotic substances is costly, but it cannot outcompete the sensitive strain, since carrying the resistance generally is costly as well, but not as costly as producing antibiotics (Fig. 1). This constant struggle could contribute to the genetic and metabolic diversity in such ecosystems (Czárán et al. 2002).

Figure 1. The complex dynamics between organisms in the environment can be compared to a game of rock-paper-scissors, with antibiotic producers competing with sensitive and resistant (non producing) bacteria.

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Others speculate that the primary function of antibiotics in nature is to act as signal molecules of microbial communication and quorum sensing, and that their lethal effects in high doses are mainly unintentional (Aminov 2009). In natural ecosystem the concentrations of antibiotics produced are much lower than in a clinical setting, and at such low levels they have been shown to alter the expression of many different genes (Fajardo & Martínez 2008). In Pseudomonas aeruginosa, sub-inhibitory levels of tobramycin have been shown to induce biofilm formation through the activation of an aminoglycoside response regulator. The production of antibiotics in soil bacteria is also frequently regulated through quorum sensing mechanisms, further indicating a possible signal function (Aminov 2009).

Different classes of antibiotics Antibiotics generally work by blocking or disrupting core functions in the bacterial cell. Many of the clinically important antibiotics target structures or metabolic functions not present in human cells, such as the cell wall or certain enzymes in the folate synthesis pathway. Other antibiotics target the information processing machinery of the cells; enzymes responsible for replication, transcription and translation (Fig. 2). These structures exist in both bacteria and mammals, but in most cases they are sufficiently different to enable selective toxicity (Walsh 2003). Cell wall synthesis inhibitors The bacterial cell wall is an attractive target for antibiotics since it is essential for structural integrity, and built up through many complex biosynthesis pathways. It also contains chemical structures unique for bacteria, such as the layer of peptidoglycan, a matrix of polysaccharide strands cross-linked by short peptides that gives the cell wall mechanical strength (Walsh 2003). β-lactams The β-lactams is the largest and clinically most important class of antibiotics. They kill bacteria by inhibiting enzymes called penicillin-binding proteins (PBPs), responsible for the final cross-linking of peptidoglycan. The βlactams are structurally very similar to the substrate of the PBPs, but when they bind they form a covalent bond to the active site, permanently inactivating the enzymes. The lack of cross-linking is weakening the peptidoglycan structure, severely destabilizing the bacterial cell wall, and eventually resulting in cell lysis (Spratt & Cromie 1988). β-lactams can be divided into several groups, for example penicillins, cephalosporins, monobactams and carbapenems (Fig. 3). This class also includes β-lactamase inhibitors such as clavulanic acid, which can be used in combinations with other β-lactams to treat infections of resistant bacteria expressing β-lactamases (Bush 2001).

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Figure 2. Antibiotics targeting different components of the information processing machinery of the cell.

Cephalosporins are one of the most clinically used antibiotics. They have proven to be very useful scaffolds for chemical modification, and there has been a continual development of improved versions of cephalosporins over time with different properties. They are often divided into different “generations” of drugs, even if there are no strict definitions of the divisions (Walsh 2003). Some of the newer cephalosporins (“fifth generation”) such as ceftaroline and ceftobiprole are effective against several important pathogens, such as methicillin resistant Staphylococcus aureus (MRSA), Escherichia coli and Klebsiella pneumoniae (Long & Williams 2014).

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Figure 3. Chemical structures of different classes of antibiotics.

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Figure 4. Antibiotics inhibiting different steps in the folate synthesis pathway.

Glycopeptides Glycopeptides kill bacteria by inhibiting the transglycosylation step in peptidoglycan synthesis. This group contains the antibiotics vancomycin, teicoplanin, ramoplanin and telavancin, used clinically as last resort treatments of MRSA and enterococcal infections (Wolter et al. 2006), as well as the veterinary antibiotic avoparcin, previously used as a growth promoting additive in animal feed (Witte 1998). Folate synthesis inhibitors Unlike humans, bacteria are dependent on folate synthesis for production of nucleic acids, and this makes the enzymes in the folate synthesis pathway excellent targets for antibiotics. Important classes of folate synthesis inhibitors are sulfonamides, which inhibit the dihydropteroate synthetase (DHPS), and inhibitors of the dihydrofolate reductase (DHFR) such as trimethoprim. Since these antibiotics target two different steps in the same synthesis pathway, they are often used together giving a synergistic effect (Fig. 4). Folate synthesis inhibitors generally possess broad spectrum activity, and they are frequently used to treat infections in the urinary and respiratory tracts (Hawser et al. 2006). Ribosomal inhibitors The ribosomes are very complex macromolecular machines, and they can be inhibited by many groups of antibiotics. Unfortunately, mitochondrial ribosomes are structurally very similar to bacterial ribosomes, due to the prokaryotic evolutionary origin of our mitochondria. Because of this, some antibiotics that target the bacterial ribosome will also be toxic to mitochondria (McKee et al. 2006). Aminoglycosides. Aminoglycosides disrupt protein synthesis by binding to the 30S subunit of the ribosome, which either blocks translation or induces misreading of the mRNA. Streptomycin was the first aminoglycoside to be used clinically, and the first antibiotic to be effective against tuberculosis. Aminoglycosides are bactericidal, and mainly effective against Gram-negative bacteria. Some important aminoglycosides are streptomycin, kanamycin, gentamycin and spectinomycin (Jana & Deb 2006). They are occasionally used clinically in 19

combination treatments together with β-lactams (Hallander et al. 1982), but their use is somewhat limited by their side effects; high doses of aminoglycosides can cause damage to kidneys and cells in the inner ear due to mitochondrial toxicity. While the kidneys usually recover after therapy, the cells in the inner ear do not; hearing loss and tinnitus are common side effects of aminoglycoside treatment (Huth et al. 2011). Besides the clinical use, aminoglycosides are used in agriculture to control fire blight, a bacterial disease affecting apples and pears (McManus et al. 2002). Tetracyclines Tetracyclines are broad spectrum, bacteriostatic antibiotics that bind to the 30S subunit of the ribosome and block elongation during translation. They are active against a very wide range of bacteria, Gram-negative as well as Gram-positive, and even some protozoans such as the malaria parasite, Plasmodium falciparum. When they were first introduced in the clinic, resistance levels were very low, but since then many pathogenic bacteria have acquired resistance genes. Tetracyclines have been used extensively in animal feed at subtherapeutic levels (Chopra & Roberts 2001). A new member of the tetracycline family was introduced in 2005, tigecycline, and it is active against many bacteria that are resistant to other tetracyclines (Doan et al. 2006). Macrolides Macrolides are bacteriostatic drugs that are mainly effective against Grampositive bacteria (Fig. 5A). They bind to the polypeptide exit tunnel in the 50S subunit of the ribosome, thereby blocking peptidyl transfer and protein elongation. They are mainly used for treating respiratory tract infections caused by pneumococci, streptococci or mycoplasma, as well as Chlamydia infections. Clinically important macrolide antibiotics are erythromycin, clarithromycin and telithromycin (Retsema & Fu 2001), while the drugs tylosin and spiramycin are used as a food additives in animal feed to promote growth (Wegener 2003). Chloramphenicol Chloramphenicol is a broad-spectrum bacteriostatic antibiotic that was discovered in 1949. It binds to the 50S subunit, inhibiting the peptidyl transferase center of the ribosome. Due to the rather high toxicity, chloramphenicol is rarely used systemically in the developed nations nowadays, but it is still used topically as well as to treat eye infections (Walsh 2003). Oxazolidinones The first antibacterial drug in the oxazolidinone family, linezolid, was developed in the 1990s and released on the market in 2000. At that time, it was the only new class of antibiotics that had been brought to clinical use since 20

the early 1960s (Fischbach & Walsh 2009). It was developed to treat infections by Gram-positive bacteria, especially methicillin resistant Staphylococcus aureus (MRSA) infections (Bozdogan & Appelbaum 2004). Oxazolidinones can have some toxicity due to their inhibition of mitochondrial ribosomes (McKee et al. 2006). DNA gyrase inhibitors Fluoroquinolones The fluoroquinolones are a group of synthetic antibiotics that interferes with DNA replication by inhibiting the DNA gyrase or topoisomerase enzymes. This inhibition causes double strand breaks in the bacterial genome, leading to death. These broad-spectrum antibiotics are mainly used clinically to treat serious infections (Walsh 2003). The most widely used compounds in medicine are ciprofloxacin, ofloxacin, levofloxacin, lomefloxacin and norfloxacin, while enrofloxacin, danofloxacin, sarafloxacin, orbifloxacin, marbofloxacin, and difloxacin are common veterinary fluoroquinolones (Picó & Andreu 2007). RNA polymerase inhibitors Rifamycins The most clinically used antibiotic of the rifamycin class is rifampicin, and it is one of the main drugs used in the treatment of tuberculosis (Walsh 2003). It is a broad-spectrum bactericidal antibiotic that inhibits bacterial growth by binding near the active site of RNA polymerase, blocking the elongation of the mRNA transcript (Campbell et al. 2001). Membrane disruption Antimicrobial peptides Antimicrobial peptides are produced by all kinds of organisms, and they are an essential component of the immune system of humans and other animals. They typically have broad-spectrum activity, and some have been shown to exhibit immunomodulatory properties. While currently antimicrobial peptides are not commonly found in the clinic, many are investigated as potential therapeutic agents. Different peptides have different mechanisms of action, often involving interactions with the bacterial cytoplasmic cell membrane and disruption of membrane integrity (Hancock & Sahl 2006). A concern regarding the use of human-derived antimicrobial peptides as antibiotics is that resistance development would make the bacteria more tolerant to an important part of our own immune system (Lofton et al. 2013). Polymyxins Polymyxins are cyclic peptides that disrupt the outer membrane of Gramnegative bacteria through interactions with the lipopolysaccharide (LPS) in 21

the bacterial outer membrane. This interaction leads to increased permeability of the bacterial membrane and ultimately cell death. The most widely used antibiotic from the polymyxin class is colistin, a drug discovered already in the 1940s, but not used much in the clinic due to side effects. Its use has increased in recent years when, due to increasing resistance, less toxic antibiotics cannot be used anymore (Yahav et al. 2012). To minimize the use of colistin in the clinic, there have been efforts to develop new β-lactams with improved spectrum (Long & Williams 2014).

Antibiotic resistance “The time may come when penicillin can be bought by anyone in the shops. Then there is the danger that the ignorant man may easily underdose himself and by exposing his microbes to nonlethal quantities of the drug make them resistant.” - Sir Alexander Fleming in his Nobel Lecture 1945

Ever since we first started using antibiotics to treat bacterial infections, resistant bacteria have been encountered in the clinic (Zaffiri et al. 2012). Nearly all of the more specialized human pathogens where initially entirely susceptible to most antibiotics, but decades of antibiotic use and misuse have changed that picture completely (Nikaido 1994). The resistance is steadily increasing around the world, and a report from the European Centre for Disease Prevention and Control (ECDC) in 2009 showed that multidrugresistant infections cause 25 000 deaths each year and result in extra healthcare costs and productivity losses of more than EUR 1.5 billion each year in the EU alone (ECDC 2009).

Intrinsic antibiotic resistance When the expression “antibiotic resistance” is used, it is important to differentiate between intrinsic and acquired resistance. Intrinsically resistant bacteria can be defined as “resistant without any chromosomal mutation or acquisition of resistance genes” (Nikaido 1994). Some bacteria are resistant because they lack the targeted structures, such as Mycoplasma; they are resistant to peptidoglycan synthesis inhibitors such as β-lactams and glycopeptides since they lack a peptidoglycan cell wall (Taylor-Robinson & Bébéar 1997). In other cases this intrinsic resistance is because the antibiotics never reach their target molecules inside the cells as a result of permeability barriers or active efflux (Putman et al. 2000). The barrier function of the bacterial cell wall The cell wall of Gram-positive bacteria consists of a plasma membrane surrounded by a thick layer of peptidoglycan. While this structure has consider22

able mechanical strength, it offers little protection against antibiotics. In contrast, Gram-negative bacteria have a second, outer membrane outside the peptidoglycan layer, making them intrinsically more resistant to many antibiotics (Nikaido 1994). This outer membrane has a different chemical composition than the plasma membrane; the outer leaflet contains lipopolysaccharides (LPS), complex molecules consisting of a lipid and a polysaccharide (Fig. 5C). This structure makes the outer membrane much less permeable to hydrophobic molecules than the plasma membrane (Vaara et al. 1990). To be able to take up nutrients from their environment, Gram-negative bacteria use structures called porins that form water filled protein channels through the outer membrane. They especially allow the entry of hydrophilic molecules, but the shape and the chemical environment of the different channels determine the range of molecules that can diffuse through the porins. The permeabilities of the channels vary between different porins, but also between different organisms. The porins of Pseudomonas aeruginosa are much less permeable than the E. coli porins (Nikaido 1994), and as a result the permeability of the outer membrane of Pseudomonas is 10- to 100fold lower than that of E. coli (Hancock & Speert 2000). Mycobacteria, such as Mycobacterium tuberculosis, are Gram-positive bacteria but they have a very thick, waxy cell wall of mycolic acids (Fig. 5B) that makes them intrinsically resistant to most commonly used antibiotics, such as sulfonamides, β-lactams, chloramphenicol, tetracyclines, erythromycin and vancomycin (Jarlier & Nikaido 1994). Multidrug transporters The expression of active efflux pumps with broad substrate specificity is often critical to intrinsic resistance, and without them the protective barrier function of the cell wall cannot be fully utilized (X. Z. Li et al. 1994). Pseudomonas normally constitutively express MexAB-OprM, an efflux system that confers increased resistance to multiple antibiotics, such as tetracycline, chloramphenicol and ciprofloxacin (Poole et al. 1993). Escherichia coli has a similar efflux system, AcrAB-TolC, that gives increased resistance to many lipophilic antibiotics (Nikaido & Zgurskaya 2001). Both these efflux systems create a channel spanning both the inner and the outer membranes, with MexB/AcrB as inner membrane proton antiporters, TolC/OprM as exit channels through the outer membrane, and AcrA/MexA as periplasmic adaptor proteins, linking the inner membrane transporters with the exit ducts (Fig. 5D) (Symmons et al. 2009). Since this system can pump the antibiotics straight from the cytoplasm to the outside of the outer membrane, they are very efficient in decreasing the intracellular concentration of antibiotics (Nikaido & Zgurskaya 2001).

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Figure 5. The barrier function of the bacterial cell wall. (A) The cell wall of a Grampositive bacterium. A thick layer of peptidoglycan surrounds the cytoplasmic membrane. (B) The mycobacterial cell wall. Besides the peptidoglycan (PG) layer, it also contains an arabinogalactan (AG) layer, linked to long fatty acids called mycolic acids. The thick layer of mycolic acid creates a very efficient barrier. Figure based on (Riley 2006). (C) The cell wall of a Gram-negative bacterium. Besides the inner membrane (IM) and a layer of peptidoglycan, the cell is surrounded by a second, outer membrane (OM). (D) The structure of efflux pumps such as the AcrAB-TolC or MexAB-OprM systems. Both these efflux systems create channels spanning both the inner and the outer membranes.

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It is important to note here that these genes are ancient, and that their original function is not to pump out antibiotics specifically, but more generally to protect the bacteria from toxic substances in their environment, for example bile salts in case of enteric bacteria (Nikaido & Zgurskaya 2001) or toxic metabolic intermediates. Efflux systems such as AcrAB-TolC have also been shown to be important for pathogenicity in Salmonella typhimurium (Buckley et al. 2006). Biofilms In some cases bacteria form biofilms on surfaces such as implants, catheters, teeth, bone, or form aggregates in chronic lung infections in cystic fibrosis patients. These complex bacterial communities are glued together by a matrix of polysaccharides, proteins and other biopolymers (Høiby et al. 2010). Otherwise susceptible bacteria frequently gain resistance to antibiotics when they are embedded in a biofilm. This could be explained by a number of different factors. One is that the structure of the biofilm physically protects the bacteria from the drugs. The biofilm matrix itself forms no barrier to the diffusion of antibiotics, but bacteria expressing antibiotic degrading enzymes such as β-lactamases can protect other bacteria in deeper layers if they can degrade the drug faster than it can diffuse through the biofilm (Anderl et al. 2000). The increased resistance could also be explained through changes in the bacteria; deeper in the biofilm there is often a shortage of oxygen, leading to changes in metabolism and decreased growth. These conditions can make bacteria more resistant to antibiotics, especially to antibiotics that only kill actively dividing bacteria, such as β-lactams (Stewart & Costerton 2001).

Acquired resistance Antibiotic resistance can be acquired in two fundamentally different ways, mutations in the bacterial genome or acquisition of resistance genes through horizontal gene transfer (HGT). Mutation driven resistance Resistance driven by spontaneous mutations does not depend on any external genetic material, and evolution towards this type of resistance can happen in individual patients during treatment (Maciá et al. 2005) . Decreased intracellular concentration Decreasing the intracellular concentration of antibiotics increases resistance. Besides the intrinsic mechanisms of decreased cell wall permeability and efflux pumps, this can also be achieved through mutations, making it an acquired resistance. For example, mutations lowering the expression of

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porins can reduce antibiotic uptake if an antibiotic is dependent on a certain porin for entry (Nikaido 1989). Mutations in repressor genes or global regulators can also cause increased expression of the native efflux systems, such as AcrAB-TolC in E. coli, or NorA in S. aureus, conferring resistance to fluoroquinolones and chloramphenicol (Nikaido 1994). This type of enhanced drug efflux increases resistance to many antibiotics 2-8-fold compared to the wild type. Although this is a smaller increase in resistance than is usually conferred by target alteration mutations or expression of acquired resistance genes, the spectrum of resistance is generally much broader (Piddock 2006). It is common to see synergistic mutations combining reduced influx and increased efflux of antibiotics (Nikaido 1989). Some antibiotics, mainly cationic compounds such as aminoglycosides, are dependent on the electrochemical transmembrane potential to be able to cross the inner membrane from the periplasm in Gram-negative bacteria. Mutations lowering this potential can decrease the uptake of the drug, and lead to increased antibiotic resistance (Bryan & Kwan 1983). Target alteration mutations A different way for the bacterium to increase antibiotic resistance is to gain mutations that alter the target so that the affinity of the antibiotic decreases (Fig. 6). In many cases these mutations affect the target directly, as the rpsL mutations that confers resistance to streptomycin by changing the structure of the ribosomal protein S12 (Paulander et al. 2009), or the gyrA mutations that give resistance to fluoroquinolones by altering the subunit A of DNA gyrase (Bagel et al. 1999). This type of resistance is easier to acquire if the antibiotic is not a substrate analog, but binding to its target in a different way. An example is rifampicin, which binds to the β subunit of RNA polymerase a small distance away from the active site. There are many different mutations in rpoB, the gene encoding the RNA polymerase, that lead to rifampicin resistance, and such resistance generally arises rapidly (Campbell et al. 2001). In contrast, β-lactams are structural analogs to the substrate of several essential PBPs, and consequently point mutations in PBPs conferring β-lactam resistance are less common (Spratt 1994). In other cases an enzyme can modify the target structure, and the presence or absence of modification can confer resistance. One example of this is GidB, that in Salmonella methylates a specific position on the 16S rRNA, and loss of function of gidB gives a low level resistance to streptomycin (Okamoto et al. 2007; Koskiniemi et al. 2011). Mutator phenotypes In a situation where antibiotic resistance develops through mutations, a high mutation rate can sometimes be beneficial. Under antibiotic selective pressure there is often an enrichment of so called mutator strains, which due to 26

mutations in their DNA repair machinery have dramatically increased mutation rates (Mao et al. 1997; Maciá et al. 2005). Despite the obvious risk of getting trapped in an evolutionary dead end, mutators can be winners in the short term, since the accelerated accumulation of mutations gives them an increased chance of acquiring resistance mutations before their non-mutator relatives (Q. Zhang et al. 2006). Genes conferring antibiotic resistance When the resistances are provided by novel genes, as in the cases with tetracycline resistance genes or the β-lactamases, they are usually transferred between strains by mobile elements such as conjugative plasmids (Bahl et al. 2009). Alternative enzymes A resistance mechanism similar to target alteration mutations is the acquisition of a novel gene that performs the same function as the native gene, but with reduced affinity for the antibiotic (Fig. 6), or simply to compensate the effect of the antibiotic by overproduction of the target gene (Flensburg & Sköld 1987). This is a common mechanism in trimethoprim resistance, where the effect of the inhibition of the native enzyme dihydrofolate reductase (DHFR) can be alleviated by expression of a heterologous non sensitive version (Huovinen 1987). The same mechanism is responsible for the βlactam resistance in MRSA, where the horizontally acquired gene mecA encodes a PBP with very low affinity to most β-lactams (Spratt 1994).

Figure 6. Different mechanisms conferring antibiotic resistance.

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Efflux pumps The main mechanism of high-level tetracycline resistance is horizontally acquired efflux genes such as tetA that encodes a transmembrane pump that selectively removes the tetracycline from the cytoplasm. This gene is normally repressed by the product of the gene tetR, which only allows expression of the tetA gene in the presence of tetracycline (Hillen & Berens 1994). Compared to native efflux systems such as AcrAB-TolC, acquired efflux pumps such as the tet proteins generally have a much more narrow substrate specificity (Guay & Rothstein 1993). Degradation or modification of antibiotics A third way to get resistance to an antibiotic is the production of enzymes that degrade or modify the antibiotic, making it inactive or less toxic. This is the main mechanism for β-lactam resistance, where enzymes called βlactamases can catalyze the opening of the β-lactam ring, rendering them inactive (Ambler 1980). This is also a common mechanism for aminoglycoside resistance, enzymatic inactivation of the antibiotics by acetylation, adenylation or phosphorylation (Wright 1999). In some cases the resistance conferred by the expression of an antibiotic degrading enzyme can work synergistically with mutations that reduce the uptake of antibiotics; the enzyme can then easily degrade the small amounts of antibiotics that manage to cross the outer membrane (Nikaido 1994).

Heavy metals Toxicity Heavy metals are toxic to most life forms in higher doses. The reason heavy metals are so toxic to bacteria is mainly because of their ability to disrupt or inactivate proteins by reacting with the sulfhydryl groups of cysteine residues (Stohs & Bagchi 1995). Copper is an exception; it is mainly toxic because it disrupts the ironsulfur clusters in the active site of some essential metallo-proteins, such as enzymes in the biosynthesis pathway of branched-chain amino acids. The copper ions react with the iron-sulfur clusters, replacing the iron atoms and destroying the enzymatic function (Macomber & Imlay 2009).

Resistance mechanisms Bacteria have been exposed to metals in the environment for a very long time, so their metal resistance genes are ancient (Mindlin et al. 2005). The most common resistance mechanism is efflux, and genes conferring resistance to many metals have been discovered, such as mercury, copper, 28

arsenic, zinc, nickel, lead, cadmium and silver. Many of these are found on mobile genetic elements such as plasmids, and most of them are ATP-driven pumps or cation/proton antiporters (Silver 1996). Copper resistance genes probably evolved soon after earths atmosphere started to contain oxygen, since this event made copper more bioavailable. (Dupont et al. 2011) E. coli normally have two different efflux systems for copper; CopA in the inner membrane that pumps the ions into the periplasm, and CusCBA in the outer membrane that pumps the metal to the outside of the cell (Macomber & Imlay 2009). Arsenic resistance genes are usually found on plasmids, and they frequently encode the genes arsRDABC, where ArsR is a regulatory protein, ArsA and ArsB form an inner membrane arsenite efflux pump, arsC encodes an enzyme that reduces arsenate to arsenite (Carlin et al. 1995), and ArsD is an arsenic chaperone that binds arsenite in the cytoplasm and delivers it to the ArsA pump (Lin et al. 2006). Silver resistance systems are often functionally and mechanistically similar to the copper resistance systems. One such system, the sil operon, contains the regulatory proteins SilRS, the periplasmic silver-binding protein SilE, as well as the efflux pumps SilP and SilCBA. SilP pumps the silver across the inner membrane, while SilCBA is similar to the AcrAB-TolC system (Silver 2003).

The role of horizontal gene transfer “Never underestimate an adversary that has a three-point-five-billion-year head start.” - Abagail Salvers, University of Illinois (Drexler 2002)

Human pathogens have a fundamentally different ecological niche than soil bacteria, and until recently they never had any selection pressure to evolve genes for antibiotic resistance, since they would never have encountered any antibiotic-producing organisms (Fajardo & Martínez 2008). For antibiotics that are derived from natural sources, the most common resistance mechanism is to acquire new genes that encode enzymes that degrade the antibiotic or modify its target, or pumps that specifically remove the drug from the cytoplasm (Spratt 1994). Since the pathogenic bacteria did not possess these resistance genes before humans started using antibiotics, they must have somehow acquired them from non-pathogenic bacteria (Martínez 2009). It is possible to predict when the phylogeny of a specific gene is different than the phylogeny of the host organism, based on the homology, codon bias, and GC content of a gene (Lal et al. 2008), and looking at such data it is clear the vast majority of clinical resistance genes recently have been acquired through HGT (D'Costa et al. 2007). 29

Origin of resistance genes The resistance genes themselves are often ancient: analysis of bacteria isolated from places with very little or no contact with humans still show the presence of many different genes encoding antibiotic resistance (Bhullar et al. 2012). In many cases, these genes are found in antibiotic producing strains such as streptomyces, where they are needed for self-protection from their own antibiotics (D'Costa et al. 2006), but in some cases the resistance genes probably had other functions in their native organism (Aminov 2009). The problem we are facing today is the transfer of these genes from nonpathogenic environmental bacteria to the taxonomically very distant bacteria in the human microbiome and to important human pathogens (Martínez 2008; Forsberg et al. 2012). Metagenomic analysis of resistance genes show that the genes found in pathogens in the clinic are exactly the same as those found in soil and water, strongly suggesting that environmental bacteria are the original source (D'Costa et al. 2007; Forsberg et al. 2012). This transfer is an evolutionary a very recent event, enabled by the strong selection caused by the widespread use of antibiotics (Aminov 2009; Wright 2010). Interestingly, bacteria in the human gut microflora belonging to the phyla Bacteroidetes and Firmicutes carry diverse antibiotic resistance genes, but they have low homology with those found in pathogenic bacteria, indicating that the rate of HGT between these two groups of bacteria is low even though they often reside in the same locale (Sommer et al. 2009).

Mobile genetic elements A substantial part of the HGT between different species, especially of resistance genes, occurs through mobile genetic elements, such as transposons, integrons and plasmids (Stokes & Gillings 2011). Transposons Transposons are genetic elements with the ability to move from one genetic location to another. This is accomplished via an enzyme called transposase, and the gene encoding this protein is generally carried on the transposon itself. The sequences indicating the ends of the transposon are inverted repeats, recognized by the transposase (Fig. 7). Transposons are not dependent on sequence homology for insertion and can insert randomly, but the transposases sometimes have certain sequence preferences (Calos & Miller 1980). Transposons can jump between different locations in a bacterial genome, but they can also be horizontally transferred via conjugative plasmids or transducing phage. Some transposons are physically cut out from the genome during transposition, and then inserted elsewhere, while others are copied (Grinsted et al. 1990).

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Figure 7. Structures and mechanisms of transposons. (A) IS elements only consist of a transposase gene and flanking inverted repeats. (B) Composite transposons consist of two IS elements, flanking accessory genes. The figure shows the transposon Tn5, carrying resistance genes encoding resistance to kanamycin, bleomycin and streptomycin. (C) Non-composite transposons only have one pair of inverted repeats at the ends. (D) Transposon “jumping” from one place to another. The transposases bind to the inverted repeats (1), cut out the transposon (2) and insert it at another place (3).

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Transposition is potentially destructive for the host since random insertions can disrupt important genes, so most transposons are under tight regulation, and jump rarely (Nagy & Chandler 2004). The smallest transposons are called insertion sequence elements (IS elements), and they only consist of the transposase gene and the flanking inverted repeats (Fig. 7A). IS elements are extremely common, and can be found in almost all bacteria, and on many conjugative plasmids (Siguier et al. 2006). A larger type of transposons is the composite transposons (Fig. 7B). They consist of two IS elements, flanking accessory genes, and when they jump they also transpose the DNA between them (Calos & Miller 1980). Since they only require one transposase gene to function, they are not always symmetric, and one of the IS elements might have a defective transposase. Composite transposons can be randomly created de novo by two IS elements inserting close to each other (Mahillon et al. 1999). In the so-called unit-, or non-composite transposons, the accessory genes are part of the core transposon unit, and instead of two IS elements they only have one pair of inverted repeats at the ends (Fig. 7C) (Grinsted et al. 1990). The clinically important Tn21 transposons, often found on conjugative multi-resistance plasmids, belong to this group. As accessory genes, they carry a class 1 integron (see below) as well as genes conferring resistance to mercury (Liebert et al. 1999). Integrons Integrons are ancient genetic elements that probably have been around for hundreds of millions of years. They are recombination based genetic systems that use modular genetic cassettes to generate genomic diversity, and they are very common in environmental bacteria in soil and water (Gillings 2014). A minimal integron contain three different components. A gene encoding a site-specific recombinase of the tyrosine recombinase family called integrase, a recombination site recognized by the integrase called attI, and finally a promoter that can drive the expression of the gene cassettes (Fig. 8). The integron can acquire new genes from a pool of gene cassettes that can be exchanged between different integrons (Collis & Hall 1995). These gene cassettes generally only contain an open reading frame with a ribosome binding site (RBS) and a recombination site called attC (Stokes et al. 2001). They can exist in a free circular form that can be captured by the integrons and inserted into an array of genes. The cassettes are recognized and integrated through site-specific recombination between attI and attC, placing the new gene next to the promoter (Partridge et al. 2009). This tightly controlled exchange and integration of new genes has many benefits. Since the genes are always integrated at a specific site, they do not

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Figure 8. Structure and mechanism of a class 1 integron. The integron contains a gene encoding an integrase, a promoter driving the expression of the cassette array, a recombination site recognized by the integrase called attI, and an array of gene cassettes. Gene cassettes can be inserted into the array through recombination between the attC of the circular cassette and the attI of the integron. Cassettes can also be excised from the array by the integrase and exchanged between different integrons.

risk disrupting chromosomal genes. They are also inserted in the correct orientation in front of a promoter, ensuring that the newly acquired genes can be immediately expressed and utilized (Gillings 2014). The integrons are highly dynamic systems, so closely related bacteria can have very different sets of gene cassettes in their integrons. Metagenomic sequencing of gene cassettes show that many of them have no known homologies, but those that do seem to confer new functionality such as novel metabolic functions or resistances to different toxins (Stokes et al. 2001; Koenig et al. 2008). The total pool of gene cassettes has an enormous diversity, and homology analysis of the open reading frames suggests that the genes have phylogenetically heterogeneous origins (Koenig et al. 2008). This suggests that integrons have an important role in genome evolution of environmental bacteria. The integrons found in pathogenic bacteria in the clinic typically belong to the class 1 integrons, a type that is normally found in bacteria in soil and freshwater (Stokes et al. 2001). Unlike the integrons found in the environmental bacteria, the integrons found in the clinic are very recent constructions, which have evolved during the last 70 years since humans started using antibiotics. These integrons are usually mobile, and they can carry a wide assortment of resistance gene cassettes. In nature, there is an enormous diversity of integrons, while in contrast those found in the clinic are very similar. This strongly suggest that they are ancestors from one single event, when a class 1 integron was combined with a transposon, similar to the current transposon Tn402 (Gillings 2014). This new construct had the function33

ality of both an integron and transposon, and since the Tn402 also has a preference of inserting into certain plasmids, making the horizontal spread more efficient, this has been a huge evolutionary success (Minakhina et al. 1999). Many common resistance integrons still carry some genes from these early events, such as a truncated qac gene (qacE∆1) as well as the gene sul1, conferring resistance to quaternary ammonium compounds (QACs) and sulfonamides, respectively (Gillings et al. 2009). Many of the transposons related to Tn402, such as Tn21, carry genes conferring resistance to metals, such as the mer operon, giving resistance to mercury (Kholodii et al. 1993). The integron integrase genes are often activated in the cell via the SOS response, a global stress response to DNA damage. This system is activated during exposure to certain antibiotics, such as fluoroquinolones, suggesting that antibiotic treatment can increase the activity of integrons in bacteria (Guerin et al. 2009). Today bacteria carrying multidrug resistance integrons are widespread, both in humans, in agriculture and in the environment. Studies done on farm animals in Spain show that up to 80% of the E. coli in their gut flora have integrons; most of them are class 1 (Marchant et al. 2013). These integrons are also incredibly common in bacteria isolated in water treatment plants and agricultural soils (D. Li et al. 2009; Byrne-Bailey et al. 2011).

Vectors of HGT Conjugative plasmids Because of their ability to rapidly spread genes between unrelated bacterial species, conjugative plasmids are one of the most important vectors for horizontal gene transfer (Smillie et al. 2010). Their role in spreading genes for antibiotic resistance was discovered early (Foster 1983), and today the conjugative plasmids carrying resistance genes have become a major problem, especially in Gram-negative bacteria in clinical settings (Piddock 2012). The plasmids themselves are ancient, but their role in spreading antibiotic resistance is new. Studies of plasmids in bacterial samples from the “preantibiotic era” show that conjugative plasmids were common even before the use of antibiotics, but those plasmids lacked antibiotic resistance genes (V. M. Hughes & Datta 1983). While mobile genetic elements such as transposons can move resistance genes between different plasmids or the chromosome, plasmids can transfer these genes to different bacteria. Plasmids are circular DNA molecules, able to replicate independently of the bacterial chromosome. In general they contain the genes needed for replication, stability and partitioning, as well as accessory genes such as those conferring antibiotic resistance. Two plasmids using the same replication systems cannot be stably maintained in the same cell; based on this plasmids are divided into different incompatibility groups (Carattoli 2009). Conjuga34

tive plasmids also carry genes for transfer between bacteria, called tra genes (Frost et al. 1994). The host range for conjugation varies between different plasmids, but some can be highly promiscuous (Thomas & Nielsen 2005). Transfer of one plasmid between species such as Klebsiella to E. coli within a patient has been observed (Sandegren et al. 2012), and the bacteria can later spread between patients in hospitals due to patient-to-patient contact or lacking hygiene. Many of the conjugative plasmids isolated in hospitals carry a wide range of antibiotic resistance genes, as well as genes conferring resistance to biocides or metals such as silver, copper, mercury and arsenic (Chen et al. 2007; Woodford et al. 2009; Sandegren et al. 2012). Microbial biocides are substances used as disinfectants or preservatives, such as quaternary ammonium compounds, triclosan or chlorhexidine (Russell 2003). Transducing phage Phages are bacterial viruses, and they are by far the most common biological entities on earth. When they infect and lyse bacteria, they sometimes pack bacterial DNA from the host instead of the viral genome, so when they infect a new host these genes can be transferred and integrated into the genome of the recipient bacterium. This process is called generalized transduction, and it allows genetic transfer between bacteria. Compared to plasmids, phages generally have limited packing capacity (Frost et al. 2005), but unlike plasmids they can exist in a stable extracellular form. Since phage particles are very robust they can persist in the environment for a long time (Hurst et al. 1980). Transduction is believed to contribute to the HGT of antibiotic resistance genes, and there are many studies showing an increase of functional resistance genes and mobile genetic elements in phage particles in environments containing antibiotics (Muniesa et al. 2013). High numbers of phage particles carrying resistance genes have been found in manure from cows, pigs and poultry (Colomer-Lluch, Imamovic, et al. 2011a), hospital effluent water (Marti et al. 2014) as well as sewage and river water (Colomer-Lluch, Jofre, et al. 2011b). Studies have also demonstrated that the fraction of phages carrying antibiotic resistance genes increase drastically in the gut of mice treated with ampicillin or ciprofloxacin (Modi et al. 2013).

Barriers to HGT In nature, HGT can be something negative from the bacterial point of view, since most foreign DNA entering a bacterial cell is either infectious, as in the case of phage DNA, or genetic parasites such as conjugative plasmids full of potentially disruptive transposons. To protect themselves from these threats, bacteria have evolved several systems to identify and destroy foreign DNA; both unspecific such as methylation based restriction modification systems as well as sequence specific adaptive systems such as the CRISPR (Clus35

tered Regularly Interspaced Short Palindromic Repeats) systems (Marraffini & Sontheimer 2010). Interestingly enough, the extensive use of antibiotics by humans have to some extent changed the evolutionary pressure and we might inadvertently have selected for bacteria with lower barriers towards HGT. Studies done on enterococci from contemporary as well as historical samples predating the use of antibiotics show that the increase in antibiotic resistance during the last decades is inversely correlated to the activity of CRISPR systems (Palmer & Gilmore 2010). In a rapidly changing environment full of antibiotics, the benefits of accepting foreign genes might be higher than the risk; the incoming conjugative plasmid might contain resistance genes essential for survival.

The pUUH239.2 plasmid Multi-resistant bacterial strains causing outbreaks at hospitals have been a problem all over the world for many years, however Scandinavia has for a long time been spared from the worst of it (Lytsy et al. 2008). Some of the most problematic strains are those carrying extended spectrum beta lactamases (ESBLs), since they can give high levels of resistance towards a group of clinically very important β-lactam antibiotics. The first major outbreak of an ESBL strain at a hospital in Sweden happened between 2005 and 2007, when bacteria carrying the ESBL plasmid pUUH239.2 infected at least 247 patients at the Uppsala University Hospital (Lytsy et al. 2008; Sandegren et al. 2012; Ransjö et al. 2010). Homology analysis indicates that the plasmid was formed by recombination between two different plasmids, where the multi-resistance part came from one plasmid and most of the plasmid backbone from another (Fig. 9). The plasmid probably originated in Klebsiella pneumoniae, where it is stable, but it can be transferred by conjugation to Escherichia coli where it is unstable with a loss rate of 0.1% per generation and confers a fitness cost of about 4% per generation (Sandegren et al. 2012). The pUUH239.2 is in many ways a typical clinical conjugative multidrug resistance plasmid. It belongs to the incompatibility group IncFII, and it carries a Tn21 containing a class 1 integron with the usual qacE∆1 and sul1 genes, as well as genes conferring resistance to aminoglycosides and trimethoprim. The plasmid has also acquired the ESBL gene blaCTX-M-15, the βlactamases blaTEM-1 and blaOXA-1, and a transposon carrying the tetRA genes. Besides this, the plasmid carries genes that confer resistance to macrolides, copper, arsenic and silver (Sandegren et al. 2012).

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Figure 9. Genetic organization of the pUUH239.2 plasmid. (A) Complete plasmid map, with homologies to the related plasmids pKPN3, pEK499 and pC15-1a indicated. (B) Organization of the resistance cassette. IS26 elements are depicted in purple, resistance genes in red, and the integron integrase in green. The plasmid contains a Tn21-like transposon with a class 1 integron carrying the resistance genes dhfrXII, aadA2, qacE∆1 and sul1. It also contains a Tn1721-like transposon.

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Fitness costs In many cases, the antibiotic resistance confers a fitness cost to the bacterium, meaning that the resistant strain will have a slower growth rate, lower virulence or lower transmission rate than its sensitive relatives. In situations where all resistance mutations result in very high fitness costs, this could form an evolutionary barrier that would prevent the fixation of these mutations in the population, slowing down resistance development (Andersson 2006; Andersson & D. Hughes 2010). In environments where the bacteria encounter high levels of antibiotics, resistant bacteria can be selected despite high fitness costs, since the sensitive bacteria might not be able to grow at all or even be wiped out. It has been argued that the fitness costs associated with resistance will pose such an evolutionary disadvantage that all resistant bacteria would be outcompeted by sensitive bacteria once the selective pressure of the antibiotics were gone, but studies have shown that this is often not the case (Andersson & D. Hughes 2010). The explanation for this phenomenon could either be low cost or no cost resistance mutations (Marcusson et al. 2009), or that the bacteria evolve to compensate for the fitness cost without losing the resistance. There is of course the possibility of a complete reversion to wild type, but this is a rare event since there is only one way to revert a certain mutation, while there might be many way to compensate for the fitness cost of the resistance by mutations elsewhere in the genome. This might result in strains with both fully restored fitness and maintained resistance (Fig. 10) (Handel et al. 2006). This is very problematic, and it suggests that the reversal of bacterial resistance to antibiotics might be very slow or non-existent even if we would completely stop using antibiotics for a longer period of time (Andersson & D. Hughes 2010).

Figure 10. Compensatory evolution. The initial selection for resistance can enrich for mutants with low fitness, but these costs might later be compensated via mutations elsewhere in the genome. This could result in strains with fully restored fitness and maintained resistance. Complete reversion to wild type sequence is unlikely.

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Selection of resistance ”To date, no serious disadvantages to widespread use of these small concentrations of antibiotics have appeared, although the possibility has been raised of generating a large reservoir of antibiotic-resistant enteric bacteria.” - William L. Hewitt on the use of low levels of antibiotics in animal feed, 1967 (Hewitt 1967)

While it has been known for a long time that use of antibiotics select for antibiotic resistance, it has been debated exactly where and how the resistance arises and is enriched (Andes et al. 2006).

The dynamics of the resistome For almost all antibiotics that have been introduced in the clinic, resistant strains appeared within a few years, but the differences in the speed of resistance development between different antibiotics are large. For some antibiotics resistance appears almost instantly, while for others it can take more than ten years before any resistant strains are encountered in the clinic (Schmieder & Edwards 2012). There are many factors that can influence how rapidly resistance will arise, but one of the main factors is the exposure dynamics (Gould & MacKenzie 2002; Toprak et al. 2012). What levels of antibiotics will bacteria be exposed to, and for how long? How much of the antibiotic is used, how is it used, and where is it used? There are clear correlations between antibiotic use and resistance developments (ECDC 2009). In the EU, the countries that use most antibiotics generally also face the biggest problems with clinical resistance. Greek physicians prescribe twice as much antibiotics per capita than Swedish, and the problem with resistance is much larger (ECDC 2011b; ECDC 2011a). Exposure is only one of the factors affecting resistance development though; the molecular mechanisms behind the antibiotic have an effect as well, as has the fitness cost associated with resistance (Andersson & D. Hughes 2010), as well as whether there are resistance genes from environmental bacteria available through horizontal gene transfer (Martínez 2008).

The mutant selective window hypothesis One of the dominating theories of selection of resistance is the mutant selective window hypothesis, which states that selection of resistant mutants occurs in a concentration range spanning from the minimum inhibitory concentration (MIC) of the sensitive strain to the MIC of the resistant mutant (Drlica 2003; Drlica & Zhao 2007). The main focus has been on how high levels of antibiotics need to be to avoid enrichment of resistance, the “mutant preventive concentration” (Gould & MacKenzie 2002), but not as much effort 39

has been made to map the lower limit of this window. It could be argued that also concentrations below the MIC of the sensitive strain would select for resistance, since these antibiotic levels could lower the growth rate of sensitive bacteria (Fig. 11). The main goal of this thesis was to investigate the role of very low levels of antibiotics in the selection of antibiotic resistance, and how the fitness costs of different resistance mutations, genes or plasmids will affect this selection.

Sub-MIC selection of resistance Enrichment of resistant bacteria at low antibiotic concentrations could have large consequences, since environments containing small amounts of antibiotics are more prevalent than those reaching the high levels found in patients during treatment (Kümmerer 2003). It also happens that the serum levels of an antibiotic drop below the MIC during antibiotic treatments, depending on the elimination rate of the drug and the time between doses (Drusano 1988). This is especially a problem when antibiotics are prescribed and taken outside of the clinic; patients often forget to take their pills at the correct time (Vrijens & Urquhart 2005).

Figure 11. Growth rates as a function of antibiotic concentration. Green indicates a concentration interval where the susceptible strain (blue line) will outcompete the resistant strain (red line). Orange (sub-MIC selective window) and red (traditional mutant selective window) indicate concentration intervals where the resistant strain will outcompete the susceptible strain. MICsusc = minimal inhibitory concentration of the susceptible strain, MICres = minimal inhibitory concentration of the resistant strain and MSC = minimal selective concentration. Figure from paper II.

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Finally there are body compartments where the antibiotic concentrations are much lower than the serum levels because of limited tissue penetration, such as fat tissue (Joukhadar et al. 2001) or abscesses (Wagner et al. 2006). Certain antibiotics, for example tetracyclines and macrolides, are prescribed in low doses for months or even years to treat chronic, non-infectious diseases because of their anti-inflammatory and immunomodulatory properties (Voils et al. 2005; Perret & Tait 2014). Patients suffering from the skin condition rosacea are frequently treated with sub-MIC doses (40 mg/day) of doxycycline for long periods of time (Alikhan et al. 2010). From a genetic point of view, it is possible that selection of resistance at sub-inhibitory concentrations will generate a different mutational spectrum than those seen at concentrations above MIC. The low selection pressure will only allow low-cost resistance mutations or genes to enrich, and over longer periods of time the bacteria might be able to gain a high level of resistance at a very low cost (paper II and paper IV).

Antibiotics and heavy metals in the environment Unlike drugs used to treat non-infectious diseases such as cancer or cardiovascular diseases, the use of antibiotics does not only affect the person taking the drug. Because of the risk of antibiotic resistance development it also affects the surrounding people and the environment. Large amounts of antibiotics are released into natural environments, both from human patients and livestock, as well as in wastewater released from pharmaceutical production plants (Lindberg et al. 2007; D. Li et al. 2009; Larsson et al. 2007), and studies clearly show that these antibiotics can have a dramatic effect on the prevalence of resistance genes among the bacteria in the affected environments (Gaze et al. 2011; Jechalke, Heuer, et al. 2014b; Zhu et al. 2013). The complex microbial populations in these environments have been studied to map the prevalence of resistance genes. However, different results are obtained depending on if growth based or molecular methods are used to identify bacteria or detect antibiotic resistance. Only a fraction of the bacteria in an environmental sample can be cultivated, so culture based methods will never be able to give a complete picture. PCR based methods on the other hand require some previous knowledge about the genetic targets, such as the sequence of rRNA genes or known resistance genes (Khan & Yadav 2004). An alternative to trying to detect the resistance genes directly is to design primers targeting genetic structures for HGT such as integrons and plasmids, since they are known to be good indicators for the presence of antibiotic resistance due to anthropogenic influence (Lupo et al. 2012; Gaze et al. 2011).

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Use in agriculture “We pay for cheap meat by sacrificing some of the most important drugs ever developed.” – New York Times, June 2011 (Editorial 2011)

It was discovered in the 1950s that adding broad-spectrum antibiotics in animal feed could increase the growth of farm animals, and because of the economical benefits this quickly became common practice (Hewitt 1967). At the same time as we try to limit the unnecessary usage of antibiotics in human medicine, enormous amounts of broad-spectrum antibiotics are given to farm animals. In many cases, the antibiotics used are the very same drugs or structurally related compounds that are used in the clinic (Allen et al. 2010; Witte 1998). Variation in usage around the world Exact numbers on the volume of global antibiotic usage are not available, but it is assumed that only a small fraction of the global production of antibiotics is used in human medicine. The rest is used in agriculture for growth promotion or mass prophylaxis, where entire populations of livestock are treated to prevent disease (WHO 2012). Especially the growth promotion use is very problematic from a resistance development perspective, since the concentrations used are lower than therapeutic doses, and the treatments can go on for long periods of time (Anderson et al. 2003). Within the EU it is no longer allowed to use antibiotics for growth promotion, but the usage in agriculture is still high; more than 8,000 tonnes of veterinary antimicrobial agents are used every year, mainly for mass treatment of livestock. The differences between countries within the EU are large; countries like Italy and Spain uses ten times more antibiotics per kilogram of meat produced compared to Sweden (EMA 2013). The situation in the US is very different since the use of antibiotics for growth promotion is still legal, and the use in agriculture is 50% higher than the worst countries in the EU (Cully 2014). It is estimated that in 2011 more than 13,500 tonnes of antimicrobials were used in the US food-producing animals, whereof 42% were broad spectrum tetracyclines (FDA 2013). Estimations by the Union of Concerned Scientists (UCS) suggest that 70% of the antibiotics consumed in the US are used in agriculture for non-therapeutic purposes (Mellon et al. 2001). Still, there are countries that are even worse: for example, China is one of the world’s biggest consumers of antibiotics. A study from 2007 estimate that more than 95,000 tonnes of antibiotics are used in livestock annually (Zhu et al. 2013), and not surprisingly, the country also has enormous problems with antibiotic resistance in the clinic (Hvistendahl 2012).

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Effects on animal gut microbiota It has been known for a long time that low levels of antibiotics in animal feed cause an enrichment of resistance. A study in the mid seventies showed that the addition of tetracycline in chicken feed resulted in a very large fraction of tetracycline resistant bacteria in their gut microbiota (S. B. Levy et al. 1976). Similarly, a study in Denmark in 1995 showed that 80% of chickens treated with the glycopeptide avoparcin for growth promotion carried vancomycin resistant enterococci (VRE) in their gut flora, while this bacterium was completely absent in the flora of chickens from ecological poultry farms (Aarestrup 1995). Ever since the use of avoparcin for animal growth promotion was banned in the EU in 1997, a decrease in the amount of VRE in the gut flora of farm animals has been observed (van den Bogaard et al. 2000). Overall, it is clear that low levels of antibiotics in animal feed are problematic, since it makes each animal a living factory for the production of resistant bacteria. Effects on the environment Spread of antibiotics Similar to humans, about half of the antibiotic dose fed to animals get excreted unchanged in urine and feces, and in some cases up to 90% (Sarmah et al. 2006). Since manure is rich in nutrients it is often spread on agricultural fields as fertilizer, and once in the soil the antibiotics can remain there for years. Their degradation time in soil depends on several factors, such as chemical stability, degradation by microorganisms and binding to soil particles (Jechalke, Heuer, et al. 2014b). For some antibiotics such as tetracycline, the resistant organisms do not degrade the drug since most mechanisms conferring resistance are based on efflux and ribosomal protection. Because of this, low levels of tetracyclines can remain in the environment for a long time, causing a continuous selection for resistance (Hillen & Berens 1994). Other drugs, like ciprofloxacin, are chemically very stable and bind tightly to soil particles, thus prolonging the exposure time to the antibiotic (Picó & Andreu 2007). Sometimes even low concentrations of antibiotics can have an effect on the soil microbiome, as in the case of sulfonamides where low levels can enrich for antibiotic resistance as well as promote horizontal gene transfer (Jechalke, Heuer, et al. 2014b). Furthermore, runoff from the fields can spread the antibiotics to nearby rivers and lakes (Burkholder et al. 2006). Spread of heavy metals Large amounts of heavy metals such as copper and zinc have been used in animal feed as growth promoting agents and to boost feed efficiency, an effect believed to be due to the antimicrobial properties of the metals (Jacob et al. 2010). Unlike antibiotics, the metals never degrade, so they accumulate 43

over time in soil, rivers and lakes (Arunakumara et al. 2013). Copper has been added to swine feed to promote growth since the 1960ies (Apgar et al. 1995), and arsenic has been added to both cattle, poultry and swine feed in the form of, for example, Roxarsone, 3-nitro-4-hydroxyphenylarsonic acid (Garbarino et al. 2003). This has lead to large amounts of copper and arsenic contaminating agricultural fields and nearby waters (Silbergeld & Nachman 2008; F. Zhang et al. 2012). Analysis of pig, poultry and cattle manure on a farm in China showed high levels of heavy metals (F. Zhang et al. 2012), and a study has shown that there is a correlation between the levels of copper and zinc in the manure and resistance to β-lactams (Hölzel et al. 2012). Another study demonstrated that increased copper levels in soil could enrich for bacteria resistant to tetracycline and vancomycin (Berg et al. 2010). Several other studies confirm that heavy metals can co-select for antibiotic resistance (Baker-Austin et al. 2006; Seiler & Berendonk 2012). Spread of resistance genes The manure from farm animals does not only contain a mix of antibiotics and heavy metals, but also resistance genes and resistant bacteria, which eventually end up together in the soil. Even if many of the gut bacteria are badly adapted for living in the soil, the spreading of manure can have large effects on the soil bacterial communities (Jechalke, Heuer, et al. 2014b). A recent study of resistance genes in manure and soil on Chinese swine farms showed that there are enormous amounts of resistance genes in both soil and manure, and that they are very diverse. Analysis of manure samples from animals fed antibiotics showed that antibiotic resistance genes where enriched almost 30,000-fold compared to the antibiotic-free manure controls, and some mobile genetic elements such as transposases were enriched even more, up to 90,000-fold. The most common mobile genetic element found was IS26, often flanking various resistance genes. The study also found a very strong correlation between the abundance of antibiotic resistance genes and the antibiotic and metal concentrations (Zhu et al. 2013). There are many other studies linking antibiotics in manure with high rates of horizontal gene transfer. A study investigating the plasmids in swine manure showed that it contains large amounts of conjugative plasmids carrying multiple resistance genes (Binh et al. 2008). Soil that had been fertilized with manure from pigs treated with the fluoroquinolone difloxacin showed an enrichment of class 1 integrons and mobile genetic elements (Jechalke, Focks, et al. 2014a), and similar results were reported in soil amended with pig slurry from pigs fed with the macrolide antibiotic tylosin (Gaze et al. 2011). Together, these results demonstrate that the spreading of manure containing antibiotics and heavy metals on soil gives environmental bacteria and gut bacteria from farm animal a suitable setting for mixing and exchanging antibiotic resistance genes.

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Use in aquaculture During the last 25 years fish farming has increased drastically, and in 2009 half of the fish and shellfish consumed globally was produced in aquaculture (Naylor et al. 2009). Because of the high population densities in the net cages, diseases easily spread among the fish, and large amounts of antibiotics are used to treat infected populations (S. M. Armstrong et al. 2005). A wide range of different antibiotics is used, such as oxytetracycline, florfenicol, fluoroquinolones, sulfonamides, amoxicillin, erythromycin and gentamicin (Sapkota et al. 2008). Just like in agriculture, most of the antibiotics are still active when they are excreted by the treated animals, and they end up in the water and the sediment below the cages where the bacterial communities will be exposed to sub-inhibitory concentrations of antibiotics (Capone et al. 1996). Even if fish pathogens and the environmental bacteria living in the sediment are different from human pathogens, there is evidence suggesting that some clinical resistance genes actually have their origin in aquatic bacteria (Lupo et al. 2012). For example, the ESBL gene blaCTX-M originate in the bacterium Kluyvera (Poirel et al. 2002; Canton et al. 2012) common in the fish intestinal flora (Navarrete et al. 2010), a type of fluoroquinolone resistance genes called qnr originate in marine bacterial species (Lupo et al. 2012), and an IncU plasmid containing a tetracycline resistance gene have been isolated in both Aeromonas in fish and in E. coli in the clinic (Rhodes et al. 2000). Transfer of resistant bacteria to humans There are many studies showing that antibiotic resistant bacteria selected in livestock can easily be transferred to humans, either via direct contact with the animals, or through meat products (Smith et al. 2002; Marshall & S. B. Levy 2011). Transfer via animal contact Farm workers, veterinarians and people working in the meat industry are groups at risk for exposure to antibiotic resistant bacteria from animals. Already in the seventies it was shown that the use of tetracycline in animal feed not only had effects on the gut microbiota of the treated animals, but also on the farmers. A study investigating the potential transfer of resistant bacteria from farm animals to humans discovered that within six months of adding antibiotics to the animal feed, it was possible to detect changes in the gut flora of the farmers. To make things worse, there was an enrichment of resistance to multiple antibiotics in both the chickens and the humans, not only resistance to tetracycline (S. B. Levy et al. 1976). Similarly, studies have demonstrated that carriage of MRSA is strongly linked to living close to swine farms (Carrel et al. 2014), and that workers in the poultry industry are 45

more than 30 times more likely to carry gentamicin resistant E. coli (Price et al. 2007). During the last few years, the use of whole genome sequencing (WGS) has become a powerful method to phylogenetically track the transfer of bacteria between animals and humans. WGS data from samples of the strain S. aureus CC398 collected from all over the world were used to track its phylogeny. The results revealed that the ancestor strain was an antibiotic susceptible strain from humans that somehow got transferred to animals. There it acquired resistance to both tetracycline and methicillin, converting it to an MRSA strain. This novel strain then transferred back to humans, causing a rapid increase in livestock-associated MRSA (LA-MRSA) infections (Price et al. 2012). Transfer via food Nowadays there are plenty of evidence showing that the use of antibiotics in animal feed contributes to the problem with antibiotic resistant bacteria in the clinic via contaminated animal food products (Smith et al. 2002). A study in Netherlands in 1997 showed that VRE was present in the gut flora of 20% of persons eating meat, while it was completely absent among tested vegetarians, indicating that consumption of contaminated meat was the source (Schouten et al. 1997). In 2007, bacteria isolated from commercial chicken meat were compared with bacteria isolated from patients in a hospital nearby, and the results showed that the antibiotic resistant bacteria from the patients were identical to the poultry strains, while the susceptible strains were not (Johnson et al. 2007). Multidrug resistant E. coli causing urinary tract infections in humans have also been shown to be of animal origin, most likely transferred via contaminated dairy or meat products (Ramchandani et al. 2005). A study that performed WGS of multidrug resistant Salmonella typhimurium DT104 samples, taken from both humans and farm animals during a period of 22 years, showed that each host had their own Salmonella populations, but that there was exchange of bacteria and resistance genes between the animal and human bacterial populations (Mather et al. 2013). The transfer risk is not limited to meat and dairy products; when humans eat crops such as root or leaf vegetables from fields fertilized with manure, there is also a risk that the vegetables are contaminated with fecal pathogenic bacteria from the manure (Natvig et al. 2002). Regulation of agricultural use of antibiotics Because of the mounting evidence of a link between agricultural use of antibiotics and antibiotic resistant bacteria among humans, the use of antibiotics as additives in animal feed to promote growth was banned in the EU in 2006 (EU 2005). Perhaps surprisingly, no long-term loss in productivity has oc-

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curred, based on numbers from the pork industry in Denmark (Aarestrup et al. 2010). Meanwhile in the US, there has been long discussions whether or not to ban the use of antibiotics for growth promotion (Editorial 2012), but strong protests from the pharmaceutical industry has so far resulted in FDA only recommending voluntary regulation, no bans have been issued yet. The new guidelines from FDA in 2013 recommends the antibiotic manufacturers to remove the growth-promotion use from labels, making non-medical use of them illegal (Kuehn 2014). It is still unclear if this voluntary approach will work, and there are concerns that the lack of monitoring of the antibiotic use in the US will make these recommendations toothless (S. Levy 2014). In general, a big part of the problem is commercial interests; the antibiotic manufacturers want to sell their products, and also the veterinarians make a profit from selling antibiotics to farmers. In 1995 Denmark passed a law that forbad veterinarians from profiting on antibiotics sales, and together with a rigorous system for monitoring the use of antibiotics on farms, this has lowered the use of antibiotics in the Danish agriculture drastically (Aarestrup 2012).

Antibiotics in wastewater When humans and animals are treated with antibiotics, the selection of resistant bacteria is not restricted to their bodies. Most of the antibiotics are excreted unchanged through urine and feces and reach sewage treatment plants, and they eventually pollute rivers or soil when the sludge is used as fertilizer (Berkner et al. 2014). Sewage water and river water have been found to contain β-lactam resistance genes such as blaCTX-M, as well as fluoroquinolone resistance genes (Colomer-Lluch, Jofre, et al. 2011b; Marti et al. 2014). Activated sludge treatment Most wastewater treatment plants (WWTPs) use a biological treatment process called “activated sludge” that accelerate biological degradation of organic contaminants in the wastewater through aeration of the water, promoting microbial growth (Barnard 1975). The sludge contains a very dense, complex bacterial community (Snaidr et al. 1997), fed by a constant inflow of nutrients and new bacteria, while exposed to varying sub-inhibitory concentrations of antibiotics. This is close to a perfect environment for horizontal gene transfer and selection of resistance, and metagenomic sequencing of plasmids in WWTP samples show a high diversity of plasmids, rich in genetic elements such as transposons, integrons and resistance genes (Schlüter et al. 2008). Also the phage populations in wastewater treatment plants can contain large amount of genes conferring resistance to antibiotics (CaleroCáceres et al. 2014). 47

Antibiotic resistance genes in waste water In the WWTP there is a constant influx of new genetic material, and especially wastewater from hospitals can be very rich in resistance genes (Volkmann et al. 2004). A study of German wastewater identified genes conferring resistance to aminoglycosides, fluoroquinolones, macrolides, tetracyclines, trimethoprim, sulfa and rifampicin, and some of these genes were identical to recently discovered clinical resistance genes (Szczepanowski et al. 2009). In a study of human commensal bacteria in a wastewater treatment plant in Poland receiving mainly wastewater of domestic origin, isolates of fecal coliforms and enterococci showed high levels of antibiotic resistance. Among the coliforms, 34% were resistant to ampicillin, 23% to tetracycline, 11% to trimethoprim/ sulfamethoxazole and 10% to ciprofloxacin. Among the enterococci, 44% were resistant to erythromycin, 20% to tetracycline and 29% to ciprofloxacin (Łuczkiewicz et al. 2010). Selection of resistance in WWTPs Because of the antibiotics, biocides and heavy metals in the wastewater, there is a constant selection pressure for increased resistance. Studies show that the fraction of resistant bacteria is higher in the treated than in the untreated wastewater, suggesting that there is an enrichment of antibiotic resistance in the bacterial populations during the wastewater treatment process (Łuczkiewicz et al. 2010). Studies of the correlation between antibiotic concentrations and the occurrence of antibiotic resistance in wastewater demonstrated that the presence of antibiotics and biocides in the water had a significant effect on the composition of the microbiome, and there was a significant correlation between the concentration of tetracyclines in the water and the fraction of antibiotic resistant bacteria. This enrichment was not limited to tetracycline resistance, suggesting that the different resistance genes are linked, and that the selection for one of the resistances co-selects for the others (Novo et al. 2013). Efflux water and sludge from WWTPs The antibiotics and resistant bacteria do not stay in the WWTPs. The treated water is released into rivers or lakes (Rizzo et al. 2013), while the sludge, the solid fraction of the wastewater, is collected and frequently used as a fertilizer of soil (Thiele-Bruhn 2003). Enormous amounts of resistant bacteria enter rivers from water treatment plants. A study of enterococci in WWTPs in Portugal showed that the effluent released into natural waters can contain more than 104 cfu/ml, and that almost half of them are resistant to multiple antibiotics (Martins da Costa et al. 2006). The compounds that do not end up in the water, such as ciprofloxacin, instead end up in the sludge, where drugs are enriched and they eventually end up in the soil when the sludge is used as fertilizer. Since fluoroquinolones are chemically very stable and bind to 48

soil particles, they will slowly be released in low concentrations creating a selection pressure during a long period of time (Girardi et al. 2011). The sludge also contains heavy metals (Walter et al. 2006), which could accumulate in the soil and co-select for antibiotic resistance (Baker-Austin et al. 2006).

Figure 12. Agricultural and clinical use of antibiotics result in a spread of antibiotic residues, resistant bacteria and resistance genes in the ecosystem. Subinhibitory levels of antibiotics and heavy metals cause an enrichment of resistance in environmental bacteria, increasing the risk of transfer of resistance genes to pathogens. Adapted from (Singer & Williams-Nguyen 2014). Illustration by Pikkei Yuen.

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Other sources “Well I'm standing by a river, but the water doesn't flow. It boils with every poison you can think of.” – Chris Rea, “Road to Hell”

Pharmaceutical production plants Depending on how the wastewater is treated, the large-scale industrial production of pharmaceuticals can be a major source of antibiotics in the environments. Wastewater efflux from pharmaceutical productions plants in India release massive amounts of active antibiotics straight into the rivers; the levels of ciprofloxacin in the efflux can be up to 31 mg/l, a concentration higher than the plasma levels in a human patient during treatment, and equivalent to approximately 45 kg of ciprofloxacin released every day (Larsson et al. 2007). Similarly, a South Korean study in 2010 detected concentrations of 44 mg/l lincomycin, 24.8 µg/l sulfamethoxazole, and 10.1 µg/l trimethoprim in the efflux from pharmaceutical manufacture WWTPs (Sim et al. 2011). The concentrations of antibiotics can be very high even after massive dilution in natural waters; lake water close to a WWTP near Hyderabad, India, contained up to 6.5 mg/l ciprofloxacin, 0.52 mg/l norfloxacin, and 0.16 mg/l enoxacin, while samples from nearby wells contained up to 14 mg/l ciprofloxacin, showing that the contaminations also reach the ground water (Fick et al. 2009). Several of these concentrations are far above the clinical breakpoints of resistance for E. coli; the MIC breakpoint for ciprofloxacin resistance in Enterobacteriaceae according to the European Committee on Antimicrobial Susceptibility Testing (EUCAST) is 1 mg/l. Besides the antibiotics, the effluent water can also contain bacteria; an analysis of bacteria isolated from the effluent of an antibiotic production WWTP in China showed high levels of multiple antibiotic resistance. Nearly 80% of the isolates were resistant to 10 or more different antibiotics, and many of them carried class 1 integrons (D. Li et al. 2009). Sources of heavy metals and biocides Heavy metals Metals are already naturally present in high levels in many environments, and besides sources previously mentioned, sewage sludge and manure, there are many other anthropogenic sources of metal contaminations (Nriagu & Pacyna 1988). Coal fired power plants produce millions of tonnes of ash residues every year, which are deposited in landfills or in aquatic basins that are disposed into rivers. Such ash contains very high levels of heavy metals, up to 1385 mg/kg arsenic and 1452 mg/kg copper. The aquatic basins contaminate surrounding waters; samples of ash effluent entering a lake contained up to 250 µg/l arsenic (Rowe et al. 2002). 50

Large amounts of metals can be released into the environment from mining sites. Ground water samples taken near a mine in Romania contained 50 µg/l copper, 31 µg/l cadmium, 50 µg/l lead and 3000 µg/l zinc (Bird et al. 2009). The industrial use of metals can contaminate the surrounding environments; topsoil samples taken in industrial areas in the UK were found to contain up to 2750 mg/kg copper (Kelly et al. 1996). Additionally, heavy metals are released from healthcare (Percival et al. 2005; Knetsch & Koole 2011) and urban street dusts (X. Li et al. 2001). Arsenic is naturally present in the ground water in many parts of the world (Smedley & Kinniburgh 2002), such as Bangladesh (Nickson et al. 1998) and parts of the United States (Welch et al. 2000), but it is also used in large amounts in wood treatment (Belluck et al. 2003) and in some pesticides (Baker et al. 1976). Biocides Antimicrobial biocides are used in large volumes in both industry, agriculture and in consumer products, mainly as antiseptics, disinfectants and preservatives. Some are small molecules such as hydrogen peroxide, formaldehyde and ethanol, while other are more complex (Russell 2003). One important class of biocides is the quaternary ammonium compounds (QACs), a type of cationic surfactants that kill bacteria by disrupting cell membranes (Hegstad et al. 2010). Many QACs are chemically stable, so polluted environments can expose microbes for sublethal concentrations for long periods of time (Ying 2006). Samples from QAC contaminated environments show an increased abundance of class 1 integrons carrying the genes qacE and qacE∆1, strongly suggesting that selection of biocide resistance could co-select for resistance to antibiotics (Gaze et al. 2005). Another important biocide is triclosan, a synthetic, broad-spectrum antibacterial and antifungal agent that has been used in many consumer products such as soaps, shower gels, hand lotions, deodorants, toothpastes and mouthwash to be able to label them “antibacterial” (Schweizer 2001). Low levels of triclosan can be detected in stream sediments close to cities, and there is a strong correlation between the presence of triclosan and the fraction of triclosan resistant bacteria isolated from the sediment (Drury et al. 2013). It has been demonstrated that resistance development to triclosan through increased efflux can also confer resistance to many antibiotics (Chuanchuen et al. 2001; Karatzas et al. 2007). The widespread use of biocides in consumer products such as toothpaste and cosmetics is potentially problematic, since it could cause an enrichment of antimicrobial resistance in the bacteria of the mouth or skin microflora (Hegstad et al. 2010).

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Present investigations

Paper I Activation of cryptic aminoglycoside resistance in Salmonella enterica Aminoglycosides are a clinically important class of antibiotics that inhibit protein synthesis by binding to the small ribosomal subunit of bacteria. One way for bacteria to acquire resistance to aminoglycosides is target alterations; examples are mutations in the gene rpsL encoding the ribosomal protein S12 (Springer et al. 2001) or a change in methylation of the 16S rRNA conferred by mutations leading to the inactivation of the methyltransferase GidB (Okamoto et al. 2007). Another way is to express antibiotic modifying enzymes, such as aminoglycoside acetyltransferases, adenyltransferases or phosphotransferases (Wright 1999). Finally, aminoglycosides require a certain electrochemical potential over the inner membrane for antibiotic uptake (Bryan & Kwan 1983); mutations that impair the electron transport chain, thereby lowering the membrane potential, will often increase aminoglycoside resistance, but at a high fitness cost. It has previously been shown that small colony variants (SCVs), mutant subpopulations of bacteria with slow growth rates, can have increased resistance towards many antibiotics (Cano et al. 2003), but mechanistically this is not well understood. SCVs are observed in many different bacterial species (Proctor et al. 2006), and are of clinical importance since they besides the increasing antibiotic resistance also can allow bacteria to escape the host immune system (Cano et al. 2003). In this paper, we show that the chromosomally encoded cryptic resistance gene aadA is responsible for the high aminoglycoside resistance in SCVs of Salmonella typhimurium LT2, and that it together with mutations in the gene gidB can confer high levels of resistance to the aminoglycosides streptomycin and spectinomycin. Inactivation of the aadA gene in the SCVs decreases the resistance to wild type levels, and beta-galactosidase assays with translational fusions of the aadA promoter and the first three codons of the aadA open reading frame with lacZ as well as transcriptional fusions show that expression of the aadA gene is upregulated on both transcriptional and translational levels in SCVs.

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Figure 13. The different mechanisms leading to increased streptomycin resistance in Salmonella typhimurium LT2 SCVs. The boxes in purple represent experiments done to elucidate the role of the stringent response in the expression of the cryptic aadA gene.

We could also show that expression of aadA is controlled by the stringent response regulator ppGpp. The level of ppGpp in the bacterial cell is increased during amino acid or carbon starvation, and it is dependent on the activity of the synthetase RelA as well as the enzyme SpoT that can both synthesize and hydrolyze ppGpp (Stephens et al. 1975; Bremer & Dennis 2008). Knocking out relA and spoT in a streptomycin resistant SCV strain lowers the MIC of streptomycin to the same levels as seen in an aadA knockout, while overexpression of relA gives an increased resistance to streptomycin. Also, growth on minimal media supplemented with 0.2% glucose or glycerol gives wild type S. typhimurium a 16- to 32-fold increased MIC to streptomycin and spectinomycin compared to growth on rich media, and the upregulation of aadA during these conditions could be confirmed using beta-galactosidase assays. Since the level of ppGpp is higher during growth on minimal media (Bremer & Dennis 2008), this further supports our hypothesis that aadA gene expression is regulated through the stringent response. Two of the SCVs studied had a slow growth rate due to stop codon mutations in the genes ubiA (ubiquinone biosynthesis) or hemA (haem biosynthesis) causing defects in their electron transport chain (Pränting & Andersson 2010), and interestingly, in the presence of streptomycin the growth rates of 53

these mutants were increased 6-40%. It is known that streptomycin causes an increase in the ribosomal misreading frequency (Gorini & Kataja 1964), so this effect could be explained by streptomycin-induced readthrough of the stop codons, resulting in increased expression of these growth rate limiting enzymes. When combined with rpsL mutations that impair the binding of streptomycin to the ribosome, this effect was no longer observed. Also, the presence of nonsense suppressor tRNAs increased the growth rate, and streptomycin could then no longer further stimulate growth. Another observation is that in a strain where the hemA gene has been completely deleted, streptomycin can no longer increase the growth rate, further supporting the stop codon readthrough hypothesis.

Paper II Selection of resistant bacteria at very low antibiotic concentrations It has been known for a long time that exposing bacteria to antibiotics will select for resistant mutants, but the exact dynamics of this selection have not been well characterized (Gould & MacKenzie 2002). At the time of this study it had been hypothesized that low concentrations of antibiotics could be important for selection of resistant mutants, but experimental evidence for that was lacking. The aim of this study was to investigate the lower limits of the “mutant selective window”, the antibiotic concentration interval where enrichment of resistant mutants occur. In this study the minimum selective concentrations (MSCs) of different antibiotics was determined for several resistance mutations or resistance genes in Salmonella typhimurium and Escherichia coli. We found, using sensitive competition experiments, that selection of resistant bacteria occurs at extremely low antibiotic concentrations of three clinically important classes of antibiotics; aminoglycosides (streptomycin), tetracyclines (tetracycline), and fluoroquinolones (ciprofloxacin). Isogenic resistant and sensitive strains of Salmonella typhimurium and Escherichia coli were tagged with two different fluorescent markers (ECFP and EYFP) and competed at sub-inhibitory concentrations of antibiotics. The cultures were maintained by a 1000-fold dilution every 24 hours, and the fraction of resistant bacteria in the population was monitored at each dilution step using flow cytometry. By analyzing how the fraction of resistant bacteria in the population changed over time, the selection coefficients, the fitness costs of resistance and the MSCs could be calculated.

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Figure 14. The sub-MIC selective window can be much larger than the traditional selective window. In the case of ciprofloxacin, the resistance mutation gyrA (S83L) in Escherichia coli gives a sub-MIC selective window with a range of approximately 230x, while the traditional selective window has a range of 17x.

The results showed that for three clinically important antibiotics, drug concentrations up to several hundred-fold below the minimal inhibitory concentration (MIC) of susceptible bacteria could enrich for resistance, even when initially the fraction of resistant bacteria was very small. It is interesting to note that the sub-MIC selective window can be many times larger than what is traditionally thought to be the selective window. In the case of ciprofloxacin, the resistance mutation with the lowest fitness cost (gyrA (S83L)) gives a sub-MIC selective window with a antibiotic concentration range of approximately 230 times, while the traditional selective window has a range of 17 times. Concentrations of ciprofloxacin in sewage water (Sim et al. 2011), sludge (Olofsson et al. 2012), as well as soils fertilized with manure (Martínez-Carballo et al. 2007) are frequently above the MSC, suggesting that enrichment of resistance will occur in such environments. Our results suggest that the MSC is highly dependent on the fitness cost of the resistance mutation; the lower the fitness cost of the resistance is, the lower the MSC will be. We could also show that de novo mutants can be selected at sub-MIC concentrations of antibiotics. The enrichment of resistant subpopulations in the bacterial cultures could be monitored by cycling independent lineages of sensitive wild type strains at low concentrations of streptomycin and ciprofloxacin, and plating 105 cells on agar plates containing different concentrations of antibiotics every 100 generations. In the case of streptomycin, ¼ of MIC was enough to rapidly select for de novo resistance. Initially, only small 55

fractions of bacteria with low-level resistance were present, but over time the size of these subpopulations grew. As the cycling proceeded, new subpopulations with even higher resistance appeared, and after 700 generations there were subpopulations that could grow on 128 µg/ml streptomycin (32x MIC) in several of the lineages, 128 times higher than the concentration they had been exposed to. At these low antibiotic levels, resistance mutations conferring high fitness costs will not be enriched; only mutations where the fitness cost is lower than the growth reduction caused by the antibiotic in susceptible bacteria will be competitive. This suggests that a new spectrum of low-cost or nocost resistance mutations will be enriched in such conditions. In conclusion, this study shows that the very low antibiotic levels which are present in many natural environments or in certain body compartments during antibiotic treatment are relevant for the enrichment and maintenance of pre-existing resistant mutants as well as for the selection of de novo mutants.

Paper III Selection for a multidrug resistance plasmid by sublethal levels of antibiotics and heavy metals While paper II focused on the sub-MIC selection of chromosomal resistance mutations or genes, this work investigates the selection and maintenance of large multidrug resistance plasmids. These conjugative plasmids are in many cases responsible for the resistance in clinically isolated pathogenic bacteria, and they often confer resistance to a wide range of antimicrobial substances, such as antibiotics, biocides and heavy metals. This has implications for their maintenance and selection; since the different resistances are genetically linked, selection for one of the resistances will co-select for the others. This also means that there could be combination effects, where several different substances might have an additive or even synergistic selective effect on plasmid maintenance. In this paper we chose to study the selective maintenance of the large conjugative multidrug resistance plasmid pUUH239.2 isolated at the Uppsala University Hospital in 2005 during a large nosocomial outbreak of extendedspectrum β-lactamase (ESBL) producing Klebsiella pneumoniae and Escherichia coli. These types of resistance plasmids are common among Gramnegative ESBL producing bacteria, a serious problem in the clinic worldwide (Hawkey & Jones 2009; Pitout 2010; D'Andrea et al. 2013). Besides conferring resistance to β-lactams, aminoglycosides, tetracyclines, macrolides, sulfonamides and trimethoprim, it also carries resistance genes against the heavy metals silver, copper and arsenic. Such genetic linkage between anti56

biotic resistance genes and metal resistance genes is very common (Foster 1983; Ghosh et al. 2000; Stepanauskas et al. 2006; Baker-Austin et al. 2006; Stokes & Gillings 2011), and a consequence of this is that the presence of heavy metals indirectly can select for antibiotic resistance. The proportion of bacteria in a population carrying a certain conjugative plasmid is dependent on several parameters; the conjugation frequency, the loss rate of the plasmid and the selection coefficient. The selection coefficient is in turn dependent on the fitness cost of the plasmid as well as the potential benefit of carrying the plasmid, such as resistance to antibiotics or other toxins. Without the presence of selection, the carriage of the pUUH239.2 plasmid confers a fitness cost of around 4% (Sandegren et al. 2012). For maintenance of the plasmid in a bacterial population, this cost has to be balanced by an external selection pressure. In this study, we conducted competition experiments to determine the minimal concentrations of antibiotics and metals needed for plasmid selection. The results are similar to those of paper II for both antibiotics and heavy metals; levels far below the MIC are enough for enrichment of the plasmid, despite the associated fitness costs. Most impressive was the results from the arsenic experiments; the MSC is close to 140-fold lower than the MIC of the susceptible strain. There are many environments containing several antibacterial substances such as antibiotics and heavy metals at levels near or above the MSC (Stepanauskas et al. 2006; Olofsson et al. 2012; Manzetti & Ghisi 2014). Some environments become contaminated through the agricultural use of antibiotics and heavy metals (Sarmah et al. 2006; Hölzel et al. 2012), while others are polluted by therapeutic use of antibiotics, for example sewage treatment plants (Negreanu et al. 2012; Michael et al. 2013). Since complex mixtures of several substances are so common, it is important to study their combined selection pressure on resistant bacteria. Competition experiments using different combinations of antibiotics and heavy metals showed that the combined effect varies from synergistic to less than additive. However, the observed effect was always that when a compound is added, the MSC of the others were lowered. This means that the total selective pressure in a complex environment can be sufficient to select for resistance, even if the levels of the individual substances are below the MSC. This study further investigated the correlation between the fitness costs of resistance and the MSC. After transferring resistance genes from the pUUH239.2 plasmid to the bacterial chromosome, thereby eliminating the need for maintenance of the entire plasmid effectively lowering the fitness cost, we observed that the MSC decreased correspondingly. Such genetic events are common in nature, for example when mobile genetic elements transfer resistance cassettes from plasmids to the chromosome (Beyrouthy et al. 2014), or through compensatory mutations elsewhere in the genome (An57

dersson & D. Hughes 2010). This suggests that as the fitness costs of resistance genes approach zero, even trace levels of antibiotics or heavy metals might be enough to enrich them.

Paper IV Evolution of resistance at non-lethal (sub-MIC) levels of antibiotics The aim of this study was to investigate the spectrum of resistance mutations that arise during sub-MIC selection. When exposed to antibiotic levels above the MIC, resistant mutants can be enriched even if they carry high fitness costs since all competing bacteria die, but at concentrations far below the MIC only low-cost resistance mutations should arise in the population. It is possible that the spectrum of resistance mutations that is selected during these conditions is very different than the mutations found when selection happens at higher concentrations above MIC. To investigate this, a number of antibiotic resistant clones isolated after being cycled for 900 generation at sub-MIC concentrations of streptomycin and ciprofloxacin (see paper II) were whole genome sequenced, and all mutations were identified. Reconstructions of the strains with the candidate resistance mutations in an isogenic background were made to investigate which mutations or combination of mutations were responsible for the resistance. In the case of ciprofloxacin, the only relevant mutations found were the already well-known resistance mutations in the gyrA and marR genes (Marcusson et al. 2009). For streptomycin, however, the picture was more complex. All of the sequenced strains that showed high-level resistance to streptomycin (>128 µg/ml) were mutator strains and thus had a high number of mutations (>100 mutations/strain). Mutations frequently found in vitro conferring a high level of resistance to streptomycin are in the rpsL gene, encoding the ribosomal protein S12 (Ozaki et al. 1969); interestingly we did not find such mutations in our evolved strains. When comparing the different lineages we found a pattern of similarly mutated genes. Worth noting here is the gidB gene; all of the isolated mutants carry potential loss of function mutations in this gene. This is not surprising, as we had already found that this can give low-level resistance to aminoglycosides at a low fitness cost (paper I). Restoring the gidB gene lowered the resistance to near wild type levels in all mutant lineages, suggesting that this mutation was critical for the high level of resistance.

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Figure 15. High level of streptomycin resistance in Salmonella is possible through three different resistance mechanisms in synergy. Expression of the aminoglycoside adenyl transferase gene aadA lowers the concentration of active drug through chemical modification, mutations in gidB indirectly modifies the drug target to decrease binding, and mutations in the respiratory chain lowers the membrane potential, leading to a decrease in uptake of the drug.

We know from earlier work (paper I) that the cryptic resistance gene aadA can be involved in streptomycin resistance in Salmonella, and one of the mutants had acquired a mutation upstream of aadA that might increase expression levels. Deletion of the aadA gene in the mutant strains caused a dramatic loss of resistance in all lineages. We previously showed that the aadA gene in Salmonella is regulated through the stringent response, a system that increases the level of the global regulator ppGpp upon nutrient starvation (paper I). To investigate the role of ppGpp regulation, deletions were made of the ppGpp synthetase genes relA and spoT in the mutant background, and this lowered the resistance. Together these experiments show that the expression of AadA is essential for the high-level streptomycin resistance selected at sub-MIC concentrations, and that this expression is regulated through the stringent response. Another group of mutations observed in several of the clones were in genes involved in electron transport of the respiratory chain, such as the genes cyoB, encoding cytochrome o oxidase subunit I, and nuoG, encoding a subunit of NADH dehydrogenase. Similar mutations are common in aminoglycoside resistant SCVs, where they are believed to decrease antibiotic uptake by lowering the electrochemical potential over the inner membrane (Bryan & Kwan 1983). Other mutations that might affect membrane potential were identified in the metal transport proteins trkH, a potassium trans59

porter, and znuA, a component in the zinc uptake system. Reconstruction of these mutations revealed strong epistatic interactions between them, where some of them only had an effect on resistance levels if they were combined. Together with the ∆gidB mutation, a combination of the mutations in cyoB, nuoG, trkH and znuA confers a streptomycin resistance level of more than 1024 µg/ml, as high as the original isolated mutant. In conclusion, this study deepens our understanding of the mutational spectrum of resistance acquired during long-term exposure to subinhibitory concentrations of antibiotics. If low cost, high resistance mutations are available, such as gyrase mutations conferring resistance to ciprofloxacin, they will be enriched also at levels far below the MIC. If no such mutations are available, as in the case of streptomycin resistance in Salmonella, we observed how combinations of many mutations through three different resistance mechanisms synergistically confer a high level of resistance.

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Concluding remarks

“Ruin is the destination toward which all men rush, each pursuing his own best interest in a society that believes in the freedom of the commons. Freedom in a commons brings ruin to all.” – Garrett Hardin, “The Tragedy of the Commons”, 1968 (Hardin 1968)

Antibiotics are finite resources. Using an antibiotic will eventually lead to selection of resistant bacteria, which makes the antibiotic ineffective. They are also shared resources; once resistant bacteria have evolved they do not respect borders and spread rapidly, making antibiotic resistance a global problem. According to economics theory the “tragedy of the commons” occurs when it is tempting for individuals to exploit shared resources for their own gain, but in doing so they are going against the long-term interests of society by depleting the resource. The main reason why we have an increasing problem with antibiotic resistant bacteria today, is that this valuable common resource has been handled irresponsibly for many decades. This thesis demonstrates the problem with subinhibitory concentrations of antibiotics and heavy metals selecting resistant bacteria. We have studied the lower boundaries of the mutant selective window, using bacteria with different resistance mutations, different chromosomal resistance genes (paper II) as well as large a conjugative multidrug resistance plasmid (paper III). We have shown that levels of antibiotics far below the MIC are enough to enrich for resistance, and that the sub-MIC selective window can be remarkably wide. The minimal selective concentration is dependent on the fitness cost of the resistance mutation, and we found that for low cost resistance even trace levels of antibiotics are enough for selection. Despite this, even the costly multidrug resistance plasmids studied in paper III could be maintained at subinhibitory levels of antibiotics and heavy metals. Because the resistance genes are linked, combinations of antibiotics or heavy metals could together increase the selective pressure, and our results clearly show that there can be additive or even synergistic effects of such combinations. In environments contaminated with a complex mix of pollutants, this effect could be significant for selection of bacteria carrying multidrug resistance plasmids. Additionally, in paper II we have demonstrated that sub-MIC levels of antibiotics can be enough to select de novo resistant mutants. In paper IV we expanded the study of these de novo mutants, and observed that re-

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sistance enriched at sub-MIC concentrations can have a different mutational spectrum than mutants selected above MIC. Environments containing selective concentrations of antimicrobials are present in wastewater treatment plants, large areas of polluted farmland as well as rivers and lakes polluted by pharmaceutical industry waste. The main sources of these pollutions are the careless use of antibiotics in agriculture together with the overuse of antibiotics in the clinic in many parts of the world. The use of subinhibitory levels of antibiotics in animal feed is inexcusable, since it is not motivated by concern for animal welfare, but rather for increased profits on meat production. There is an increasing amount of evidence suggesting that agricultural use of antibiotics is the critical step in mobilization and transfer of antibiotic resistance genes from environmental bacteria to human pathogens. The only long-term solution to this problem is a global ban on the use of antibiotics in animal feed and in aquaculture. Until this is realized, we need to investigate other options to decrease utilization of antibiotics for food production. It has been suggested to introduce a fee for the veterinary use of antibiotics, which could be easier to administer than a total ban (Hollis & Ahmed 2013); if the cost of antibiotics usage would be higher than the value of the increased growth, then this practice would no longer be financially viable. Besides the agricultural use, the prescription of antibiotics must be regulated better; too much antibiotics are prescribed for viral infections, or to satisfy patients after a doctor’s visit (Laxminarayan et al. 2013). It is also important to develop better tools for the diagnosis of infections, so that the appropriate antibiotic could be prescribed and unnecessary use of broadspectrum drugs avoided. Further, collecting and purifying the urine from patients during antibiotic treatment could reduce the release of antibiotics from hospitals, and consequently in the environment. In order to take these measures we need to change the public opinion about use of antibiotics by educating about the issues with resistant bacteria. In general, people do not value antibiotics high enough; they have forgotten the time before we had them, and how deadly bacterial infections used to be. An increased public awareness about antibiotics and antibiotic resistance could lead to stricter laws regulating the use of antibiotics. Historically, there have been similar cases; in 1962 the book “Silent Spring” was released, raising the public awareness of the widespread use and misuse of the pesticide DDT. The book caused a strong pressure on politicians, and the use of DDT was drastically decreased in the US before it was completely banned ten years later. The future need of new antibiotics is inevitable, but developing new drugs is a long and expensive process. While pharmaceutical companies lack the financial incentives to develop new antibiotics, the academic sector needs financial support to carry out the research. Organizations such as the EU or 62

the WHO might be the only ones with the financial strength to fund such projects. When we manage to develop new antibiotics, we need to learn from our mistakes and use them more responsible than we have done so far.

63

Svensk sammanfattning

”Antibiotika är ett underverk. Ett underverk som gjort att många av er som läser just detta kan läsa just detta. Ett mirakel vi förstör i en allt snabbare takt.” - Björn Olsen, Professor i infektionssjukdomar, Uppsala universitet

Antibiotika är en ändlig resurs. Användning av antibiotika kommer nästan alltid med tiden att leda till att resistenta bakterier uppstår, vilket gör behandlingarna verkningslösa. Antibiotika är dessutom en gemensam resurs. När resistenta bakterier väl har utvecklats respekterar de inga gränser utan sprider sig snabbt, vilket gör antibiotikaresistens till ett globalt problem. Den främsta anledningen till att vi har ett växande problem med antibiotikaresistenta bakterier i dag är att denna värdefulla gemensamma resurs har hanterats oansvarigt under flera decennier. Det omfattande bruket och missbruket av antibiotika inom sjukvården samt jordbruket har orsakat en anrikning av resistenta bakterier som nu allvarligt hotar vår förmåga att behandla bakteriella infektioner. Tungmetaller och antibakteriella ämnen kan orsaka antibiotikaresistens Detta problem förvärras ytterligare av att det finns andra ämnen än antibiotika som kan orsaka antibiotikaresistens. En grupp sådana ämnen är tungmetaller, exempelvis koppar, silver, kvicksilver, arsenik och bly. Tungmetaller är mycket giftiga för bakterier och många andra organismer, och därför har de bland annat använts flitigt som tillskott i djurfoder, till att impregnera trä samt i bottenfärger på båtar. Bakterier kan bli resistenta mot tungmetaller, precis som mot antibiotika, och dessa resistenser är ofta tätt sammankopplade. Det beror på att bakterier kan byta resistensgener med varandra, och olika gener som ger resistens mot olika giftiga ämnen sitter ofta tätt intill varandra som multiresistens-kassetter i bakteriernas DNA. Detta innebär att om man utsätter bakterier för tungmetaller så anrikar man ofta även bakterier med antibiotikaresistens, och vice versa. Även andra antibakteriella ämnen, exempelvis triclosan, ett ämne som ibland tillsätts i tandkrämer och diskmedel, kan ha liknande effekter. Även låga nivåer av antibiotika och tungmetaller kan orsaka resistens Det har varit känt sedan länge att höga koncentrationer av antibiotika kan anrika resistenta bakterier. Däremot vet vi betydligt mindre om den nedre gränsen för när antibiotika kan orsaka resistens. I denna avhandling har vi 64

undersökt vilken roll låga koncentrationer av antibiotika och tungmetaller spelar för utveckling av antibiotikaresistens. Våra försök visar att även mycket låga nivåer av antibiotika och tungmetaller kan anrika resistenta bakterier, och i vissa fall är dessa nivåer flera hundra gånger lägre än den lägsta koncentrationen som hindrar tillväxten av känsliga bakterier. Även bakterier som ursprungligen var helt känsliga kunde med tiden utveckla hög resistens mot antibiotika, trots att de enbart utsatts för mycket låga nivåer. Vi kunde även observera att blandningar av små mängder antibiotika och tungmetaller kan orsaka en ökning av andelen multiresistenta bakterier, även om koncentrationen av varje ämne var och en för sig inte var tillräckligt hög för att orsaka anrikning. Denna ”cocktail-effekt” skulle kunna ha stora konsekvenser för uppkomst av resistens, eftersom miljöer som avloppsvatten ofta innehåller en blandning av låga nivåer av många olika kemikalier och tungmetaller. Har resistensen alltid en kostnad? Bakterier betalar nästan alltid ett pris för sin resistens. Antibiotikaresistenta bakterier växer generellt sett lite långsammare än sina känsliga släktingar, och ibland är de även sämre på att orsaka sjukdomar. I det här avseendet är just låga koncentrationer av antibiotika problematiska, eftersom vi kunde se att dessa i första hand anrikar bakterier som trots sin höga resistens växer normalt. Så länge antibiotikaresistensen är kostsam för bakterierna så finns det en chans att de skulle konkurreras ut och försvinna om vi slutade använda antibiotika, men resistenta bakterier som växer normalt kommer sannolikt att finnas kvar för alltid. Varför har vi ett problem med antibiotikaresistens idag? Våra resultat visar att antibiotikaresistenta bakterier kan uppstå och anrikas i miljöer förorenade med låga nivåer av antibiotika och tungmetaller. Exempel på sådana miljöer är avloppsreningsverk, förorenad jordbruksmark samt floder och sjöar som förorenats av utsläpp från läkemedelsindustrin. De viktigaste källorna till dessa utsläpp är oansvarig användning av antibiotika i jordbruket tillsammans med överdriven utskrivning av antibiotika. Den största delen av den antibiotika som produceras globalt används inte till att behandla sjuka människor, utan som tillskott i djurfoder inom köttproduktion. Detta är förbjudet inom EU, men i länder som USA och Kina används ofta låga halter av antibiotika i djurfoder under lång tid för att få djuren att växa snabbare. Detta görs inte av omsorg om djurens välbefinnande, utan enbart för att öka vinsterna vid köttproduktion. När gödsel från djuren sedan sprids på åkrarna hamnar både antibiotika och resistenta bakterier från djurens tarmflora i jorden. Även produktionen av odlad fisk medför förbrukning av antibiotika. Ungefär hälften av den fisk och de skaldjur som konsumeras globalt är odlade. Sydostasien och Kina har stora odlingar av hajmal (pangasius) och jätteräkor, och Chile producerar stora mängder odlad lax. Inom 65

både djuruppfödning och fiskodling används antibiotika för att kunna hålla många djur tätt tillsammans på små ytor, eftersom dessa levnadsförhållanden ökar risken för smittspridning dramatiskt. Även om detta håller ner priset på kött och fisk så betalar vi ett mycket högt pris. Det finns allt mer bevis som tyder på att just jordbrukets användning av antibiotika är en av de viktigaste orsakerna till dagens problem med antibiotikaresistens. Problemet är inte att maten innehåller antibiotikarester, utan att den kan föra med sig resistenta bakterier från djuren. Vad kan vi göra för att motverka problemet? Den enda långsiktiga lösningen på detta problem är ett globalt förbud mot användning av antibiotika i djurfoder, samt en minskning av onödig antibiotikautskrivning. Om vi inte lyckas lösa problemet med antibiotikaresistens riskerar mänskligheten att hamna i samma situation som före antibiotikans tidsålder. För bara hundra år sedan var medellivslängden betydligt kortare. Många dog av lunginflammationer och blodförgiftningar innan de nådde vuxen ålder, och till och med små sår kunde vara livsfarliga. Idag skulle vi få ytterligare problem, i och med att många patienter på sjukhus har nedsatt immunförsvar. Det kan vara för tidigt födda barn eller patienter som genomgår cancerbehandlingar eller transplantationer. Dessa patienter är ofta infektionskänsliga och helt beroende av att vi har fungerande antibiotika. Den avancerade sjukvård som vi har idag skulle helt enkelt inte fungera utan antibiotika. Det kan ta mycket lång tid innan vi lyckas utveckla nya antibiotika, så det är viktigt att vi använder dem vi har på ett ansvarsfullt sätt.

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Acknowledgements

First of all I would like to thank my supervisor Dan for inspiring me and introducing me to the wonderful world of bacterial genetics. Thanks for letting me work independently and for always believing in me, even when I get strange ideas and want to design some weird new genetic constructs. It has been great working for you. I would not have gotten this far without the help of Linus, thank you for always listening to my questions and thoughts whenever I stop by your office for a cup of coffee and some good advice. I would also like to thank Diarmaid for his insightful input on my projects, and Göte, my examiner. Staffan, thanks for your feedback on my project during my half-time seminar, and Magnus for interesting discussions about CRISPR and SynBio. Thanks to my collegues: Marlen, we have had a lot of fun though the years, whether it’s partying at Värmlands, hiking in the Grand Canyon or exploring hidden gardens in Spanish towns. Marius, I always enjoy our discussions about deep and not so deep matters, from character development in Game of Thrones to international politics and history. Erik L, it has been great working with you in iGEM, in the DA lab and in the gym. I like our conversations about synthetic biology and about life in general. Jessica, thanks for the good late evening talks over some snacks in the lab, and for sharing office with me while writing my thesis. I would like to thank Franzi for fun parties; Eva, for your energy and work in IPhA; Doug, for all the music videos and cat pictures; Jon, for interesting discussions in the lab and good times in the States; Hervé, for being a great lab bench neighbor, always providing good advice and cynical humor. Thanks to Lisa T, for teaching me about the world of Marvel and Game of Thrones; Michael, for exploring San Francisco and Las Vegas with me; Hava, for interesting conversations; Cao Sha, for co-authoring my first paper; Ulrika, for keeping the lab nice and orderly; Karin, for all your help in the lab; Jocke, for good advice on bacterial genetics; Anna K, for fun talks about plants and weird fishes; Lisa A, for teaching me about copper and arsenic; Sohaib, for bringing up important ethical issues about antimicrobial peptides, and Gerrit, for the discussions about optimizing competition experiments. To the DA alumni Anna Z, Maria, Chris, Peter and Song, you made this group an awesome place to 67

start working in! Sanna, you inspired me when I first started in the lab, and you still do. To the new PhD students in the corridor, Linnéa and Fredrika, you have made a great start, and I am sure you will go far! A big thanks to the students that helped me with my projects during the years, it was fun working with all of you! Carolina, much of the work in this thesis is based on your hard work cycling all those lineages of bacteria. Tomas, the fluorescent strains you constructed are still cornerstones in our lab. Christoffer, your work on the experiments in paper III was excellent, and the flip-plasmid you constructed has been very useful. Amanda, your persistence in working with those bacteria that did not want to cooperate was impressive, and I really enjoyed our games of Quizkampen. Micke S, it was fun designing primers with you and trying to tame the replication origin of the pUUH plasmid. Robin, great work on the CRISPR project! There is a paper in Nature Biotechnology now that shows the same thing, but we both know that we did it first! Thanks to my co-authors outside of the D7:3 corridor. Otto Berg, Eva Tano and the padlock people: Anja M, Jenny, David H and Mats Nilsson, thanks for good collaborations. To the co-authors of the SynBio Manual, Tony and Josefine, it has been fun writing a book and teaching the world about synthetic biology and chromoproteins. I would also like to thank some other people at BMC: Mirthe, for being a wonderful friend and for all your help and support. I have really appreciated our talks about life and science through the years; Patrik, for the coffee break company and for cooking delicious dinners together with Hanna E. Thanks to Cecilia, for all the fun boardgaming evenings; Julia F, for many great talks about movies, science and life in general; Petter H for teaching me the magic of mutagenesis; Lars A, for beers at Värmlands and introducing me to the world of gems; Mina, for the beer and teaching together with me; Else, for the coffee breaks and the tasty stroopwafels. All the iGEM people, it has been so much fun designing and constructing engineered bacteria with you! Lei, thanks for starting the first iGEM team on BMC together with Antonio and Lidaw. Tomas, Sibel, Kalle, Laura, Hamid, Cherno and Johanna, thanks for the good times in the iGEM lab, at Snerikes, in Amsterdam and in Boston. Sabri, for late night cloning and talk about pepper plants, and Arvid, Olle, Caroline W, Emy, Katarina, Joel, Julia B, Hampus and Anders E, for great fun during iGEM 2012! A big thanks to Daniel C for interesting talks about synthetic biology and for providing me with the BioBrick plasmids. I would also like to thank Anders V for supervising the iGEM team, and Micke N, it was fun instructing iGEM with you! 68

To my friends outside of BMC: Christian & Anna, Gustav & Hanna and Per L, thank you for dragging me away from the lab bench every now and then, whether it’s for a weekend in the forest outside Köping or a week in Miami, I am happy to have such good friends. Anders, Caroline, Ville, Linus, Carolin, Erika, Robin, Elin, and Birgitta, thanks for the fantastic Urf05 reunions, I hope to see you all again soon! Daniel N, thanks for hosting nice visits in Stockholm, and Per E, for fun adventures whether it’s in Linköping, London or Lordaeron. Ola, thanks for encouraging me to do a PhD, and for your advice on life in academia. I would like to thank my parents, my father Jan-Olof and my mother Gudrun, for all your support. My sister Emelie, thank you for awesome dinners and for encouraging me to move to Uppsala, it is wonderful to live close to you once again. I would also like to thank Stefan, for boat trips and fishing, and Samuel, for being such a nice nephew. And finally, Pikkei, thank you for being who you are.

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Acta Universitatis Upsaliensis Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine 1053 Editor: The Dean of the Faculty of Medicine A doctoral dissertation from the Faculty of Medicine, Uppsala University, is usually a summary of a number of papers. A few copies of the complete dissertation are kept at major Swedish research libraries, while the summary alone is distributed internationally through the series Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine. (Prior to January, 2005, the series was published under the title “Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine”.)

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