Microbiology, Metagenomics and Bioinformatics

Johan Bengtsson-Palme, University of Gothenburg

Browsing Posts tagged Environment

After a long wait (1) Sara Lundström’s paper establishing minimal selective concentrations (MSCs) for the antibiotic tetracycline in complex microbial communities (2), of which I am a co-author, has gone online. Personally, I think this paper is among the finest work I have been involved in; a lot of good science have gone into this publication. Risk assessment and management of antibiotics pollution is in great need of scientific data to underpin mitigation efforts (3). This paper describes a method to determine the minimal selective concentrations of antibiotics, and investigates different endpoints for measuring those MSCs. The method involves a testing system highly relevant for aquatic communities, in which bacteria are allowed to form biofilms in aquaria under controlled antibiotic exposure. Using the system, we find that 1 μg/L tetracycline selects for the resistance genes tetA and tetG, while 10 μg/L tetracycline is required to detect changes of phenotypic resistance. In short, the different endpoints studied (and their corresponding MSCs) were:

  • CFU counts on R2A plates with 20 μg/mL tetracycline – MSC = 10 μg/L
  • MIC range – MSC ~ 10-100 μg/L
  • PICT, leucine uptake after short-term TC challenge – MSC ~ 100 μg/L
  • Increased resistance gene abundances, metagenomics – MSC range: 0.1-10 μg/L
  • Increased resistance gene abundances, qPCR (tetA and tetG) – MSC ≤ 1 μg/L
  • Changes to taxonomic diversity – no significant changes detected
  • Changes to taxonomic community composition – MSC ~ 1-10 μg/L

This study confirms that the estimated PNECs we reported recently (4) correspond well to experimentally determined MSCs, at least for tetracycline. Importantly, the selective concentrations we report for tetracycline overlap with those that have been reported in sewage treatment plants (5). We also see that tetracycline not only selects for tetracycline resistance genes, but also resistance genes against other classes of antibiotics, including sulfonamides, beta-lactams and aminoglycosides. Finally, the approach we describe can be used for improved in risk assessment for (also other) antibiotics, and to refine the emission limits we suggested in a recent paper based on theoretical calculations (4).

References and notes

  1. Okay, seriously: how can a journal’s production team return the proofs for a paper within 24 hours of acceptance, and then wait literally five weeks before putting the final proofs online? Nothing against STOTEN, but I honestly wonder what was going on beyond the scenes here.
  2. Lundström SV, Östman M, Bengtsson-Palme J, Rutgersson C, Thoudal M, Sircar T, Blanck H, Eriksson KM, Tysklind M, Flach C-F, Larsson DGJ: Minimal selective concentrations of tetracycline in complex aquatic bacterial biofilms. Science of the Total Environment, 553, 587–595 (2016). doi: 10.1016/j.scitotenv.2016.02.103 [Paper link]
  3. Ågerstrand M, Berg C, Björlenius B, Breitholtz M, Brunstrom B, Fick J, Gunnarsson L, Larsson DGJ, Sumpter JP, Tysklind M, Rudén C: Improving environmental risk assessment of human pharmaceuticals. Environmental Science and Technology (2015). doi:10.1021/acs.est.5b00302
  4. Bengtsson-Palme J, Larsson DGJ: Concentrations of antibiotics predicted to select for resistant bacteria: Proposed limits for environmental regulation. Environment International, 86, 140-149 (2016). doi: 10.1016/j.envint.2015.10.015
  5. Michael I, Rizzo L, McArdell CS, Manaia CM, Merlin C, Schwartz T, Dagot C, Fatta-Kassinos D: Urban wastewater treatment plants as hotspots for the release of antibiotics in the environment: a review. Water Research, 47, 957–995 (2013). doi:10.1016/j.watres.2012.11.027

Yesterday was an intensive day for typesetters apparently, since they put two of my papers online on the same day. This second paper was published in Environment International, and focuses on predicting minimal selective concentrations for all antibiotics present in the EUCAST database (1).

Today (well, up until yesterday at least), we have virtually no knowledge of which environmental concentrations that can exert a selection pressure for antibiotic resistant bacteria. However, experimentally determining minimal selective concentrations (MSCs) in complex ecosystems would involve immense efforts if done for all antibiotics. Therefore, efforts to theoretically determine MSCs for different antibiotics have been suggested (2,3). In this paper we therefore estimate upper boundaries for selective concentrations for all antibiotics in the EUCAST database, based on the assumption that selective concentrations a priori must be lower than those completely inhibiting growth. Data on Minimal Inhibitory Concentrations (MICs) were obtained for 122 antibiotics and antibiotics combinations, the lowest observed MICs were identified for each of those across all tested species, and to compensate for limited species coverage, we adjusted the lowest MICs for the number of tested species. We finally assessed Predicted No Effect Concentrations (PNECs) for resistance selection using an assessment factor of 10 to account for the differences between MICs and MSCs. Since we found that the link between taxonomic similarity between species and lowest MIC was weak, we have not compensated for the taxonomic diversity that each antibiotic was tested against – only for limited number of species tested. In most cases, our PNECs for selection of resistance were below available PNECs for ecotoxicological effects retrieved from FASS. Also, concentrations predicted to be selective have, for some antibiotics, been detected in regular sewage treatment plants (4), and are greatly exceeded in environments polluted by pharmaceutical pollution (5-7), often with drastic consequences in terms of resistance gene enrichments (8-10). This is a central issue since in principle a transfer event of a novel resistance determinant from an environmental bacteria to an (opportunistic) human pathogen only need to occur once to become a clinical problem (11). Once established, the gene could then spread through human activities, such as trade and travel (7,13). Importantly, this paper:

The paper is available under open access here. We hope, and believe, that the data will be of great use in environmental risk assessments, in efforts by industries, regulatory agencies or purchasers of medicines to define acceptable environmental emissions of antibiotics, in the implementation of environmental monitoring programs, for directing mitigations, and for prioritizing future studies on environmental antibiotic resistance.

References:

  1. Bengtsson-Palme J, Larsson DGJ: Concentrations of antibiotics predicted to select for resistant bacteria: Proposed limits for environmental regulation. Environment International, 86, 140-149 (2016). doi: 10.1016/j.envint.2015.10.015 [Paper link]
  2. Ågerstrand M, Berg C, Björlenius B, Breitholtz M, Brunstrom B, Fick J, Gunnarsson L, Larsson DGJ, Sumpter JP, Tysklind M, Rudén C: Improving environmental risk assessment of human pharmaceuticals. Environmental Science and Technology (2015). doi:10.1021/acs.est.5b00302
  3. Tello A, Austin B, Telfer TC: Selective pressure of antibiotic pollution on bacteria of importance to public health. Environmental Health Perspectives, 120, 1100–1106 (2012). doi:10.1289/ehp.1104650
  4. Michael I, Rizzo L, McArdell CS, Manaia CM, Merlin C, Schwartz T, Dagot C, Fatta-Kassinos D: Urban wastewater treatment plants as hotspots for the release of antibiotics in the environment: a review. Water Research, 47, 957–995 (2013). doi:10.1016/j.watres.2012.11.027
  5. Larsson DGJ, de Pedro C, Paxeus N: Effluent from drug manufactures contains extremely high levels of pharmaceuticals. Journal of Hazardous Materials, 148, 751–755 (2007). doi:10.1016/j.jhazmat.2007.07.008
  6. Fick J, Söderström H, Lindberg RH, Phan C, Tysklind M, Larsson DGJ: Contamination of surface, ground, and drinking water from pharmaceutical production. Environmental Toxicology and Chemistry, 28, 2522–2527 (2009). doi:10.1897/09-073.1
  7. Larsson DGJ: Pollution from drug manufacturing: review and perspectives. Philosophical Transactions of the Royal Society London, Series B Biological Sciences, 369 (2014). doi:10.1098/rstb.2013.0571
  8. Bengtsson-Palme J, Boulund F, Fick J, Kristiansson E, Larsson DGJ: Shotgun metagenomics reveals a wide array of antibiotic resistance genes and mobile elements in a polluted lake in India. Frontiers in Microbiology, Volume 5, Issue 648 (2014). doi: 10.3389/fmicb.2014.00648 [Paper link]
  9. Kristiansson E, Fick J, Janzon A, Grabic R, Rutgersson C, Weijdegård B, Söderström H, Larsson DGJ: Pyrosequencing of antibiotic-contaminated river sediments reveals high levels of resistance and gene transfer elements. PLoS ONE, Volume 6, e17038 (2011). doi:10.1371/journal.pone.0017038.
  10. Marathe NP, Regina VR, Walujkar SA, Charan SS, Moore ERB, Larsson DGJ, Shouche YS: A Treatment Plant Receiving Waste Water from Multiple Bulk Drug Manufacturers Is a Reservoir for Highly Multi-Drug Resistant Integron-Bearing Bacteria. PLoS ONE, Volume 8, e77310 (2013). doi:10.1371/journal.pone.0077310
  11. Bengtsson-Palme J, Larsson DGJAntibiotic resistance genes in the environment: prioritizing risks. Nature Reviews Microbiology, 13, 369 (2015). doi: 10.1038/nrmicro3399-c1 [Paper link]
  12. Bengtsson-Palme J, Angelin M, Huss M, Kjellqvist S, Kristiansson E, Palmgren H, Larsson DGJ, Johansson A: The human gut microbiome as a transporter of antibiotic resistance genes between continents. Antimicrobial Agents and Chemotherapy, 59, 10, 6551-6560 (2015). doi: 10.1128/AAC.00933-15 [Paper link]

Yesterday, a paper I co-authored with my colleagues Chandan Pal, Erik Kristiansson and Joakim Larsson on the co-occurences of resistance genes against antibiotics, biocides and metals in bacterial genomes and plasmids became published in BMC Genomics. In this paper (1) we utilize the publicly available, fully sequenced, genomes and plasmids in GenBank to investigate the co-occurence network of resistance genes, to better understand risks for co-selection for resistance against different types of compounds. In short, the findings of the paper are that:

  • ARGs are associated with BMRG-carrying bacteria and the co-selection potential of biocides and metals is specific towards certain antibiotics
  • Clinically important genera host the largest numbers of ARGs and BMRGs and those also have the highest co-selection potential
  • Bacteria isolated from human and domestic animal origins have the highest co-selection potential
  • Plasmids with co-selection potential tend to be conjugative and carry toxin-antitoxin systems
  • Mercury and QACs are potential co-selectors of ARGs on plasmids, however BMRGs are common on chromosomes and could still have indirect co-selection potential
  • 14 percent of bacteria and more than 70% of the plasmids completely lacked resistance genes

This analysis was possible thanks to the BacMet database of antibacterial biocide and metal resistance genes, published about two years ago (2). The visualization of the plasmid co-occurence network we ended up with can be seen below. Note the strong connection between the mercury resistance mer operon and the antibiotic resistance genes to the right.

On a side note, it is interesting to note that the underrepresentation of detoxification systems in marine environments we noted last year (3) still seems to hold for genomes (and particularly plasmids), supporting the genome streamlining hypothesis (4).

References:

  1. Pal C, Bengtsson-Palme J, Kristiansson E, Larsson DGJ: Co-occurrence of resistance genes to antibiotics, biocides and metals reveals novel insights into their co-selection potential. BMC Genomics, 16, 964 (2015). doi: 10.1186/s12864-015-2153-5 [Paper link]
  2. Pal C, Bengtsson-Palme J, Rensing C, Kristiansson E, Larsson DGJ: BacMet: Antibacterial Biocide and Metal Resistance Genes Database. Nucleic Acids Research, 42, D1, D737-D743 (2014). doi: 10.1093/nar/gkt1252 [Paper link]
  3. Bengtsson-Palme J, Alm Rosenblad M, Molin M, Blomberg A: Metagenomics reveals that detoxification systems are underrepresented in marine bacterial communities. BMC Genomics, 15, 749 (2014). doi: 10.1186/1471-2164-15-749 [Paper link]
  4. Giovannoni SJ, Cameron TJ, Temperton B: Implications of streamlining theory for microbial ecology. ISME Journal, 8, 1553-1565 (2014).

I am very happy to announce that our paper on the metagenomes of periphyton communities (1) have been accepted in Frontiers in Microbiology (Aquatic Microbiology section). This project has been one of my longest running, as it started as my master thesis in 2010 and has gone through several metamorphoses before hitting its final form.

Briefly, our main findings are that:

  1. Periphyton communities harbor an extraordinary diversity of organisms, including viruses, bacteria, algae, fungi, protozoans and metazoans
  2. Bacteria are by far the most abundant
  3. We find functional indicators of the biofilm form of life in periphyton involve genes coding for enzymes that catalyze the production and degradation of extracellular polymeric substances
  4. Genes encoding enzymes that participate in anaerobic pathways are found in the biofilms suggesting that anaerobic or low-oxygen micro-zones within the biofilms exist

Most of this work has been carried out by my colleague Kemal Sanli, who have been doing a wonderful job pulling this together, with the help of Henrik Nilsson and Martin Eriksson. It also deserves to be noted that this work was the starting point for the Metaxa software (2,3), which recently reached version 2.1.1.

References

  1. Sanli K, Bengtsson-Palme J, Nilsson RH, Kristiansson E, Alm Rosenblad M, Blanck H, Eriksson KM: Metagenomic sequencing of marine periphyton: Taxonomic and functional insights into biofilm communities. Frontiers in Microbiology, 6, 1192 (2015). doi: 10.3389/fmicb.2015.01192 [Paper link]
  2. Bengtsson J, Eriksson KM, Hartmann M, Wang Z, Shenoy BD, Grelet G, Abarenkov K, Petri A, Alm Rosenblad M, Nilsson RH: Metaxa: A software tool for automated detection and discrimination among ribosomal small subunit (12S/16S/18S) sequences of archaea, bacteria, eukaryotes, mitochondria, and chloroplasts in metagenomes and environmental sequencing datasets. Antonie van Leeuwenhoek, 100, 3, 471-475 (2011). doi:10.1007/s10482-011-9598-6. [Paper link]
  3. Bengtsson-Palme J, Hartmann M, Eriksson KM, Pal C, Thorell K, Larsson DGJ, Nilsson RH: Metaxa2: Improved identification and taxonomic classification of small and large subunit rRNA in metagenomic data. Molecular Ecology Resources, 15, 6, 1403–1414 (2015). doi: 10.1111/1755-0998.12399 [Paper link]

I have had the pleasure to be chosen as a speaker for next week’s (ten days from now) Swedish Bioinformatics Workshop. My talk is entitled “Turn up the signal – wipe out the noise: Gaining insights into bacterial community functions using metagenomic data“, and will largely deal with the same questions as my talk on EDAR3 in May this year. As then, the talk will highlight the some particular pitfalls related to interpretation of data, and exemplify how flawed analysis practices can result in misleading conclusions regarding community function, and use examples from our studies of environments subjected to pharmaceutical pollution in India, the effect of travel on the human resistome, and modern municipal wastewater treatment processes.

The talk will take place on Thursday, September 24, 2015 at 16:30. The full program for the conference can be found here. And also, if you want a sneak peak of the talk, you can drop by on Friday 13.00 at Chemistry and Molecular Biology, where I will give a seminar on the same topic in the Monthly Bioinformatic Practical Meetings series.

Late last year, an opinion paper by José Martínez, Teresa Coque and Fernando Baquero was published in Nature Reviews Microbiology (1). In this paper, the authors present a system – resistance readiness conditions (RESCon) – for ranking the risks associated with the detection of antibiotic resistance genes. They also outline the obstacles associated with determining risks presented by antibiotic resistance genes in environmental microbial communities in terms of their potential to transfer to human pathogens. Generally, I am very positive about this paper, which I think is a must-read for anyone who works with antibiotic resistance genes in metagenomes, regardless of it they stem from the human gut or the external environment.

There is, however, one very important aspect that struck me and many other members of our research group as curious: the proposed system assign antibiotic resistance genes already present on mobile genetic elements in human pathogens to the highest risk category (RESCon 1), while resistance genes encoding novel resistance mechanisms not yet been found on mobile elements in a pathogen are considered to be part of lower risk categories. We believe that this system will overestimate the risks associated with well-known resistance factors that are already circulating among human pathogens and under-appreciate the potentially disastrous consequences that the transfer of previously unknown resistance determinants from the environmental resistome could have (exemplified by the rapid clinical spread of the NDM-1 metallo-beta-lactamase gene (2,3)).

With this in mind me and Joakim Larsson wrote a response letter to Nature Reviews Microbiology that went online last monday (4), together with the authors’ reply to us (5). (I strongly suggest that you read the entire original paper (1) before you read the reply (5) to our response letter (4), since Martinez et al. changes the scope slightly from the original paper in their response letter, and these clarifications may (or may not) have been in response to our arguments.)

In our response, we also stress that the abundances of resistance genes, and not only their presence, should be accounted for when estimating risks (although that last point might have been slightly obscured due to the very low word limit). In other words, we think that identifying environmental hotspots for antibiotic resistance genes, where novel resistance genes could be selected for (6,7,8), is of great importance for mitigating public health risks related to environmental antibiotic resistance. Please read our full thoughts on the matter in Nature Reviews Microbiology.

Similar issues will be touched upon in my talk at the EDAR2015 conference later in May. Hope to see you there!

References

  1. Martinez JL, Coque TM, Baquero F: What is a resistance gene? Ranking risk in resistomes. Nat Rev Microbiol 2015, 13:116–123.
  2. Kumarasamy KK, et al.: Emergence of a new antibiotic resistance mechanism in India, Pakistan, and the UK: a molecular, biological, and epidemiological study. Lancet Infect Dis 2010, 10:597–602.
  3. Walsh TR, Weeks J, Livermore DM, Toleman MA: Dissemination of NDM‐1 positive bacteria in the New Delhi environment and its implications for human health: an environmental point prevalence study. Lancet Infect Dis 2011, 11:355–362.
  4. Bengtsson-Palme J, Larsson DGJ: Antibiotic resistance genes in the environment: prioritizing risks. Nat Rev Microbiol 2015, Advance online publication. doi:10.1038/nrmicro3399‐c1
  5. Martinez JL, Coque TM, Baquero F: Prioritizing risks of antibiotic resistance genes in all metagenomes. Nat Rev Microbiol 2015, Advance online publication. doi:10.1038/nrmicro3399‐c2
  6. Kristiansson E, et al.: Pyrosequencing of antibiotic‐contaminated river sediments reveals high levels of resistance and gene transfer elements. PLoS ONE 2011, 6:e17038.
  7. Bengtsson‐Palme J, Boulund F, Fick J, Kristiansson E, Larsson DGJ: Shotgun metagenomics reveals a wide array of antibiotic resistance genes and mobile elements in a polluted lake in India. Front Microbiol 2014, 5:648.
  8. Marathe NP, et al.: A treatment plant receiving waste water from multiple bulk drug manufacturers is a reservoir for highly multi‐drug resistant integron‐bearing bacteria. PLoS ONE 2013, 8:e77310.

I will be giving a talk at the Third International symposium on the environmental dimension of antibiotic resistance (EDAR2015) next month (five weeks from now. The talk is entitled “Turn up the signal – wipe out the noise: Gaining insights into antibiotic resistance of bacterial communities using metagenomic data“, and will deal with handling of metagenomic data in antibiotic resistance gene research. The talk will highlight the some particular pitfalls related to interpretation of data, and exemplify how flawed analysis practices can result in misleading conclusions regarding antibiotic resistance risks. I will particularly address how taxonomic composition influences the frequencies of resistance genes, the importance of knowledge of the functions of the genes in the databases used, and how normalization strategies influence the results. Furthermore, we will show how the context of resistance genes can allow inference of their potential to spread to human pathogens from environmental or commensal bacteria. All these aspects will be exemplified by data from our studies of environments subjected to pharmaceutical pollution in India, the effect of travel on the human resistome, and modern municipal wastewater treatment processes.

The talk will take place on Monday, May 18, 2015 at 13:20. The full scientific program for the conference can be found here. Registration for the conference is still possible, although not for the early-bird price. I look forward to see a lot of the people who will attend the conference, and hopefully also you!

It is nice to see that Indian media has picked up the story about antibiotic resistance genes in the heavily polluted Kazipally lake. In this case, it is the Deccan Chronicle who have been reporting on our findings and briefly interviewed Prof. Joakim Larsson about the study. The issue of pharmaceutical pollution of the environment in drug-producing countries is still rather under-reported and public perception of the problem might be rather low. Therefore, it makes me happy to see an Indian newspaper reporting on the issue. The scientific publication referred to can be found here.

A couple of days ago a paper was published in Environmental Sciences Europe summarizing the EU report on effect-based tools for use in toxicology in the aquatic environment I have been involved in (1). This report was officially published last spring (2), and can be found here, with the annex available on the European Commission document website. My contribution to the paper was, as with the report, in the genomics and metagenomics section. The paper briefly presents modern bioassays, biomarkers and ecological methods that can be used for aquatic monitoring of the environment.

References:

  1. Wernersson A-S, Carere M, Maggi C, Tusil P, Soldan P, James A, Sanchez W, Dulio V, Broeg K, Reifferscheid G, Buchinger S, Maas H, Van Der Grinten E, O’Toole S, Ausili A, Manfra L, Marziali L, Polesello S, Lacchetti I, Mancini L, Lilja K, Linderoth M, Lundeberg T, Fjällborg B, Porsbring T, Larsson DGJ, Bengtsson-Palme J, Förlin L, Kienle C, Kunz P, Vermeirssen E, Werner I, Robinson CD, Lyons B, Katsiadaki I, Whalley C, den Haan K, Messiaen M, Clayton H, Lettieri T, Negrão Carvalho R, Gawlik BM, Hollert H, Di Paolo C, Brack W. Kammann U, Kase R: The European technical report on aquatic effect-based monitoring tools under the water framework directive. Environmental Sciences Europe, 27, 7 (2015). doi: 10.1186/s12302-015-0039-4 [Paper link]
  2. Wernersson A-S, Carere M, Maggi C, Tusil P, Soldan P, James A, Sanchez W, Broeg K, Kammann U, Reifferscheid G, Buchinger S, Maas H, Van Der Grinten E, Ausili A, Manfra L, Marziali L, Polesello S, Lacchetti I, Mancini L, Lilja K, Linderoth M, Lundeberg T, Fjällborg B, Porsbring T, Larsson DGJ, Bengtsson-Palme J, Förlin L, Kase R, Kienle C, Kunz P, Vermeirssen E, Werner I, Robinson CD, Lyons B, Katsiadaki I, Whalley C, den Haan K, Messiaen M, Clayton H, Lettieri T, Negrão Carvalho R, Gawlik BM, Dulio V, Hollert H, Di Paolo C, Brack W (2014). Technical Report on Aquatic Effect-Based Monitoring Tools. European Commission. Technical Report 2014-077, Office for Official Publications of European Communities, ISBN: 978-92-79-35787-9. doi:10.2779/7260

In a recent paper in Nature, a completely new antibiotic – teixobactin – is described (1). The really cool thing about this antibiotic is that it was discovered in a screen of uncultured bacteria, grown using new technology that enable controlled growth of single colonies in situ. I really like this idea, and I think the prospect of a novel antibiotic using a previously unexploited mechanism is super-promising, particularly in the light of alarming resistance development in clinically important pathogens (2,3). What really annoys me about the paper is the claim (already in the abstract) that since “we did not obtain any mutants of Staphylococcus aureus or Mycobacterium tuberculosis resistant to teixobactin (…) the properties of this compound suggest a path towards developing antibiotics that are likely to avoid development of resistance.” To me, this sounds pretty much like a bogus statement; in essence telling me that we apparently have not learned anything from the 70 years of antibiotics usage and resistance development. After working with antibiotic resistance a couple of years, particularly from the environmental perspective, I have a very disturbing feeling that there is already resistance mechanisms against teixobactin waiting out in the wild (4,5). Pretending that lack of mutation-associated resistance development means that there could not be resistance development did not help vancomycin (6,7), and we now see VRE (Vancomycin Resistant Enterococcus) showing up as a major problem in clinics. The “avoid development of resistance” claim is downright irresponsible, and the cynic in me cannot help to think that NovoBiotic Pharmaceuticals (the affiliation of almost half of the authors) has a monetary finger in this jar. In the end, time will tell how “resistance-resilient” teixobactin is and how well we can handle the gift of a novel antibiotic.

  1. Ling LL, Schneider T, Peoples AJ, Spoering AL, Engels I, Conlon BP, Mueller A, Schäberle TF, Hughes DE, Epstein S, Jones M, Lazarides L, Steadman VA, Cohen DR, Felix CR, Fetterman KA, Millett WP, Nitti AG, Zullo AM, Chen C, Lewis K: A new antibiotic kills pathogens without detectable resistance. Nature (2015). doi:10.1038/nature14098
  2. Finley RL, Collignon P, Larsson DGJ, McEwen SA, Li X-Z, Gaze WH, Reid-Smith R, Timinouni M, Graham DW, Topp E: The scourge of antibiotic resistance: the important role of the environment. Clin Infect Dis, 57: 704–710 (2013).
  3. French GL: The continuing crisis in antibiotic resistance. Int J Antimicrob Agents, 36 Suppl 3:S3–7 (2010).
  4. Bengtsson-Palme J, Boulund F, Fick J, Kristiansson E, Larsson DGJ: Shotgun metagenomics reveals a wide array of antibiotic resistance genes and mobile elements in a polluted lake in India. Frontiers in Microbiology, 5: 648 (2014).
  5. Larsson DGJ: Antibiotics in the environment. Ups J Med Sci, 119: 108–112 (2014).
  6. Wright GD: Mechanisms of resistance to antibiotics. Curr Opin Chem Biol, 7:563–569 (2003).
  7. Werner G, Strommenger B, Witte W: Acquired vancomycin resistance in clinically relevant pathogens. Future Microbiol, 3: 547–562 (2008).