Category: Papers

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]

The paper we published in August on travelers carrying resistance genes with them in their gut microbiota has now been typeset and got proper volume and issue numbers assigned to it in Antimicrobial Agents and Chemotherapy. Take a look at it, I personally think it’s quite good-looking.

Also, if you understand Swedish, here is an interview with me broadcasted on Swedish Radio last month about this study and the consequences of it.

The new citation for the paper is:

• 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]

There have been quite a lot of buzz this week around the travel paper we published earlier this month. Twitter aside, the findings of the paper has also been covered by a range of news outlets, both in Sweden and internationally. Today, I was on Swedish radio talking resistance problems for about ten minutes (listen here; in Swedish). Here’s a few takes on the story I gathered around the web:

Science Daily
Business Standard
Z News
Englemed Health News
Läkemedelsvärlden (in Swedish)
Sveriges Radio (in Swedish)
Göteborgs-Posten (in Swedish)

Earlier today, my most recent paper (1) became available online, describing resistance gene patterns in the gut microbiota of Swedes before and after travel to the Indian peninsula and central Africa. In this work, we have used metagenomic sequencing of the intestinal microbiome of Swedish students returning from exchange programs to show that the abundance of antibiotic resistance genes in several classes are increased after travel. This work reiterates the findings of several papers describing uptake of resistant bacteria (2-8) or resistance genes (9-11) after travel to destinations with worse resistance situation.

Our paper is important because it:

1. Addresses the abundance of a vast range of resistance genes (more than 300).
2. Finds evidence for that the overall relative abundance of antibiotic resistance genes increased after travel, without any intake of antibiotics.
3. Shows that the sensitivity of metagenomics was, despite very deep sequencing efforts, not sufficient to detect acquisition of the low-abundant (CTX-M) resistance genes responsible for observed ESBL phenotypes.
4. Reveals a “core resistome” of resistance genes that are more or less omnipresent, and remain relatively stable regardless of travel, while changes seem to occur in the more variable part of the resistome.
5. Hints at increased abundance of Proteobacteria after travel, although this increase could not specifically be linked to resistance gene increases.
6. Uses de novo metagenomic assembly to physically link resistance genes in the same sample, giving hints of co-resistance patterns in the gut microbiome.

The paper was a collaboration with Martin Angelin, Helena Palmgren and Anders Johansson at Umeå University, and was made possible by bioinformatics support from SciLifeLab in Stockholm. I highly recommend reading it as a complement to e.g. the Forslund et al. paper (12) describing country-specific antibiotic resistance patterns in the gut microbiota.

Taken together, this study offers a broadened perspective on how the antibiotic resistance potential of the human gut microbiome changes after travel, providing an independent complement to previous studies targeting a limited number of bacterial species or antibiotic resistance genes. Understanding how resistance genes travels the globe is hugely important, since resistance in principle only need to appear in a pathogen once; improper hygiene and travel may then spread novel resistance genes across continents rapidly (13,14).

References

1. 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. Antimicrob Agents Chemother Accepted manuscript posted online (2015). doi: 10.1128/AAC.00933-15 [Paper link]
2. Gaarslev K, Stenderup J: Changes during travel in the composition and antibiotic resistance pattern of the intestinal Enterobacteriaceae flora: results from a study of mecillinam prophylaxis against travellers’ diarrhoea. Curr Med Res Opin 9:384–387 (1985).
3. Paltansing S, Vlot JA, Kraakman MEM, Mesman R, Bruijning ML, Bernards AT, Visser LG, Veldkamp KE: Extended-spectrum β-lactamase-producing enterobacteriaceae among travelers from the Netherlands. Emerging Infect. Dis. 19:1206–1213 (2013).
4. Ruppé E, Armand-Lefèvre L, Estellat C, El-Mniai A, Boussadia Y, Consigny PH, Girard PM, Vittecoq D, Bouchaud O, Pialoux G, Esposito-Farèse M, Coignard B, Lucet JC, Andremont A, Matheron S: Acquisition of carbapenemase-producing Enterobacteriaceae by healthy travellers to India, France, February 2012 to March 2013. Euro Surveill. 19 (2014).
5. Kennedy K, Collignon P: Colonisation with Escherichia coli resistant to “critically important” antibiotics: a high risk for international travellers. Eur J Clin Microbiol Infect Dis 29:1501–1506 (2010).
6. Tham J, Odenholt I, Walder M, Brolund A, Ahl J, Melander E: Extended-spectrum beta-lactamase-producing Escherichia coli in patients with travellers’ diarrhoea. Scand. J. Infect. Dis. 42:275–280 (2010).
7. Östholm-Balkhed Å, Tärnberg M, Nilsson M, Nilsson LE, Hanberger H, Hällgren A, Travel Study Group of Southeast Sweden: Travel-associated faecal colonization with ESBL-producing Enterobacteriaceae: incidence and risk factors. J Antimicrob Chemother 68:2144–2153 (2013).
8. Kantele A, Lääveri T, Mero S, Vilkman K, Pakkanen SH, Ollgren J, Antikainen J, Kirveskari J: Antimicrobials increase travelers’ risk of colonization by extended-spectrum betalactamase-producing enterobacteriaceae. Clin Infect Dis 60:837–846 (2015).
9. von Wintersdorff CJH, Penders J, Stobberingh EE, Oude Lashof AML, Hoebe CJPA, Savelkoul PHM, Wolffs PFG: High rates of antimicrobial drug resistance gene acquisition after international travel, The Netherlands. Emerging Infect. Dis. 20:649–657 (2014).
10. Tängdén T, Cars O, Melhus A, Löwdin E: Foreign travel is a major risk factor for colonization with Escherichia coli producing CTX-M-type extended-spectrum beta-lactamases: a prospective study with Swedish volunteers. Antimicrob Agents Chemother 54:3564–3568 (2010).
11. Dhanji H, Patel R, Wall R, Doumith M, Patel B, Hope R, Livermore DM, Woodford N: Variation in the genetic environments of bla(CTX-M-15) in Escherichia coli from the faeces of travellers returning to the United Kingdom. J Antimicrob Chemother 66:1005–1012 (2011).
12. Forslund K, Sunagawa S, Kultima JR, Mende DR, Arumugam M, Typas A, Bork P: Country-specific antibiotic use practices impact the human gut resistome. Genome Res 23:1163–1169 (2013).
13. Bengtsson-Palme J, Larsson DGJ: Antibiotic resistance genes in the environment: prioritizing risks. Nat Rev Microbiol 13:396 (2015).
14. Larsson DGJ: Antibiotics in the environment. Ups J Med Sci 119:108–112 (2014).

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.

A couple of days ago, a paper I have co-authored describing an ITS sequence dataset for chimera control in fungi went online as an advance online publication in Microbes and Environments. There are several software tools available for chimera detection (e.g. Henrik Nilsson‘s fungal chimera checker (1) and UCHIME (2)), but these generally rely on the presence of a chimera-free reference dataset. Until now, there was no such dataset is for the fungal ITS region, and we in this paper (3) introduce a comprehensive, automatically updated reference dataset for fungal ITS sequences based on the UNITE database (4). This dataset supports chimera detection throughout the fungal kingdom and for full-length ITS sequences as well as partial (ITS1 or ITS2 only) datasets. We estimated the dataset performance on a large set of artificial chimeras to be above 99.5%, and also used the dataset to remove nearly 1,000 chimeric fungal ITS sequences from the UNITE database. The dataset can be downloaded from the UNITE repository. Thereby, it is also possible for users to curate the dataset in the future through the UNITE interactive editing tools.

References:

1. Nilsson RH, Abarenkov K, Veldre V, Nylinder S, Wit P de, Brosché S, Alfredsson JF, Ryberg M, Kristiansson E: An open source chimera checker for the fungal ITS region. Molecular Ecology Resources, 10, 1076–1081 (2010).
2. Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics, 27, 16, 2194-2200 (2011). doi:10.1093/bioinformatics/btr381
3. Nilsson RH, Tedersoo L, Ryberg M, Kristiansson E, Hartmann M, Unterseher M, Porter TM, Bengtsson-Palme J, Walker D, de Sousa F, Gamper HA, Larsson E, Larsson K-H, Kõljalg U, Edgar R, Abarenkov K: A comprehensive, automatically updated fungal ITS sequence dataset for reference-based chimera control in environmental sequencing efforts. Microbes and Environments, Advance Online Publication (2015). doi: 10.1264/jsme2.ME14121
4. Kõljalg U, Nilsson RH, Abarenkov K, Tedersoo L, Taylor AFS, Bahram M, Bates ST, Bruns TT, Bengtsson-Palme J, Callaghan TM, Douglas B, Drenkhan T, Eberhardt U, Dueñas M, Grebenc T, Griffith GW, Hartmann M, Kirk PM, Kohout P, Larsson E, Lindahl BD, Lücking R, Martín MP, Matheny PB, Nguyen NH, Niskanen T, Oja J, Peay KG, Peintner U, Peterson M, Põldmaa K, Saag L, Saar I, Schüßler A, Senés C, Smith ME, Suija A, Taylor DE, Telleria MT, Weiß M, Larsson KH: Towards a unified paradigm for sequence-based identification of Fungi. Molecular Ecology, 22, 21, 5271–5277 (2013). doi: 10.1111/mec.12481

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

After almost a year in different stages of review and revision, in which the paper (but not the software) saw a total transformation, I am happy to announce that the paper describing Metaxa2 has been accepted in Molecular Ecology Resources and is available in a rudimentary online early form. The figures in this version are not that pretty, but those who wants to read the paper asap, you have the possibility to do so.

This means that if you have been using Metaxa2 for a publication, there is now a new preferred way of citing this, namely:

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 (2015). doi: 10.1111/1755-0998.12399

The paper (1), apart from describing the new Metaxa version, also brings a very thorough evaluation of the software, compared to other tools for taxonomic classification implemented in QIIME (2). In short, we show that:

• Metaxa2 can make trustworthy taxonomic classifications even with reads as short as 100 bp
• Generally, the performance is reliable across the entire SSU rRNA gene, regardless of which V-region a read is derived from
• Metaxa2 can reliably recapture species composition from short-read metagenomic data, comparable with results of amplicon sequencing
• Metaxa2 outperforms other popular tools such as Mothur (3), the RDP Classifier (4), Rtax (5) and the QIIME implementation of Uclust (6) in terms of proportion of correctly classified reads from metagenomic data
• The false positive rate of Metaxa2 is very close to zero; far superior to many of the above mentioned tools, many of which assume that reads must derive from the rRNA gene

Metaxa2 can be downloaded here. We have already used it for around two years internally, and it forms the base of the taxonomic classifications in e.g. our recently published paper on antibiotic resistance in a polluted Indian lake (7).

References

1. 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 (2015). doi: 10.1111/1755-0998.12399 [Paper link]
2. Caporaso JG, Kuczynski J, Stombaugh J et al.: QIIME allows analysis of high-throughput community sequencing data. Nature Methods, 7, 335–336 (2010).
3. Schloss PD, Westcott SL, Ryabin T et al.: Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Applied and Environmental Microbiology, 75, 7537–7541 (2009).
4. Wang Q, Garrity GM, Tiedje JM, Cole JR: Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Applied and Environmental Microbiology, 73, 5261–5267 (2007).
5. Soergel DAW, Dey N, Knight R, Brenner SE: Selection of primers for optimal taxonomic classification of environmental 16S rRNA gene sequences. The ISME Journal, 6, 1440–1444 (2012).
6. Edgar RC: Search and clustering orders of magnitude faster than BLAST. Bioinformatics, 26, 2460–2461 (2010).
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. Frontiers in Microbiology, 5, 648 (2014).

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).