Microbiology, Metagenomics and Bioinformatics

Johan Bengtsson-Palme, University of Gothenburg | Wisconsin Institute for Discovery

Welcome

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My name is Johan Bengtsson-Palme. I am an assistant professor at the Sahlgrenska Academy, residing in Gothenburg on the Swedish west coast. My research concerns microbiology and microbial ecology, primarily focusing on investigating antibiotic resistance and interactions in bacterial communities through metagenomics and bioinformatics. I also have an interest in molecular taxonomy and improving the quality of reference databases. I work closely with the group of Joakim Larsson, Erik Kristiansson and Henrik Nilsson. To contact me, feel free to send an e-mail to my firstname.lastname@microbiology.se

Recently, Le Page et al. published a paper in Environmental International (1), partially building on the predicted no-effect concentrations for resistance selection for 111 antibiotics that me and Joakim Larsson published around two years ago (2). In their paper, the authors stress that discharge limits for antibiotics need to consider their potency to affect both environmental and human health, which we believe is a very reasonable standpoint, and to which we agree. However, we do not agree on the authors’ claim that cyanobacteria would often be more sensitive to antibiotics than the most sensitive human-associated bacteria (1). Importantly, we also think that it is a bit unclear from the paper which protection goals are considered. Are the authors mainly concerned with protecting microbial diversity in ecosystems, protecting ecosystem functions and services, or protecting from risks for resistance selection? This is important because it influence why one would want to mitigate, and therefore who would perform which actions. To elaborate a little on our standpoints, we wrote a short correspondence piece to Environment International, which is now published (3). (It has been online for a few days, but without a few last-minute changes we did to the proof, and hence I’m only posting about it now when the final version is online.) There is indeed an urgent need for discharge limits for antibiotics, particularly for industrial sources (4) and such limits would have tremendous value in regulation efforts, and in development of environmental criteria within public procurement and generic exchange programs (5). Importantly, while we are all for taking ecotoxicological data into account when doing risk assessment, we think that there should be solid scientific ground for mitigations and that regulations need to consider the benefits versus the costs, which is what we want to convey in our response to Le Page et al.

References

  1. Le Page G, Gunnarsson L, Snape J, Tyler CR: Integrating human and environmental health in antibiotic risk assessment: a critical analysis of protection goals, species sensitivity and antimicrobial resistance. Environment International, in press (2017). doi: 10.1016/j.envint.2017.09.013
  2. 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
  3. Bengtsson-Palme J, Larsson DGJ: Protection goals must guide risk assessment for antibiotics. Environment International, in press (2017). doi: 10.1016/j.envint.2017.10.019
  4. Bengtsson-Palme J, Larsson DGJ: Time to limit antibiotic pollution. The Medicine Maker, 0416, 302, 17–18 (2016). [Paper link]
  5. Bengtsson-Palme J, Gunnarsson L, Larsson DGJ: Can branding and price of pharmaceuticals guide informed choices towards improved pollution control during manufacturing? Journal of Cleaner Production, 171, 137–146 (2018). doi: 10.1016/j.jclepro.2017.09.247

Yesterday, Swedish television channel TV4 highlighted a recent publication by myself, Lina Gunnarsson and Joakim Larsson, in which we show that the price of pharmaceuticals is linked to the environmental standards of production countries. Surprisingly, however, this link seems to be mostly driven by whether the product is generic or original (branded), which in turns affect the prices.

In the study (1), published in Journal of Cleaner Production, we have used an exclusive set of Swedish sales data for pharmaceuticals combined with data on the origin of the active ingredients, obtained under an agreement to not identify individual manufacturers or products. We used this data to determine if price pressure and generic substitution could be linked to the general environmental performance and the corruption levels of the production countries, as measured by the Environmental Performance Index (2) and the Corruption Perception Index (3). In line with what we believed, India was the largest producer of generics, while Europe and the USA dominated the market for branded products (1). Importantly, we found that the price and environmental performance index of the production countries were linked, but that this relationship was largely explained by whether the product was original or generic.

To some extent, this relationship would allow buyers to select products that likely originate from countries that, in general terms, have better pollution control, which was also highlighted in the news clip that TV4 produced. However, what was lacking from that clip was the fact that this approach lacks resolution, because it does not say anything about the environmental footprint of individual products. We therefore conclude that to better allow consumers, hospitals and pharmacies to influence the environmental impact of their product choices, there is need for regulation and, importantly, transparency in the production chain, as has also been pointed out earlier (4,5). To this end, emissions from manufacturing need to be measured, allowing for control and follow-up on industry commitments towards sustainable manufacturing of pharmaceuticals (6). Since the discharges from pharmaceutical manufacturing not only leads to consequences to the local environment (7,8), but also in the case of antibiotics has potentially global consequences in terms of increasing risks for resistance development (9), limiting discharges is an urgent need to avoid a looming antibiotic resistance crisis (10).

The paper was also highlighted by the Centre for Antibiotic Resistance Research, and can be read here or here.

References

  1. Bengtsson-Palme J, Gunnarsson L, Larsson DGJ: Can branding and price of pharmaceuticals guide informed choices towards improved pollution control during manufacturing? Journal of Cleaner Production, 171, 137–146 (2018). doi: 10.1016/j.jclepro.2017.09.247
  2. Hsu A, Alexandre N, Cohen S, Jao P, Khusainova E: 2016 Environmental Performance Index. Yale University, New Haven, CT, USA (2016). http://epi.yale.edu/reports/2016-report
  3. Transparency International: Corruption Perceptions Index 2014. Transparency International, Berlin, Germany (2014). http://www.transparency.org/cpi2014/in_detail
  4. Larsson DGJ, Fick J: Transparency throughout the production chain–a way to reduce pollution from the manufacturing of pharmaceuticals? Regulatory Toxicology and Pharmacology, 53, 161–163 (2009). doi:10.1016/j.yrtph.2009.01.008
  5. Ågerstrand M, Berg C, Björlenius B, Breitholtz M, Brunström B, Fick J, Gunnarsson L, Larsson DGJ, Sumpter JP, Tysklind M, Rudén C: Improving environmental risk assessment of human pharmaceuticals. Environmental Science & Technology, 49, 5336–5345 (2015). doi:10.1021/acs.est.5b00302
  6. Industry Roadmap for Progress on Combating Antimicrobial Resistance: Industry Roadmap for Progress on Combating Antimicrobial Resistance – September 2016. (2016). http://www.ifpma.org/wp-content/uploads/2016/09/Roadmap-for-Progress-on-AMR-FINAL.pdf
  7. 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
  8. aus der Beek T, Weber FA, Bergmann A, Hickmann S, Ebert I, Hein A, Küster A: Pharmaceuticals in the environment–Global occurrences and perspectives. Environmental Toxicology and Chemistry, 35, 823–835 (2016). doi:10.1002/etc.3339
  9. 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
  10. Bengtsson-Palme J, Larsson DGJ: Time to limit antibiotic pollution. The Medicine Maker, 0416, 302, 17–18 (2016). [Paper link]

Myself, Joakim Larsson and Erik Kristiansson have written a review on the environmental factors that influence development and spread of antibiotic resistance, which was published today in FEMS Microbiology Reviews. The review (1) builds on thoughts developed in the latter parts of my PhD thesis (2), and seeks to provide a synthesis knowledge gained from different subfields towards the current understanding of evolutionary and ecological processes leading to clinical appearance of resistance genes, as well as the important environmental dispersal barriers preventing spread of resistant pathogens.

We postulate that emergence of novel resistance factors and mobilization of resistance genes are likely to occur continuously in the environment. However, the great majority of such genetic events are unlikely to lead to establishment of novel resistance factors in bacterial populations, unless there is a selection pressure for maintaining them or their fitness costs are negligible. To enable measures to prevent resistance development in the environment, it is therefore critical to investigate under what conditions and to what extent environmental selection for resistance takes place. Selection for resistance is likely less important for the dissemination of resistant bacteria, but will ultimately depend on how well the species or strain in question thrives in the external environment. Metacommunity theory (3,4) suggests that dispersal ability is central to this process, and therefore opportunistic pathogens with their main habitat in the environment may play an important role in the exchange of resistance factors between humans and the environment. Understanding the dispersal barriers hindering this exchange is not only key to evaluate risks, but also to prevent resistant pathogens, as well as novel resistance genes, from reaching humans.

Towards the end of the paper, we suggest certain environments that seem to be more important from a risk management perspective. We also discuss additional problems linked to the development of antibiotic resistance, such as increased evolvability of bacterial genomes (5) and which other types of genes that may be mobilized in the future, should the development continue (1,6). In this review, we also further develop thoughts on the relative risks of re-recruiting and spreading well-known resistance factors already circulating in pathogens, versus recruitment of completely novel resistance genes from environmental bacteria (7). While the latter case is likely to be very rare, and thus almost impossible to quantify the risks for, the consequences of such (potentially one-time) events can be dire.

I personally think that this is one of the best though-through pieces I have ever written, and since it is open access and (in my biased opinion) written in a fairly accessible way, I recommend everyone to read it. It builds on the ecological theories for resistance ecology developed by, among others, Fernando Baquero and José Martinez (8-13). Over the last year, it has been stressed several times at meetings (e.g. at the EDAR conferences in August) that there is a need to develop an ecological framework for antibiotic resistance genes. I think this paper could be one of the foundational pillars on such an endeavor and look forward to see how it will fit into the growing literature on the subject!

References

  1. Bengtsson-Palme J, Kristiansson E, Larsson DGJ: Environmental factors influencing the development and spread of antibiotic resistance. FEMS Microbiology Reviews, accepted manuscript (2017). doi: 10.1093/femsre/fux053
  2. Bengtsson-Palme J: Antibiotic resistance in the environment: a contribution from metagenomic studies. Doctoral thesis (medicine), Department of Infectious Diseases, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, 2016. [Link]
  3. Bengtsson J: Applied (meta)community ecology: diversity and ecosystem services at the intersection of local and regional processes. In: Verhoef HA, Morin PJ (eds.). Community Ecology: Processes, Models, and Applications. Oxford: Oxford University Press, 115–130 (2009).
  4. Leibold M, Norberg J: Biodiversity in metacommunities: Plankton as complex adaptive systems? Limnology and Oceanography, 1278–1289 (2004).
  5. Gillings MR, Stokes HW: Are humans increasing bacterial evolvability? Trends in Ecology and Evolution, 27, 346–352 (2012).
  6. Gillings MR: Evolutionary consequences of antibiotic use for the resistome, mobilome and microbial pangenome. Frontiers in Microbiology, 4, 4 (2013).
  7. Bengtsson-Palme J, Larsson DGJ: Antibiotic resistance genes in the environment: prioritizing risks. Nature Reviews Microbiology, 13, 369 (2015). doi: 10.1038/nrmicro3399-c1
  8. Baquero F, Alvarez-Ortega C, Martinez JL: Ecology and evolution of antibiotic resistance. Environmental Microbiology Reports, 1, 469–476 (2009).
  9. Baquero F, Tedim AP, Coque TM: Antibiotic resistance shaping multi-level population biology of bacteria. Frontiers in Microbiology, 4, 15 (2013).
  10. Berendonk TU, Manaia CM, Merlin C et al.: Tackling antibiotic resistance: the environmental framework. Nature Reviews Microbiology, 13, 310–317 (2015).
  11. Hiltunen T, Virta M, Laine A-L: Antibiotic resistance in the wild: an eco-evolutionary perspective. Philosophical Transactions of the Royal Society B: Biological Sciences, 372 (2017) doi: 10.1098/rstb.2016.0039.
  12. Martinez JL: Bottlenecks in the transferability of antibiotic resistance from natural ecosystems to human bacterial pathogens. Frontiers in Microbiology, 2, 265 (2011).
  13. Salyers AA, Amábile-Cuevas CF: Why are antibiotic resistance genes so resistant to elimination? Antimicrobial Agents and Chemotherapy, 41, 2321–2325 (1997).

Today, Microbiome put online a paper lead-authored by my colleague Fanny Berglund – one of Erik Kristiansson’s brilliant PhD students – in which we identify 76 novel metallo-ß-lactamases (1). This feat was made possible because of a new computational method designed by Fanny, which uses a hidden Markov model based on known B1 metallo-ß-lactamases. We analyzed over 10,000 bacterial genomes and plasmids and over 5 terabases of metagenomic data and could thereby predict 76 novel genes. These genes clustered into 59 new families of metallo-β-lactamases (given a 70% identity threshold). We also verified the functionality of 21 of these genes experimentally, and found that 18 were able to hydrolyze imipenem when inserted into Escherichia coli. Two of the novel genes contained atypical zinc-binding motifs in their active sites. Finally, we show that the B1 metallo-β-lactamases can be divided into five major groups based on their phylogenetic origin. It seems that nearly all of the previously characterized mobile B1 β-lactamases we identify in this study were likely to have originated from chromosomal genes present in species within the Proteobacteria, particularly Shewanella spp.

This study more than doubles the number of known B1 metallo-β-lactamases. As with the study by Boulund et al. (2) which we published last month on computational discovery of novel fluoroquinolone resistance genes (which used a very similar approach but on a completely different type of genes), this study also supports the hypothesis that environmental bacterial communities act as sources of uncharacterized antibiotic resistance genes (3-7). Fanny have done a fantastic job on this paper, and I highly recommend reading it in its entirety (it’s open access so you have virtually no excuse not to). It can be found here.

References

  1. Berglund F, Marathe NP, Österlund T, Bengtsson-Palme J, Kotsakis S, Flach C-F, Larsson DGJ, Kristiansson E: Identification of 76 novel B1 metallo-β-lactamases through large-scale screening of genomic and metagenomic data. Microbiome, 5, 134 (2017). doi: 10.1186/s40168-017-0353-8
  2. Boulund F, Berglund F, Flach C-F, Bengtsson-Palme J, Marathe NP, Larsson DGJ, Kristiansson E: Computational discovery and functional validation of novel fluoroquinolone resistance genes in public metagenomic data sets. BMC Genomics, 18, 682 (2017). doi: 10.1186/s12864-017-4064-0
  3. Bengtsson-Palme J, Larsson DGJ: Antibiotic resistance genes in the environment: prioritizing risks. Nature Reviews Microbiology, 13, 369 (2015). doi: 10.1038/nrmicro3399-c1
  4. Allen HK, Donato J, Wang HH et al.: Call of the wild: antibiotic resistance genes in natural environments. Nature Reviews Microbiology, 8, 251–259 (2010).
  5. Berendonk TU, Manaia CM, Merlin C et al.: Tackling antibiotic resistance: the environmental framework. Nature Reviews Microbiology, 13, 310–317 (2015).
  6. Martinez JL: Bottlenecks in the transferability of antibiotic resistance from natural ecosystems to human bacterial pathogens. Frontiers in Microbiology, 2, 265 (2011).
  7. Finley RL, Collignon P, Larsson DGJ et al.: The scourge of antibiotic resistance: the important role of the environment. Clinical Infectious Diseases, 57, 704–710 (2013).

ITSx in Bioconda

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Mattias de Hollander at the Netherlands Institute of Ecology kindly informed me that they recently added the ITSx 1.1b version to the Bioconda package manager. This will make it easy for Conda users to install ITSx automatically into their systems and pipelines and also for others who are using conda. The Bioconda version can be found here. I would like to thank Mattias for this initiative and hope that the Bioconda version of ITSx will find much use!

BMC Genomics today published a paper first-authored by my long-time colleague Fredrik Boulund, which describes a computational screen of genomes and metagenomes for novel qnr fluoroquinolone resistance genes (1). The study makes use of Fredrik’s well-designed and updated qnr-prediction pipeline, but in contrast to his previous publication based on the pipeline from 2012 (2), we here study a 20-fold larger dataset of almost 13 terabases of sequence data. Based on this data, the pipeline predicted 611 putative qnr genes, including all previously described plasmid-mediated qnr gene families. 20 of the predicted genes were previously undescribed, and of these nine were selected for experimental validation. Six of those tested genes improved the survivability under ciprofloxacin exposure when expressed in Escherichia coli. The study shows that qnr genes are almost ubiquitous in environmental microbial communities. This study also lends further credibility to the hypothesis that environmental bacterial communities can act as sources of previously uncharacterized antibiotic resistance genes (3-7). The study can be read in its entirety here.

References

  1. Boulund F, Berglund F, Flach C-F, Bengtsson-Palme J, Marathe NP, Larsson DGJ, Kristiansson E: Computational discovery and functional validation of novel fluoroquinolone resistance genes in public metagenomic data sets. BMC Genomics, 18, 682 (2017). doi: 10.1186/s12864-017-4064-0
  2. Boulund F, Johnning A, Pereira MB, Larsson DGJ, Kristiansson E: A novel method to discover fluoroquinolone antibiotic resistance (qnr) genes in fragmented nucleotide sequences. BMC Genomics, 13, 695 (2012). doi: 10.1186/1471-2164-13-695
  3. Bengtsson-Palme J, Larsson DGJ: Antibiotic resistance genes in the environment: prioritizing risks. Nature Reviews Microbiology, 13, 369 (2015). doi: 10.1038/nrmicro3399-c1
  4. Allen HK, Donato J, Wang HH et al.: Call of the wild: antibiotic resistance genes in natural environments. Nature Reviews Microbiology, 8, 251–259 (2010).
  5. Berendonk TU, Manaia CM, Merlin C et al.: Tackling antibiotic resistance: the environmental framework. Nature Reviews Microbiology, 13, 310–317 (2015).
  6. Martinez JL: Bottlenecks in the transferability of antibiotic resistance from natural ecosystems to human bacterial pathogens. Frontiers in Microbiology, 2, 265 (2011).
  7. Finley RL, Collignon P, Larsson DGJ et al.: The scourge of antibiotic resistance: the important role of the environment. Clinical Infectious Diseases, 57, 704–710 (2013).