Tag: Antibiotic resistance

Last week, a paper resulting from a collaboration with Stefanie Heß and Viktor Jonsson was published in Environmental Science & Technology. In the paper, we build a quantitative model for the emergence of antibiotic resistance genes in human pathogens and populate it using the few numbers that are available on different processes (bacterial uptake, horizontal gene transfer rates, rate of mobilization of chromosomal genes, etc.) in the literature (1).

In short, we find that in order for the environment to play an important role in the appearance of novel resistance genes in pathogens, there needs to be a substantial flow of bacteria from the environment to the human microbiome. We also find that most likely the majority of resistance genes in human pathogens have very small fitness costs associated with them, if any cost at all.

The model makes three important predictions:

1. The majority of ARGs present in pathogens today should have very limited effects on fitness. The model caps the average fitness impact for ARGs currently present in human pathogens between −0.2 and +0.1% per generation. By determining the fitness effects of carrying individual ARGs in their current hosts, this prediction could be experimentally tested.
2. The most likely location of ARGs 70 years ago would have been in human-associated bacteria. By tracking ARGs currently present in human pathogens across bacterial genomes, it may be possible to trace the evolutionary history of these genes and thereby identify their likely hosts at the beginning of the antibiotic era, similar to what was done by Stefan Ebmeyer and his colleagues (2). What they found sort-of corroborate the findings of our model and lend support to the idea that most ARGs may not originate in the environment. However, this analysis is complicated by the biased sampling of fully sequenced bacterial genomes, most of which originate from human specimens. That said, the rapid increase in sequencing capacity may make full-scale analysis of ARG origins using genomic data possible in the near future, which would enable testing of this prediction of the model.
3. If the origins of ARGs currently circulating in pathogens can be established, the range of reasonable dispersal ability levels from the environment to pathogens narrows dramatically. Similarly, if the rates of mobilization and horizontal transfer of resistance genes could be better determined by experiments, the model would predict the likely origins more precisely. Just establishing a ball-park range for the mobilization rate would dramatically restrict the possible outcomes of the model. Thus, a more precise determination of any of these parameters would enable several more specific predictions by the model.

This paper has a quite interesting backstory, beginning with me having leftover time on a bus ride in Madison (WI), thinking about whether you could quantize the conceptual framework for resistance gene emergence we described in our 2018 review paper in FEMS Reviews Microbiology (3). This spurred the first attempt at such a model, which then led to Stefanie Heß and me applying for support from the Centre for Antibiotic Resistance Research at the University of Gothenburg (CARe) to develop this idea further. We got this support and Stefanie spent a few days with me in Gothenburg developing this idea into a model we could implement in R.

However, at that point we realized we needed more modeling expertise and brought in Viktor Jonsson to make sure the model was robust. From there, it took us about 1.5 years to refine and rerun the model about a million times… By the early spring this year, we had a reasonable model that we could write a manuscript around, and this is what now is published. It’s been an interesting and very nice ride together with Stefanie and Viktor!

References

1. Bengtsson-Palme J, Jonsson V, Heß S: What is the role of the environment in the emergence of novel antibiotic resistance genes? A modelling approach. Environmental Science & Technology, Article ASAP (2021). doi: 10.1021/acs.est.1c02977 [Paper link]
2. Ebmeyer S, Kristiansson E, Larsson DGJ: A framework for identifying the recent origins of mobile antibiotic resistance genes. Communications Biology 4 (2021). doi: 10.1038/s42003-020-01545-5
3. Bengtsson-Palme J, Kristiansson E, Larsson DGJ: Environmental factors influencing the development and spread of antibiotic resistance. FEMS Microbiology Reviews, 42, 1, 68–80 (2018). doi: 10.1093/femsre/fux053 [Paper link]

Last week, I published 13 (!!) papers in the EFSA Journal on how to assess concentrations of antibiotics that could select for antibiotic resistance in animal feed (1-13). Or, well, you could also look at it as that the EFSA Biohaz panel that I have been a part of for more than two years published our final 13-part report.

Regardless of how you view it, this set of papers have two main takeaways:

1. We present a method to establish Predicted Minimal Selective Concentrations (PMSCs) for antibiotics. This method uses a combination of Dan Andersson’s approach to MSCs (14) and the method I published with Joakim Larsson around five years ago to establish predicted no-effect concentrations (PNECs) for antibiotics based on MIC data (15). The combination is a powerful (but very cautious) tool to estimate minimal selective concentrations for antibiotics (1), and we have subsequently applied this method to animal feed contamination with antibiotics, but…
2. There is way too little data to establish PMSCs for most antibiotics with any certainty. Really, the lack of data is so bad that for many of the antibiotic classes we could not make a reasonable assessment. Thus the main conclusion might be that we need a lot more data on how low concentrations of antibiotics that select for antibiotic resistance, both in laboratory systems and in more realistic settings.

References

1. EFSA Panel on Biological Hazards (BIOHAZ)*, Allende A, Koutsoumanis K, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Ru G, Simmons M, Skandamis P, Suffredini E, Andersson DI, Bampidis V, Bengtsson-Palme J, Bouchard D, Ferran A, Kouba M, López Puente S, López-Alonso M, Saxmose Nielsen S, Pechová A, Petkova M, Girault S, Broglia A, Guerra B, Lorenzo Innocenti M, Liébana E, López-Gálvez G, Manini P, Stella P, Peixe L: Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 1: Methodology, general data gaps and uncertainties. EFSA Journal, 19, 10 (2021). doi: 10.2903/j.efsa.2021.6852 [Paper link]
2. EFSA Panel on Biological Hazards (BIOHAZ)*, Allende A, Koutsoumanis K, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Ru G, Simmons M, Skandamis P, Suffredini E, Andersson DI, Bampidis V, Bengtsson-Palme J, Bouchard D, Ferran A, Kouba M, López Puente S, López-Alonso M, Saxmose Nielsen S, Pechová A, Petkova M, Girault S, Broglia A, Guerra B, Lorenzo Innocenti M, Liébana E, López-Gálvez G, Manini P, Stella P, Peixe L: Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 2: Aminoglycosides/aminocyclitols: apramycin, paromomycin, neomycin and spectinomycin. EFSA Journal, 19, 10 (2021). doi: 10.2903/j.efsa.2021.6853 [Paper link]
3. EFSA Panel on Biological Hazards (BIOHAZ)*, Allende A, Koutsoumanis K, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Ru G, Simmons M, Skandamis P, Suffredini E, Andersson DI, Bampidis V, Bengtsson-Palme J, Bouchard D, Ferran A, Kouba M, López Puente S, López-Alonso M, Saxmose Nielsen S, Pechová A, Petkova M, Girault S, Broglia A, Guerra B, Lorenzo Innocenti M, Liébana E, López-Gálvez G, Manini P, Stella P, Peixe L: Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 3: Amprolium. EFSA Journal, 19, 10 (2021). doi: 10.2903/j.efsa.2021.6854 [Paper link]
4. EFSA Panel on Biological Hazards (BIOHAZ)*, Allende A, Koutsoumanis K, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Ru G, Simmons M, Skandamis P, Suffredini E, Andersson DI, Bampidis V, Bengtsson-Palme J, Bouchard D, Ferran A, Kouba M, López Puente S, López-Alonso M, Saxmose Nielsen S, Pechová A, Petkova M, Girault S, Broglia A, Guerra B, Lorenzo Innocenti M, Liébana E, López-Gálvez G, Manini P, Stella P, Peixe L: Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 4: ß-Lactams: amoxicillin and penicillin. EFSA Journal, 19, 10 (2021). doi: 10.2903/j.efsa.2021.6855 [Paper link]
5. EFSA Panel on Biological Hazards (BIOHAZ)*, Allende A, Koutsoumanis K, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Ru G, Simmons M, Skandamis P, Suffredini E, Andersson DI, Bampidis V, Bengtsson-Palme J, Bouchard D, Ferran A, Kouba M, López Puente S, López-Alonso M, Saxmose Nielsen S, Pechová A, Petkova M, Girault S, Broglia A, Guerra B, Lorenzo Innocenti M, Liébana E, López-Gálvez G, Manini P, Stella P, Peixe L: Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 5: Lincosamides: lincomycin. EFSA Journal, 19, 10 (2021). doi: 10.2903/j.efsa.2021.6856 [Paper link]
6. EFSA Panel on Biological Hazards (BIOHAZ)*, Allende A, Koutsoumanis K, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Ru G, Simmons M, Skandamis P, Suffredini E, Andersson DI, Bampidis V, Bengtsson-Palme J, Bouchard D, Ferran A, Kouba M, López Puente S, López-Alonso M, Saxmose Nielsen S, Pechová A, Petkova M, Girault S, Broglia A, Guerra B, Lorenzo Innocenti M, Liébana E, López-Gálvez G, Manini P, Stella P, Peixe L: Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 6: Macrolides: tilmicosin, tylosin and tylvalosin. EFSA Journal, 19, 10 (2021). doi: 10.2903/j.efsa.2021.6858 [Paper link]
7. EFSA Panel on Biological Hazards (BIOHAZ)*, Allende A, Koutsoumanis K, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Ru G, Simmons M, Skandamis P, Suffredini E, Andersson DI, Bampidis V, Bengtsson-Palme J, Bouchard D, Ferran A, Kouba M, López Puente S, López-Alonso M, Saxmose Nielsen S, Pechová A, Petkova M, Girault S, Broglia A, Guerra B, Lorenzo Innocenti M, Liébana E, López-Gálvez G, Manini P, Stella P, Peixe L: Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 7: Amphenicols: florfenicol and thiamphenicol. EFSA Journal, 19, 10 (2021). doi: 10.2903/j.efsa.2021.6859 [Paper link]
8. EFSA Panel on Biological Hazards (BIOHAZ)*, Allende A, Koutsoumanis K, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Ru G, Simmons M, Skandamis P, Suffredini E, Andersson DI, Bampidis V, Bengtsson-Palme J, Bouchard D, Ferran A, Kouba M, López Puente S, López-Alonso M, Saxmose Nielsen S, Pechová A, Petkova M, Girault S, Broglia A, Guerra B, Lorenzo Innocenti M, Liébana E, López-Gálvez G, Manini P, Stella P, Peixe L: Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 8: Pleuromutilins: tiamulin and valnemulin. EFSA Journal, 19, 10 (2021). doi: 10.2903/j.efsa.2021.6860 [Paper link]
9. EFSA Panel on Biological Hazards (BIOHAZ)*, Allende A, Koutsoumanis K, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Ru G, Simmons M, Skandamis P, Suffredini E, Andersson DI, Bampidis V, Bengtsson-Palme J, Bouchard D, Ferran A, Kouba M, López Puente S, López-Alonso M, Saxmose Nielsen S, Pechová A, Petkova M, Girault S, Broglia A, Guerra B, Lorenzo Innocenti M, Liébana E, López-Gálvez G, Manini P, Stella P, Peixe L: Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 9: Polymyxins: colistin. EFSA Journal, 19, 10 (2021). doi: 10.2903/j.efsa.2021.6861 [Paper link]
10. EFSA Panel on Biological Hazards (BIOHAZ)*, Allende A, Koutsoumanis K, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Ru G, Simmons M, Skandamis P, Suffredini E, Andersson DI, Bampidis V, Bengtsson-Palme J, Bouchard D, Ferran A, Kouba M, López Puente S, López-Alonso M, Saxmose Nielsen S, Pechová A, Petkova M, Girault S, Broglia A, Guerra B, Lorenzo Innocenti M, Liébana E, López-Gálvez G, Manini P, Stella P, Peixe L: Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 10: Quinolones: flumequine and oxolinic acid. EFSA Journal, 19, 10 (2021). doi: 10.2903/j.efsa.2021.6862 [Paper link]
11. EFSA Panel on Biological Hazards (BIOHAZ)*, Allende A, Koutsoumanis K, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Ru G, Simmons M, Skandamis P, Suffredini E, Andersson DI, Bampidis V, Bengtsson-Palme J, Bouchard D, Ferran A, Kouba M, López Puente S, López-Alonso M, Saxmose Nielsen S, Pechová A, Petkova M, Girault S, Broglia A, Guerra B, Lorenzo Innocenti M, Liébana E, López-Gálvez G, Manini P, Stella P, Peixe L: Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 11: Sulfonamides. EFSA Journal, 19, 10 (2021). doi: 10.2903/j.efsa.2021.6863 [Paper link]
12. EFSA Panel on Biological Hazards (BIOHAZ)*, Allende A, Koutsoumanis K, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Ru G, Simmons M, Skandamis P, Suffredini E, Andersson DI, Bampidis V, Bengtsson-Palme J, Bouchard D, Ferran A, Kouba M, López Puente S, López-Alonso M, Saxmose Nielsen S, Pechová A, Petkova M, Girault S, Broglia A, Guerra B, Lorenzo Innocenti M, Liébana E, López-Gálvez G, Manini P, Stella P, Peixe L: Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 12: Tetracycline, chlortetracycline, oxytetracycline, and doxycycline. EFSA Journal, 19, 10 (2021). doi: 10.2903/j.efsa.2021.6864[Paper link]
13. EFSA Panel on Biological Hazards (BIOHAZ)*, Allende A, Koutsoumanis K, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Ru G, Simmons M, Skandamis P, Suffredini E, Andersson DI, Bampidis V, Bengtsson-Palme J, Bouchard D, Ferran A, Kouba M, López Puente S, López-Alonso M, Saxmose Nielsen S, Pechová A, Petkova M, Girault S, Broglia A, Guerra B, Lorenzo Innocenti M, Liébana E, López-Gálvez G, Manini P, Stella P, Peixe L: Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 13: Trimethoprim. EFSA Journal, 19, 10 (2021). doi: 10.2903/j.efsa.2021.6865 [Paper link]
14. Gullberg E, Cao S, Berg OG, Ilbäck C, Sandegren L, Hughes D, et al.: Selection of resistant bacteria at very low antibiotic concentrations. PLoS Pathogens 7, e1002158 (2011). doi: 10.1371/journal.ppat.1002158
15. 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]

Here’s a nice popular summary of the paper that I published with Emil Burman last month on how temperature affects the microbial model community THOR. I think Miles Martin at The Academic Times did a great distilling my ramblings into a coherent story. Good job Miles!

I did not know about The Academic Times before this but will keep an eye on this relatively new publication aiming to popularize and distill scientific content for other scientists.

In other popularization-of-science-news, I got interviewed last week by New Scientist about a very exciting paper that came out this week on travelers picking up antibiotic resistance genes in Africa and Asia. The study was quite similar to what we did back in 2015, but used a much larger data set and uncovered that there are many, many more resistance genes that are enriched after travel than what we found using our more limited dataset. Very cool study, and you can read the New Scientist summary here.

In this episode Microbiology Lab Pod, the team (Johan Bengtsson-Palme, Emil Burman, Anna Abramova, Marcus Wenne, Sebastian Wettersten and Mahbuba Lubna Akter, Shumaila Malik, Emilio Rudbeck and Camille Wuyts) discusses the evolution of antibiotic resistance from different perspectives. We also interview Rémi Gschwind about his work on novel antibiotic resistance genes in the EMBARK program.

The specific papers discussed in the pod (with approximate timings) are as follows:

• 7:45 – EMBARK website: http://antimicrobialresistance.eu
• 26:15 – Seemann, T., 2014. Prokka: rapid prokaryotic genome annotation. Bioinformatics 30, 2068–2069. https://doi.org/10.1093/bioinformatics/btu153
• 29:00 – Bengtsson-Palme, J., Larsson, D.G.J., 2015. Antibiotic resistance genes in the environment: prioritizing risks. Nature reviews Microbiology 13, 396. https://doi.org/10.1038/nrmicro3399-c1
• 29:30 – Ebmeyer, S., Kristiansson, E., Larsson, D.G.J., 2021. A framework for identifying the recent origins of mobile antibiotic resistance genes. Communications Biology 4. https://doi.org/10.1038/s42003-020-01545-5
• 54:15 – Gillings, M.R., Stokes, H.W., 2012. Are humans increasing bacterial evolvability? Trends in Ecology & Evolution 27, 346–352. https://doi.org/10.1016/j.tree.2012.02.006
• 55:15 – Woods, L.C., et al., 2020. Horizontal gene transfer potentiates adaptation by reducing selective constraints on the spread of genetic variation. Proc Natl Acad Sci USA 117, 26868–26875. https://doi.org/10.1073/pnas.2005331117
• 76:15 – Card, K.J., Thomas, M.D., Graves, J.L., Barrick, J.E., Lenski, R.E., 2021. Genomic evolution of antibiotic resistance is contingent on genetic background following a long-term experiment with Escherichia coli. Proc Natl Acad Sci USA 118, e2016886118. https://doi.org/10.1073/pnas.2016886118

The podcast was recorded on March 18, 2021. If you want to reach out to us with comments, suggestions, or other feedback, please send an e-mail to podcast at microbiology dot se or contact @bengtssonpalme via Twitter. The music that can be heard on the pod is composed by Johan Bengtsson-Palme and is taken from the album Cafe Phonocratique.

Podcast: Play in new window | Download

Subscribe: RSS

I am happy to report that today a preprint on a recent collaboration with Christian Wurzbacher‘s group came out on bioRxiv. In the preprint study, we explore microbial communities in stormwater runoff from roads in terms of microbial composition and the potential for these settings to disseminate and select for antibiotic resistance, as well as metal resistance. My part of this study is quite small; I mostly provided the analysis of resistance genes on integrons, but it was a fun study and I look forward to work more with Christian and his excellent team!

Full reference:

• Ligouri R, Rommel SH, Bengtsson-Palme J, Helmreich B, Wurzbacher C: Microbial retention and resistances in stormwater quality improvement devices treating road runoff. bioRxiv, 426166 (2021). doi: 10.1101/2021.01.12.426166 [Link]

This is the fifth episode of the Microbiology Lab Pod and has been lying around on my computer almost finished for way too long. It was recorded on September 23, and the bigger-than-ever-before crew (Johan Bengtsson-Palme, Emil Burman, Haveela Kunche, Anna Abramova, Marcus Wenne, Sebastian Wettersten and Mahbuba Lubna Akter) is joined by Fanny Berglund to discuss computational discovery of novel resistance genes. We also discuss antibiotic resistance mechanisms, particularly in Pseudomonas aeruginosa.

The specific papers discussed in the pod (with approximate timings) are as follows:

• 5:30 – Berglund, F., Johnning, A., Larsson, D.G.J., Kristiansson, E., 2020. An updated phylogeny of the metallo-b-lactamases. Journal of Antimicrobial Chemotherapy 7. https://doi.org/10.1093/jac/dkaa392
• 5:45 – Berglund, F., Österlund, T., Boulund, F., Marathe, N.P., Larsson, D.G.J., Kristiansson, E., 2019. Identification and reconstruction of novel antibiotic resistance genes from metagenomes. Microbiome 7, 52. https://doi.org/10.1186/s40168-019-0670-1
• 6:00 – Berglund, F., Marathe, N.P., Österlund, T., Bengtsson-Palme, J., Kotsakis, S., Flach, C.-F., Larsson, D.G.J., Kristiansson, E., 2017. Identification of 76 novel B1 metallo-β-lactamases through large-scale screening of genomic and metagenomic data. Microbiome 5, i29. https://doi.org/10.1186/s40168-017-0353-8
• 6:15 – Boulund, F., Berglund, F., Flach, C.-F., Bengtsson-Palme, J., Marathe, N.P., Larsson, D.G.J., Kristiansson, E., 2017. Computational discovery and functional validation of novel fluoroquinolone resistance genes in public metagenomic data sets. BMC Genomics 18, 438. https://doi.org/10.1186/s12864-017-4064-0
• 37:15 – Crippen, C.S., Jr., M.J.R., Sanchez, S., Szymanski, C.M., 2020. Multidrug Resistant Acinetobacter Isolates Release Resistance Determinants Through Contact-Dependent Killing and Bacteriophage Lysis. Frontiers in Microbiology 11. https://doi.org/10.3389/fmicb.2020.01918
• 52:15 – Leonard, A.F.C., Zhang, L., Balfour, A.J., Garside, R., Hawkey, P.M., Murray, A.K., Ukoumunne, O.C., Gaze, W.H., 2018. Exposure to and colonisation by antibiotic-resistant E. coli in UK coastal water users: Environmental surveillance, exposure assessment, and epidemiological study (Beach Bum Survey). Environment International 114, 326–333. https://doi.org/10.1016/j.envint.2017.11.003
• 53:30 – Bengtsson-Palme, J., Kristiansson, E., Larsson, D.G.J., 2018. Environmental factors influencing the development and spread of antibiotic resistance. FEMS Microbiology Reviews 42, 25. https://doi.org/10.1093/femsre/fux053
• 54:30 – Leonard, A.F.C., Zhang, L., Balfour, A.J., Garside, R., Gaze, W.H., 2015. Human recreational exposure to antibiotic resistant bacteria in coastal bathing waters. Environment International 82, 92–100. https://doi.org/10.1016/j.envint.2015.02.013
• 55:30 – Ahmed, M.N., Abdelsamad, A., Wassermann, T., et al., 2020. The evolutionary trajectories of P. aeruginosa in biofilm and planktonic growth modes exposed to ciprofloxacin: beyond selection of antibiotic resistance. npj Biofilms and Microbiomes 6. https://doi.org/10.1038/s41522-020-00138-8
• 69:30 – Rezzoagli, C., Archetti, M., Mignot, I., Baumgartner, M., Kümmerli, R., 2020. Combining antibiotics with antivirulence compounds can have synergistic effects and reverse selection for antibiotic resistance in Pseudomonas aeruginosa. PLOS Biology 18, e3000805. https://doi.org/10.1371/journal.pbio.3000805
• 79:45 – Allen, R.C., Popat, R., Diggle, S.P., Brown, S.P., 2014. Targeting virulence: can we make evolution-proof drugs? Nature reviews Microbiology 12, 300–308. https://doi.org/10.1038/nrmicro3232
• 80:45 – Köhler, T., Perron, G.G., Buckling, A., van Delden, C., 2010. Quorum Sensing Inhibition Selects for Virulence and Cooperation in Pseudomonas aeruginosa. PLoS Pathogens 6, e1000883. https://doi.org/10.1371/journal.ppat.1000883

The podcast was recorded on September 23, 2020. If you want to reach out to us with comments, suggestions or other feedback, please send an e-mail to podcast at microbiology dot se or contact @bengtssonpalme via Twitter. The music that can be heard on the pod is composed by Johan Bengtsson-Palme and is taken from the album Cafe Phonocratique.

Podcast: Play in new window | Download

Subscribe: RSS

I am very happy to share the news that I have been awarded with the Gothenburg Society of Medicine and the Sahlgrenska Academy’s prize to young researchers for our research on the effects of antibiotics on bacteria, including, of course, antibiotic resistance.

I am incredibly honoured by being selected for this award. I am also thrilled with that the Gothenburg Society of Medicine, which is a society mostly for medical doctors, sees the value in our broad, one-health, take on antibiotic resistance as well as other effect that antibiotics may have on microbes, both in the human body and in the environment. The recognition of antibiotic resistance as a one-health problem with solutions both within and outside of the typical medical setting is instrumental for our ability to curb future resistance development.

The award ceremony will take place in connection with the Gothenburg Society of Medicine’s closing meeting on 2 December, where I will present our research together with the senior awardee Professor Claes Ohlsson, who is awarded for his groundbreaking research on osteoporosis.

For a bit more than a year, I have been part of an EFSA panel on biological hazards on cross contamination with antibiotic substances in animal feed. This week the panel has launched an open consultation on sections of the draft scientific opinion, including the proposed methodology and the data gaps identified. Anyone who are interested can submit written comments before 18 November 2020, and the full information can be found at the EFSA website.

Fun things on a Friday! First of all, we have updated our lab member page with some beautiful photos! Thanks Marcus for brining your camera today!

Second, our review of factors important for antibiotic resistance development in the environment has been recognised by FEMS Microbiology Reviews as one of the papers which have made the most impact across their portfolio. It has been added to a new (well, this is old news, so semi-new) collection of papers – ‘Articles with Impact’ – many of which are very well worth a read!

Have a nice weekend!

In the third episode of Microbiology Lab Pod, recorded in June, a crew consisting of Johan Bengtsson-Palme, Emil Burman, Haveela Kunche and Anna Abramova goes into depth with what we knew about the novel coronavirus at the time. We also talk about Emil‘s master thesis, potential alternative antibiotic treatment regimes and the lung microbiome in cystic fibrosis.

Unfortunately, the sound quality of this episode is quite bad at times. We have tried to rescue the audio as best as we can, but it is still a bit annoying. We promise to do better next time!

The specific papers discussed in the pod (with approximate timings) are as follows:

• 18:15 – Lozano, G.L., Bravo, J.I., Garavito Diago, M.F., Park, H.B., Hurley, A., Peterson, S.B., Stabb, E.V., Crawford, J.M., Broderick, N.A., Handelsman, J., 2019. Introducing THOR, a Model Microbiome for Genetic Dissection of Community Behavior. mBio 10. https://doi.org/10.1128/mBio.02846-18
• 25:15 – Ghazizadeh, Z. et al. 2020 Androgen Regulates SARS-CoV-2 Receptor Levels and Is Associated with Severe COVID-19 Symptoms in Men. bioArxiv, https://doi.org/10.1101/2020.05.12.091082
• 34:45 – St. John, A.L., Rathore, A.P.S 2020. Early Insights into Immune Responses during COVID-19. The Journal of Immunology 205, 555-564. https://doi.org/10.4049/jimmunol.2000526
• 49:30 – Worobey, M., Pekar, J., Larsen, B.B., Nelson, M.I., Hill, V., Joy, J.B., Rambaut, A., Suchard, M.A., Wertheim, J.O., Lemey, P., 2020. The emergence of SARS-CoV-2 in Europe and the US. bioRxiv. https://doi.org/10.1101/2020.05.21.109322
• 52:00 – La Rosa, G., Mancini, P., Bonanno Ferraro, G., Veneri, C., Iaconelli, M., Bonadonna, L., Lucentini, L., Suffredini, E., 2020. SARS-CoV-2 has been circulating in northern Italy since December 2019: evidence from environmental monitoring. medRxiv. https://doi.org/10.1101/2020.06.25.20140061
• 52:30 – https://lakartidningen.se/aktuellt/nyheter/2020/06/viruset-kan-ha-funnits-i-dalarna-redan-i-december/
• 53:15 – Deslandes, A., Berti, V., Tandjaoui-Lambotte, Y., Alloui, C., Carbonnelle, E., Zahar, J.R., Brichler, S., Cohen, Y., 2020. SARS-CoV-2 was already spreading in France in late December 2019. International Journal of Antimicrobial Agents 55, 106006. https://doi.org/10.1016/j.ijantimicag.2020.106006
• 54:45 – Li, X., Giorgi, E.E., Marichannegowda, M.H., Foley, B., Xiao, C., Kong, X.-P., Chen, Y., Gnanakaran, S., Korber, B., Gao, F., 2020. Emergence of SARS-CoV-2 through recombination and strong purifying selection. Science Advances eabb9153. https://doi.org/10.1126/sciadv.abb9153
• 56:00 – Lehmann, D., Halbwax, M.L., Makaga, L., Whytock, R., Ndindiwe Malata, L., Bombenda Mouele, W., Momboua, B.R., Koumba Pambo, A.F., White, L.J.T., 2020. Pangolins and bats living together in underground burrows in Lopé National Park, Gabon. African Journal of Ecology 58, 540–542. https://doi.org/10.1111/aje.12759
• 61:15 – Cuthbertson, L., Walker, A.W., Oliver, A.E., Rogers, G.B., Rivett, D.W., Hampton, T.H., Ashare, A., Elborn, J.S., De Soyza, A., Carroll, M.P., Hoffman, L.R., Lanyon, C., Moskowitz, S.M., O’Toole, G.A., Parkhill, J., Planet, P.J., Teneback, C.C., Tunney, M.M., Zuckerman, J.B., Bruce, K.D., van der Gast, C.J., 2020. Lung function and microbiota diversity in cystic fibrosis. Microbiome 8. https://doi.org/10.1186/s40168-020-00810-3
• 70:15 – Hansen, E., Karslake, J., Woods, R.J., Read, A.F., Wood, K.B., 2020. Antibiotics can be used to contain drug-resistant bacteria by maintaining sufficiently large sensitive populations. PLOS Biology 18, e3000713. https://doi.org/10.1371/journal.pbio.3000713

The podcast was recorded on June 23, 2020. If you want to reach out to us with comments, suggestions or other feedback, please send an e-mail to podcast at microbiology dot se or contact @bengtssonpalme via Twitter. The music that can be heard on the pod is composed by Johan Bengtsson-Palme and is taken from the album Cafe Phonocratique.

Podcast: Play in new window | Download

Subscribe: RSS