My name is Johan Bengtsson-Palme. I am an assistant professor at the Division of Systems Biology at Chalmers University of Technology in Gothenburg and the Sahlgrenska Academy at University of Gothenburg, funded by the Wallenberg DDLS initiative. My research group works with data driven microbiology and microbial ecology, primarily focusing on investigating antibiotic resistance, pathogenesis and interactions in bacterial communities through large-scale experimental work, metagenomics and bioinformatics. I also have an interest in molecular taxonomy and improving the quality of reference databases. You can read more about our research interests here. To contact me, feel free to send an e-mail to my firstname.lastname@microbiology.se

Today, I will be giving a talk at the EDAR8 conference in Brisbane, which will partially cover something that I has been cooking in the research group for some time. It started off with a recurring need to see if a particular antibiotic resistance gene (ARG) was truly new or if it had been detected in previous studies. And after having done the same procedures in several studies, we started to think that maybe it would make sense to build a resource that could be used to keep track of both established and latent ARGs (1) and that could be easily updated over time. And the result is CLEVER – a scheme for Classification of Latent and Established Variants of Extant Antibiotic Resistance Genes.

CLEVER is two things. First, it is a set of definitions for ARGs, making it easier to assign them to categories, for example for risk assessment. Second, it is a database based on these criteria, and to the best of our knowledge the first resource to organize both established and latent ARGs into the same coherent database structure, while still keeping them categorized. To achieve this, CLEVER integrates data from ResFinder (2), CARD (3), ResFinderFG (4), as well as ARGs predicted by the fARGene (5) and MUSTARD (6) tools, gathered from published literature (6-13),

Very briefly, CLEVER is built on the following definitions:

• Established ARG (E): An ARG that is experimentally verified to confer antibiotic resistance and is present in human pathogens.
• Latent ARG (L): An ARG that confers a resistance function (or is predicted to do so), but does not exist in pathogens
• Mobile ARG (M): An ARG which is present on a mobile genetic element, which could be plasmids, integrons, transposons or integrative conjugative elements.
• Chromosomal ARG (C): Any ARG that does not meet the criteria for a mobile ARG above.
• Validated ARG (V): An ARG for which the resistance function has been verified in laboratory experiments, by showing that the presence of the gene increases the MIC of the host compared to an otherwise isogenic strain that does not carry the gene, or alternatively that over-expression of the gene induces a higher MIC compared to an isogenic reference strain.
• Predicted ARG (P): An ARG for which its function has not been verified experimentally (see above), but has been predicted to be an ARG by fARGene
• Structure-predicted ARG (S): An ARG for which its function has not been verified experimentally (see above), but has been predicted to be an ARG based on 3D-structure similarity by MUSTARD

Importantly, what CLEVER also does is to give names (CLEVER IDs) to latent ARGs that currently does not have any consistent way to refer to them. This makes it possible to unambiguously reference a particular ARG family across studies, which is crucial for risk assessment and understanding the spread of AMR.

Finally, by classifying ARGs as established or latent, mobile or chromosomal and verified or predicted makes it possible to identity particular latent ARGs that until now has gone under the radar. Particularly, latent ARGs that already appear on mobile genetic elements and have several mobile variants, are likely to be imminent AMR threats to human health, making them “most-wanted” ARGs that should be targeted for phenotypic evaluation and potential inclusion into AMR surveillance efforts.

By specifically looking into potential ARGs against the last-resort antibiotics carbapenems, colistin, tigecycline and plazomicin, and pulling out latent ARGs that belong to classes potentially conferring resistance to these antibiotics that are already present on plasmids, we can already present a list of five ARGs of imminent concern, which we label the first CLEVER list of most-wanted ARGs: ~blaA-145, ~blaD2-129, ~aac6p-147, ~aph2b-14, and ~aph6-89.

Naturally, there is still a lot work to be done on CLEVER, but I am very proud of what we have already, and I think that the current version (2.0) already has potential to be very useful for AMR studies. We have already started using this internally in the lab and within SEARCHER quite extensively in the last few months, so I am happy to see the use of this resource in the larger AMR community!

References:

1. Inda-Díaz JS, Lund D, Parras-Moltó M, Johnning A, Bengtsson-Palme J, Kristiansson E. Latent antibiotic resistance genes are abundant, diverse, and mobile in human, animal, and environmental microbiomes. Microbiome 2023;11:44. https://doi.org/10.1186/s40168-023-01479-0.
2. Bortolaia V, Kaas RS, Ruppe E, Roberts MC, Schwarz S, Cattoir V, et al. ResFinder 4.0 for predictions of phenotypes from genotypes. Journal of Antimicrobial Chemotherapy 2020;75:3491–500. https://doi.org/10.1093/jac/dkaa345.
3. Jia B, Raphenya AR, Alcock B, Waglechner N, Guo P, Tsang KK, et al. CARD 2017: expansion and model-centric curation of the comprehensive antibiotic resistance database. Nucleic Acids Research 2016:gkw1004. https://doi.org/10.1093/nar/gkw1004.
4. Gschwind R, Ugarcina Perovic S, Weiss M, Petitjean M, Lao J, Coelho LP, et al. ResFinderFG v2.0: a database of antibiotic resistance genes obtained by functional metagenomics. Nucleic Acids Research 2023:gkad384. https://doi.org/10.1093/nar/gkad384.
5. Berglund F, Österlund T, Boulund F, Marathe NP, Larsson DGJ, Kristiansson E. Identification and reconstruction of novel antibiotic resistance genes from metagenomes. Microbiome 2019;7, 52. https://doi.org/10.1186/s40168-019-0670-1
6. Ruppé E, Ghozlane A, Tap J, Pons N, Alvarez A-S, Maziers N, et al. Prediction of the intestinal resistome by a three-dimensional structure-based method. Nature Microbiology 2019;4:112–23. https://doi.org/10.1038/s41564-018-0292-6.
7. Inda-Díaz JS, Lund D, Parras-Moltó M, Johnning A, Bengtsson-Palme J, Kristiansson E. Latent antibiotic resistance genes are abundant, diverse, and mobile in human, animal, and environmental microbiomes. Microbiome 2023;11:44. https://doi.org/10.1186/s40168-023-01479-0.
8. Victor MP, Radisic V, Grevskott DH, Marathe NP. Hospital effluent in a low-resistance setting is responsible for dissemination of novel antibiotic resistance genes into the marine environment. Ecotoxicology and Environmental Safety 2025;301:118390. https://doi.org/10.1016/j.ecoenv.2025.118390.
9. Victor MP, Øvreås L, Marathe NP. Characterization of known and novel clinically important antibiotic resistance genes and novel microbes from wastewater-impacted high Arctic fjord sediments. Science of The Total Environment 2025;985:179699. https://doi.org/10.1016/j.scitotenv.2025.179699.
10. Li B, Jiang L, Johnson T, Wang G, Sun W, Wei G, et al. Global health risks lurking in livestock resistome. Sci Adv 2025;11:eadt8073. https://doi.org/10.1126/sciadv.adt8073.
11. Somerville V, Meola M, Nunes-Richards A, Bengtsson-Palme J, Neukamm J, Majander K, et al. Microbial community dynamics in a traditional Swiss mountain cheese over 142 years of cheesemaking 2026. https://doi.org/10.64898/2026.02.26.708305.
12. Coche‐Miranda J, Arros P, Canales N, Berríos‐Pastén C, Azziz G, Lagos R, et al. Antarctic soil microbiomes encode structurally conserved and phylogenetically diverse beta‐lactamases. iMetaOmics 2026;e70118. https://doi.org/10.1002/imo2.70118.
13. Wang K, Xu J, Li X, Zhu P, Suo R, Lu X, et al. Evolutionary selection of trimethoprim-resistant dfrA genes in lytic phages affects phage and host fitness during infection. Sci Adv 2025;11:eadt4817. https://doi.org/10.1126/sciadv.adt4817.

I am happy to (finally) report that the second part of Emil Burman‘s PhD thesis was published over the weekend in FEMS Microbiology Letters! This paper has spent almost a year in peer review, but that’s even more reason to celebrate that it is finally out.

In this paper, we have studied how Pseudomonas aeruginosa compete with other members in microbial communities (1). To study this, we introduced two different P. aeruginosa strains into the microbial model community THOR (2): the relatively non-virulent PAO1 and the model strain for virulent P. aeruginosa PA14. First of all, we could show that P. aeruginosa invasion significantly disrupted the biofilms formed by THOR. In addition, this disruption was greater, both in terms of reduction of biofilm biomass and changes in microbial community composition, during invasion with PA14 than for PAO1. This suggests that the virulence traits expressed by P. aeruginosa can also play a role in its ability to outcompete other microbes, i.e. that virulence and competition traits are linked.

Along these lines, we also studied the invasion ability of an O-antigen-deficient P. aeruginosa strain, which had even further reduced competitive ability. Finally, we investigated two naturally occurring P. aeruginosa isolates for their invasion ability in THOR: the clinical isolates CCUG73475 (from a patient with septic bacteremia) and CCUG71613 (from a patient with chronic pneumonia). Invasion with the pneumonia-derived isolate CCUG71613 resulted in minimal changes to the THOR community, while invasion with the sepsis-derived isolate CCUG73475 led to a reduction in the CFU counts of all THOR community members, suggesting differences in virulence and competition traits between different clinical isolates.

The paper was a collaboration with Lars Jelsbak and Mikkel Anbo at the Technical University of Denmark, and was conceived during a visit that Emil and I did there in 2022. Emil actually looked at a whole bunch of strains with their O-antigens replaced, but in the end the virulence story was the most coherent one we could tell, and the rest of the O-antigen data will likely be sitting on a shelf never to be released. Sometimes academia works like that. But I am happy about the outcome of our collaboration with Lars and Mikkel!

The study builds on our work on different disturbances to community interactions in THOR, where Emil has previous work on how temperature changes the interactions between the community members (3). We also have data on genes in P. aeruginosa that are important for community invasion in THOR which is in the pipeline to be submitted, along with a study on antibiotic exposure on P. aeruginosa. So even if Emil has defended his thesis the work on his work lives on!

References

1. Burman E, Anbo M, Jelsbak L, Bengtsson-Palme J: Virulent strains of Pseudomonas aeruginosa are more disruptive during invasion of a microbial model community. FEMS Microbiology Letters, fnag090 (Advance article) (2026). doi: 10.1093/femsle/fnag090
2. Lozano GL, Bravo JI, Garavito Diago MF, Park HB, Hurley A, Peterson SB, Stabb EV, Crawford JM, Broderick NA, Handelsman J: Introducing THOR, a Model Microbiome for Genetic Dissection of Community Behavior. mBio, 10, 2, e02846-18 (2019). doi: 10.1128/mBio.02846-18
3. Burman E, Bengtsson-Palme J: Microbial community interactions are sensitive to small differences in temperature. Frontiers in Microbiology, 12, 672910 (2021). doi: 10.3389/fmicb.2021.672910

I am very happy to report on our most recently published paper – and the first one I have co-authored with my PhD supervisor Joakim Larsson in more than six years – which is a product of the BIOCIDE project. In the paper, published in FEMS Microbiology Ecology, Daniel Jaén-Luchoro has been collecting hundreds of MIC data points for biocides and metals to create the first complete and relatively comparable (more on that in a bit) dataset of bacterial sensitivity data for biocides (1).

This was a much bigger undertaking that in might sound like, but it is important for out understanding of how potent metals and biocides are for inhibiting bacterial growth. Basically, Daniel has been putting together an entire EUCAST (2,3) for biocides and metals, which is potentially extremely useful. This in turn can be used to better estimate the risks for co-selection of resistance to antibiotics.

Daniel was able to collect data for 53 antibacterial biocides, 21 metals, and 17 related compounds, resulting in 20,378 MIC values across 164 bacterial species. Of course the data is very overrepresented by clinically relevant organisms, including Staphylococcus aureus and Escherichia coli. Also, certain biocides were studied more than others, such as chlorhexidine and benzalkonium chloride, which was also true for metals that were mostly represented by copper, zinc, arsenic, cadmium and silver.

Importantly, we saw that there is a variety of method to measure MICs for biocides and metals, which means that a lot of the data is not directly comparable. Also, some authors did not even report the exact conditions they measured MICs under. This emphasizes the urgent need for standardized susceptibility testing methodology and consistent terminology for research on biocide and metal resistance. By centralizing MIC data, we provide an important foundation for future efforts to assess ecological risks and co-selection with antibiotic resistance. We aim to integrate this into an update to the BacMet database (4,5) that hopefully will be come available in the near future!

References

1. Jaén-Luchoro D, Larsson DGJ, Bengtsson-Palme J: Bacterial sensitivity distributions for biocides and metals. FEMS Microbiology Ecology, Advance article fiag075 (2026). http://dx.doi.org/10.1093/femsec/fiag075
2. https://mic.eucast.org
3. Kahlmeter G, Turnidge J: Wild-type distributions of minimum inhibitory concentrations and epidemiological cut-off values—laboratory and clinical utility. Clinical Microbiology Reviews 36:e00100-22. https://doi.org/10.1128/cmr.00100-22
4. http://bacmet.biomedicine.gu.se
5. 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). http://dx.doi.org/10.1093/nar/gkt1252

I’ve been terribly bad at keeping updates on what we have published in the last year or so – there have just been a bit too much other things to do. So I thought it was time to take a look at what we have published in the last year before some really cool stuff hits the press this summer and fall (hopefully more on that soon!!)

Let’s start with some EMBARK/SEARCHER output. Several lab members (Anna, Marcus and I) have been involved in a paper using functional metagenomics to find novel cefiderocol resistance genes (1). We found four resistance genes, including three ꞵ-lactamases (VEB-3, an OXA-372 homolog, and a YbxI homolog) and a partial penicillin-binding protein homolog, none of which had been previously reported as a cefiderocol resistance gene. The blaVEB-3 gene was associated with a mobile genetic element. We could find three of them using shotgun metagenomics, showing that the blaVEB-3 gene was widespread across France, Sweden, Germany and Pakistan, hinting at efficient dissemination of this gene.

I have also been involved in a collaboration paper with Thomas Berendonk and Uli Klümper‘s labs, where we investigate if fish can be sentinels of environmental antibiotic resistance, and it turns out that they are… not great for that (2).

On the topic of antibiotic resistance gene (ARG) dissemination, Máté Vass (now at SLU) lead a study published in Communications Biology investigating how water stratification affects horizontal gene transfer, with a focus on ARGs (3). The main finding of this paper is that water stratification is a constraint on horizontal gene transfer, which may have implications on how we think about ARG spread through water environments.

While we are at the topic of large-scale quantifications of ARGs in big data sets, I was super-happy to be part of a collaboration with Katariina Pärnänen on how gender (and other factors) impact ARGs in the human microbiome (4). I kept telling Katariina that this would probably yield nothing – the microbiome data was too noisy, and the signal will get lost. Yet, she persisted, and indeed it turned out we are at the point where there is enough human microbiome data to get a signal even if there is a lot of noise. So hats off to Katariina, this was your “what did I say” moment with me!

Then we have a set of mechanistic AMR studies on ARG evolution. First, Lisa Teichmann published parts of her PhD thesis, first on the gradual evolution of fluoroquinolone resistance in E. coli (5) and how this is related to the SOS response in bacteria. She then followed up with a somewhat similar paper on amoxicillin evolution in E. coli (6). The general picture of these two papers on how E. coli adapts genetically to antibiotic stress is that resistance evolution is highly antibiotic-specific and that canonical stress-response or mutagenic pathways do not uniformly explain adaptive trajectories.

Somewhat connected, Nathália Abichabki recently published a paper where we propose screening cut-off values and tolerance disk tests (TDtests) for detection of tolerance/persistence to ceftazidime-avibactam in Klebsiella pneumoniae (7). This is also related to a bunch of papers on tolerance and low-level resistance to antibiotics that will be coming out of Nathália’s thesis, so there is more coming on this front soon!

Finally – on the AMR front – Anna Abramova led an effort together with Veronika Pettersen to investigate possibility for integration of AMR surveillance systems in the Nordic countries that recently got published in Public Health (8). Anna and Veronika did a huge amount of work on this paper, but this was largely the outcome of several meetings on the NoMoReAMR consortium, where we pinpointed missed opportunities for surveillance in the otherwise relatively homogenous Nordic countries. I hope to get to work more with this consortium in the future, as I think that we have had very fruitful discussions on both AMR research and monitoring and when and where it is useful.

And so two papers not related to AMR: We had a very nice collaboration with Daniel Bojar‘s group coming out late last year in Nature Communications, looking – from many different angles – at seal milk oligosaccharides and their potential uses. While the cool finding in this paper is that seal milk seems even more complex than human breast milk in terms of milk oligosaccharides (9), we did not contribute too much in that part. Instead, Mirjam Dannborg was studying the effects of these oligosaccharides on pathogen biofilms, work that will also be part of her PhD thesis when she defends this fall!

Finally, in a collaboration with colleagues in Brazil, we published a review article on the outlook for combining 3D organoid cultures and high-throughput analysis techniques to better understand host-pathogen interactions (10). This was the result of a cross-visit collaboration between Brazil and Sweden, where me and Mirjam visited the lab of Elaine de Martinis, and Elaine, Leonardo Andrade and Nathália Abichabki visited our lab back in 2023. It’s nice to see our discussions take paper form and I hope to be working more with this wonderful team in Brazil!

Papers mentioned:

1. Gschwind R, Bonnet M, Abramova A, Jarquín-Díaz VH, Wenne M, Löber U, Godron N, Kampouris ID, Tskhay F, Nahid F, Debroucker C, Bui-Hai M, El Aiba I, Klümper U, Berendonk TU, Forslund-Startceva SK, Zahra R, Bengtsson-Palme J, Ruppé E: Cefiderocol resistance genes identified in environmental samples using functional metagenomics. ISME Journal, 20, 1, wrag010 (2026). doi: 10.1093/ismejo/wrag010 [Paper link]
2. Tskhay F, Köbsch C, Elena AX, Bengtsson-Palme J, Berendonk TU, Klümper U: Fish are poor sentinels for surveillance of riverine antimicrobial resistance. One Health, 20, 101026 (2025). doi: 10.1016/j.onehlt.2025.101026 [Paper link]
3. Vass M, Abramova A, Bengtsson-Palme J: Antimicrobial resistance dissemination via horizontal gene transfer is constrained in stratified waters. Communications Biology, 9, 435 (2026). doi: 10.1038/s42003-026-09857-8 [Paper link]
4. Salehi M, Laitinen V, Bhanushali S, Bengtsson-Palme J, Collignon P, Beggs JJ, Pärnänen K, Lahti L: Gender differences in global antimicrobial resistance. npj Biofilms and Microbiomes, 11, 79 (2025). doi: 10.1038/s41522-025-00715-9 [Paper link]
5. Teichmann L, Luitwieler SH, Bengtsson-Palme J, ter Kuile BH: Fluoroquinolone-specific resistance trajectories in E. coli and their dependence on the SOS-response. BMC Microbiology, 27, 37 (2025). doi: 10.1186/s12866-025-03771-5 [Paper link]
6. Teichmann L, Wenne M, Luitweiler S, Dugar G, Bengtsson-Palme J, ter Kuile B: Genetic Adaptation to Amoxicillin in Escherichia coli: The Limited Role of dinB and katE. PLoS ONE, 20, 2, e0312223 (2025). doi: 10.1371/journal.pone.0312223 [Paper link]
7. Abichabki N, Bellissimo-Rodrigues F, Gaspar GG, Pocente RHC, Lima DAFS, Bollela VR, Braga GUL, De Martinis ECP, Ferreira JC, Darini ALC, Bengtsson-Palme J, Andrade LN: Proposal for screening cut-off values and use of Tolerance Disk Test (TDtest) for detection of tolerance/persistence to ceftazidime-avibactam in Klebsiella pneumoniae. Diagnostic Microbiology and Infectious Disease, 116, 3, 117515 (2026). doi: 10.1016/j.diagmicrobio.2026.117515 [Paper link]
8. Abramova A, Baral A, Osińska AD, Metsä-Simola N, Räisänen K, Ribeiro Duarte AS, Helgason KO, Halldórsdóttir AM, Pärnänen K, Skov Simonsen G, Sariola S, Lahti L, Bengtsson-Palme J, Wasteson Y, Munk P, Pettersen VK: Roadmap for integrated One Health AMR surveillance in Nordic countries. Public Health, 255, 106285 (2026). doi: 10.1016/j.puhe.2026.106285 [Paper link]
9. Jin C, Lundstrøm J, Cori CR, Guu S-Y, Bennett AR, Dannborg M, Bengtsson-Palme J, Hevey R, Khoo K-H, Bojar D: Seal milk oligosaccharides rival human milk complexity and exhibit functional dynamics during lactation. Nature Communications, 16, 10067 (2025). doi: 10.1038/s41467-025-66075-2 [Paper link]
10. de Martinis ECP, Alves VF, Pereira MG, Andrade LN, Abichabki N, Abramova A, Dannborg M, Bengtsson-Palme J: Applying 3D cultures and high-throughput technologies to study host-pathogen interactions. Frontiers in Immunology, 16 (2025). doi: 10.3389/fimmu.2025.1488699[Paper link]

I am happy to share the news that my first doctoral student – Emil Burman – successfully defended his thesis yesterday, and can now introduce himself as Dr. Burman.

And in what a way he defended! During the three hour defense, he was asked all the hard questions from his opponent – Akos Kovács – who did an amazing job bringing out Emil’s vast and diverse knowledge of the field. In fact, the committee noted afterwards that it took more than one and a half hours of questioning before Emil had to admit “I don’t know the answer to that”.

Emil’s thesis, titled “Genetic Contributions to Invasion and Biofilm Disruption in a Microbial Model Community“, used the microbial model community THOR (1) to investigate community responses to environmental stress and microbial invasion. The thesis (2) consists of five papers, the first dealing with how temperature affects THOR (3), the second with how pathogenicity is related to competition ability in a community setting, the third about the genetic determinants of antibiotic susceptibility in Pseudomonas aeruginosa, the fourth about invasion with P. aeruginosa into THOR, and the last one is a proteomics study about one of the strongest hits in paper IV.

Emil has used a range of techniques, including traditional microbiological assays, transposon mutagenesis (INSeq), and proteomics, to identify genetic determinants of community stability and disruption. This has allowed him to explore how cooperative traits emerge and how pathogens like Pseudomonas aeruginosa interfere with community dynamics. His thesis can be found in an online version here.

References

1. Lozano GL, Bravo JI, Garavito Diago MF, Park HB, Hurley A, Peterson SB, Stabb EV, Crawford JM, Broderick NA, Handelsman J: Introducing THOR, a Model Microbiome for Genetic Dissection of Community Behavior. mBio, 10, 2, e02846-18 (2019). doi: 10.1128/mBio.02846-18
2. Burman E: Genetic Contributions to Invasion and Biofilm Disruption in a Microbial Model Community. PhD Thesis, University of Gothenburg (2025). https://gupea.ub.gu.se/handle/2077/87262
3. Burman E, Bengtsson-Palme J: Microbial community interactions are sensitive to small differences in temperature. Frontiers in Microbiology, 12, 672910 (2021). doi: 10.3389/fmicb.2021.672910

Over the last week, I have been featured in media in different ways, so here’s a quick summary.

I was asked to provide a comment on a recent paper on how microplastics affect antibiotic resistance development (1) for an article in Scientific American (2). I am not sure I had that much intelligent to say, other than to caution about jumping to conclusions, as we still know quite little about the risks associated with microplastics and AMR: “How much of a threat plastic-derived drug-resistant pathogens pose to humans is a question that remains to be fully understood” is one of my two quotes from the article.

I also was interviewed last week for Swedish Radio’s Vetenskapsradion (in Swedish) about another study showing that, e.g., ibuprofen could drive bacteria to higher mutation rates, indirectly triggering antibiotic resistance development (3). Such interaction effects have also been seen elsewhere (4), but the fact that they see this effect for such a commonly used drug as ibuprofen – one of our most standard painkillers – is a little bit concerning. Still I stress in the interview that we need to know much more about these interaction effects before jumping to clinical guidance.

Finally, the Foundation for Strategic Research has released the video they recorded about our research last fall. It is in Swedish, but with English subtitles, so this could be worth a watch!

References

1. Gross N, Muhvich J, Ching C, Gomez B, Horvath E,Nahum Y, Zaman MH: Effects of microplastic concentration, composition, and size on Escherichia coli biofilm-associated antimicrobial resistance. Appl Environ Microbiol, 91, e02282-24, (2025). https://doi.org/10.1128/aem.02282-24
2. Zaraska M: Microplastics Could Be Turning Bacteria into Drug-Resistant Superbugs. Scientific American, 2025-08-26. https://www.scientificamerican.com/article/microplastics-could-be-creating-dangerous-antibiotic-resistant-bacteria/
3. Chen H, Sapula SA, Turnidge J, et al.: The effect of commonly used non-antibiotic medications on antimicrobial resistance development in Escherichia coli. npj Antimicrob Resist 3, 73 (2025). https://doi.org/10.1038/s44259-025-00144-w
4. Maier L, Pruteanu M, Kuhn M, et al.: Extensive impact of non-antibiotic drugs on human gut bacteria. Nature 555, 623–628 (2018). https://doi.org/10.1038/nature25979

This spring and summer have seen some changes to the composition of the research group, with people both coming and going. First of all, we have said goodbye to two postdocs who have worked in the lab for quite some time – Máté Vass and Daniel Jaén Luchoro. Máté is moving on to a position in Uppsala, at the Swedish University of Agriculture where he will start building up his own research group. Daniel is returning to a full time position at the Sahlgrenska Hospital, where he will keep doing part-time research. We look forward to keeping on working with both of them in their new roles!

Furthermore, we also say goodbye and thank for their wonderful contributions to the lab our two master students: Emilia Valfridsson and Felix Blomfelt. Both will be greatly missed, and they have made very valuable contributions to the group’s work, which (hopefully…) will result in publications relatively soon!

Finally, we would like to extend a somewhat belated welcome to our new postdoc Yuselys Garcia-Martinez who joined us in January. Yuselys will be working in the SEARCHER project on discovering novel antibiotic resistance genes in environmental and animal microbiomes.

On a personal note, this is the first time some of my long-term lab members leave the lab, so this feels especially sad to me. At the same time, they are moving on to new exciting roles, and maintaining and developing these relationships will be an interesting continuation of my journey as a group leader.

I have written an editorial piece for the Swedish Pathogens Portal in which I reflect a bit on the upcoming EU legislation requiring monitoring of AMR in major wastewater treatment plants (1). I also veer a bit into where environmental monitoring outside of sewage may play a role, using our review paper resulting from EMBARK as the starting point (2).

This is timed to coincide with the registration deadlines for two upcoming workshops on AMR surveillance in the environment; the first being the DDLS Symposium on Data-Driven Environmental Monitoring of Infectious Disease on 7th-8th October in Uppsala, which I have been part of organising. The second is a workshop organised by CARe in Gothenburg on 28th October on the theme of sewage surveillance of antibiotic resistance, focusing on the new EU requirements.

My hope is that you will be a bit provoked by this and come to one of these workshops to discuss AMR surveillance and where to go next!

1. Bengtsson-Palme J: Surveillance of antimicrobial resistance – flying blind or flying behind? The Swedish Pathogens Portal, Editorial (2024). doi: 10.17044/scilifelab.27045433 [Link]
2. Bengtsson-Palme J, Abramova A, Berendonk TU, Coelho LP, Forslund SK, Gschwind R, Heikinheimo A, Jarquin-Diaz VH, Khan AA, Klümper U, Löber U, Nekoro M, Osińska AD, Ugarcina Perovic S, Pitkänen T, Rødland EK, Ruppé E, Wasteson Y, Wester AL, Zahra R: Towards monitoring of antimicrobial resistance in the environment: For what reasons, how to implement it, and what are the data needs? Environment International, 178, 108089 (2023). doi: 10.1016/j.envint.2023.108089 [Paper link]

Together with Anna Székely, I have been working on the organization of a DDLS Symposium on Data-Driven Environmental Monitoring of Infectious Diseases on October 7 – 8, in Uppsala.

The symposium will focus on promoting and enhancing data-driven environmental assessment for infectious diseases (including antibiotic-resistant bacteria) across various settings using diverse approaches. We now invite submission of abstracts for short talks.

Deadline for abstract submission: 18 September 
Deadline to register to attend: 25 September –> REGISTER HERE! <– This includes abstract submission.

Link to more information and the PROGRAM

I hope to see all of you working with AMR in the environment in Uppsala in October!

Ákos Kovács had the brilliant idea of putting up a temporary resource for things you bring up in a talk that you can point people to. I did not do this before my talk at ISME today, but I thought the idea was so good, so here’s a summary and collection of my ISME short-talk on the EMBARK outcomes today:

• More information on EMBARK and its successor SEARCHER can be found on the project website, here: http://antimicrobialresistance.eu Importantly, this is a team effort over four years and I only touched on a few selected things
• Within the project we have looked at typical background levels of antibiotic resistance in the environment. We have already published some of these results (for qPCR abundances) in Abramova et al. 2023
• The average resistance gene in the average environment is present in ~1 in 1000 bacteria, but the variation between different genes is huge
• Depending on monitoring goal, different target genes are relevant to use. See this table adapted from Abramova et al. 2023:

• We have also tried to make different monitoring methods for environmental AMR comparable. Those mentioned in the talk were selective culturing for resistant bacteria, qPCR and shotgun metagenomics
• This data is not yet published, but overall we see relatively good correlation between qPCR and metagenomics. This is not true for all genes, though, and unfortunately neither qPCR nor metagenomics is always better than the other
• Culturing data is not very good at predicting specific antibiotic resistance gene abundances as the class level
• Finally, we have developed methods for discovering new types of ARGs, as seen in the ResFinderFG database: Gschwind et al. 2023
• We have also used these new methods to look at differences between established ARGs and latent ARGs in a variety of environments: Inda-Díaz et al. 2023
• Our ultimate goal in EMBARK would be to develop a modular framework for environmental monitoring of antibiotic resistance. You can read more about our thinking and goals in the review paper we published last year: Bengtsson-Palme et al. 2023