Category: EMBARK

First of all, I just want to do a last reminder of PhD student position in bioinformatics and artificial intelligence applied to antibiotic resistance with Erik Kristiansson as main supervisor that closes tomorrow. More info here!

Second, two of my best and dearest colleagues at University of Gothenburg – Kaisa Thorell and Åsa Sjöling – have open postdoc positions in molecular microbiology (with Åsa) and bacterial proteomics (with Kaisa). Both of these are great opportunities to work with fantastic people on exciting subjects, so you should check these out if you are looking for postdoc positions in microbiology, molecular biology or bioinformatics! There are only a few days left to apply for these positions, so go ahead and do it now!

Finally, I am again tooting our own horn with the postdoc in innovative approaches to antibiotic resistance monitoring (within the SEARCHER program) in my own group. More info here, deadline is on July 31 with interviews to take place in August.

As part of the SEARCHER program, we are now hiring a two-year postdoc to work with innovative approaches to antibiotic resistance monitoring. You can read more about the position here and at Chalmers’ job portal, but in short we are after a wet-lab postdoc who are willing to do field work and laboratory studies to identify novel antibiotic resistance genes.

Please do not send me your CV and application letter via e-mail, but apply through the Chalmers application portal. Sending your CV to me will not increase your changes. Only contact me about this position if you have actual, relevant questions about the position (as I will otherwise get lots of unwanted e-mails…) Those questions, I am happy to answer!

This paper came out just about the same time as the PhD position with Erik Kristiansson where I will be co-supervisor was announced, and I did not want to steal that thunder with another news item, but it is now time to highlight the fantastic work of Víctor Hugo Jarquín-Díaz on antibiotic resistance genes in the gut microbiomes of mice across a gradient of pure and hybrid genotypes in the European house mouse hybrid zone. This came out in mid-April in ISME Communications and presents the interesting hypothesis that hybridisation not only shapes bacterial communities, but also antibiotic resistance gene occurrences (1).

This study is based on 16S rRNA amplicon sequencing of gut bacteria in natural populations of house mice. From this we have predicted the antibiotic resistance gene composition in the microbiomes, and found a significant increase in the predicted antibiotic resistance gene richness in hybrid mice. In other words, more and different antibiotic resistance genes were found in the hybrid mice than in the non-hybridised individuals. We believe that this could be due to a disruption of the microbiome composition in hybrid mice. The aberrant microbiomes in hybrids represent less complex communities, potentially promoting selection for resistance.

It deserves to be mentioned that this is more of a pilot study, which we hope to follow up with a more proper study targeting the resistance genes in the mice microbiomes. That said, our work suggests that host genetic variation impacts the gut microbiome and antibiotic resistance gene, at least in mice. This raises further questions on how the mammalian host genetics impact antibiotic resistance carriage in bacteria via microbiome dynamics or interaction with the environment.

I am very happy to have been part of this EMBARK collaboration with the Sofia Forslund-Startceva and Emanuel Heitlinger labs! And I am especially thankful to Víctor who pulled off this very thought-inducing study!

Reference

1. Jarquín-Díaz VH, Ferreira SCM, Balard A, Ďureje Ľ, Macholán M, Piálek J, Bengtsson-Palme J, Kramer-Schadt S, Forslund-Startceva SK, Heitlinger E: Aberrant microbiomes are associated with increased antibiotic resistance gene load in hybrid mice. ISME Communications, ycae053 (2024). doi: 10.1093/ismeco/ycae053 [Paper link]

Erik Kristiansson, who was co-supervisor for my PhD thesis, has an opening for a PhD student funded by the DDLS program. The project is combining bioinformatics and artificial intelligence with a focus on large-scale data analysis to better understand antibiotic resistance and the emergence of novel resistance genes. The research will be centered on DNA sequence analysis, inference in biological networks, and modelling of evolution. The primary applications will be related to antibiotic resistance and bacterial genomics.

I am particularly excited about this position because I will have the benefit of co-supervising the student. The student will also be part of the DDLS research school which is now being launched, which is also super-exciting for Swedish data driven life science.

The candidate is expected to have a degree in bioinformatics, mathematical statistics, mathematics, computer science, physics, molecular biology, or any equivalent topic. Previous experience in analysis of large-scale biological data is desirable. It is important to have good computing and programming skills (e.g. in Python and R), experience with the Linux/UNIX computer environment, and, to the extent possible, previous experience in working with machine learning and/or artificial intelligence.

I had such a good time with Erik as my co-supervisor, and he has put together a truly amazing supervision team with Joakim Larsson, Anna Johnning and myself. I could not imagine a better place to apply bioinformatics and ML/AI on antibiotic resistance! Deadline is June 7! Application link here: https://www.chalmers.se/om-chalmers/arbeta-hos-oss/lediga-tjanster/?rmpage=job&rmjob=12840&rmlang=SE

Time to do a rundown of conferences and meetings I will attend this fall. Double-check with your calendars and please reach out if you’re also going, so we can meet up!

September 21-24: Nordic Society of Clinical Microbiology and Infectious Diseases (NSCMID), in Örebro, Sweden. I will give a talk about the EMBARK work in the Saturday session on Metagenomics in infection, inflammatory disease and the environment

October 5-6: Conference on ‘Optimal practices to protect human health care from antimicrobial resistance selected in the veterinary domain’ organised by The Netherlands Food and Consumer Product Safety Authority (NVWA) in Amsterdam, the Netherlands. I will chair a session on October 6 on Next generation sequencing for bioinformatic based surveillance.

October 18-22: 32º Congresso Brasileiro de Microbiologia, in Foz do Iguaçu, Brazil. I will give a talk in the Saturday session (the 21st) on the use of model systems all the way to global surveillance systems to prevent future pandemics.

November 15-16: DDLS Annual Meeting, in Stockholm Sweden. I am in the organising committee for this event with the theme “The emerging role of AI in data-driven life science”.

November 17: DDLS Cell and Molecular Biology Minisymposium.

November 29: GOTBIN Annual Workshop, in Gothenburg Sweden.

This will be a fun (but intense!) fall!

I just want to point potential doctoral students’ attention to this fantastic opportunity to work with my EMBARK colleague Luis Pedro Coelho as he sets up his new lab in Brisbane in Australia at the relatively new Centre for Microbiome Research. Luis is looking for two PhD students, one who will focus on identifying and characterising the small proteins of the global microbiome and one more related to developing novel bioinformatic methods for studying microbial communities.

I can highly recommend this opportunity given that you are willing to move to Australia, as Luis is one of the most brilliant scientists I have worked with, is incredibly easy-going and fosters a lab culture I strong support. More information and application here.

In just a few days, Environment International has published two papers coming out from the EMBARK consortium which are somewhat connected to each other.

The first (or technically the second, but the other order makes more sense when explaining this…) is the first paper involving most of the people who have been working in the EMBARK consortium for an extended period of time. It’s an overview paper titled “Towards monitoring of antimicrobial resistance in the environment: For what reasons, how to implement Itit, and what are the data needs?” (1) and I think the title describes the topic pretty well. Basically, we go through why it would be interesting to monitor for antibiotic resistance in the environments, how that could be implemented and what we would need to know to get there.

The very condensed story is that if one is considering implementing monitoring for environmental resistance, these are a few things that should be considered:

• The purpose of monitoring: What is the motivation? What should be achieved? What type of risk should be assessed? What type of action would monitoring enable?
• Choice of methods: Which methods are economically feasible? Which methods would deliver results within a useful timeframe for taking appropriate actions?
• Targeted environments: In what type of environment would monitoring for a given purpose be worthwhile?
• Intended users: Who would be able to use, implement and act upon this strategy?
• Integration potential: How does this monitoring integrate with other monitoring efforts? How can the resulting data be communicated?

We then dive into the knowledge gaps we are currently facing, and particularly highlight the following areas:

• Establish how different existing methods for monitoring resistance compare to each other
• Extend pathogen-centric databases for resistance genes with latent resistance genes (2)
• Determine the locations and type of environments relevant for resistance monitoring
  To reduce costs, utilizing already existing environmental monitoring should be prioritized, as should locations integrated into operating or planned surveillance programs. More efforts should also be made to identify additional pathways for resistance transmission through the environment.
• Study the environment as a source and transmission route for antibiotic resistance
  Stratify risks associated with resistance genes found in the environment. Define typical levels of antibiotic resistance in different environments (3), and define how these levels change over time.
• Identify settings where the relationship between fecal bacteria and antibiotic resistance is absent
  Usually, these levels follow each other, but the environments where they don’t are important as they deviate from the expected baseline of resistance. This knowledge can aid in identifying situations in which it would be helpful to investigate a microbial community for resistance to specific antibiotics.
• Identify the origins for more antibiotic resistance genes (4)
  This knowledge will be instrumental in preventing the emergence of new forms of resistance in pathogens in the future.

An important outcome of this paper is that we realise that we are still not at a level of understanding where routine monitoring for resistance in the environment can be easily justified or implemented. Still, there is a need for monitoring data in natural environments to even get started, and therefore we support the implementation of national, regional and global of initiatives without having all the scientific answers. The lack of comprehensive understanding should not be an obstacle to starting environmental monitoring for AMR, nor for action against environmental development and spread of AMR.

The second paper is very much related to the first, in that it actually tries to address one of these knowledge gaps: the need for normal background levels of antibiotic resistance in different environments. In this paper, Anna Abramova did an herculean effort collecting (we hope) all qPCR data on antibiotic resistance gene abundances in the environment for the past two decades. All in all, she collected data for more than 1500 samples across 150 studies and integrated these into an analys of what we could consider normal levels of resistance in different environments.

For an ‘average’ resistance gene, we found that the normal relative abundance range was form 10^-5 to 10^-3 copies per bacterial 16S rRNA, or that around one in 1,000 bacteria would carry a given resistance gene. This level varied quite a bit between different resistance genes, however, but not so much between environmental types (except for in human and animal feces, where some resistance genes were clearly more abundant, most prominently tetracycline resistance genes). What was more striking was that there was a clear difference between environments impacted or likely impacted by human activities, as opposed to more pristine environments with little to none human impact. Some resistance genes, such as tetA, tetG, blaTEM and blaCTX-M, showed very marked differences between these impacted and non-impacted environments, making them great markers of human-activity-associated resistance.

Our final recommendations with regards to monitoring include:

• Include the intI1, sul1, blaTEM, blaCTX-M and qnrS genes in environmental monitoring, along with a selection of tetracycline resistance genes, including either tetA or tetG.
• Other potential target genes could be sul3, vanA, tetH, aadA2, floR, ereA and mexF, which are abundant in some environments, but are not often included in qPCR studies of environmental AMR
• If a gene deviates from the expected 10^-5 to 10^-3 interval, this warrants further investigation of the causes.
• Maximum acceptable levels need to be determined not only taking relative abundances of genes into account, but also risks to human health as well as the numbers of bacteria in a given volume of sample into account (5,6) and transmission routes to humans (7)
• The different standards of reporting DNA abundances constituted a complicating factor for this study. Both abundances of resistance genes relative to the 16S rRNA gene and to the sample volume or weight should be reported.
• The absence of clear trends of increases or decreases in resistance gene abundances over time indicates a need for more systematic time series data in a variety of environments.

Our results also highlighted the scarcity of resistance gene data from parts of the world, particularly from Africa and South America, and underscores the need for a concerted effort to quantify typical background levels of resistance in the environment more broadly to enable efficient environmental surveillance schemes akin to those that exist in clinical and veterinary settings.

I encourage anyone with an interesting these topics to at least skim the full papers [Monitoring overview paper here, Normal qPCR resistance abundances here]. These will be great resources and I am very proud of them both. I would really like to thank the entire EMBARK team and our collaborators in CORNELIA, WastPAN and in other organisations. I would also like to thank Anna for her hard work on collecting and analysing the qPCR data for around two years. It has been a long ride, and I think we are both happy, proud and a bit relieved to finally see this paper published!

References

1. 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, 108089 (2023). doi: 10.1016/j.envint.2023.108089
2. 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, 11, 44 (2023). doi: 10.1186/s40168-023-01479-0
3. Abramova A, Berendonk TU, Bengtsson-Palme J: A global baseline for qPCR-determined antimicrobial resistance gene prevalence across environments. Environment International, 178, 108084 (2023). doi: 10.1016/j.envint.2023.108084
4. 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
5. Larsson DGJ, Andremont A, Bengtsson-Palme J, Brandt KK, de Roda Husman AM, Fagerstedt P, Fick J, Flach C-F, Gaze WH, Kuroda M, Kvint K, Laxminarayan R, Manaia CM, Nielsen KM, Ploy M-C, Segovia C, Simonet P, Smalla K, Snape J, Topp E, van Hengel A, Verner-Jeffreys DW, Virta MPJ, Wellington EM, Wernersson A-S: Critical knowledge gaps and research needs related to the environmental dimensions of antibiotic resistance. Environment International, 117, 132–138 (2018). doi: 10.1016/j.envint.2018.04.041
6. Pruden A, Larsson DGJ, Amézquita A, Collignon P, Brandt KK, Graham DW, et al. Management options for reducing the release of antibiotics and antibiotic resistance genes to the environment. Environmental Health Perspectives, 121, 878–885 (2013). doi:10.1289/ehp.1206446
7. 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

What is the latent resistome? This is a term we coin in a new paper published yesterday in Microbiome. In the paper, we distinguish between the small number antibiotic resistance genes (ARGs) that are established, well-characterized, and available in existing resistance gene databases (what we refer to as “established ARGs”). These are typically ARGs encountered in clinical pathogens and are often already causing problems in human and animal infections. The remaining latently present ARGs, which we denote “latent ARGs”, are less or not at all studied, and are therefore much harder to detect (1). These latent ARGs are typically unknown and generally overlooked in most studies of resistance. They are also seldom accounted for in risk assessments of antibiotic resistance (2-4). This means that our view of the resistome and its diversity is incomplete, which hampers our ability to assess risk for promotion and spread of yet undiscovered resistance determinants.

In our new study, we try to alleviate this issue by analyzing more than 10,000 metagenomic samples. We show that the latent ARGs are more abundant and diverse than established ARGs in all studied environments, including the human- and animal-associated microbiomes. The total pan-resistomes, i.e., all ARGs present in an environment (including the latent ARGs), are heavily dominated by these latent ARGs. In contrast, the core resistome (the ARGs that are commonly encountered) comprise both latent and established ARGs.

In the study, we identified several latent ARGs that were shared between environments or that are already present in human pathogens. These are often located on mobile genetic elements that can be transferred between bacteria. Finally, we also show that wastewater microbiomes have surprisingly large pan- and core-resistomes, which makes this environment a potent high-risk environment for mobilization and promotion of latent ARGs, which may make it into pathogens in the future.

It is also interesting to note that this new study echoes the results of my own study from 2018, showing that soil and water environments contain a high diversity of latent ARGs (or ARGs not found in pathogens as I put it in the 2018 study), despite being almost devoid of established ARGs (5).

This project has been a collaboration with Erik Kristiansson’s research group, and particularly with Juan Inda-Diáz. It has been great fun to work with them and I hope that we will keep this collaboration going into the future! The study can be read in its entirety here.

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, 11, 44 (2023). doi: 10.1186/s40168-023-01479-0 [Paper link]
2. Martinez JL, Coque TM, Baquero F: What is a resistance gene? Ranking risk in resistomes. Nature Reviews Microbiology 2015, 13:116–123. doi:10.1038/nrmicro3399
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. Bengtsson-Palme J: Assessment and management of risks associated with antibiotic resistance in the environment. In: Roig B, Weiss K, Thoreau V (Eds.) Management of Emerging Public Health Issues and Risks: Multidisciplinary Approaches to the Changing Environment, 243–263. Elsevier, UK (2019). doi: 10.1016/B978-0-12-813290-6.00010-X
5. Bengtsson-Palme J: The diversity of uncharacterized antibiotic resistance genes can be predicted from known gene variants – but not always. Microbiome, 6, 125 (2018). doi: 10.1186/s40168-018-0508-2

UNEP last week published their report on one health responses to antimicrobial resistance (1), which I have taken part in writing (well, I think I ultimately only contributed a few sentences here and there, but apparently that counts to be listed among the report’s contributors). The report, named “Bracing for Superbugs: Strengthening environmental action in the One Health response to antimicrobial resistance” showcases the evidence for that the environment plays a key role in the development, transmission and spread of AMR.

The report tries to unpack the different aspects of environmental AMR, and offers a fairly comprehensive picture of where the science stands on the subject. We also conclude that a systems effort – “One Health” – recognizing that the health of people, animals, plants and the environment are closely connected, is needed to tackle AMR.

This report analyzes the three economic sectors and their value chains that are key drivers of AMR development and spread in the environment: pharmaceuticals and other chemicals, agriculture including the food chain, and healthcare, together with pollutants from poor sanitation, sewage and waste effluent in municipal systems.

I am very happy to have been part of this report writing team and I hope that this will spur future action on AMR from a one-health perspective. You can read the entire report here.

Reference

1. United Nations Environment Programme (2023). Bracing for Superbugs: Strengthening environmental action in the One Health response to antimicrobial resistance. Geneva

I am very happy to share with you that our two doctoral students funded by the Wallenberg DDLS initiative have now started. One of them – Marcus Wenne – is already a well-known figure in the lab, as he has been with us as a master student and then as a bioinformatician for more than a year. The other student – Vi Varga – is a completely new face in the lab and just started yesterday.

Marcus will work in a project on global environmental AMR. He will also continue on his work on large-scale metagenomics to understand community dynamics and antibiotic resistance selection in microbial communities subjected to antibiotics selection. Marcus will work very closely to EMBARK and continue the important work we have done in that project over the next four years.

Vi will study responses of microbial communities to change, with a particular focus on comparative genomics and transcriptional approaches. We will link this to both community stability, pathogenesis and resistance to antibiotics, so this project involves a little bit of everything in terms of the lab’s research interests. Vi’s background is in comparative genomics and pathogenesis, so this seems to be the perfect mix to be able to carry out this project successfully!

Very welcome to the lab Marcus and Vi! We look forward to work with you for the next four years or so!