Author: Johan

ITSx in Galaxy

I am happy to share with you that since a couple of months back there is an up-to-date version of ITSx available through Galaxy! The tool can be found here: https://usegalaxy.eu/root?tool_id=itsx

The person behind this is really Björn Grüning at the University of Freiburg. I am immensely thankful for the work he has put into this. Our intention to make sure that both the Galaxy version and the bioconda version are maintained in parallel to the one on this website, and continuously up to date!

Happy barcoding!

Published papers: Environmental monitoring of antibiotic resistance

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

New team members

Time is passing quickly, and I have not appropriately acknowledged the many newcomers we’ve had to the lab in the past couple of months. With this post I would like to say welcome to the lab to Máté Vass and Dani Jáen Luchoro (both postdocs), Jorge Agramont and Josue Mamani Jarro (doctoral students), as well as Nathália Abichabki (visiting doctoral student from Brazil)! Some of you have already spent a couple of months in the group and we very much enjoy having you here!

A week or so ago, we took this new lab picture with everyone (except for Lisa, who is in Amsterdam). I am very proud to be working with group of extremely talented, smart, funny and goodhearted people!

Very briefly, Dani will be working on updating the BacMet database as part of the BIOCIDE project, and shares his time between my group, Joakim Larsson‘s group and the Sahlgrenska hospital. Máté was recruited within the DDLS program and will work on inferring the metacommunity ecology of antibiotic resistance based on analysis of large-scale datasets. Jorge and Josue are part of the same SIDA-funded doctoral student exchange program with Bolivia and will work on different aspects of environmental antibiotic resistance and the spread of diarrheal pathogens through the environmental matrix. Nathália, finally, is working on understanding the tolerance mechanisms to antibiotics in Klebsiella pneumoniae.

All of you are very welcome to the group!

Published paper: Preterm infant microbiome and resistome

Together with our collaborators in Tromsø in Norway, we published a paper over the weekend in eBioMedicine describing the early colonization patterns of preterm infants, both in terms of the microbes that arrive early to the infants, but also in terms of the antibiotic resistance genes they carry.

In the paper (1), which is a continuation of an earlier study by part of the team (2), we analysed metagenomic data from six Norwegian neonatal intensive care units to better understand the bacterial microbiota of infants born preterm or on term and receiving different treatments. These groups included probiotic-supplemented and antibiotic-exposed extremely preterm infants (n = 29), antibiotic-exposed very preterm infants (n = 25), antibiotic-unexposed very preterm infants (n = 8), and antibiotic-unexposed full-term infants (n = 10). Stool samples were collected from the infants after 7, 28, 120, and 365 days of life and were analysed using shotgun metagenomics. We were particularly interested in the maturation of the preterm infant microbiome into a ‘normal’ healthy gut microbiome, and the colonization with bacteria carrying antibiotic resistance genes.

We found that microbiota maturation was largely determined by the length of hospitalisation for the infants and how much preterm they were. The use of probiotics rendered the gut microbiota and resistome of extremely preterm infants more alike to term infants on day 7 and partially restored the loss of species interconnectivity and stability associated with preterm delivery. Finally, colonisation with Escherichia coli was associated with the highest number of antibiotic-resistance genes in the infant microbiomes, followed by Klebsiella pneumoniae and Klebsiella aerogenes.

Being born very preterm, along with prolonged hospitalisation and frequent antibiotic use alters early life resistome and mobilome, leading to an increased gut carriage of antibiotic resistance genes and mobile genetic elements. On the other hand, the effect of probiotics was not unidirectional. Probiotics decreased resistome burden, but at the same time the bacterial strains in the probiotics appear to promote the activity of mobile genetic elements. Here, further study of the gut microbiota is necessary to be able to design strategies aiming to lower disease risk in vulnerable preterm infants.

As mentioned, this study was a collaboration with Veronika Pettersen‘s group in Tromsø, particularly Ahmed Bargheet, who have done a fabulous job on the bioinformatics and analysis of this study. I hope that we will continue this collaboration in the future (first step will be me visting Tromsø again in June!) This also continues a nice little “sidetrack” of the group’s research into the early life microbiome – previously represented by the work of Katariina Pärnänen (3) and Tove Wikström‘s vaginal microbiome study (4), which is a very interesting and relevant subject in terms of both medicine and microbial ecology. We are also setting up new collaborations in this area, so I hope that more will come out of this track in the next couple of years.

Finally, thank you Veronika for inviting me to participate in this great project!

References

  1. Bargheet A, Klingenberg C, Esaiassen E, Hjerde E, Cavanagh JP, Bengtsson-Palme J, Pettersen VK: Development of early life gut resistome and mobilome across gestational ages and microbiota-modifying treatments. eBio Medicine, 92, 104613 (2023). doi: 10.1016/j.ebiom.2023.104613
  2. Esaiassen E, Hjerde E, Cavanagh JP, Pedersen T, Andresen JH, Rettedal SI, Støen R, Nakstad B, Willassen NP, Klingenberg C: Effects of Probiotic Supplementation on the Gut Microbiota and Antibiotic Resistome Development in Preterm Infants. Frontiers in Pediatrics, 16, 6, 347 (2018). doi: 10.3389/fped.2018.00347
  3. Pärnänen K, Karkman A, Hultman J, Lyra C, Bengtsson-Palme J, Larsson DGJ, Rautava S, Isolauri E, Salminen S, Kumar H, Satokari R, Virta M: Maternal gut and breast milk microbiota affect infant gut antibiotic resistome and mobile genetic elements. Nature Communications, 9, 3891 (2018). doi: 10.1038/s41467-018-06393-w
  4. Wikström T, Abrahamsson S, Bengtsson-Palme J, Ek CJ, Kuusela P, Rekabdar E, Lindgren P, Wennerholm UB, Jacobsson B, Valentin L, Hagberg H: Microbial and human transcriptome in vaginal fluid at midgestation: association with spontaneous preterm delivery. Clinical and Translational Medicine, 12, 9, e1023 (2022). doi: 10.1002/ctm2.1023

Emil’s halftime

Some good news from the lab! Emil Burman today passed his halftime control, which means that we now can look forward to around more years of fun science together! We all congratulate Emil on this great achievement which marks an important milestone in the group, as Emil is the first of the PhD students who have reached it to this point!

Published paper: The latent resistome

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

Pandemic Preparedness Portal

I am happy to announce that I am joining the editorial committee of the Swedish Pandemic Preparedness Data Portal (formerly the Swedish COVID-19 portal). I will join five other researchers associated with SciLifeLab and will work together with the portal team to maximise the utility of the Portal for researchers, expand its content beyond SARS-CoV-2, and increase engagement with the research community. My main responsibility areas will be antibiotic resistance and emerging pathogens.

Since 2022 the portal is part of the SciLifeLab Pandemic Laboratory Preparedness (PLP) Program. It is operated by the SciLifeLab Data Centre. Over time, the popularity of the Portal has increased within the research community, the general public, and those involved in healthcare, industry, and policy making. I very much look forward to work with Luisa Hugerth (Uppsala University), Laura Carroll (Umeå University), Benjamin Murrell (Karolinska Institute), Mahmoud Naguib (Uppsala University) and Johan Ankarklev (Stockholm University) on the future of the portal!

Published report: UNEP One Health AMR response

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

20 positions for data scientists

I thought this could be interesting to some. SciLifeLab has opened 20 permanent staff positions for the new Data platform and Data Science Nodes (DSNs) organised within the DDLS program (that also funds my current position). These can be exciting opportunities to work with big data for someone who might not want to climb the academic group leader career ladder. The positions are spread out over Stockholm, Uppsala, Gothenburg and Linköping and can be found here.