Tag: Bioinformatics

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

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

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.

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!

Last week, we published a paper which has been cooking for a long time. It is the result of years of hard work from particularly the first author – Tove Wikström – but also Sanna who did the bulk of the bioinformatic analysis with some help from me (well, I mostly contributed as a sounding board for ideas, but hopefully that was useful). The paper describes the gene expression of both the human host and the microbial community in the vagina during pregnancy and how the expressed genes (and the composition of bacteria) are linked to early births (1) and was published in Clinical and Translational Medicine.

We found 17 human genes potentially influencing preterm births. Most prominently the kallikrein genes (KLK2 and KLK3) and four different forms of of metallothioneins (MT1s) were higher in the preterm group than among fullterm women. These genes may be involved in inflammatory pathways associated with preterm birth.

We also found 11 bacterial species associated with preterm birth, but most of them had low occurrence and abundance. In contrary to some earlier studies, we saw no differences in bacterial diversity or richness between women who delivered preterm and women who delivered at term. Nor did Lactobacillus crispatus – often proposed to be protective against preterm birth (2,3) – seem to be a protective factor against preterm birth. However, most other studies have used DNA-based approaches to determine the bacterial community composition, while we used a metatranscriptomic approach looking at only expressed genes. In this context it is interesting that other metatranscriptomic results (4) agree with ours in that it was mainly microbes of low occurrence that differed between the preterm and term group.

Overall, the lack of clear differences in the transcriptionally active vaginal microbiome between women with term and preterm pregnancies, suggests that the metatranscriptome has a limited ability to serve as a diagnostic tool for identification of those at high risk for preterm delivery.

Great job Tove and the rest of the team! It was a pleasure working with all of you! The entire paper can be read here.

References

1. 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 [Paper link]
2. Kindinger LM, Bennett PR, Lee YS, et al.: The interaction between vaginal microbiota, cervical length, and vaginal progesterone treatment for preterm birth risk. Microbiome, 5, 1, 1-14 (2017).
3. Tabatabaei N, Eren AM, Barreiro LB, et al.: Vaginal microbiome in early pregnancy and subsequent risk of spontaneous preterm birth: a case-control study. BJOG, 126, 3, 349-358 (2019).
4. Fettweis JM, Serrano MG, Brooks JP, et al.: The vaginal microbiome and preterm birth. Nature Medicine, 25, 6, 1012-1021 (2019).

Our open doctoral student and postdoc positions closed over the weekend, and in total we had 110 applications, although some persons applied to more than one of the positions, bringing the total number of applicants down a bit. Still, this will be a lot of work for me. I will prioritize the postdoc position, as this had the fewest applications. So if you applied to one of the two PhD student positions, please give it some time.

A quick skimming of the applications shows that we have had extraordinary high quality of applications overall, although some of the applicants will be a bit too wet-lab oriented for these specific positions.

Thanks a lot for your interest in the lab’s work! I appreciate all of your efforts!

As I wrote a few days ago, I have now started my new position at Chalmers SysBio. This position is funded by the SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS), which also funds PhD and postdoc positions. We are now announcing two doctoral student projects and one postdoc project within the DDLS program in my lab.

Common to all projects is that they will the use of large-scale data-driven approaches (including machine learning and (meta)genomic sequence analysis), high-throughput molecular methods and established theories developed for macro-organism ecology to understand biological phenomena. We are for all three positions looking for people with a background in bioinformatics, computational biology or programming. In all three cases, there will be at least some degree of analysis and interpretation of large-scale data from ongoing and future experiments and studies performed by the group and our collaborators. The positions are all part of the SciLifeLab national research school on data-driven life science, which the students and postdoc will be expected to actively participate in.

The postdoc and one of the doctoral students are expected to be involved in a project aiming to uncover interactions between the bacteria in microbiomes that are important for community stability and resilience to being colonized by pathogens. This project also seeks to unearth which environmental and genetic factors that are important determinants of bacterial invasiveness and community stability. The project tasks may include things like predicting genes involved in pathogenicity and other interactions from sequencing data, and performing large-scale screening for such genes in microbiomes.

The second doctoral student is expected to work in a project dealing with understanding and limiting the spread of antibiotic resistance through the environment, identifying genes involved in antibiotic resistance, defining the conditions that select for antibiotic resistance in different settings, and developing approaches for monitoring for antibiotic resistance in the environment. Specifically, the tasks involved in this project may be things like identifying risk environments for AMR, define potential novel antibiotic resistance genes, and building a platform for AMR monitoring data.

For all these three positions, there is some room for adapting the specific tasks of the projects to the background and requests of the recruited persons!

We are very excited to see your applications and to jointly build the next generation of data driven life scientist! Read more about the positions here.

Today was a big day, as it was my first ‘real’ working day at SysBio at Chalmers University of Technology. (Quotation marks as I have had access to an office at SysBio for a few weeks, and also because I spend the afternoon on meetings at Sahlgrenska.) Regardless, this marks the start of a transition period where the lab will be moving more and more of our routines to Chalmers, which will culminate when the lab-dependent persons will move into our new labs after the summer.

We also welcomed our Erasmus intern Manuela Seehauser to the lab today, as well as Marius Surleac who is visiting us for a few weeks from Romania.

Finally, we have announced new positions related to my new Chalmers-funding. More on those soon. Speaking of jobs, if you’re interested in doing a bioinformatics postdoc with me and Joakim Larsson you have two more days to apply for that position!

Together with Joakim Larsson‘s lab, we now have an open two-year postdoc position in bioinformatics on antibiotic resistance and biocide resistance. The development of antibiotic resistance has been driven by use of antibiotics, but antibacterial biocides also have the potential to select for antibiotic resistance. However, knowledge of which genes that contribute to biocide resistance and could be associated with antibiotic resistance is sparse. To some extent, such genes are documented in the BacMet database which we have developed, but this collection of resistance genes is only scratching the surface of all biocide resistance that exists among bacteria in the environment.

We are now looking for a postdoctoral fellow to continue the important work on bioinformatic analysis of biocide and antibiotic resistance to answer the question whether increasing biocide resistance would be a threat to human health. The postdoc will be working with the development of the BacMet database to make it more targeted towards biocidal substances and products in addition to resistance genes. The tasks include bioinformatic sequence analysis, literature studies and database and web programming. The work will also include investigations of the prevalence of the identified resistance genes in genomes and metagenomes.

The recruited person will work closely with both my group and the group of Prof. Joakim Larsson, and will participate in the JPIAMR-funded BIOCIDE project. You can apply to the postdoc position at the University of Gothenburg application portal: https://web103.reachmee.com/ext/I005/1035/job?site=7&lang=UK&validator=9b89bead79bb7258ad55c8d75228e5b7&job_id=25122

The deadline is May 4, 2022. Come work with us on this exciting topic in the intersect between two great research environments (if I may say it myself!) We look forward to your application!

I have very big and exciting news to share with you. After more than 10 years at the Sahlgrenska Academy, me and my lab will be moving from the University of Gothenburg to Chalmers University of Technology (which is physically a move of less than a kilometer, so still within Gothenburg). I have been offered a position at the Division of Systems Biology, funded by the SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS). The total funding to my lab will be 17 million SEK, with some co-funding from Chalmers added in on top of that.

I am of course very excited about this opportunity, which will bring some infrastructure that we need in-house that we don’t have easy access to today. At the same time, I am sad to leave my academic ‘home’, and the fantastic people we have been working with there for the years. I am also endlessly thankful for the support and trust that the Sahlgrenska Academy, the Institute of Biomedicine and the Department of Infectious Diseases have put into me and my research over the past years.

The transition to Chalmers will start already in May, but will be gradual and continue for a long time. We have close ties to the Sahlgrenska Academy and we will keep closely collaborating with researchers there. I will also retain an affiliation to the University of Gothenburg, at least for the near future.

All in all, this year will bring very interesting development, and this additional funding from the DDLS program will allow us to venture into new areas of bioinformatics and try out ideas that have previously been out of reach. I look forward to work with our new colleagues at Chalmers and within the DDLS program in the coming years!