My PhD supervisor Joakim Larsson has an opening for a PhD student at University of Gothenburg. The project is on the role of different wastewaters in the evolution of antibiotic resistance, and will be centered on bioinformatic analyses of large-scale data. The project will encompass analysis of bacterial growth curve data through machine learning to antibiotics with selective effects in different wastewaters. Comparative genomics and different AI-based approaches will be applied to large-scale public genome and metagenome data to better understand how resistance genes are mobilized and transferred to pathogens.
Joakim is a great scientist with a vibrant group, so if your interests is in line with the position, I strongly suggest you take a look at it! Deadline is October 30! Application link here: https://web103.reachmee.com/ext/I005/1035/job?site=7&lang=UK&validator=9b89bead79bb7258ad55c8d75228e5b7&job_id=30401
My colleague and friend Clemens Wittenbecher has an open doctoral student position at Chalmers in Data-Driven Precision Health Research. Clemens works with developing novel biomarker panels to quantify individual disease risk. The project itself will focus on innovative machine learning and artificial intelligence approaches to integrate multi-layer -omics data with bioimages of cardiovascular and metabolic tissues (computer tomography, ultrasound and magnetic resonance imaging).
Clemens is a fantastic person and a great supervisor so if your interests is in line with the position, I strongly suggest you take a look at it! Application link here:
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.
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!
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!
- 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
- 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
- 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
- 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.
- 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]
- 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
- Bengtsson-Palme J, Larsson DGJ: Antibiotic resistance genes in the environment: prioritizing risks. Nature Reviews Microbiology, 13, 369 (2015). doi: 10.1038/nrmicro3399-c1
- 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
- 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.
- 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]
- 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).
- 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).
- Fettweis JM, Serrano MG, Brooks JP, et al.: The vaginal microbiome and preterm birth. Nature Medicine, 25, 6, 1012-1021 (2019).