Tag: Bioinformatics

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.

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

I am very happy to welcome Agata Marchi back to the group as a PhD student! Agata was a master student in the group last year, doing a thesis focused on implementing a bioinformatic approach to identify differences between the genomes of host-associated and non host-associated strains of Pseudomonas aeruginosa. While one of her first tasks will be to complete this work and prepare it for publication, her doctoral studies will primarily be on the interactions between bacteria and between bacteria and host in the human microbiome and how these relate to complex diseases. She will focus on developing and applying machine learning methods to better understand this interplay.

I am – as the rest of the group – very happy to welcome Agata back to the lab!

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:

https://www.chalmers.se/en/about-chalmers/work-with-us/vacancies/?rmpage=job&rmjob=11810&rmlang=UK

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.

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!

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