Mots-Clés

microbial epigenetics methylation mobile genetic elements horizontal gene transfer

Description

Interplay between diversification of methylation systems, their target specificity and genetic mobility

The information content of the genetic alphabet is not limited to the primary nucleotide sequence but is also conveyed by chemical modifications of individual bases. This additional layer of ’epigenetic’ information shows distinct degrees of chemical diversity and complexity, and is found to be pervasive across all kingdoms of life. Propelled by recent progresses in third-generation sequencing technologies — SMRT-seq by Pacific Biosciences and nanopore sequencing by Oxford Nanopore Technologies (ONT) — more than 5,100 methylomes have been mapped to date. As a consequence, the field of bacterial epigenomics is witnessing a remarkable expansion beyond single methylome analyses to the realm of multi-omic data integration. Our recent findings on the epigenomics of bacteria [1-6] add to the growing number of studies integrating multi-omics profiling to identify putative epigenetic regulation networks.

We have previously observed an overabundance of MTases (both solitary and belonging to R-M systems) in MGEs [1]. Several of these MTases were non-specific, which increases the spectrum of possible methylation signatures. Such property might be exploited to overcome common host restriction barriers employing, for example, Type I and III restriction enzymes as the principal barrier to control against infection. In other words, these MTases may serve as antidotes against R-M systems and thereby facilitate infection of new hosts and competition with other MGEs. Heterogeneous methylation (either as an ON <-> OFF switch or through modifications of the target motif sequence), can be caused by spontaneous mutations in MTase coding genes by slipped-strand mispairing of simple sequence repeats (SSRs) or recombination between inverted repeats (the so called phasevarions or phase-variable regulons). Such heterogeneous methylation may lead to changes in gene expression and generate phenotypic plasticity within isogenic populations, thus aiding in the rapid adaptation to environmental shifts. While several studies have described multiple strategies of methylation systems’ diversification, we currently lack a detailed understanding of the interplay between such diversification, methylation specificity, and genetic mobility.

Here we aim to perform a large-scale mapping of high-quality methylomes across bacteria and archaea and use comparative genomics to test multiple hypotheses linking methylation specificity, and the success of certain mobilome elements in carving preferential routes of transfer. The ideal candidate will have a strong interest in working in the integration, interpretation and visualization of large biological datasets. Proficiency in UNIX-Linux shell is expected as well as proficiency in at least one of the following programming languages (R/Bioconductor, Python, Perl, C++). Experience in working on high performance computing/cluster platforms will be a plus. The candidate will benefit from a highly dynamic and interdisciplinary environment, including biologists, microbiologists, computer scientists, and bioinformaticians. The Genoscope (French National Sequencing Centre) has a long-standing tradition in the broad field of genomics. After having been one of the players in the human genome project, and supporting more than 650 projects serving the national scientific community, it currently focuses on the genomics of environmental organisms (e.g. TARA, BGE, ATLASEA, projects), bacterial flora of the human digestive tract, among others. This Ph.D. position will be funded pending the successful outcome of a joint candidate / lab application to the MICROBES internship call from University of Paris-Saclay (ranked in the world’s top15 universities). The contract is expected to start in January 2024.

References

1. Oliveira PH et al (2014). Nucleic Acids Res 42(16), 10618-31

2. Oliveira PH et al (2016). Proc Natl Acad Sci USA 113(20), 5658-63

3. Oliveira PH et al (2020). Nat Microbiol 5(1), 166-80

4. Oliveira PH and Fang G (2020). Trends Microbiol 29: 28-40

5. Oliveira PH (2021). mSystems, 6

6. Beavogui et al (2023). Biorxiv DOI: 10.1101/2023.08.12.553040