M2 Internship: Longitudinal analysis of gut microbiome dynamics following antibiotic exposure

SFBI; Rouen; Sur place; EUR 10 000 - 15 000; Temps partiel

Résumé du poste

SFBI in Rouen, France, offers a M2 internship focused on longitudinal analysis of gut microbiome dynamics after antibiotic exposure. You will work on metagenomic data processing, gene function analysis, and statistical analyses of microbial communities, contributing to the ABIME study on UTI patients.

The role requires a Master 2 or final-year student in bioinformatics or related fields with programming and Linux experience, plus basic knowledge of statistics and molecular biology.

Qualifications

• Master 2 or final-year engineering student in bioinformatics, computational biology, biostatistics, or related field.
• Competence in at least one programming language and experience with Linux.
• Basic knowledge of statistics and molecular biology.

Responsabilités

• Data processing (quality control, human read removal, taxonomic profiling, etc.).
• Identification and characterization of functional genes, particularly antimicrobial resistance genes.
• Microbial diversity and differential abundance analyses.

Description du poste

M2 Internship: Longitudinal analysis of gut microbiome dynamics following antibiotic exposure

Context

Urinary tract infections (UTIs) are among the major indications for antibiotic use worldwide1. However, exposure to antibiotics can disrupt the gut microbiota and exert a selective pressure favoring antimicrobial resistance2. Further, recent studies have highlighted differences in the extent of these disruptions and subsequent recovery depending on the antibiotic used and between individuals3,4. The prospective observational ABIME study investigates these dynamics in patients treated for UTIs. More than 150 stool samples have been collected longitudinally, before, during, and after exposure to different antibiotics. These samples have been sequenced using shotgun metagenomics and are available for analysis.

Objective

The main objective is to characterize the microbial and functional dynamics of the gut microbiome following exposure to several antibiotics used to treat UTIs.

Missions

The intern will mainly contribute to the computational analysis of the metagenomes, including: (i) data processing (quality control, human read removal, taxonomic profiling, ...); (ii) identification and characterization of functional genes, particularly antimicrobial resistance genes; and (iii) microbial diversity and statistical differential abundance analyses.

Profile and required skills.

We are looking for a Master 2 or final-year engineering student in bioinformatics, computational biology, biostatistics, or a related field. Competence in at least one programming language and experience with Linux are required. Basic knowledge of statistics and molecular biology is also required. Previous experience with Git, HPC environments, or workflow managers would be an advantage but could also be learned during the internship.

• Timm, M. R., Russell, S. K. & Hultgren, S. J. Urinary tract infections: pathogenesis, host susceptibility and emerging therapeutics. Nat Rev Microbiol 23, 72-86 (2025).
• Palleja, A. et al. Recovery of gut microbiota of healthy adults following antibiotic exposure. Nat Microbiol 3, 1255-1265 (2018).
• Anthony, W. E. et al. Acute and persistent effects of commonly used antibiotics on the gut microbiome and resistome in healthy adults. Cell Reports 39, 110649 (2022).
• Olivares, C. et al. A modelling framework to characterize the impact of antibiotics on the gut microbiota diversity. Gut Microbes 17, 2442523 (2025).