معرفی
Dr Guillaume Meric is an Associate Professor and Senior Lecturer in the Department of Life Sciences at the University of Bath, UK. He is also a group leader in clinical microbiology, microbial (meta)genomics, and bioinformatics. He holds a clinical affiliate appointment with the Cambridge-Baker Systems Genomics Initiative, a joint program between the Baker Heart & Diabetes Institute (Australia) and the University of Cambridge (UK). Additionally, he has honorary appointments at Uppsala University (Sweden), the University of Melbourne, La Trobe University, and Monash University (Australia).
His research focuses on the bioinformatic analysis of large-scale human population cohort datasets with microbial components, particularly metagenomic sequences from the gut. His work explores host-microbe interactions, the role of the microbiome in diseases like diabetes and cardiovascular conditions, the impact of medications on the gut resistome, and the genetic basis of pathogen variation. Key interests include:
- Ecology of bacterial pathogens in the human gut
- Genetic basis of pathogenic variation
- Effects of antibiotics and non-antibiotic drugs on the microbiome
- Links between gut microbiota, host genetics, diet, and disease
- Human gut archaeome and lifestyle associations
His recent publications (2024–2025) demonstrate a strong trend in analyzing population-level microbiome data, particularly from the FINRISK cohort, to understand how diet, alcohol, and antimicrobials influence gut microbial communities and disease risk. These studies employ advanced metagenomic and computational techniques, contributing to precision medicine and public health.
Dr Meric contributes to UN Sustainable Development Goals related to good health and well-being. His work has been cited in scientific literature and picked up by news outlets and social media platforms. He is accepting doctoral students and leads the MericLab research group.
He is actively engaged in interdisciplinary collaborations across the UK, Australia, and Sweden, particularly in systems genomics and microbiome research. His work is supported by data from large population cohorts and involves extensive computational and statistical modeling.
