Metabolism is not merely a source of energy: it continuously instructs gene regulation by shaping chromatin marks and transcriptional programs. Over the years, I have progressively investigated this metabolism-gene regulation axis across complementary biological scales and questions - from skin physiology and microbiome-host interactions to the regulation of cellular senescence and its pathophysiological consequences in aging and cancer. Along this path, I have pursued integrative studies bridging genetics, functional genomics, and systems modeling to understand how metabolic rewiring reshapes regulatory networks in diverse physiological and pathophysiological settings. These projects have provided me with strong expertise in molecular and cellular biology as well as computational biology, including bioinformatics, data integration, and network inference. At the interface of experimental biology and computation, I have developed an integrated view of how metabolic states translate into epigenetic and transcriptional programs that govern cell fate decisions, including senescence. Moving forward, I will build on this framework to address pathophysiological questions at the intersection of metabolism, epigenetics, and aging.

I am currently working at the Montpellier Cancer Research Institute as a postdoctoral fellow, in the unit Molecular Oncogenesis headed by Laurent Le Cam.

My research connects experimental biology, functional genomics and computational modelling to understand how metabolic states reshape regulatory networks. Across projects, I combine molecular and cellular biology with RNA-seq, ATAC-seq, CUT&RUN, ChIP-seq, metabolomics, quantitative genetics and machine-learning strategies to move from omic profiles to mechanistic hypotheses.

ATAC-seq as an integrative assay for aging and cancer

Developing ATAC-seq beyond chromatin accessibility into an all-in-one assay for genetic, epigenetic and aging-related signatures.

Skin microbiome and metabolome crosstalk

Integrative microbiome and metabolome analyses to understand how microbial communities shape skin physiology, barrier function and inflammatory risk.

p53/E4F1-mediated metabolic and epigenetic control of senescence

Dissecting how p53-associated metabolic programs, pyruvate metabolism and acetyl-CoA production shape chromatin states and stabilize senescence during aging.

Toward a systems view of cellular senescence

Time-resolved multi-omic analyses of senescence to identify regulatory hierarchies, chromatin transitions and vulnerabilities in aging and cancer.

Combined DNA and RNA sequencing for RNA editing event discovery

A stringent DNA/RNA-seq framework to distinguish genuine RNA editing events from sequencing, mapping and biological noise.

Integrating linkage analysis with whole genome sequencing to dissect complex phenotypes

Combining linkage mapping, whole-genome sequencing, selection signatures and expression QTLs to prioritize causal genes for complex traits.

Selected papers highlighting the main biological questions and methodological approaches developed across my research trajectory.

For the complete publication record, open the Publications page from the navigation menu.

My teaching connects molecular mechanisms with practical data analysis. I focus on helping biologists move from a biological question to an experimental strategy, a reproducible workflow and a critical interpretation of the results.

Molecular basis of cellular senescence and aging

Lectures connecting senescence, p53 biology, metabolism, epigenetics and aging-related pathophysiology for Master-level biology and health students.

Epigenomic data analysis with UNIX and R

Hands-on training in ChIP-seq, ATAC-seq and MNase-seq analysis, from sequencing quality control to peak calling, normalization and functional interpretation.

In silico in-depth analyses of transcriptomic data with UNIX

Practical training for biologists in RNA-seq data analysis with UNIX, from raw data quality control to alignment, variant calling and transcript model inference.

Visualisation of genomic data with ggplot

Training in data visualization with R and ggplot, with emphasis on readable figures, exploratory analysis and reproducible communication of genomic data.

I have supervised or co-supervised research trainees at doctoral, Master 2 and Master 1 levels, mainly on projects combining functional genomics, bioinformatics, epigenomics, metabolism and senescence biology.

Mentoring snapshot

• 1 PhD student co-supervised on aging, senescence and metabolic adaptability.
• 7 Master 2 internships in bioinformatics, epigenomics, cancer biology and structural genomics.
• 2 Master 1 internships in molecular and cellular biology.
• Member of a PhD thesis committee.

Recent projects include ATAC-seq-based detection of cancer mutations and genome instability, p53/E4F1-mediated metabolic and epigenetic reprogramming during senescence, molecular signatures of senescence from multi-omic data, and in vivo metabolic adaptation during aging.

• pierre-francois.roux@inserm.fr
• Campus Val d'Aurelle, 208 avenue des Apothicaires, 34298 Montpellier cedex 5 FRANCE