Next-generation mass spectrometry for microbial metabolomics

We employ state-of-the-art instrumentation and specialised expertise to conduct high-throughput mass-spectrometry metabolomics across thousands of microbial extracts. Our approach integrates customised analytical pipelines with advanced pre-enrichment techniques, optimised chromatography, and innovative hybrid mass-spectrometry acquisitions — including emerging ionization technologies — to enhance detection of specific metabolite classes. We further incorporate single-cell isolation technologies to expand our access to microbial metabolic potential.

Research aims

By combining cutting-edge technologies with poly-targeted strategies for monitoring select molecular classes, we maximise both sensitivity and data interpretability. Our commitment to continuous analytical and computational refinement enables us to push detection and identification limits in high-throughput settings. Our ultimate goal is to deliver the most advanced analytical pipeline for rapid microbial-metabolome characterization, revealing the complex metabolic networks that underpin microbial functions and interactions within diverse environments.

Current projects

• ANR POPS — "Deciphering the rOle of PolyamineS in bacterial virulence" (ANR-24-CE44-1190, €193k, 2023–2027). Investigates how polyamines modulate bacterial virulence in Pseudomonas aeruginosa and Staphylococcus aureus. The HolobiomicsLab develops advanced metabolomics approaches for profiling and interpreting the S. aureus metabolome upon polyamine exposure.
• Microbiomics (Académie 4, IdEx Université Côte d'Azur, 2023, €50k). Establishes a high-throughput experimental integrative-omics pipeline, combining single-cell dispensing with rapid advanced metabolomics and state-of-the-art computation to accelerate generation of comprehensive microbial libraries.

Selected publications

• Nothias, L.-F., Schmid, R., Garlet, A., et al. (2024). Functional metabolomics of the human scalp: a metabolic niche for Staphylococcus epidermidis. mSystems, 9(2), e0035623. 10.1128/msystems.00356-23
• Kunyavskaya, O., Tagirdzhanov, A. M., Caraballo-Rodríguez, A. M., et al. (2021). Nerpa: a tool for discovering biosynthetic gene clusters of bacterial nonribosomal peptides. Metabolites, 11(10), 693. 10.3390/metabo11100693
• Cao, L., Gurevich, A., Alexander, K. L., et al. (2019). MetaMiner: a scalable peptidogenomics approach for discovery of ribosomal peptide natural products with blind modifications from microbial communities. Cell Systems, 9(6), 600–608.e4. 10.1016/j.cels.2019.09.004