Selected Publications

• Sénécaut N., Poulain P., Lignières L., Terrier S., Legros V., Chevreux G., Lelandais G., Camadro J.‑M. Quantitative Proteomics in Yeast: From bSLIM and Proteome Discoverer Outputs to Graphical Assessment of the Significance of Protein Quantification Scores. Yeast Functional Genomics: Methods and Protocols, 275–292, 2022. https://doi.org/10.1007/978‑1‑0716‑2257‑5_16. Presents an extended bSLIM labeling workflow for quantitative proteomics in yeast and introduces graphical strategies to assess the robustness of protein quantification scores using Proteome Discoverer outputs.:contentReference[oaicite:1]{index=1}

• Lignières L., Legros V., Khelil M., Sénécaut N., Lauber M. A., Camadro J.‑M., et al. Capillary Liquid Chromatography Coupled with Mass Spectrometry for Analysis of Nanogram Protein Quantities on a Wide‑Pore Superficially Porous Particle Column in Top‑Down Proteomics. Journal of Chromatography B, 1214, 123566, 2022. https://doi.org/10.1016/j.jchromb.2022.123566. Describes an optimized capillary LC–MS setup with wide‑pore superficially porous columns, achieving high‑quality top‑down proteomic separations from nanogram protein samples and demonstrating enhanced chromatographic resolution and versatility.:contentReference[oaicite:2]{index=2}

• Sénécaut N., Alves G., Weisser H., Lignières L., Terrier S., Yang‑Crosson L., Poulain P., Lelandais G., Yu Y.‑K., Camadro J.‑M. Novel Insights into Quantitative Proteomics from an Innovative Bottom‑Up Simple Light Isotope Metabolic (bSLIM) Labeling Data Processing Strategy. Journal of Proteome Research, 20(3):1476–1487, 2021. https://doi.org/10.1021/acs.jproteome.0c00478. Introduces the bSLIM labeling strategy and associated data‑processing workflows for deep quantitative proteomic analysis, improving the quantification of metabolic labeling experiments.:contentReference[oaicite:3]{index=3}

• Lignières L., Sénécaut N., Dang T., et al. Extending the Range of SLIM‑Labeling Applications: From Human Cell Lines in Culture to Caenorhabditis elegans Whole‑Organism Labeling. Journal of Proteome Research, 2023. https://doi.org/10.1021/acs.jproteome.2c00699. Expands SLIM‑labeling quantification approaches to multicellular systems, demonstrating successful incorporation and analysis of labeled proteomes in complex biological models.:contentReference[oaicite:4]{index=4}

PhD Manuscript

• Sénécaut N. New Quantification Approaches of Proteome Variations at the Intact Protein Level: Experimental and Computational Analyses. Université Paris – Institut Jacques Monod, 2022 (PhD Thesis). Presents an integrated experimental and computational framework for the quantification of proteome variations at the intact protein level, combining high‑resolution MS with advanced signal processing and statistical approaches.