Biology subjects

Gillet, L. C.

Publications and source records attributed to Gillet, L. C..

2 recordsLinked to original sources

bioRxiv2020

Network analysis identifies regulators of lineage-specific phenotypes in Mycobacterium tuberculosis

The Mycobacterium tuberculosis (Mtb) complex includes ten phylogenetically distinct human-adapted lineages with varying geographical distributions and pathogenicity. Lineage 1 (L1) is associated with low virulence, while Lineage 2 (L2) is linked to hyper-virulence, increased transmission, and drug resistance. We performed multi-layer comparative analyses integrating whole-genome sequencing with quantitative transcriptomic and proteomic profiling of a panel of L1 and L2 clinical strains, each grown under two in vitro conditions. Our data revealed variable correlations between transcript and protein levels across strains and gene categories, indicating lineage-specific post-translational regulation. Transcriptional and translational differences scaled with phylogenetic distance, with one in three SNPs on average leading to gene expression changes. A newly developed genome-scale transcriptional regulatory model identified master transcription factors--closely linked to the sigma factor network--whose targets were differentially expressed between L1 and L2. Notably, DosR proteins showed higher basal levels and a stronger nitric oxide (NO) response in L2. Time-course validation using an Rv1985c induction and wild-type H37Rv under hypoxia and reaeration confirmed the role of Rv1985c in the differentially expressed genes between L1 and L2. These findings suggest that limited genetic variation can translate into significant phenotypic differences via differential regulation of key transcriptional networks. HighlightsO_LIProteomic and transcriptomic characterization of fully sequenced diverse L1 and L2 clinical strains of Mtb. C_LIO_LIPost translational control mechanisms for regulatory and virulence genes are mitigated in Mtb L2. C_LIO_LIA genome-scale transcriptional framework identifies DosR, Rv1985c, Lsr2 and Rv0691c as master transcription factors responsible for differential target gene expression in L2 compared to L1 strains. C_LIO_LIL1 and L2 DosR proteins respond differently to nitric oxide stress, thus determining a relevant phenotype. C_LIO_LITime-course phenotypic and transcriptomic data under hypoxia and reaeration validate Rv1985c as a key transcription factor differentiating L2 and L1 strains. C_LI

systems biology↗

bioRxiv2018

Ultra-sensitive proteome profiling of FACS-isolated cell populations by data-independent acquisition-MS: Application to human hematopoietic stem and progenitor cells

Physiological processes in multicellular organisms depend on the function and interactions of a multitude of specialized cell types operating in context. Fluorescence-activated cell sorting (FACS) provides a powerful tool to determine the cell type composition of complex mixtures and to purify highly homogeneous cell populations using a small number of differentially expressed marker proteins. These populations can be further characterized, e.g. by phenotypic or molecular analyses.\n\nWe describe an ultra-sensitive mass spectrometric method for the robust quantitative and reproducible proteomic analysis of cohorts of FACS-isolated cell samples. It uses a minimum of post-sorting sample processing steps prior to data-independent acquisition MS on a current generation Orbitrap hybrid mass spectrometer. The method provides highly accurate and reproducible quantitative proteome profiles across the cohort with an average coefficient of variance <15% from as little as 150 ng of total peptide mass. We quantified the proteome of 25,000 sorted human hematopoietic stem/multipotent progenitor cell and three committed progenitor cell subpopulations (common myeloid progenitors, megakaryocyte-erythrocyte progenitors and granulocyte-macrophage progenitors) isolated from five healthy donors. On average, 5,851 protein groups were identified per sample. After stringent filtering, a subset of 4,131 protein groups ([≥]2 peptides) was used for differential comparison across the 20 samples, defining unique proteomic signatures for each cell type tested. A comparison of proteomic and transcriptomic profiles of the four cell types indicated hematopoietic stem/multipotent progenitor cell-specific divergent regulation of biochemical processes that are essential for maintaining stemness and were detected at the proteome rather than the transcriptome level.\n\nThe technology supports the generation of extensive and accurate quantitative proteomic profiles from low numbers of FACS-purified cells providing new information about the biochemical state of the analyzed cell types that is essential for basic and translational research.

systems biology↗