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Daunesse M, Legendre R, Varet H, Pain A, Chica C. ePeak: from replicated chromatin profiling data to epigenomic dynamics. NAR Genom Bioinform 2022; 4:lqac041. [PMID: 35664802 PMCID: PMC9154330 DOI: 10.1093/nargab/lqac041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2021] [Revised: 04/05/2022] [Accepted: 05/05/2022] [Indexed: 11/14/2022] Open
Abstract
We present ePeak, a Snakemake-based pipeline for the identification and quantification of reproducible peaks from raw ChIP-seq, CUT&RUN and CUT&Tag epigenomic profiling techniques. It also includes a statistical module to perform tailored differential marking and binding analysis with state of the art methods. ePeak streamlines critical steps like the quality assessment of the immunoprecipitation, spike-in calibration and the selection of reproducible peaks between replicates for both narrow and broad peaks. It generates complete reports for data quality control assessment and optimal interpretation of the results. We advocate for a differential analysis that accounts for the biological dynamics of each chromatin factor. Thus, ePeak provides linear and nonlinear methods for normalisation as well as conservative and stringent models for variance estimation and significance testing of the observed marking/binding differences. Using a published ChIP-seq dataset, we show that distinct populations of differentially marked/bound peaks can be identified. We study their dynamics in terms of read coverage and summit position, as well as the expression of the neighbouring genes. We propose that ePeak can be used to measure the richness of the epigenomic landscape underlying a biological process by identifying diverse regulatory regimes.
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Affiliation(s)
- Maëlle Daunesse
- Bioinformatics and Biostatistics Hub, Institut Pasteur, Université de Paris, Paris F-75015, France
| | - Rachel Legendre
- Bioinformatics and Biostatistics Hub, Institut Pasteur, Université de Paris, Paris F-75015, France
| | - Hugo Varet
- Bioinformatics and Biostatistics Hub, Institut Pasteur, Université de Paris, Paris F-75015, France
| | - Adrien Pain
- Bioinformatics and Biostatistics Hub, Institut Pasteur, Université de Paris, Paris F-75015, France
| | - Claudia Chica
- Bioinformatics and Biostatistics Hub, Institut Pasteur, Université de Paris, Paris F-75015, France
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Mazzuoli MV, Daunesse M, Varet H, Rosinski-Chupin I, Legendre R, Sismeiro O, Gominet M, Kaminski PA, Glaser P, Chica C, Trieu-Cuot P, Firon A. The CovR regulatory network drives the evolution of Group B Streptococcus virulence. PLoS Genet 2021; 17:e1009761. [PMID: 34491998 PMCID: PMC8448333 DOI: 10.1371/journal.pgen.1009761] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Revised: 09/17/2021] [Accepted: 08/09/2021] [Indexed: 01/31/2023] Open
Abstract
Virulence of the neonatal pathogen Group B Streptococcus is under the control of the master regulator CovR. Inactivation of CovR is associated with large-scale transcriptome remodeling and impairs almost every step of the interaction between the pathogen and the host. However, transcriptome analyses suggested a plasticity of the CovR signaling pathway in clinical isolates leading to phenotypic heterogeneity in the bacterial population. In this study, we characterized the CovR regulatory network in a strain representative of the CC-17 hypervirulent lineage responsible of the majority of neonatal meningitis. Transcriptome and genome-wide binding analysis reveal the architecture of the CovR network characterized by the direct repression of a large array of virulence-associated genes and the extent of co-regulation at specific loci. Comparative functional analysis of the signaling network links strain-specificities to the regulation of the pan-genome, including the two specific hypervirulent adhesins and horizontally acquired genes, to mutations in CovR-regulated promoters, and to variability in CovR activation by phosphorylation. This regulatory adaptation occurs at the level of genes, promoters, and of CovR itself, and allows to globally reshape the expression of virulence genes. Overall, our results reveal the direct, coordinated, and strain-specific regulation of virulence genes by the master regulator CovR and suggest that the intra-species evolution of the signaling network is as important as the expression of specific virulence factors in the emergence of clone associated with specific diseases. Streptococcus agalactiae, commonly known as the Group B Streptococcus (GBS), is a commensal bacterium of the intestinal and vaginal tracts found in approximately 30% of healthy adults. However, GBS is also an opportunistic pathogen and the leading cause of neonatal invasive infections. Epidemiologic data have identified a particular GBS clone, designated the CC-17 hypervirulent clonal complex, as responsible for the overwhelming majority of neonatal meningitis. The hypervirulence of CC-17 has been linked to the expression of two specific surface proteins increasing their abilities to cross epithelial and endothelial barriers. In this study, we characterized the role of the major regulator of virulence gene expression, the CovR response regulator, in a representative hypervirulent strain. Transcriptome and genome-wide binding analysis reveal the architecture of the CovR signaling network characterized by the direct repression of a large array of virulence-associated genes, including the specific hypervirulent adhesins. Comparative analysis in a non-CC-17 wild type strain demonstrates a high level of plasticity of the regulatory network, allowing to globally reshape pathogen-host interaction. Overall, our results suggest that the intra-species evolution of the regulatory network is an important factor in the emergence of GBS clones associated with specific pathologies.
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Affiliation(s)
- Maria-Vittoria Mazzuoli
- Unité Biologie des Bactéries Pathogènes à Gram-positif, CNRS UMR2001 Microbiologie Intégrative et Moléculaire, Institut Pasteur, Paris, France
- Sorbonne Paris Cité, Université de Paris, Paris, France
| | - Maëlle Daunesse
- Hub de Bioinformatique et Biostatistique—Département Biologie Computationnelle, Institut Pasteur, Paris, France
| | - Hugo Varet
- Hub de Bioinformatique et Biostatistique—Département Biologie Computationnelle, Institut Pasteur, Paris, France
- Plate-forme Technologique Biomics—Centre de Ressources et Recherches Technologiques (C2RT), Institut Pasteur, Paris, France
| | - Isabelle Rosinski-Chupin
- Unité Écologie et Évolution de la Résistance aux Antibiotiques, CNRS UMR3525, Institut Pasteur, Paris, France
| | - Rachel Legendre
- Hub de Bioinformatique et Biostatistique—Département Biologie Computationnelle, Institut Pasteur, Paris, France
- Plate-forme Technologique Biomics—Centre de Ressources et Recherches Technologiques (C2RT), Institut Pasteur, Paris, France
| | - Odile Sismeiro
- Unité Biologie des Bactéries Pathogènes à Gram-positif, CNRS UMR2001 Microbiologie Intégrative et Moléculaire, Institut Pasteur, Paris, France
- Plate-forme Technologique Biomics—Centre de Ressources et Recherches Technologiques (C2RT), Institut Pasteur, Paris, France
| | - Myriam Gominet
- Unité Biologie des Bactéries Pathogènes à Gram-positif, CNRS UMR2001 Microbiologie Intégrative et Moléculaire, Institut Pasteur, Paris, France
| | - Pierre Alexandre Kaminski
- Unité Biologie des Bactéries Pathogènes à Gram-positif, CNRS UMR2001 Microbiologie Intégrative et Moléculaire, Institut Pasteur, Paris, France
| | - Philippe Glaser
- Unité Écologie et Évolution de la Résistance aux Antibiotiques, CNRS UMR3525, Institut Pasteur, Paris, France
| | - Claudia Chica
- Hub de Bioinformatique et Biostatistique—Département Biologie Computationnelle, Institut Pasteur, Paris, France
| | - Patrick Trieu-Cuot
- Unité Biologie des Bactéries Pathogènes à Gram-positif, CNRS UMR2001 Microbiologie Intégrative et Moléculaire, Institut Pasteur, Paris, France
| | - Arnaud Firon
- Unité Biologie des Bactéries Pathogènes à Gram-positif, CNRS UMR2001 Microbiologie Intégrative et Moléculaire, Institut Pasteur, Paris, France
- * E-mail:
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Hubstenberger A, Courel M, Bénard M, Souquere S, Ernoult-Lange M, Chouaib R, Yi Z, Morlot JB, Munier A, Fradet M, Daunesse M, Bertrand E, Pierron G, Mozziconacci J, Kress M, Weil D. P-Body Purification Reveals the Condensation of Repressed mRNA Regulons. Mol Cell 2017; 68:144-157.e5. [PMID: 28965817 DOI: 10.1016/j.molcel.2017.09.003] [Citation(s) in RCA: 432] [Impact Index Per Article: 61.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2017] [Revised: 06/05/2017] [Accepted: 08/31/2017] [Indexed: 01/27/2023]
Abstract
Within cells, soluble RNPs can switch states to coassemble and condense into liquid or solid bodies. Although these phase transitions have been reconstituted in vitro, for endogenous bodies the diversity of the components, the specificity of the interaction networks, and the function of the coassemblies remain to be characterized. Here, by developing a fluorescence-activated particle sorting (FAPS) method to purify cytosolic processing bodies (P-bodies) from human epithelial cells, we identified hundreds of proteins and thousands of mRNAs that structure a dense network of interactions, separating P-body from non-P-body RNPs. mRNAs segregating into P-bodies are translationally repressed, but not decayed, and this repression explains part of the poor genome-wide correlation between RNA and protein abundance. P-bodies condense thousands of mRNAs that strikingly encode regulatory processes. Thus, we uncovered how P-bodies, by condensing and segregating repressed mRNAs, provide a physical substrate for the coordinated regulation of posttranscriptional mRNA regulons.
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Affiliation(s)
- Arnaud Hubstenberger
- UPMC Univ Paris 06, Institut de Biologie Paris-Seine (IBPS), CNRS UMR 7622, F-75005 Paris, France; Université Côte d'Azur, CNRS, Inserm, iBV, Nice, France.
| | - Maïté Courel
- UPMC Univ Paris 06, Institut de Biologie Paris-Seine (IBPS), CNRS UMR 7622, F-75005 Paris, France
| | - Marianne Bénard
- UPMC Univ Paris 06, Institut de Biologie Paris-Seine (IBPS), CNRS UMR 7622, F-75005 Paris, France
| | - Sylvie Souquere
- CNRS UMR-9196, Institut Gustave Roussy, F-94800 Villejuif, France
| | - Michèle Ernoult-Lange
- UPMC Univ Paris 06, Institut de Biologie Paris-Seine (IBPS), CNRS UMR 7622, F-75005 Paris, France
| | - Racha Chouaib
- UPMC Univ Paris 06, Institut de Biologie Paris-Seine (IBPS), CNRS UMR 7622, F-75005 Paris, France; IGMM, CNRS, University Montpellier, F-34090 Montpellier, France
| | - Zhou Yi
- UPMC Univ Paris 06, Institut de Biologie Paris-Seine (IBPS), CNRS UMR 7622, F-75005 Paris, France
| | | | - Annie Munier
- UPMC Univ Paris 06, LUMIC, UMS30, F-75005 Paris, France
| | | | - Maëlle Daunesse
- École Normale Supérieure, PSL Research University, CNRS, Inserm, Institut de Biologie de l'École Normale Supérieure (IBENS), Genomic Paris Centre, IBENS, F-75005 Paris, France
| | | | - Gérard Pierron
- CNRS UMR-9196, Institut Gustave Roussy, F-94800 Villejuif, France
| | | | - Michel Kress
- UPMC Univ Paris 06, Institut de Biologie Paris-Seine (IBPS), CNRS UMR 7622, F-75005 Paris, France
| | - Dominique Weil
- UPMC Univ Paris 06, Institut de Biologie Paris-Seine (IBPS), CNRS UMR 7622, F-75005 Paris, France.
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