RESUMO
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.
Assuntos
Regulação da Expressão Gênica , Proteoma/genética , RNA Mensageiro/genética , Regulon , Ribonucleoproteínas/genética , Fracionamento Celular , Citoplasma/metabolismo , Grânulos Citoplasmáticos/química , Grânulos Citoplasmáticos/metabolismo , Ontologia Genética , Células HEK293 , Células HeLa , Humanos , Anotação de Sequência Molecular , Transição de Fase , Biossíntese de Proteínas , Proteoma/metabolismo , Estabilidade de RNA , RNA Mensageiro/metabolismo , Ribonucleoproteínas/metabolismoRESUMO
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.
Assuntos
Proteínas de Bactérias/fisiologia , Redes Reguladoras de Genes , Streptococcus agalactiae/patogenicidade , Fatores de Virulência/fisiologia , Virulência/genética , Proteínas de Bactérias/genética , Cromossomos Bacterianos , Genes Bacterianos , Interações Hospedeiro-Patógeno , Humanos , Regiões Promotoras Genéticas , Prófagos/genética , Streptococcus agalactiae/genética , Transcrição Gênica/fisiologia , Fatores de Virulência/genéticaRESUMO
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.