Biology subjects

Charloteaux, B.

Publications and source records attributed to Charloteaux, B..

4 recordsLinked to original sources

bioRxiv2021

Binary Interactome Models of Inner- Versus Outer-Complexome Organization

Hundreds of different protein complexes that perform important functions across all cellular processes, collectively comprising the "complexome" of an organism, have been identified1. However, less is known about the fraction of the interactome that exists outside the complexome, in the "outer-complexome". To investigate features of "inner"- versus outer-complexome organisation in yeast, we generated a high-quality atlas of binary protein-protein interactions (PPIs), combining three previous maps2-4 and a new reference all-by-all binary interactome map. A greater proportion of interactions in our map are in the outer-complexome, in comparison to those found by affinity purification followed by mass spectrometry5-7 or in literature curated datasets8-11. In addition, recent advances in deep learning predictions of PPI structures12 mirror the existing experimentally resolved structures in being largely focused on the inner complexome and missing most interactions in the outer-complexome. Our new PPI network suggests that the outer-complexome contains considerably more PPIs than the inner-complexome, and integration with functional similarity networks13-15 reveals that interactions in the inner-complexome are highly detectable and correspond to pairs of proteins with high functional similarity, while proteins connected by more transient, harder-to-detect interactions in the outer-complexome, exhibit higher functional heterogeneity.

systems biology↗

bioRxiv2021

The viral oncoproteins Tax and HBZ reprogram the cellular mRNA splicing landscape

While viral infections are known to hijack the transcription and translation of the host cell, the extent to which encoded viral proteins coordinate these perturbations remains unclear. Here we demonstrate that the oncoviral proteins Tax and HBZ interact with specific components of the spliceosome machinery, including the U2 auxiliary factor large subunit (U2AF2), and the complementary factor for APOBEC-1 (A1CF), respectively. Tax and HBZ perturb the splicing landscape in T-cells by altering cassette exons in opposing manners, with Tax inducing exon inclusion while HBZ induces exon exclusion. Among Tax- and HBZ-dependent splicing changes, we identify events that are also altered in Adult T cell leukemia (ATL) patients, and in well-known cancer census genes. Our interactome mapping approach, applicable to other viral oncogenes, has identified spliceosome perturbation as a novel mechanism coordinately used by Tax and HBZ to reprogram the transcriptome. HighlightsO_LITax and HBZ interact with RNA-binding proteins as well as transcription factors C_LIO_LIHTLV-1 encoded proteins Tax and HBZ alter the splicing landscape in T-cells C_LIO_LITax and HBZ expression affect alternative splicing of 33 and 63 cancer genes, respectively C_LIO_LIOpposing roles for Tax and HBZ in deregulation of gene expression C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=158 HEIGHT=200 SRC="FIGDIR/small/427104v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@b5f6f0org.highwire.dtl.DTLVardef@6725b3org.highwire.dtl.DTLVardef@1dc32fborg.highwire.dtl.DTLVardef@19728c6_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2019

A reference map of the human protein interactome

Global insights into cellular organization and function require comprehensive understanding of interactome networks. Similar to how a reference genome sequence revolutionized human genetics, a reference map of the human interactome network is critical to fully understand genotype-phenotype relationships. Here we present the first human \"all-by-all\" binary reference interactome map, or \"HuRI\". With ~53,000 high-quality protein-protein interactions (PPIs), HuRI is approximately four times larger than the information curated from small-scale studies available in the literature. Integrating HuRI with genome, transcriptome and proteome data enables the study of cellular function within essentially any physiological or pathological cellular context. We demonstrate the use of HuRI in identifying specific subcellular roles of PPIs and protein function modulation via splicing during brain development. Inferred tissue-specific networks reveal general principles for the formation of cellular context-specific functions and elucidate potential molecular mechanisms underlying tissue-specific phenotypes of Mendelian diseases. HuRI thus represents an unprecedented, systematic reference linking genomic variation to phenotypic outcomes.

systems biology↗

bioRxiv2017

Transcriptome wide analysis of natural antisense transcripts shows their potential role in breast cancer.

Non-coding RNAs (ncRNA) represent at least 1/5 of the mammalian transcript amount, and about 90% of the genome length is actively transcribed. Many ncRNAs have been demonstrated to play a role in cancer. Among them, natural antisense transcripts (NAT) are RNA sequences which are complementary and overlapping to those of protein-coding transcripts (PCT). NATs were punctually described as regulating gene expression, and are expected to act more frequently in cis than other ncRNAs that commonly function in trans. In this work, 22 breast cancers expressing estrogen receptors and their paired healthy tissues were analyzed by strand-specific RNA sequencing. To highlight the potential role of NATs in gene regulations occurring in breast cancer, three different gene extraction methods were used: differential expression analysis of NATs between tumor and healthy tissues, differential correlation analysis of paired NAT/PCT between tumor and healthy tissues, and NAT/PCT read count ratio variation between tumor and healthy tissues. Each of these methods yielded lists of NAT/PCT pairs that were demonstrated to be enriched in survival-associated genes on an independent cohort (TCGA). This work allows to highlight NAT lists that display a strong potential to affect the expression of genes involved in the breast cancer pathology.

genomics↗