Biology subjects

Combes, F.

Publications and source records attributed to Combes, F..

3 recordsLinked to original sources

bioRxiv2024

Proteomics-based characterization of ribosome heterogeneity in adult mouse organs

While long thought to be invariable in all cellular organisms, evidence has emerged that the translation process, i.e. protein assembly from mRNA sequence decoding, is regulated by variable features of the translation machinery. Notably, ribosomes, the functional units of protein synthesis, display variations in their composition, depending on the developmental stage, cell type or physiopathological context, thus providing a new level of actionable regulation of gene expression. Yet, a comprehensive map of the heterogeneity of ribosome composition in ribosomal proteins (RPs) in different organs and tissues is not available. In this work, we explored tissue-specific ribosome heterogeneity using mass spectrometry-based quantitative proteomic characterization of ribosomal fractions purified from 14 adult mouse organs and tissues. We performed crossed clustering and statistical analyses of RP composition to highlight stable, variable and tissue-specific RPs across organs and tissues. Focusing on specific RPs, we validated their relative abundance with a targeted proteomic approach, which gave further insight into the tissue-specific ribosome RP signature. Finally, we investigated the origin of RP variations in ribosome fraction of the different tissues, by comparing RP relative abundances in our proteomic dataset and in three independent transcriptomic datasets. Interestingly, we found that, in some tissues, the RP abundance in purified ribosomes does not always correlate with the corresponding RP transcript level, arguing for a translational regulation of RP expression, and/or a regulated incorporation of RPs into ribosomes. Altogether, our data support the notion of a tissue-specific RP signature of ribosomes, which opens avenues to study how specific ribosomal composition provides an additional level of regulation to control gene expression in different tissues and organs.

biochemistry↗

bioRxiv2020

Corticosteroids and cellulose purification improve respectively the in vivo translation and vaccination efficacy of self-amplifying mRNAs

Synthetic mRNAs are an appealing therapeutic platform with multiple biomedical applications ranging from protein replacement therapy to vaccination. In comparison to conventional mRNA, synthetic self-amplifying mRNAs (sa-mRNAs) are gaining increased interest due to their higher and longer-lasting expression. However, sa-mRNAs also elicit an innate immune response, which may complicate the clinical translation of this platform. Approaches to reduce the innate immunity of sa-mRNAs have not been studied in detail. In this work we investigated the effect of several innate immune inhibitors and a novel cellulose-based mRNA purification approach on the type I interferon (IFN) response, translation and vaccination efficacy of our formerly developed sa-mRNA vaccine against Zika virus. Among the investigated inhibitors, we found that topical application of clobetasol at the sa-mRNA injection site was the most efficient in suppressing the type I IFN response and increasing the translation of sa-mRNA. However, clobetasol prevented the formation of antibodies against sa-mRNA encoded antigens and should therefore be avoided in a vaccination context. Residual dsRNA by-products of the in vitro transcription reaction are known inducers of immediate type I IFN responses. We additionally demonstrate drastic reduction of these dsRNA by-products upon cellulose-based purification, consequently reducing the innate immune response and improving sa-mRNA vaccination efficacy.

immunology↗

bioRxiv2017

PEPA test: fast and powerful differential analysis from relative quantitative proteomics data using shared peptides

We propose a new hypothesis test for the differential abundance of proteins in mass-spectrometry based relative quantification. An important feature of this type of high-throughput analyses is that it involves an enzymatic digestion of the sample proteins into peptides prior to identification and quantification. Due to numerous homology sequences, different proteins can lead to peptides with identical amino acid chains, so that their parent protein is ambiguous. These so-called shared peptides make the protein-level statistical analysis a challenge, so that they are often not accounted for. In this article, we use a linear model describing peptide-protein relationships to build a likelihood ratio test of differential abundance for proteins. We show that the likelihood ratio statistic can be computed in linear time with the number of peptides. We also provide the asymptotic null distribution of a regularized version of our statistic. Experiments on both real and simulated datasets show that our procedures outperforms state-of-the-art methods. The procedures are available via the pepa.test function of the DAPAR Bioconductor R package.

bioinformatics↗