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Identification of host proteins differentially associated with HIV-1 RNA splice variants.

ABSTRACT: HIV-1 generates unspliced (US), partially spliced (PS), and completely spliced (CS) classes of RNAs, each playing distinct roles in viral replication. Elucidating their host protein 'interactomes' is crucial to understanding virus-host interplay. Here, we present HyPR-MS_SV for isolation of US, PS, and CS transcripts from a single population of infected CD4+ T-cells and mass spectrometric identification of their in vivo protein interactomes. Analysis revealed 212 proteins differentially associated with the unique RNA classes, including preferential association of regulators of RNA stability with US and PS transcripts and, unexpectedly, mitochondria-linked proteins with US transcripts. Remarkably, >80 of these factors screened by siRNA knockdown impacted HIV-1 gene expression. Fluorescence microscopy confirmed several to co-localize with HIV-1 US RNA and exhibit changes in abundance and/or localization over the course of infection. This study validates HyPR-MS_SV for discovery of viral splice variant protein interactomes and provides an unprecedented resource of factors and pathways likely important to HIV-1 replication.

SUBMITTER: Knoener R

PROVIDER: S-EPMC7906601 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Identification of host proteins differentially associated with HIV-1 RNA splice variants.

Knoener Rachel R Evans Edward E Becker Jordan T JT Scalf Mark M Benner Bayleigh B Sherer Nathan M NM Smith Lloyd M LM

eLife 20210225

HIV-1 generates unspliced (US), partially spliced (PS), and completely spliced (CS) classes of RNAs, each playing distinct roles in viral replication. Elucidating their host protein 'interactomes' is crucial to understanding virus-host interplay. Here, we present HyPR-MS<sub>SV</sub> for isolation of US, PS, and CS transcripts from a single population of infected CD4+ T-cells and mass spectrometric identification of their in vivo protein interactomes. Analysis revealed 212 proteins differentiall ...[more]

PMID: 33629952

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Project description:Proteogenomics, i.e. comprehensive integration of genomics and proteomics data, is a powerful approach identifying novel protein biomarkers. This is especially the case for proteins that differ structurally between disease and control conditions. As tumor development is associated with aberrant splicing, we focus on this rich source of cancer specific biomarkers. To this end, we developed a proteogenomic pipeline, Splicify, which is able to detect differentially expressed protein isoforms. Splicify is based on integrating RNA massive parallel sequencing data and tandem mass spectrometry proteomics data to identify protein isoforms resulting from differential splicing between two conditions. Proof of concept was obtained by applying Splicify to RNA sequencing and mass spectrometry data obtained from colorectal cancer cell line SW480, before and after siRNA-mediated down-modulation of the splicing factors SF3B1 and SRSF1. These analyses revealed 2172 and 149 differentially expressed isoforms, respectively, with peptide confirmation upon knock-down of SF3B1 and SRSF1 compared to their controls. Splice variants identified included RAC1, OSBPL3, MKI67 and SYK. One additional sample was analyzed by PacBio Iso-Seq full-length transcript sequencing after SF3B1 down-modulation. This analysis verified the alternative splicing identified by Splicify and in addition identified novel splicing events that were not represented in the human reference genome annotation. Therefore, Splicify offers a validated proteogenomic data analysis pipeline for identification of disease specific protein biomarkers resulting from mRNA alternative splicing. Splicify is publicly available on GitHub (https://github.com/NKI-TGO/SPLICIFY) and suitable to address basic research questions using pre-clinical model systems as well as translational research questions using patient-derived samples, e.g. allowing to identify clinically relevant biomarkers. This dataset corresponds to a publication in Molecular & Cellular Proteomics 16: 10.1074/mcp.TIR117.000056, 1850–1863, 2017, PMID: 28747380. Mass spectrometry data corresponding to this entry is available at ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD006486.

Project description:BackgroundThere are currently no vaccines or antivirals available for dengue virus infection, which can cause dengue hemorrhagic fever and death. A better understanding of the host pathogen interaction is required to develop effective therapies to treat DENV. In particular, very little is known about how cellular RNA binding proteins interact with viral RNAs. RNAs within cells are not naked; rather they are coated with proteins that affect localization, stability, translation and (for viruses) replication.Methodology/principal findingsSeventy-nine novel RNA binding proteins for dengue virus (DENV) were identified by cross-linking proteins to dengue viral RNA during a live infection in human cells. These cellular proteins were specific and distinct from those previously identified for poliovirus, suggesting a specialized role for these factors in DENV amplification. Knockdown of these proteins demonstrated their function as viral host factors, with evidence for some factors acting early, while others late in infection. Their requirement by DENV for efficient amplification is likely specific, since protein knockdown did not impair the cell fitness for viral amplification of an unrelated virus. The protein abundances of these host factors were not significantly altered during DENV infection, suggesting their interaction with DENV RNA was due to specific recruitment mechanisms. However, at the global proteome level, DENV altered the abundances of proteins in particular classes, including transporter proteins, which were down regulated, and proteins in the ubiquitin proteasome pathway, which were up regulated.Conclusions/significanceThe method for identification of host factors described here is robust and broadly applicable to all RNA viruses, providing an avenue to determine the conserved or distinct mechanisms through which diverse viruses manage the viral RNA within cells. This study significantly increases the number of cellular factors known to interact with DENV and reveals how DENV modulates and usurps cellular proteins for efficient amplification.

Dataset Information

Identification of host proteins differentially associated with HIV-1 RNA splice variants.

Publications

Identification of host proteins differentially associated with HIV-1 RNA splice variants.

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