Dataset Information

Unbiased proteomic profiling of host cell extracellular vesicle composition and dynamics upon HIV-1 infection.

ABSTRACT: Cells release diverse types of extracellular vesicles (EVs), which transfer complex signals to surrounding cells. Specific markers to distinguish different EVs (e.g. exosomes, ectosomes, enveloped viruses like HIV) are still lacking. We have developed a proteomic profiling approach for characterizing EV subtype composition and applied it to human Jurkat T cells. We generated an interactive database to define groups of proteins with similar profiles, suggesting release in similar EVs. Biochemical validation confirmed the presence of preferred partners of commonly used exosome markers in EVs: CD81/ADAM10/ITGB1, and CD63/syntenin. We then compared EVs from control and HIV-1-infected cells. HIV infection altered EV profiles of several cellular proteins, including MOV10 and SPN, which became incorporated into HIV virions, and SERINC3, which was re-routed to non-viral EVs in a Nef-dependent manner. Furthermore, we found that SERINC3 controls the surface composition of EVs. Our workflow provides an unbiased approach for identifying candidate markers and potential regulators of EV subtypes. It can be widely applied to in vitro experimental systems for investigating physiological or pathological modifications of EV release.

SUBMITTER: Martin-Jaular L

PROVIDER: S-EPMC8047442 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Unbiased proteomic profiling of host cell extracellular vesicle composition and dynamics upon HIV-1 infection.

Martin-Jaular Lorena L Nevo Nathalie N Schessner Julia P JP Tkach Mercedes M Jouve Mabel M Dingli Florent F Loew Damarys D Witwer Kenneth W KW Ostrowski Matias M Borner Georg H H GHH Théry Clotilde C

The EMBO journal 20210311 8

Cells release diverse types of extracellular vesicles (EVs), which transfer complex signals to surrounding cells. Specific markers to distinguish different EVs (e.g. exosomes, ectosomes, enveloped viruses like HIV) are still lacking. We have developed a proteomic profiling approach for characterizing EV subtype composition and applied it to human Jurkat T cells. We generated an interactive database to define groups of proteins with similar profiles, suggesting release in similar EVs. Biochemical ...[more]

PMID: 33709510

Similar Datasets

Project description:PurposeThe etiology of conjunctivitis is often misdiagnosed. An ideal diagnostic test would identify all possible infectious causes. In this study, we apply unbiased metagenomic RNA deep sequencing (MDS) to identify pathogens causing conjunctivitis.DesignMolecular study of prospectively collected conjunctival swabs from patients with presumed infectious conjunctivitis.ParticipantsPatients with presumed acute infectious conjunctivitis.MethodsConjunctival swabs were collected from patients presenting with acute conjunctivitis. Swabs were processed for MDS. Pathogens were identified using a rapid computational pipeline to analyze the nonhost sequences obtained from MDS. Differential gene expression analysis was performed to evaluate for host transcriptome signatures for infectious types. Clinical samples were deidentified, and laboratory personnel handling the samples and interpreting the data were masked.Main outcome measuresPathogens and differential transcripts identified by MDS.ResultsMetagenomic RNA deep sequencing detected pathogens in 86% (12/14) of the patients tested. Swabs from 10 of 14 patients were positive for human adenovirus (HAdV) while swabs from 2 of 14 patients were positive for Vittaforma corneae (a parasitic fungal species of the microsporidia group). Samples positive for HAdV by RNA-seq were independently verified in a CLIA-certified laboratory. Pathogen-directed polymerase chain reaction confirmed the presence of V. corneae genome in the samples positive by RNA-seq. Local host transcriptome analysis identified 12 differentially expressed genes that provided distinct expression signatures for patients infected with HAdV compared with V. corneae.ConclusionsMetagenomic RNA deep sequencing can reliably detect and quantify common and rare pathogens causing conjunctivitis, and identify strains. The unbiased nature of metagenomic RNA deep sequencing allowed an expanded scope of pathogen detection, including fungal species not commonly associated with acute conjunctivitis. In addition, the identification of infection type-specific local host transcriptome signatures may allow for pathogen detection even when the pathogen load is too low for direct identification.

Project description:Nef is an accessory viral protein that promotes HIV-1 replication, facilitating alterations in cellular pathways via multiple protein-protein interactions. The advent of proteomics has expanded the focus on better identification of novel molecular pathways regulating disease progression. In this study, nef was sequenced from randomly selected patients, however, sequence variability identified did not elicited any specific mutation that could have segregated HIV-1 patients in different stages of disease progression. To explore the difference in Nef functionality based on sequence variability we used proteomics approach. Proteomic profiling was done to compare the effect of Nef variants in host cell protein expression. 2DGE in control and Nef transfected SupT1 cells demonstrated several differentially expressed proteins. Fourteen protein spots were detected with more than 1.5 fold difference. Significant down regulation was seen in six unique protein spots in the Nef treated cells. Proteins were identified as Cyclophilin A, EIF5A-1 isoform B, Rho GDI 1 isoform a, VDAC1, OTUB1 and α-enolase isoform 1 (ENO1) through LC-MS/MS. The differential expression of the 6 proteins was analyzed by Real time PCR, Western blotting and Immunofluorescence studies with two Nef variants (RP14 and RP01) in SupT1 cells. There was contrasting difference between the effect of these Nef variants upon the expression of these six proteins. Downregulation of α-enolase (ENO1), VDAC1 and OTUB1 was more significant by Nef RP01 whereas Cyclophilin A and RhoGDI were found to be more downregulated by Nef RP14. This difference in Nef variants upon host protein expression was also studied through a site directed mutant of Nef RP01 (55AAAAAAA61) and the effect was found to be reversed. Deciphering the role of these proteins mediated by Nef variants will open a new avenue of research in understanding Nef mediated pathogenesis. Overall study determines modulation of cellular protein expression in T cells by HIV-1 Nef variants.

Project description:Growing evidence supports the importance of extracellular vesicle (EV) as mediators of communication in pathological processes, including those underlying respiratory disease. However, establishing methods for isolating and characterizing EVs remains challenging, particularly for respiratory samples. This study set out to address this challenge by comparing different EV isolation methods and evaluating their impacts on EV yield, markers of purity, and proteomic signatures, utilizing equine/horse bronchoalveolar lavage samples. Horses can serve as effective translational animal models for respiratory studies due to similarities with human immune responses, shared environmental exposures, and naturally occurring respiratory diseases including asthma. Further, horses are long-lived large animals that allow for longitudinal sample collection, and provide large sample volume and cell yield, which are particularly useful since EV research is commonly limited by low sample yields. Here, EVs were isolated from horse bronchoalveolar lavage fluid (BALF) using four different methods (ultracentrifugation, microcentrifugation, and two sizes of size exclusion chromatography columns) and characterized by measuring particle counts, EV purity, total protein yield, and proteomic cargo, with a specific focus on vesicle surface marker expression potentially informing cell type of origin. We found that size exclusion chromatography yielded the highest particle counts, greatest EV purity markers and elevated vesicle surface marker expression. Overall proteomic profiles differed across isolation methods, with size exclusion chromatography clustering separately from centrifugation. Taken together, our results demonstrate that different isolation methods impact characteristics of EVs, notably that size exclusion chromatography, compared to centrifugation methods, resulted in higher EV purity and better characterized proteomic diversity, including information on EV cell-of-origin. This is the first study to characterize proteomic profiles of EVs following different isolation methods using equine BALF. The results of this study will pave the way for future studies using equine and human samples to characterize respiratory tract EVs.

Project description:The extracellular vesicle (EV) surface proteome (surfaceome) acts as a fundamental signalling gateway by bridging intra- and extracellular signalling networks, dictates EVs' capacity to communicate and interact with their environment, and is a source of potential disease biomarkers and therapeutic targets. However, our understanding of surface protein composition of large EVs (L-EVs, 100-800 nm, mean 310 nm, ATP5F1A, ATP5F1B, DHX9, GOT2, HSPA5, HSPD1, MDH2, STOML2), a major EV-subtype that are distinct from small EVs (S-EVs, 30-150 nm, mean 110 nm, CD44, CD63, CD81, CD82, CD9, PDCD6IP, SDCBP, TSG101) remains limited. Using a membrane impermeant derivative of biotin to capture surface proteins coupled to mass spectrometry analysis, we show that out of 4143 proteins identified in density-gradient purified L-EVs (1.07-1.11 g/mL, from multiple cancer cell lines), 961 proteins are surface accessible. The surface molecular diversity of L-EVs include (i) bona fide plasma membrane anchored proteins (cluster of differentiation, transporters, receptors and GPI anchored proteins implicated in cell-cell and cell-ECM interactions); and (ii) membrane surface-associated proteins (that are released by divalent ion chelator EDTA) implicated in actin cytoskeleton regulation, junction organization, glycolysis and platelet activation. Ligand-receptor analysis of L-EV surfaceome (e.g., ITGAV/ITGB1) uncovered interactome spanning 172 experimentally verified cognate binding partners (e.g., ANGPTL3, PLG, and VTN) with highest tissue enrichment for liver. Assessment of biotin inaccessible L-EV proteome revealed enrichment for proteins belonging to COPI/II-coated ER/Golgi-derived vesicles and mitochondria. Additionally, despite common surface proteins identified in L-EVs and S-EVs, our data reveals surfaceome heterogeneity between the two EV-subtype. Collectively, our study provides critical insights into diverse proteins operating at the interactive platform of L-EVs and molecular leads for future studies seeking to decipher L-EV heterogeneity and function.

Dataset Information

Unbiased proteomic profiling of host cell extracellular vesicle composition and dynamics upon HIV-1 infection.

Publications

Unbiased proteomic profiling of host cell extracellular vesicle composition and dynamics upon HIV-1 infection.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets