Cell-of-origin-specific proteomics of extracellular vesicles.

Autor:	Kehrloesser S; Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK., Cast O; Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK., Elliott TS; Medical Research Council Laboratory of Molecular Biology, Francis Crick Ave, Cambridge CB2 0QH, UK., Ernst RJ; Medical Research Council Laboratory of Molecular Biology, Francis Crick Ave, Cambridge CB2 0QH, UK., Machel AC; Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK., Chen JX; Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK.; Institute of Molecular Biology, Ackermannweg 4, 55128 Mainz, Germany., Chin JW; Medical Research Council Laboratory of Molecular Biology, Francis Crick Ave, Cambridge CB2 0QH, UK., Miller ML; Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK.; Oncology Data Science, Oncology R&D, AstraZeneca, 1 Francis Crick Ave, Cambridge CB2 0AA, UK.
Jazyk:	angličtina
Zdroj:	PNAS nexus [PNAS Nexus] 2023 Apr 03; Vol. 2 (4), pp. pgad107. Date of Electronic Publication: 2023 Apr 03 (Print Publication: 2023).
DOI:	10.1093/pnasnexus/pgad107
Abstrakt:	The ability to assign cellular origin to low-abundance secreted factors in extracellular vesicles (EVs) would greatly facilitate the analysis of paracrine-mediated signaling. Here, we report a method, named selective isolation of extracellular vesicles (SIEVE), which uses cell type-specific proteome labeling via stochastic orthogonal recoding of translation (SORT) to install bioorthogonal reactive groups into the proteins derived from the cells targeted for labeling. We establish the native purification of intact EVs from a target cell, via a bioorthogonal tetrazine ligation, leading to copurification of the largely unlabeled EV proteome from the same cell. SIEVE enables capture of EV proteins at levels comparable with those obtained by antibody-based methods, which capture all EVs regardless of cellular origin, and at levels 20× higher than direct capture of SORT-labeled proteins. Using proteomic analysis, we analyze nonlabeled cargo proteins of EVs and show that the enhanced sensitivity of SIEVE allows for unbiased and comprehensive analysis of EV proteins from subpopulations of cells as well as for cell-specific EV proteomics in complex coculture systems. SIEVE can be applied with high efficiency in a diverse range of existing model systems for cell-cell communication and has direct applications for cell-of-origin EV analysis and for protein biomarker discovery. (© The Author(s) 2023. Published by Oxford University Press on behalf of National Academy of Sciences.)
Databáze:	MEDLINE
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