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EV-origin: Enumerating the tissue-cellular origin of circulating extracellular vesicles using exLR profile

Extracellular vesicles (EVs) are complex ecosystems that can be derived from all body cells and circulated in the body fluids. Characterizing the tissue-cellular source contributing to circulating EVs provides biological information about the cell or tissue of origin and their functional states. How...

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Autores principales: Li, Yuchen, He, Xigan, Li, Qin, Lai, Hongyan, Zhang, Hena, Hu, Zhixiang, Li, Yan, Huang, Shenglin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7588739/
https://www.ncbi.nlm.nih.gov/pubmed/33133426
http://dx.doi.org/10.1016/j.csbj.2020.10.002
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author Li, Yuchen
He, Xigan
Li, Qin
Lai, Hongyan
Zhang, Hena
Hu, Zhixiang
Li, Yan
Huang, Shenglin
author_facet Li, Yuchen
He, Xigan
Li, Qin
Lai, Hongyan
Zhang, Hena
Hu, Zhixiang
Li, Yan
Huang, Shenglin
author_sort Li, Yuchen
collection PubMed
description Extracellular vesicles (EVs) are complex ecosystems that can be derived from all body cells and circulated in the body fluids. Characterizing the tissue-cellular source contributing to circulating EVs provides biological information about the cell or tissue of origin and their functional states. However, the relative proportion of tissue-cellular origin of circulating EVs in body fluid has not been thoroughly characterized. Here, we developed an approach for digital EVs quantification, called EV-origin, that enables enumerating of EVs tissue-cellular source contribution from plasma extracellular vesicles long RNA sequencing profiles. EV-origin was constructed by the input matrix of gene expression signatures and robust deconvolution algorithm, collectively used to separate the relative proportions of each tissue or cell type of interest. EV-origin respectively predicted the relative enrichment of seven types of hemopoietic cells and sixteen solid tissue subsets from exLR-seq profile. Using the EV-origin approach, we depicted an integrated landscape of the traceability system of plasma EVs for healthy individuals. We also compared the heterogenous tissue-cellular source components from plasma EVs samples with diverse disease status. Notably, the aberrant liver fraction could reflect the development and progression of hepatic disease. The liver fraction could also serve as a diagnostic indicator and effectively separate HCC patients from normal individuals. The EV-origin provides an approach to decipher the complex heterogeneity of tissue-cellular origin in circulating EVs. Our approach could inform the development of exLR-based applications for liquid biopsy.
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spelling pubmed-75887392020-10-30 EV-origin: Enumerating the tissue-cellular origin of circulating extracellular vesicles using exLR profile Li, Yuchen He, Xigan Li, Qin Lai, Hongyan Zhang, Hena Hu, Zhixiang Li, Yan Huang, Shenglin Comput Struct Biotechnol J Research Article Extracellular vesicles (EVs) are complex ecosystems that can be derived from all body cells and circulated in the body fluids. Characterizing the tissue-cellular source contributing to circulating EVs provides biological information about the cell or tissue of origin and their functional states. However, the relative proportion of tissue-cellular origin of circulating EVs in body fluid has not been thoroughly characterized. Here, we developed an approach for digital EVs quantification, called EV-origin, that enables enumerating of EVs tissue-cellular source contribution from plasma extracellular vesicles long RNA sequencing profiles. EV-origin was constructed by the input matrix of gene expression signatures and robust deconvolution algorithm, collectively used to separate the relative proportions of each tissue or cell type of interest. EV-origin respectively predicted the relative enrichment of seven types of hemopoietic cells and sixteen solid tissue subsets from exLR-seq profile. Using the EV-origin approach, we depicted an integrated landscape of the traceability system of plasma EVs for healthy individuals. We also compared the heterogenous tissue-cellular source components from plasma EVs samples with diverse disease status. Notably, the aberrant liver fraction could reflect the development and progression of hepatic disease. The liver fraction could also serve as a diagnostic indicator and effectively separate HCC patients from normal individuals. The EV-origin provides an approach to decipher the complex heterogeneity of tissue-cellular origin in circulating EVs. Our approach could inform the development of exLR-based applications for liquid biopsy. Research Network of Computational and Structural Biotechnology 2020-10-14 /pmc/articles/PMC7588739/ /pubmed/33133426 http://dx.doi.org/10.1016/j.csbj.2020.10.002 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research Article
Li, Yuchen
He, Xigan
Li, Qin
Lai, Hongyan
Zhang, Hena
Hu, Zhixiang
Li, Yan
Huang, Shenglin
EV-origin: Enumerating the tissue-cellular origin of circulating extracellular vesicles using exLR profile
title EV-origin: Enumerating the tissue-cellular origin of circulating extracellular vesicles using exLR profile
title_full EV-origin: Enumerating the tissue-cellular origin of circulating extracellular vesicles using exLR profile
title_fullStr EV-origin: Enumerating the tissue-cellular origin of circulating extracellular vesicles using exLR profile
title_full_unstemmed EV-origin: Enumerating the tissue-cellular origin of circulating extracellular vesicles using exLR profile
title_short EV-origin: Enumerating the tissue-cellular origin of circulating extracellular vesicles using exLR profile
title_sort ev-origin: enumerating the tissue-cellular origin of circulating extracellular vesicles using exlr profile
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7588739/
https://www.ncbi.nlm.nih.gov/pubmed/33133426
http://dx.doi.org/10.1016/j.csbj.2020.10.002
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