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Identifying extracellular vesicle populations from single cells

Extracellular vesicles (EVs) are constantly secreted from both eukaryotic and prokaryotic cells. EVs, including those referred to as exosomes, may have an impact on cell signaling and an incidence in diseased cells. In this manuscript, a platform to capture, quantify, and phenotypically classify the...

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Autores principales: Nikoloff, Jonas M., Saucedo-Espinosa, Mario A., Kling, André, Dittrich, Petra S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8463870/
https://www.ncbi.nlm.nih.gov/pubmed/34518226
http://dx.doi.org/10.1073/pnas.2106630118
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author Nikoloff, Jonas M.
Saucedo-Espinosa, Mario A.
Kling, André
Dittrich, Petra S.
author_facet Nikoloff, Jonas M.
Saucedo-Espinosa, Mario A.
Kling, André
Dittrich, Petra S.
author_sort Nikoloff, Jonas M.
collection PubMed
description Extracellular vesicles (EVs) are constantly secreted from both eukaryotic and prokaryotic cells. EVs, including those referred to as exosomes, may have an impact on cell signaling and an incidence in diseased cells. In this manuscript, a platform to capture, quantify, and phenotypically classify the EVs secreted from single cells is introduced. Microfluidic chambers of about 300 pL are employed to trap and isolate individual cells. The EVs secreted within these chambers are then captured by surface-immobilized monoclonal antibodies (mAbs), irrespective of their intracellular origin. Immunostaining against both plasma membrane and cytosolic proteins was combined with highly sensitive, multicolor total internal reflection fluorescence microscopy to characterize the immobilized vesicles. The data analysis of high-resolution images allowed the assignment of each detected EV to one of 15 unique populations and demonstrated the presence of highly heterogeneous phenotypes even at the single-cell level. The analysis also revealed that each mAb isolates phenotypically different EVs and that more vesicles were effectively immobilized when CD63 was targeted instead of CD81. Finally, we demonstrate how a heterogeneous suppression in the secreted vesicles is obtained when the enzyme neutral sphingomyelinase is inhibited.
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spelling pubmed-84638702021-10-27 Identifying extracellular vesicle populations from single cells Nikoloff, Jonas M. Saucedo-Espinosa, Mario A. Kling, André Dittrich, Petra S. Proc Natl Acad Sci U S A Physical Sciences Extracellular vesicles (EVs) are constantly secreted from both eukaryotic and prokaryotic cells. EVs, including those referred to as exosomes, may have an impact on cell signaling and an incidence in diseased cells. In this manuscript, a platform to capture, quantify, and phenotypically classify the EVs secreted from single cells is introduced. Microfluidic chambers of about 300 pL are employed to trap and isolate individual cells. The EVs secreted within these chambers are then captured by surface-immobilized monoclonal antibodies (mAbs), irrespective of their intracellular origin. Immunostaining against both plasma membrane and cytosolic proteins was combined with highly sensitive, multicolor total internal reflection fluorescence microscopy to characterize the immobilized vesicles. The data analysis of high-resolution images allowed the assignment of each detected EV to one of 15 unique populations and demonstrated the presence of highly heterogeneous phenotypes even at the single-cell level. The analysis also revealed that each mAb isolates phenotypically different EVs and that more vesicles were effectively immobilized when CD63 was targeted instead of CD81. Finally, we demonstrate how a heterogeneous suppression in the secreted vesicles is obtained when the enzyme neutral sphingomyelinase is inhibited. National Academy of Sciences 2021-09-21 2021-09-13 /pmc/articles/PMC8463870/ /pubmed/34518226 http://dx.doi.org/10.1073/pnas.2106630118 Text en Copyright © 2021 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by/4.0/This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY) (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Physical Sciences
Nikoloff, Jonas M.
Saucedo-Espinosa, Mario A.
Kling, André
Dittrich, Petra S.
Identifying extracellular vesicle populations from single cells
title Identifying extracellular vesicle populations from single cells
title_full Identifying extracellular vesicle populations from single cells
title_fullStr Identifying extracellular vesicle populations from single cells
title_full_unstemmed Identifying extracellular vesicle populations from single cells
title_short Identifying extracellular vesicle populations from single cells
title_sort identifying extracellular vesicle populations from single cells
topic Physical Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8463870/
https://www.ncbi.nlm.nih.gov/pubmed/34518226
http://dx.doi.org/10.1073/pnas.2106630118
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