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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2021
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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. |
format | Online Article Text |
id | pubmed-8463870 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
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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