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Simple Method to Quantify Protein Abundances from 1000 Cells
[Image: see text] The rise of single-cell transcriptomics has created an urgent need for similar approaches that use a minimal number of cells to quantify expression levels of proteins. We integrated and optimized multiple recent developments to establish a proteomics workflow to quantify proteins f...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7331059/ https://www.ncbi.nlm.nih.gov/pubmed/32637829 http://dx.doi.org/10.1021/acsomega.0c01191 |
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author | Vitrinel, Burcu Iannitelli, Dylan E. Mazzoni, Esteban O. Christiaen, Lionel Vogel, Christine |
author_facet | Vitrinel, Burcu Iannitelli, Dylan E. Mazzoni, Esteban O. Christiaen, Lionel Vogel, Christine |
author_sort | Vitrinel, Burcu |
collection | PubMed |
description | [Image: see text] The rise of single-cell transcriptomics has created an urgent need for similar approaches that use a minimal number of cells to quantify expression levels of proteins. We integrated and optimized multiple recent developments to establish a proteomics workflow to quantify proteins from as few as 1000 mammalian stem cells. The method uses chemical peptide labeling, does not require specific equipment other than cell lysis tools, and quantifies >2500 proteins with high reproducibility. We validated the method by comparing mouse embryonic stem cells and in vitro differentiated motor neurons. We identify differentially expressed proteins with small fold changes and a dynamic range in abundance similar to that of standard methods. Protein abundance measurements obtained with our protocol compared well to corresponding transcript abundance and to measurements using standard inputs. The protocol is also applicable to other systems, such as fluorescence-activated cell sorting (FACS)-purified cells from the tunicate Ciona. Therefore, we offer a straightforward and accurate method to acquire proteomics data from minimal input samples. |
format | Online Article Text |
id | pubmed-7331059 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-73310592020-07-06 Simple Method to Quantify Protein Abundances from 1000 Cells Vitrinel, Burcu Iannitelli, Dylan E. Mazzoni, Esteban O. Christiaen, Lionel Vogel, Christine ACS Omega [Image: see text] The rise of single-cell transcriptomics has created an urgent need for similar approaches that use a minimal number of cells to quantify expression levels of proteins. We integrated and optimized multiple recent developments to establish a proteomics workflow to quantify proteins from as few as 1000 mammalian stem cells. The method uses chemical peptide labeling, does not require specific equipment other than cell lysis tools, and quantifies >2500 proteins with high reproducibility. We validated the method by comparing mouse embryonic stem cells and in vitro differentiated motor neurons. We identify differentially expressed proteins with small fold changes and a dynamic range in abundance similar to that of standard methods. Protein abundance measurements obtained with our protocol compared well to corresponding transcript abundance and to measurements using standard inputs. The protocol is also applicable to other systems, such as fluorescence-activated cell sorting (FACS)-purified cells from the tunicate Ciona. Therefore, we offer a straightforward and accurate method to acquire proteomics data from minimal input samples. American Chemical Society 2020-06-19 /pmc/articles/PMC7331059/ /pubmed/32637829 http://dx.doi.org/10.1021/acsomega.0c01191 Text en Copyright © 2020 American Chemical Society This is an open access article published under an ACS AuthorChoice License (http://pubs.acs.org/page/policy/authorchoice_termsofuse.html) , which permits copying and redistribution of the article or any adaptations for non-commercial purposes. |
spellingShingle | Vitrinel, Burcu Iannitelli, Dylan E. Mazzoni, Esteban O. Christiaen, Lionel Vogel, Christine Simple Method to Quantify Protein Abundances from 1000 Cells |
title | Simple Method to Quantify Protein Abundances from
1000 Cells |
title_full | Simple Method to Quantify Protein Abundances from
1000 Cells |
title_fullStr | Simple Method to Quantify Protein Abundances from
1000 Cells |
title_full_unstemmed | Simple Method to Quantify Protein Abundances from
1000 Cells |
title_short | Simple Method to Quantify Protein Abundances from
1000 Cells |
title_sort | simple method to quantify protein abundances from
1000 cells |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7331059/ https://www.ncbi.nlm.nih.gov/pubmed/32637829 http://dx.doi.org/10.1021/acsomega.0c01191 |
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