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Proteomics for Low Cell Numbers: How to Optimize the Sample Preparation Workflow for Mass Spectrometry Analysis
[Image: see text] Nowadays, massive genomics and transcriptomics data can be generated at the single-cell level. However, proteomics in this setting is still a big challenge. Despite the great improvements in sensitivity and performance of mass spectrometry instruments and the better knowledge on sa...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical
Society
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8419858/ https://www.ncbi.nlm.nih.gov/pubmed/34328739 http://dx.doi.org/10.1021/acs.jproteome.1c00321 |
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author | Kassem, Sara van der Pan, Kyra de Jager, Anniek L. Naber, Brigitta A. E. de Laat, Inge F. Louis, Alesha van Dongen, Jacques J. M. Teodosio, Cristina Díez, Paula |
author_facet | Kassem, Sara van der Pan, Kyra de Jager, Anniek L. Naber, Brigitta A. E. de Laat, Inge F. Louis, Alesha van Dongen, Jacques J. M. Teodosio, Cristina Díez, Paula |
author_sort | Kassem, Sara |
collection | PubMed |
description | [Image: see text] Nowadays, massive genomics and transcriptomics data can be generated at the single-cell level. However, proteomics in this setting is still a big challenge. Despite the great improvements in sensitivity and performance of mass spectrometry instruments and the better knowledge on sample preparation processing, it is widely acknowledged that multistep proteomics workflows may lead to substantial sample loss, especially when working with paucicellular samples. Still, in clinical fields, frequently limited sample amounts are available for downstream analysis, thereby hampering comprehensive characterization at protein level. To aim at better protein and peptide recoveries, we compare existing and novel approaches in the multistep sample preparation protocols for mass spectrometry studies, from sample collection, cell lysis, protein quantification, and electrophoresis/staining to protein digestion, peptide recovery, and LC-MS/MS instruments. From this critical evaluation, we conclude that the recent innovations and technologies, together with high quality management of samples, make proteomics on paucicellular samples possible, which will have immediate impact for the proteomics community. |
format | Online Article Text |
id | pubmed-8419858 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | American Chemical
Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-84198582021-09-07 Proteomics for Low Cell Numbers: How to Optimize the Sample Preparation Workflow for Mass Spectrometry Analysis Kassem, Sara van der Pan, Kyra de Jager, Anniek L. Naber, Brigitta A. E. de Laat, Inge F. Louis, Alesha van Dongen, Jacques J. M. Teodosio, Cristina Díez, Paula J Proteome Res [Image: see text] Nowadays, massive genomics and transcriptomics data can be generated at the single-cell level. However, proteomics in this setting is still a big challenge. Despite the great improvements in sensitivity and performance of mass spectrometry instruments and the better knowledge on sample preparation processing, it is widely acknowledged that multistep proteomics workflows may lead to substantial sample loss, especially when working with paucicellular samples. Still, in clinical fields, frequently limited sample amounts are available for downstream analysis, thereby hampering comprehensive characterization at protein level. To aim at better protein and peptide recoveries, we compare existing and novel approaches in the multistep sample preparation protocols for mass spectrometry studies, from sample collection, cell lysis, protein quantification, and electrophoresis/staining to protein digestion, peptide recovery, and LC-MS/MS instruments. From this critical evaluation, we conclude that the recent innovations and technologies, together with high quality management of samples, make proteomics on paucicellular samples possible, which will have immediate impact for the proteomics community. American Chemical Society 2021-07-30 2021-09-03 /pmc/articles/PMC8419858/ /pubmed/34328739 http://dx.doi.org/10.1021/acs.jproteome.1c00321 Text en © 2021 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Kassem, Sara van der Pan, Kyra de Jager, Anniek L. Naber, Brigitta A. E. de Laat, Inge F. Louis, Alesha van Dongen, Jacques J. M. Teodosio, Cristina Díez, Paula Proteomics for Low Cell Numbers: How to Optimize the Sample Preparation Workflow for Mass Spectrometry Analysis |
title | Proteomics for
Low Cell Numbers: How to Optimize the
Sample Preparation Workflow for Mass Spectrometry Analysis |
title_full | Proteomics for
Low Cell Numbers: How to Optimize the
Sample Preparation Workflow for Mass Spectrometry Analysis |
title_fullStr | Proteomics for
Low Cell Numbers: How to Optimize the
Sample Preparation Workflow for Mass Spectrometry Analysis |
title_full_unstemmed | Proteomics for
Low Cell Numbers: How to Optimize the
Sample Preparation Workflow for Mass Spectrometry Analysis |
title_short | Proteomics for
Low Cell Numbers: How to Optimize the
Sample Preparation Workflow for Mass Spectrometry Analysis |
title_sort | proteomics for
low cell numbers: how to optimize the
sample preparation workflow for mass spectrometry analysis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8419858/ https://www.ncbi.nlm.nih.gov/pubmed/34328739 http://dx.doi.org/10.1021/acs.jproteome.1c00321 |
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