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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2021
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.
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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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