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Ultrasensitive single-cell proteomics workflow identifies >1000 protein groups per mammalian cell
We report on the combination of nanodroplet sample preparation, ultra-low-flow nanoLC, high-field asymmetric ion mobility spectrometry (FAIMS), and the latest-generation Orbitrap Eclipse Tribrid mass spectrometer for greatly improved single-cell proteome profiling. FAIMS effectively filtered out sin...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society of Chemistry
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8178986/ https://www.ncbi.nlm.nih.gov/pubmed/34163866 http://dx.doi.org/10.1039/d0sc03636f |
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author | Cong, Yongzheng Motamedchaboki, Khatereh Misal, Santosh A. Liang, Yiran Guise, Amanda J. Truong, Thy Huguet, Romain Plowey, Edward D. Zhu, Ying Lopez-Ferrer, Daniel Kelly, Ryan T. |
author_facet | Cong, Yongzheng Motamedchaboki, Khatereh Misal, Santosh A. Liang, Yiran Guise, Amanda J. Truong, Thy Huguet, Romain Plowey, Edward D. Zhu, Ying Lopez-Ferrer, Daniel Kelly, Ryan T. |
author_sort | Cong, Yongzheng |
collection | PubMed |
description | We report on the combination of nanodroplet sample preparation, ultra-low-flow nanoLC, high-field asymmetric ion mobility spectrometry (FAIMS), and the latest-generation Orbitrap Eclipse Tribrid mass spectrometer for greatly improved single-cell proteome profiling. FAIMS effectively filtered out singly charged ions for more effective MS analysis of multiply charged peptides, resulting in an average of 1056 protein groups identified from single HeLa cells without MS1-level feature matching. This is 2.3 times more identifications than without FAIMS and a far greater level of proteome coverage for single mammalian cells than has been previously reported for a label-free study. Differential analysis of single microdissected motor neurons and interneurons from human spinal tissue indicated a similar level of proteome coverage, and the two subpopulations of cells were readily differentiated based on single-cell label-free quantification. |
format | Online Article Text |
id | pubmed-8178986 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | The Royal Society of Chemistry |
record_format | MEDLINE/PubMed |
spelling | pubmed-81789862021-06-22 Ultrasensitive single-cell proteomics workflow identifies >1000 protein groups per mammalian cell Cong, Yongzheng Motamedchaboki, Khatereh Misal, Santosh A. Liang, Yiran Guise, Amanda J. Truong, Thy Huguet, Romain Plowey, Edward D. Zhu, Ying Lopez-Ferrer, Daniel Kelly, Ryan T. Chem Sci Chemistry We report on the combination of nanodroplet sample preparation, ultra-low-flow nanoLC, high-field asymmetric ion mobility spectrometry (FAIMS), and the latest-generation Orbitrap Eclipse Tribrid mass spectrometer for greatly improved single-cell proteome profiling. FAIMS effectively filtered out singly charged ions for more effective MS analysis of multiply charged peptides, resulting in an average of 1056 protein groups identified from single HeLa cells without MS1-level feature matching. This is 2.3 times more identifications than without FAIMS and a far greater level of proteome coverage for single mammalian cells than has been previously reported for a label-free study. Differential analysis of single microdissected motor neurons and interneurons from human spinal tissue indicated a similar level of proteome coverage, and the two subpopulations of cells were readily differentiated based on single-cell label-free quantification. The Royal Society of Chemistry 2020-11-17 /pmc/articles/PMC8178986/ /pubmed/34163866 http://dx.doi.org/10.1039/d0sc03636f Text en This journal is © The Royal Society of Chemistry https://creativecommons.org/licenses/by-nc/3.0/ |
spellingShingle | Chemistry Cong, Yongzheng Motamedchaboki, Khatereh Misal, Santosh A. Liang, Yiran Guise, Amanda J. Truong, Thy Huguet, Romain Plowey, Edward D. Zhu, Ying Lopez-Ferrer, Daniel Kelly, Ryan T. Ultrasensitive single-cell proteomics workflow identifies >1000 protein groups per mammalian cell |
title | Ultrasensitive single-cell proteomics workflow identifies >1000 protein groups per mammalian cell |
title_full | Ultrasensitive single-cell proteomics workflow identifies >1000 protein groups per mammalian cell |
title_fullStr | Ultrasensitive single-cell proteomics workflow identifies >1000 protein groups per mammalian cell |
title_full_unstemmed | Ultrasensitive single-cell proteomics workflow identifies >1000 protein groups per mammalian cell |
title_short | Ultrasensitive single-cell proteomics workflow identifies >1000 protein groups per mammalian cell |
title_sort | ultrasensitive single-cell proteomics workflow identifies >1000 protein groups per mammalian cell |
topic | Chemistry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8178986/ https://www.ncbi.nlm.nih.gov/pubmed/34163866 http://dx.doi.org/10.1039/d0sc03636f |
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