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A fully automated FAIMS-DIA mass spectrometry-based proteomic pipeline
Here, we present a standardized, “off-the-shelf” proteomics pipeline working in a single 96-well plate to achieve deep coverage of cellular proteomes with high throughput and scalability. This integrated pipeline streamlines a fully automated sample preparation platform, a data-independent acquisiti...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10626189/ https://www.ncbi.nlm.nih.gov/pubmed/37729920 http://dx.doi.org/10.1016/j.crmeth.2023.100593 |
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author | Reilly, Luke Lara, Erika Ramos, Daniel Li, Ziyi Pantazis, Caroline B. Stadler, Julia Santiana, Marianita Roberts, Jessica Faghri, Faraz Hao, Ying Nalls, Mike A. Narayan, Priyanka Liu, Yansheng Singleton, Andrew B. Cookson, Mark R. Ward, Michael E. Qi, Yue A. |
author_facet | Reilly, Luke Lara, Erika Ramos, Daniel Li, Ziyi Pantazis, Caroline B. Stadler, Julia Santiana, Marianita Roberts, Jessica Faghri, Faraz Hao, Ying Nalls, Mike A. Narayan, Priyanka Liu, Yansheng Singleton, Andrew B. Cookson, Mark R. Ward, Michael E. Qi, Yue A. |
author_sort | Reilly, Luke |
collection | PubMed |
description | Here, we present a standardized, “off-the-shelf” proteomics pipeline working in a single 96-well plate to achieve deep coverage of cellular proteomes with high throughput and scalability. This integrated pipeline streamlines a fully automated sample preparation platform, a data-independent acquisition (DIA) coupled with high-field asymmetric waveform ion mobility spectrometer (FAIMS) interface, and an optimized library-free DIA database search strategy. Our systematic evaluation of FAIMS-DIA showing single compensation voltage (CV) at −35 V not only yields the deepest proteome coverage but also best correlates with DIA without FAIMS. Our in-depth comparison of direct-DIA database search engines shows that Spectronaut outperforms others, providing the highest quantifiable proteins. Next, we apply three common DIA strategies in characterizing human induced pluripotent stem cell (iPSC)-derived neurons and show single-shot mass spectrometry (MS) using single-CV (−35 V)-FAIMS-DIA results in >9,000 quantifiable proteins with <10% missing values, as well as superior reproducibility and accuracy compared with other existing DIA methods. |
format | Online Article Text |
id | pubmed-10626189 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-106261892023-11-07 A fully automated FAIMS-DIA mass spectrometry-based proteomic pipeline Reilly, Luke Lara, Erika Ramos, Daniel Li, Ziyi Pantazis, Caroline B. Stadler, Julia Santiana, Marianita Roberts, Jessica Faghri, Faraz Hao, Ying Nalls, Mike A. Narayan, Priyanka Liu, Yansheng Singleton, Andrew B. Cookson, Mark R. Ward, Michael E. Qi, Yue A. Cell Rep Methods Article Here, we present a standardized, “off-the-shelf” proteomics pipeline working in a single 96-well plate to achieve deep coverage of cellular proteomes with high throughput and scalability. This integrated pipeline streamlines a fully automated sample preparation platform, a data-independent acquisition (DIA) coupled with high-field asymmetric waveform ion mobility spectrometer (FAIMS) interface, and an optimized library-free DIA database search strategy. Our systematic evaluation of FAIMS-DIA showing single compensation voltage (CV) at −35 V not only yields the deepest proteome coverage but also best correlates with DIA without FAIMS. Our in-depth comparison of direct-DIA database search engines shows that Spectronaut outperforms others, providing the highest quantifiable proteins. Next, we apply three common DIA strategies in characterizing human induced pluripotent stem cell (iPSC)-derived neurons and show single-shot mass spectrometry (MS) using single-CV (−35 V)-FAIMS-DIA results in >9,000 quantifiable proteins with <10% missing values, as well as superior reproducibility and accuracy compared with other existing DIA methods. Elsevier 2023-09-19 /pmc/articles/PMC10626189/ /pubmed/37729920 http://dx.doi.org/10.1016/j.crmeth.2023.100593 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Reilly, Luke Lara, Erika Ramos, Daniel Li, Ziyi Pantazis, Caroline B. Stadler, Julia Santiana, Marianita Roberts, Jessica Faghri, Faraz Hao, Ying Nalls, Mike A. Narayan, Priyanka Liu, Yansheng Singleton, Andrew B. Cookson, Mark R. Ward, Michael E. Qi, Yue A. A fully automated FAIMS-DIA mass spectrometry-based proteomic pipeline |
title | A fully automated FAIMS-DIA mass spectrometry-based proteomic pipeline |
title_full | A fully automated FAIMS-DIA mass spectrometry-based proteomic pipeline |
title_fullStr | A fully automated FAIMS-DIA mass spectrometry-based proteomic pipeline |
title_full_unstemmed | A fully automated FAIMS-DIA mass spectrometry-based proteomic pipeline |
title_short | A fully automated FAIMS-DIA mass spectrometry-based proteomic pipeline |
title_sort | fully automated faims-dia mass spectrometry-based proteomic pipeline |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10626189/ https://www.ncbi.nlm.nih.gov/pubmed/37729920 http://dx.doi.org/10.1016/j.crmeth.2023.100593 |
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