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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...

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Autores principales: 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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
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.
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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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