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dia-PASEF data analysis using FragPipe and DIA-NN for deep proteomics of low sample amounts
The dia-PASEF technology uses ion mobility separation to reduce signal interferences and increase sensitivity in proteomic experiments. Here we present a two-dimensional peak-picking algorithm and generation of optimized spectral libraries, as well as take advantage of neural network-based processin...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9270362/ https://www.ncbi.nlm.nih.gov/pubmed/35803928 http://dx.doi.org/10.1038/s41467-022-31492-0 |
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author | Demichev, Vadim Szyrwiel, Lukasz Yu, Fengchao Teo, Guo Ci Rosenberger, George Niewienda, Agathe Ludwig, Daniela Decker, Jens Kaspar-Schoenefeld, Stephanie Lilley, Kathryn S. Mülleder, Michael Nesvizhskii, Alexey I. Ralser, Markus |
author_facet | Demichev, Vadim Szyrwiel, Lukasz Yu, Fengchao Teo, Guo Ci Rosenberger, George Niewienda, Agathe Ludwig, Daniela Decker, Jens Kaspar-Schoenefeld, Stephanie Lilley, Kathryn S. Mülleder, Michael Nesvizhskii, Alexey I. Ralser, Markus |
author_sort | Demichev, Vadim |
collection | PubMed |
description | The dia-PASEF technology uses ion mobility separation to reduce signal interferences and increase sensitivity in proteomic experiments. Here we present a two-dimensional peak-picking algorithm and generation of optimized spectral libraries, as well as take advantage of neural network-based processing of dia-PASEF data. Our computational platform boosts proteomic depth by up to 83% compared to previous work, and is specifically beneficial for fast proteomic experiments and those with low sample amounts. It quantifies over 5300 proteins in single injections recorded at 200 samples per day throughput using Evosep One chromatography system on a timsTOF Pro mass spectrometer and almost 9000 proteins in single injections recorded with a 93-min nanoflow gradient on timsTOF Pro 2, from 200 ng of HeLa peptides. A user-friendly implementation is provided through the incorporation of the algorithms in the DIA-NN software and by the FragPipe workflow for spectral library generation. |
format | Online Article Text |
id | pubmed-9270362 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-92703622022-07-10 dia-PASEF data analysis using FragPipe and DIA-NN for deep proteomics of low sample amounts Demichev, Vadim Szyrwiel, Lukasz Yu, Fengchao Teo, Guo Ci Rosenberger, George Niewienda, Agathe Ludwig, Daniela Decker, Jens Kaspar-Schoenefeld, Stephanie Lilley, Kathryn S. Mülleder, Michael Nesvizhskii, Alexey I. Ralser, Markus Nat Commun Article The dia-PASEF technology uses ion mobility separation to reduce signal interferences and increase sensitivity in proteomic experiments. Here we present a two-dimensional peak-picking algorithm and generation of optimized spectral libraries, as well as take advantage of neural network-based processing of dia-PASEF data. Our computational platform boosts proteomic depth by up to 83% compared to previous work, and is specifically beneficial for fast proteomic experiments and those with low sample amounts. It quantifies over 5300 proteins in single injections recorded at 200 samples per day throughput using Evosep One chromatography system on a timsTOF Pro mass spectrometer and almost 9000 proteins in single injections recorded with a 93-min nanoflow gradient on timsTOF Pro 2, from 200 ng of HeLa peptides. A user-friendly implementation is provided through the incorporation of the algorithms in the DIA-NN software and by the FragPipe workflow for spectral library generation. Nature Publishing Group UK 2022-07-08 /pmc/articles/PMC9270362/ /pubmed/35803928 http://dx.doi.org/10.1038/s41467-022-31492-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Demichev, Vadim Szyrwiel, Lukasz Yu, Fengchao Teo, Guo Ci Rosenberger, George Niewienda, Agathe Ludwig, Daniela Decker, Jens Kaspar-Schoenefeld, Stephanie Lilley, Kathryn S. Mülleder, Michael Nesvizhskii, Alexey I. Ralser, Markus dia-PASEF data analysis using FragPipe and DIA-NN for deep proteomics of low sample amounts |
title | dia-PASEF data analysis using FragPipe and DIA-NN for deep proteomics of low sample amounts |
title_full | dia-PASEF data analysis using FragPipe and DIA-NN for deep proteomics of low sample amounts |
title_fullStr | dia-PASEF data analysis using FragPipe and DIA-NN for deep proteomics of low sample amounts |
title_full_unstemmed | dia-PASEF data analysis using FragPipe and DIA-NN for deep proteomics of low sample amounts |
title_short | dia-PASEF data analysis using FragPipe and DIA-NN for deep proteomics of low sample amounts |
title_sort | dia-pasef data analysis using fragpipe and dia-nn for deep proteomics of low sample amounts |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9270362/ https://www.ncbi.nlm.nih.gov/pubmed/35803928 http://dx.doi.org/10.1038/s41467-022-31492-0 |
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