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Combination of automated sample preparation and micro-flow LC–MS for high-throughput plasma proteomics

BACKGROUND: Non-invasive detection of blood-based markers is a critical clinical need. Plasma has become the main sample type for clinical proteomics research because it is easy to obtain and contains measurable protein biomarkers that can reveal disease-related physiological and pathological change...

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Autores principales: Ye, Xueting, Cui, Xiaozhen, Zhang, Luobin, Wu, Qiong, Sui, Xintong, He, An, Zhang, Xinyou, Xu, Ruilian, Tian, Ruijun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9824974/
https://www.ncbi.nlm.nih.gov/pubmed/36611134
http://dx.doi.org/10.1186/s12014-022-09390-w
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author Ye, Xueting
Cui, Xiaozhen
Zhang, Luobin
Wu, Qiong
Sui, Xintong
He, An
Zhang, Xinyou
Xu, Ruilian
Tian, Ruijun
author_facet Ye, Xueting
Cui, Xiaozhen
Zhang, Luobin
Wu, Qiong
Sui, Xintong
He, An
Zhang, Xinyou
Xu, Ruilian
Tian, Ruijun
author_sort Ye, Xueting
collection PubMed
description BACKGROUND: Non-invasive detection of blood-based markers is a critical clinical need. Plasma has become the main sample type for clinical proteomics research because it is easy to obtain and contains measurable protein biomarkers that can reveal disease-related physiological and pathological changes. Many efforts have been made to improve the depth of its identification, while there is an increasing need to improve the throughput and reproducibility of plasma proteomics analysis in order to adapt to the clinical large-scale sample analysis. METHODS: We have developed and optimized a robust plasma analysis workflow that combines an automated sample preparation platform with a micro-flow LC–MS-based detection method. The stability and reproducibility of the workflow were systematically evaluated and the workflow was applied to a proof-of-concept plasma proteome study of 30 colon cancer patients from three age groups. RESULTS: This workflow can analyze dozens of samples simultaneously with high reproducibility. Without protein depletion and prefractionation, more than 300 protein groups can be identified in a single analysis with micro-flow LC–MS system on a Orbitrap Exploris 240 mass spectrometer, including quantification of 35 FDA approved disease markers. The quantitative precision of the entire workflow was acceptable with median CV of 9%. The preliminary proteomic analysis of colon cancer plasma from different age groups could be well separated with identification of potential colon cancer-related biomarkers. CONCLUSIONS: This workflow is suitable for the analysis of large-scale clinical plasma samples with its simple and time-saving operation, and the results demonstrate the feasibility of discovering significantly changed plasma proteins and distinguishing different patient groups. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12014-022-09390-w.
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spelling pubmed-98249742023-01-08 Combination of automated sample preparation and micro-flow LC–MS for high-throughput plasma proteomics Ye, Xueting Cui, Xiaozhen Zhang, Luobin Wu, Qiong Sui, Xintong He, An Zhang, Xinyou Xu, Ruilian Tian, Ruijun Clin Proteomics Research BACKGROUND: Non-invasive detection of blood-based markers is a critical clinical need. Plasma has become the main sample type for clinical proteomics research because it is easy to obtain and contains measurable protein biomarkers that can reveal disease-related physiological and pathological changes. Many efforts have been made to improve the depth of its identification, while there is an increasing need to improve the throughput and reproducibility of plasma proteomics analysis in order to adapt to the clinical large-scale sample analysis. METHODS: We have developed and optimized a robust plasma analysis workflow that combines an automated sample preparation platform with a micro-flow LC–MS-based detection method. The stability and reproducibility of the workflow were systematically evaluated and the workflow was applied to a proof-of-concept plasma proteome study of 30 colon cancer patients from three age groups. RESULTS: This workflow can analyze dozens of samples simultaneously with high reproducibility. Without protein depletion and prefractionation, more than 300 protein groups can be identified in a single analysis with micro-flow LC–MS system on a Orbitrap Exploris 240 mass spectrometer, including quantification of 35 FDA approved disease markers. The quantitative precision of the entire workflow was acceptable with median CV of 9%. The preliminary proteomic analysis of colon cancer plasma from different age groups could be well separated with identification of potential colon cancer-related biomarkers. CONCLUSIONS: This workflow is suitable for the analysis of large-scale clinical plasma samples with its simple and time-saving operation, and the results demonstrate the feasibility of discovering significantly changed plasma proteins and distinguishing different patient groups. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12014-022-09390-w. BioMed Central 2023-01-07 /pmc/articles/PMC9824974/ /pubmed/36611134 http://dx.doi.org/10.1186/s12014-022-09390-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Ye, Xueting
Cui, Xiaozhen
Zhang, Luobin
Wu, Qiong
Sui, Xintong
He, An
Zhang, Xinyou
Xu, Ruilian
Tian, Ruijun
Combination of automated sample preparation and micro-flow LC–MS for high-throughput plasma proteomics
title Combination of automated sample preparation and micro-flow LC–MS for high-throughput plasma proteomics
title_full Combination of automated sample preparation and micro-flow LC–MS for high-throughput plasma proteomics
title_fullStr Combination of automated sample preparation and micro-flow LC–MS for high-throughput plasma proteomics
title_full_unstemmed Combination of automated sample preparation and micro-flow LC–MS for high-throughput plasma proteomics
title_short Combination of automated sample preparation and micro-flow LC–MS for high-throughput plasma proteomics
title_sort combination of automated sample preparation and micro-flow lc–ms for high-throughput plasma proteomics
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9824974/
https://www.ncbi.nlm.nih.gov/pubmed/36611134
http://dx.doi.org/10.1186/s12014-022-09390-w
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