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用于无标记蛋白质组学多平台评估的四重蛋白参考材料和数据集。

Quartet protein reference materials and datasets for multi-platform assessment of label-free proteomics.

机构信息

State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Institutes of Biomedical Sciences, Human Phenome Institute, Zhongshan Hospital, Fudan University, Shanghai, 200433, China.

State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China.

出版信息

Genome Biol. 2023 Sep 7;24(1):202. doi: 10.1186/s13059-023-03048-y.

DOI:10.1186/s13059-023-03048-y
PMID:37674236
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10483797/
Abstract

BACKGROUND

Quantitative proteomics is an indispensable tool in life science research. However, there is a lack of reference materials for evaluating the reproducibility of label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based measurements among different instruments and laboratories.

RESULTS

Here, we develop the Quartet standard as a proteome reference material with built-in truths, and distribute the same aliquots to 15 laboratories with nine conventional LC-MS/MS platforms across six cities in China. Relative abundance of over 12,000 proteins on 816 mass spectrometry files are obtained and compared for reproducibility among the instruments and laboratories to ultimately generate proteomics benchmark datasets. There is a wide dynamic range of proteomes spanning about 7 orders of magnitude, and the injection order has marked effects on quantitative instead of qualitative characteristics.

CONCLUSION

Overall, the Quartet offers valuable standard materials and data resources for improving the quality control of proteomic analyses as well as the reproducibility and reliability of research findings.

摘要

背景

定量蛋白质组学是生命科学研究中不可或缺的工具。然而,缺乏用于评估不同仪器和实验室之间基于无标记液相色谱-串联质谱(LC-MS/MS)测量的重现性的参考材料。

结果

在这里,我们开发了 Quartet 标准品作为具有内置真实性的蛋白质组参考材料,并将相同的等分试样分发给中国六个城市的 15 个实验室,这些实验室配备了 9 种常规 LC-MS/MS 平台。从 816 个质谱文件中获得了超过 12000 种蛋白质的相对丰度,并对仪器和实验室之间的重现性进行了比较,最终生成了蛋白质组基准数据集。蛋白质组具有约 7 个数量级的宽动态范围,进样顺序对定量而非定性特征有显著影响。

结论

总体而言, Quartet 为提高蛋白质组分析的质量控制以及研究结果的重现性和可靠性提供了有价值的标准材料和数据资源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be92/10483797/c85ddbb033ca/13059_2023_3048_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be92/10483797/d13bcebeac24/13059_2023_3048_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be92/10483797/d1afb609b0fd/13059_2023_3048_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be92/10483797/d9f48a137a54/13059_2023_3048_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be92/10483797/be064f5e52de/13059_2023_3048_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be92/10483797/1a682cc0cab7/13059_2023_3048_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be92/10483797/4be9815557bb/13059_2023_3048_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be92/10483797/aa4b89ca17f0/13059_2023_3048_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be92/10483797/c85ddbb033ca/13059_2023_3048_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be92/10483797/d13bcebeac24/13059_2023_3048_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be92/10483797/d1afb609b0fd/13059_2023_3048_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be92/10483797/d9f48a137a54/13059_2023_3048_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be92/10483797/be064f5e52de/13059_2023_3048_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be92/10483797/1a682cc0cab7/13059_2023_3048_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be92/10483797/4be9815557bb/13059_2023_3048_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be92/10483797/aa4b89ca17f0/13059_2023_3048_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be92/10483797/c85ddbb033ca/13059_2023_3048_Fig8_HTML.jpg

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