文献类型： 外文期刊

作者： Gao, Huanhuan ¹ ; Zhu, Yi ¹ ; Wang, Dongxue ⁴ ; Nie, Zongxiang ⁶ ; Wang, He ¹ ; Wang, Guibin ⁴ ; Liang, Shuang ⁷ ; Xie, Yuting ¹ ; Sun, Yingying ¹ ; Jiang, Wenhao ¹ ; Dong, Zhen ¹ ; Qian, Liqin ¹ ; Wang, Xufei ⁸ ; Liang, Mengdi ⁸ ; Chen, Min ⁹ ; Fang, Houqi ⁹ ; Zeng, Qiufang ¹⁰ ; Tian, Jiao ¹⁰ ; Sun, Zeyu ¹¹ ; Xue, Juan ¹² ; Li, Shan ¹² ; Chen, Chen ¹⁴ ; Liu, Xiang ¹⁴ ; Lyu, Xiaolei ¹⁴ ; Guo, Zhenchang ¹⁵ ; Qi, Yingzi ¹⁵ ; Wu, Ruoyu ¹⁶ ; Du, Xiaoxian ¹⁶ ; Tong, Tingde ¹⁵ ; Kong, Fengchun ¹⁴ ; Han, Liming ¹⁶ ; Wang, Minghui ¹⁶ ; Zhao, Yang ¹⁷ ; Dai, Xinhua ¹⁷ ; He, Fuchu ⁴ ; Guo, Tiannan ¹ ;

作者机构： 1.Westlake Univ, Hangzhou Peoples Hosp 1, Sch Med, State Key Lab Med Prote, Hangzhou, Zhejiang, Peoples R China

2.Westlake Ctr Intelligent Prote, Westlake Lab Life Sci & Biomed, Hangzhou, Zhejiang, Peoples R China

3.Westlake Univ, Sch Life Sci, Res Ctr Ind Future, Hangzhou, Zhejiang, Peoples R China

4.Beijing Inst Life, Beijing Proteome Res Ctr, Natl Ctr Prot Sci Beijing, State Key Lab Med Prote, Beijing, Peoples R China

5.Int Acad Phronesis Med, Guangzhou, Guangdong, Peoples R China

6.Westlake Om Hangzhou Biotechnol Co Ltd, Hangzhou, Peoples R China

7.Zhejiang Acad Agr Sci, Inst Agroprod Safety & Nutr, Hangzhou 310021, Peoples R China

8.Guangzhou Med Univ, Sino French Hoffmann Inst, Sch Basic Med Sci, State Key Lab Resp Dis, Guangzhou, Peoples R China

9.Luming Biotechnol Co Ltd, Shanghai, Peoples R China

10.Shanghai Appl Prot Technol Co Ltd, Shanghai, Peoples R China

11.Zhejiang Univ, State Key Lab Diag & Treatment Infect Dis, Natl Clin Res Ctr Infect Dis, Collaborat Innovat Ctr Diag & Treatment Infect Dis, Hangzhou, Zhejiang, Peoples R China

12.Hubei Univ Med, Taihe Hosp, Inst Infect & Immun, Shiyan, Hubei, Peoples R China

13.Huazhong Agr Univ, Coll Biomed & Hlth, Wuhan, Hubei, Peoples R China

14.SCIEX Ltd, Shanghai, Peoples R China

15.Thermo Fisher Sci, Shanghai, Peoples R China

16.Bruker Daltonics, Beijing, Peoples R China

17.Natl Inst Metrol, Technol Innovat Ctr Mass Spectrometry State Market, Ctr Adv Measurement Sci, Beijing 100029, Peoples R China

期刊名称：NATURE COMMUNICATIONS （ 影响因子：15.7； 五年影响因子：17.2 ）

ISSN：

年卷期： 2025 年 16 卷 1 期

页码：

收录情况： SCI

摘要： Quality control (QC) in mass spectrometry (MS)-based proteomics is mainly based on data-dependent acquisition (DDA) analysis of standard samples. Here, we collect 2754 files acquired by data independent acquisition (DIA) and paired 2638 DDA files from mouse liver digests using 21 mass spectrometers across nine laboratories over 31 months. Our data demonstrate that DIA-based LC-MS/MS-related consensus QC metrics exhibit higher sensitivity compared to DDA-based QC metrics in detecting changes in LC-MS status. We then prioritize 15 metrics and invite 21 experts to manually assess the quality of 2754 DIA files based on those metrics. We develop an AI model for DIA-based QC using 2110 training files. It achieves AUCs of 0.91 (LC) and 0.97 (MS) in the first validation dataset (n = 528), and 0.78 (LC) and 0.94 (MS) in an independent validation dataset (n = 116). Finally, we develop an offline software called iDIA-QC for convenient adoption of this methodology.