Standard operating procedure combined with comprehensive quality control system for multiple LC-MS platforms urinary proteomics

X Xiang Liu H Haidan Sun X Xinhang Hou J Jiameng Sun M Min Tang (Key Laboratory of Birth Defects and Related Diseases of Women and Children, Department of Paediatrics, West China Second University Hospital, State Key Laboratory of Biotherapy, Sichuan University) Y Yong-Biao Zhang Y Yongqian Zhang W Wei Sun C Chao Liu Y Youhe Gao S Shuxuan Tang Z Ziyun Shen K Kehui Liu L Lulu Jia J Jing Wei (State Key Laboratory of Electronic Thin Films and Integrated Devices, School of Optoelectronic Science and Engineering) J Jianqiang Wu X Xiaoyue Tang Y Yanchang Li G Guibin Wang X Xinying Sui L Lihua Zhang (Center for Functional Nanomaterials) H Huiming Yuan X Xinxin Liu D Dong Liu (Hefei National Research Center for Physical Sciences at the Microscale, School of Chemistry and Materials Science, National Synchrotron Radiation Laboratory) Q Qi Zhang X Xindan Qiu G Guanbo Wang M Mo Hu Y Ye Tian M Minjie Tan P Peng Xue L Liman Guo Q Qing Zhang Y Yongsheng Chen (Department of Neurosurgery The Tenth Affiliated Hospital Southern Medical University Dongguan China) J Jianguo Ji W Weiyi Hu W Wenyuan Zhu M Min Huang Y Yingzi Qi X Xianming Liu (Institutes of Biomedical Sciences and Department of Chemistry, Fudan University) X Xiaoxian Du J Ji Luo L Lingsheng Chen Y Yinghua Zhao

Abstract

Abstract Urinary proteomics is emerging as a potent tool for detecting sensitive and non-invasive biomarkers. At present, the comparability of urinary proteomics data across diverse liquid chromatography−mass spectrometry (LC-MS) platforms remains an area that requires investigation. In this study, we conduct a comprehensive evaluation of urinary proteome across multiple LC-MS platforms. To systematically analyze and assess the quality of large-scale urinary proteomics data, we develop a comprehensive quality control (QC) system named MSCohort, which extracted 81 metrics for individual experiment and the whole cohort quality evaluation. Additionally, we present a standard operating procedure (SOP) for high-throughput urinary proteome analysis based on MSCohort QC system. Our study involves 20 LC-MS platforms and reveals that, when combined with a comprehensive QC system and a unified SOP, the data generated by data-independent acquisition (DIA) workflow in urine QC samples exhibit high robustness, sensitivity, and reproducibility across multiple LC-MS platforms. Furthermore, we apply this SOP to hybrid benchmarking samples and clinical colorectal cancer (CRC) urinary proteome including 527 experiments. Across three different LC-MS platforms, the analyses report high quantitative reproducibility and consistent disease patterns. This work lays the groundwork for large-scale clinical urinary proteomics studies spanning multiple platforms, paving the way for precision medicine research.

Article Details

Volume / Issue Vol. 16, Issue 1
Published January 26, 2025
ISSN 2041-1723
Publisher Nature Portfolio

Journal Info

Nature Communications

Nature Portfolio

ISSN: 2041-1723 Open Access Life Sciences

Authors (44)

X

Xiang Liu

H

Haidan Sun

X

Xinhang Hou

J

Jiameng Sun

M

Min Tang

Key Laboratory of Birth Defects and Related Diseases of Women and Children, Department of Paediatrics, West China Second University Hospital, State Key Laboratory of Biotherapy, Sichuan University

Y

Yong-Biao Zhang

Y

Yongqian Zhang

W

Wei Sun

C

Chao Liu

Y

Youhe Gao

S

Shuxuan Tang

Z

Ziyun Shen

K

Kehui Liu

L

Lulu Jia

J

Jing Wei

State Key Laboratory of Electronic Thin Films and Integrated Devices, School of Optoelectronic Science and Engineering

J

Jianqiang Wu

X

Xiaoyue Tang

Y

Yanchang Li

G

Guibin Wang

X

Xinying Sui

L

Lihua Zhang

Center for Functional Nanomaterials

H

Huiming Yuan

X

Xinxin Liu

D

Dong Liu

Hefei National Research Center for Physical Sciences at the Microscale, School of Chemistry and Materials Science, National Synchrotron Radiation Laboratory

Q

Qi Zhang

X

Xindan Qiu

G

Guanbo Wang

M

Mo Hu

Y

Ye Tian

M

Minjie Tan

P

Peng Xue

L

Liman Guo

Q

Qing Zhang

Y

Yongsheng Chen

Department of Neurosurgery The Tenth Affiliated Hospital Southern Medical University Dongguan China

J

Jianguo Ji

W

Weiyi Hu

W

Wenyuan Zhu

M

Min Huang

Y

Yingzi Qi

X

Xianming Liu

Institutes of Biomedical Sciences and Department of Chemistry, Fudan University

X

Xiaoxian Du

J

Ji Luo

L

Lingsheng Chen

Y

Yinghua Zhao