PSL-LCCL: a resource for subcellular protein localization in liver cancer cell line SK_HEP1

Author:

Huang Fang,Tang Xia1,Ye Bo2,Wu Songfeng32,Ding Keyue1ORCID

Affiliation:

1. Medical Genetic Institute of Henan Province, Henan Provincial People’s Hospital, Henan Key Laboratory of Genetic Disease and Functional Genomics, National Health Commission Key Laboratory of Birth Defect Prevention, Henan Provincial People’s Hospital of Henan University, People’s Hospital of Zhengzhou University, #7 Road Weiwu, Jinshui District, Zhengzhou, Henan 450003, People’s Republic of China

2. Department of Bioinformatics, School of Basic Medicine, Chongqing Medical University, #1 Road Yixueyuan, Yuzhong District, Chongqing 400016, People’s Republic of China

3. State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug of Chinese Academy of Medical Sciences, Institute of Lifeomics, #38 life science park, Changping District, Beijing 102206, People’s Republic of China

Abstract

Abstract The characterization of subcellular protein localization provides a basis for further understanding cellular behaviors. A delineation of subcellular localization of proteins on cytosolic membrane-bound organelles in human liver cancer cell lines (hLCCLs) has yet to be performed. To obtain its proteome-wide view, we isolated and enriched six cytosolic membrane-bound organelles in one of the hLCCLs (SK_HEP1) and quantified their proteins using mass spectrometry. The vigorous selection of marker proteins and a machine-learning-based algorithm were implemented to localize proteins at cluster and neighborhood levels. We validated the performance of the proposed method by comparing the predicted subcellular protein localization with publicly available resources. The profiles enabled investigating the correlation of protein domains with their subcellular localization and colocalization of protein complex members. A subcellular proteome database for SK_HEP1, including (i) the subcellular protein localization and (ii) the subcellular locations of protein complex members and their interactions, was constructed. Our research provides resources for further research on hLCCLs proteomics. Database URL: http://www.igenetics.org.cn/project/PSL-LCCL/

Funder

Henan Provincial Key Laboratory of Genetic Diseases and Functional Genomics

Publisher

Oxford University Press (OUP)

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,Information Systems

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. dbMisLoc: A Manually Curated Database of Conditional Protein Mis-localization Events;Interdisciplinary Sciences: Computational Life Sciences;2023-03-31

2. Application of Machine Learning in Spatial Proteomics;Journal of Chemical Information and Modeling;2022-11-15

3. Recent Advances in the Prediction of Subcellular Localization of Proteins and Related Topics;Frontiers in Bioinformatics;2022-05-19

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