Precise prediction of phase-separation key residues by machine learning.

Journal: Nature communications
PMID: 38531854

Abstract

Understanding intracellular phase separation is crucial for deciphering transcriptional control, cell fate transitions, and disease mechanisms. However, the key residues, which impact phase separation the most for protein phase separation function have remained elusive. We develop PSPHunter, which can precisely predict these key residues based on machine learning scheme. In vivo and in vitro validations demonstrate that truncating just 6 key residues in GATA3 disrupts phase separation, enhancing tumor cell migration and inhibiting growth. Glycine and its motifs are enriched in spacer and key residues, as revealed by our comprehensive analysis. PSPHunter identifies nearly 80% of disease-associated phase-separating proteins, with frequent mutated pathological residues like glycine and proline often residing in these key residues. PSPHunter thus emerges as a crucial tool to uncover key residues, facilitating insights into phase separation mechanisms governing transcriptional control, cell fate transitions, and disease development.

Authors

  • Jun Sun
    School of Environmental and Chemical Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, Jiangsu Province, PR China.
  • Jiale Qu
    RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Cai Zhao
    RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Xinyao Zhang
    RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Xinyu Liu
    Institute of Medical Technology, Peking University Health Science Center, Beijing, China.
  • Jia Wang
    Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun, Jilin, China.
  • Chao Wei
    Beijing Institute of Technology, Beijing, 10081, China.
  • Xinyi Liu
    Department of Pharmacy, Second Xiangya Hospital, Central South University, Changsha 410011, China.
  • Mulan Wang
    RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Pengguihang Zeng
    RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Xiuxiao Tang
    RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Xiaoru Ling
    RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Li Qing
    RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Shaoshuai Jiang
    RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Jiahao Chen
    The First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, 310006, China.
  • Tara S R Chen
    Department of Rehabilitation Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, Guangdong, 518107, China.
  • Yalan Kuang
    Department of Thoracic Surgery and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, 610041, China.
  • Jinhang Gao
    Department of Thoracic Surgery and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, 610041, China.
  • Xiaoxi Zeng
  • Dongfeng Huang
    Department of Rehabilitation Medicine, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510080, China.
  • Yong Yuan
    Department of Thoracic Surgery and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, 610041, China. yongyuan@scu.edu.cn.
  • Lili Fan
    Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, School of Traditional Chinese Medicine, Jinan University, Guangzhou, Guangdong, China. fanlili@jnu.edu.cn.
  • Haopeng Yu
    Department of Thoracic Surgery and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, 610041, China. yuhaopeng@wchscu.cn.
  • Junjun Ding
    Department of Thoracic Surgery and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, 610041, China. dingjunj@mail.sysu.edu.cn.

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