SISPRO: Signature Identification for Spatial Proteomics

Ying Zhou; Yintao Zhang; Fengcheng Li; Xichen Lian; Qi Zhu; Feng Zhu; Yunqing Qiu

doi:10.1016/j.jmb.2022.167944

SISPRO: Signature Identification for Spatial Proteomics

J Mol Biol. 2023 Jul 15;435(14):167944. doi: 10.1016/j.jmb.2022.167944. Epub 2023 Jan 10.

Authors

Ying Zhou¹, Yintao Zhang², Fengcheng Li³, Xichen Lian³, Qi Zhu⁴, Feng Zhu⁵, Yunqing Qiu⁶

Affiliations

¹ State Key Laboratory for Diagnosis and Treatment of Infectious Disease, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang Provincial Key Laboratory for Drug Clinical Research and Evaluation, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310000, China. Electronic address: https://twitter.com/zhou36847275.
² College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China; Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou 330110, China. Electronic address: https://twitter.com/ZYintao.
³ College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China; Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou 330110, China.
⁴ College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
⁵ College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China; Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou 330110, China. Electronic address: zhufeng@zju.edu.cn.
⁶ State Key Laboratory for Diagnosis and Treatment of Infectious Disease, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang Provincial Key Laboratory for Drug Clinical Research and Evaluation, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310000, China. Electronic address: qiuyq@zju.edu.cn.

PMID: 37356911
DOI: 10.1016/j.jmb.2022.167944

Abstract

Spatial proteomics aims for a global description of organelle-specific protein distribution and dynamics, which is essential for understanding the molecular functions and cellular processes in health and disease. However, the application of this technique is seriously restricted by the neglect of robustness among proteomic signatures identified using standard statistical frameworks. Moreover, it is still a major bottleneck to automatically interpretate the identified proteomic signatures due to lack of integration of subcellular information. Herein, an online-tool SISPRO was constructed to (a) identify proteomic signatures with good robustness and accuracy via collectively evaluating relative weighted consistency (CWrel) & area under the curve (AUC) and (b) interpretate the identified signature based on comprehensive subcellular information from 9 organelles and 22 subcellular structures. All in all, SISPRO provides the endeavor to realize the simultaneous improvement of robustness and accuracy in signature identification and the unique capacity in biological annotation lies in its wide coverage of proteins and comprehensive spatial information. SISPRO is expected to be critical in spatial proteomic studies, which can be freely accessed without any login requirement at https://idrblab.org/sispro/.

Keywords: accuracy; organelle-specific biological interpretation; robustness; signature identification; spatial proteomics.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Organelles* / metabolism
Proteins* / metabolism
Proteomics* / methods

Substances

Proteins