Computational prediction of secreted proteins in gram-negative bacteria

Xinjie Hui; Zewei Chen; Junya Zhang; Moyang Lu; Xuxia Cai; Yuping Deng; Yueming Hu; Yejun Wang

doi:10.1016/j.csbj.2021.03.019

Computational prediction of secreted proteins in gram-negative bacteria

Comput Struct Biotechnol J. 2021 Mar 22:19:1806-1828. doi: 10.1016/j.csbj.2021.03.019. eCollection 2021.

Authors

Xinjie Hui¹, Zewei Chen¹, Junya Zhang¹, Moyang Lu², Xuxia Cai¹, Yuping Deng¹, Yueming Hu¹, Yejun Wang^{1

3}

Affiliations

¹ Youth Innovation Team of Medical Bioinformatics, Shenzhen University Health Science Center, Shenzhen 518060, China.
² College of Basic Medical Sciences, Army Medical University, Chongqing 400038, China.
³ Department of Cell Biology and Genetics, Shenzhen University Health Science Center, Shenzhen 518060, China.

Abstract

Gram-negative bacteria harness multiple protein secretion systems and secrete a large proportion of the proteome. Proteins can be exported to periplasmic space, integrated into membrane, transported into extracellular milieu, or translocated into cytoplasm of contacting cells. It is important for accurate, genome-wide annotation of the secreted proteins and their secretion pathways. In this review, we systematically classified the secreted proteins according to the types of secretion systems in Gram-negative bacteria, summarized the known features of these proteins, and reviewed the algorithms and tools for their prediction.

Keywords: Gram-negative bacteria; Prediction; Protein secretion system; Secreted protein; Transmembrane protein.

Publication types

Review