ePath: an online database towards comprehensive essential gene annotation for prokaryotes

• Published in: Scientific reports Vol. 9; no. 1; pp. 12949 - 11
• Main Authors: Kong, Xiangzhen, Zhu, Bin, Stone, Victoria N., Ge, Xiuchun, El-Rami, Fadi E., Donghai, Huangfu, Xu, Ping
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 10.09.2019; Nature Publishing Group
• Subjects: 631/208/325/1506; 631/208/721; Algorithms; Computational Biology - methods; Computer applications; Computer Simulation; Databases, Factual; Genes, Essential; Humanities and Social Sciences; Information processing; Internet; Molecular Sequence Annotation; multidisciplinary; Online data bases; Prokaryotes; Prokaryotic Cells - metabolism; Science; Science (multidisciplinary)
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-019-49098-w

Experimental techniques for identification of essential genes (EGs) in prokaryotes are usually expensive, time-consuming and sometimes unrealistic. Emerging in silico methods provide alternative methods for EG prediction, but often possess limitations including heavy computational requirements and lack of biological explanation. Here we propose a new computational algorithm for EG prediction in prokaryotes with an online database (ePath) for quick access to the EG prediction results of over 4,000 prokaryotes ( https://www.pubapps.vcu.edu/epath/ ). In ePath, gene essentiality is linked to biological functions annotated by KEGG Ortholog (KO). Two new scoring systems, namely, E_score and P_score, are proposed for each KO as the EG evaluation criteria. E_score represents appearance and essentiality of a given KO in existing experimental results of gene essentiality, while P_score denotes gene essentiality based on the principle that a gene is essential if it plays a role in genetic information processing, cell envelope maintenance or energy production. The new EG prediction algorithm shows prediction accuracy ranging from 75% to 91% based on validation from five new experimental studies on EG identification. Our overall goal with ePath is to provide a comprehensive and reliable reference for gene essentiality annotation, facilitating the study of those prokaryotes without experimentally derived gene essentiality information.