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Sci Rep. 2019 Sep 10;9(1):12949. doi: 10.1038/s41598-019-49098-w.

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

Author information

1
Philips Institute for Oral Health Research, Virginia Commonwealth University, Richmond, Virginia, 23298, United States of America.
2
Application Services, Virginia Commonwealth University, Richmond, Virginia, United States of America.
3
Philips Institute for Oral Health Research, Virginia Commonwealth University, Richmond, Virginia, 23298, United States of America. pxu@vcu.edu.
4
Department of Microbiology and Immunology, Virginia Commonwealth University, Richmond, Virginia, United States of America. pxu@vcu.edu.
5
Center for Biological Data Science, Virginia Commonwealth University, Richmond, Virginia, United States of America. pxu@vcu.edu.

Abstract

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.

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