KnockTB: Repository of Essential genes in Mycobacterium tuberculosis
Priti Vishnoi, Institute of Genomics and Integrative Biology, Delhi, India
Kumari Sonal, Institute of Genomics and Integrative Biology, Delhi, India
Anshu Bhardwaj, Council of Scientific and Industrial Research, Delhi, India
Anurag Passi, Council of Scientific and Industrial Research, Delhi, India
Anupam Kumar Mondal, Institute of Genomics and Integrative Biology, Delhi, India
Priyanka Priyadarshini, Council of Scientific and Industrial Research, Delhi, India
Vikas Kumar, Goethe University, Frankfurt, Germany
Anup Shah, Institute of Genomics and Integrative Biology, Delhi, India
Akanksha Jain, Council of Scientific and Industrial Research, Delhi, India
Kausik Bhattacharya, Institute of Genomics and Integrative Biology, Delhi, India
OSDD Consortium, Council of Scientific and Industrial Research, Delhi, India
Mycobacterium tuberculosis is a leading cause of death in developing world. With the increasing rates of drug resistance cases, the identification of genes that are required for the growth and survival of this organism may provide new targets for the design of anti-mycobacterial agents. We have undertaken an exhaustive data-mining approach to curate genes that are required for the growth, survival and virulence of mycobacterium. These genes are involved in many essential pathways of bacteria, which are essential for its metabolic requirements such as Trehalose Biosynthesis, Polyketide Synthesis Pathway. This data is systematically curated and organized into a database with user-friendly interface. The information in this database, knockTB, encompass experimental and in silico studies on gene essentiality. This database has been curated with the help of OSDD Community members. KnockTB has edit and update options to ensure that the data can be constantly updated and edited with increasing understanding of the pathogen biology. As of now the database has 700 genes with essentiality information in broth, macrophage and mice model. It also captures essentiality information from in silico knockouts. In addition to this, the gene function, its pathway and interacting partners are also reported. For better understanding of the essentiality, the presence of these genes is also reported in the mycobacterial cluster. With each annotation, the source of the information and the email of the annotators is also documented. Here we describe how this data can used to predict potential drug targets and vaccine candidates. In this data we have listed 47 drug targets with their experimental evidence of essentiality.
