Systems biology of tuberculosis


Autoria(s): Chandra, Nagasuma; Kumar, Dhiraj; Rao, Kanury
Data(s)

01/09/2011

Resumo

Systems biology seeks to study biological systems as a whole, by adopting an integrated approach to study and understand the function of biological systems, particularly, the response of such systems to various perturbations. In this article, we focus on the Indian efforts towards systems-level studies of Mycobacterium tuberculosis and its interaction with the host. Availability of a variety of genome-scale experimental data, providing first level `omics' descriptions of the pathogen, render it feasible to study it at a systems level. Various aspects of the pathogen, from metabolic pathways to protein-protein interaction networks have been modelled and simulated, while host-pathogen interactions have been studied experimentally using siRNA-based techniques. These studies have been useful in obtaining a global perspective of the pathogen and its interactions with the host in many ways. For example, significant insights have been gained about different aspects such as proteins essential for bacterial survival, proteins that are highly influential in the network, pathways that are highly connected, host factors responsible for maintaining the TB infection and key factors involved in autophagy and pathogenesis. A rational pipeline developed for drug target identification incorporating analyses of the interactome, reactome, genome, pocketome and the transcriptome is discussed. Finally, exploring host factors as drug targets and insights about the emergence of drug resistance are also discussed. (C) 2011 Elsevier Ltd. All rights reserved.

Formato

application/pdf

Identificador

http://eprints.iisc.ernet.in/41658/1/Systems_Biology.pdf

Chandra, Nagasuma and Kumar, Dhiraj and Rao, Kanury (2011) Systems biology of tuberculosis. In: Tuberculosis, 91 (5, SI). pp. 487-496.

Publicador

Elsevier Science

Relação

http://dx.doi.org/10.1016/j.tube.2011.02.008

http://eprints.iisc.ernet.in/41658/

Palavras-Chave #BioInformatics Centre
Tipo

Journal Article

PeerReviewed