A Systems Level Comparison of Mycobacterium tuberculosis, Mycobacterium leprae and Mycobacterium smegmatis Based on Functional Interaction Network Analysis

Abstract

Mycobacterium leprae is a pathogenic bacteria that causes leprosy, a disease which affects mainly the skin, peripherical nerves, eyes and mucosa of the upper respiratory tract. Despite significant progress recorded in the last few years to stop this disease through a Multi-Drug Therapy (MDT) strategy, every year there are new reported cases of the disease. According to the World Health Organization, there were 192,242 new cases at the beginning of 2011. Mycobacterium leprae cannot be cultured in the laboratory but can be grown in mouse foot pads and more recently in nine banded armadillos because of its susceptibility to leprosy. Its highly reduced genome makes it an interesting species as a model for reductive evolution within the mycobacterial genus; it shares the same ancestor with Mycobacterium tuberculosis (MTB). A functional network for MTB was generated previously and extensive computational analyses were conducted to reveal the biological organization of the organism on the basis of the network’s topological properties. Here, we use genomic sequences and functional data from public databases to build protein functional networks for another slow grower, Mycobacterium leprae (MLP) and the fast growing non-pathogenic Mycobacterium smegmatis (MSM). Together with the MTB network, this provides an opportunity for comparison of three mycobacteria with different sized genomes. In this paper, we use network centrality measures to systematically compare MTB, MLP and MSM to quantify differences between these organisms at the systems biology level and to study network biology and evolution.