Molecular signatures for gene expression in Mycobacterium leprae: A bioinformatic analysis

Abstract

Mycobacterium leprae is an obligate intracellular parasite that has been difficult to study due to its inability to grow in artificial media and its late generation time. Differential gene expressions depend upon specific molecular signatures in and around specific genes in the genome. In silico bioinformatic studies can complement the analysis of data generated through wet-lab experiments. We analyzed molecular signatures in highly and lowly expressed genes (HEGs and LEGs) in M. leprae using DAMBE software. Secondary data from Akama et al. (2010) were used to select RNA expression levels of HEGs and LEGs. Minimum folding energies in 5′UTR of HEGs were higher (less negative) than in LEGs, and the Shine Dalgarno binding patterns were more clearly defined for HEGs than in LEGs. There were no differences in relative synonymous codon usage patterns, codon adaptation indices, and indices of translation elongations. Our analysis suggests that the molecular signatures in the 5′UTRs may have a greater role in determining the overall expression of the genes of M. leprae.