Identification of robust genes in transcriptional regulatory network of Mycobacterium tuberculosis

IET Syst Biol. 2020 Oct;14(5):292-296. doi: 10.1049/iet-syb.2020.0039.

Abstract

About 30% of the world population is infected with Mycobacterium tuberculosis (MTB). It is well known that the gene expression in MTB is highly variable, thus screening of traditional single-gene in MTB has been incapable to meet the desires of clinical diagnosis. In this report, the authors systemically analysed the transcription regulatory network (TRN) in MTB H37Rv. The complex interplay of these gene interactions has been revealed using exhaustive topological and global analysis of TRN using parameters including indegree, outdegree, degree, directed and undirected average path length (APL), and randomly performed. Results from indegree analysis reveal a set of important genes, including papA5 and Rv0177 which are associated with high indegree values. Gene ontology analysis suggested their importance in the virulence of MTB. In addition, APL and analysis of highly significant genes further identified some critical genes with different APL values. Among the list of genes identified, the csoR gene has the shortest directed APL score and high outdegree value, thus suggesting their importance in maintaining network topology. This study provides a comprehensive analysis of TRN and offers a good basis of understanding for developing experimental study in search of new therapeutic targets against MTB H37Rv pathogen.

MeSH terms

  • Computational Biology
  • Gene Expression Regulation, Bacterial*
  • Gene Regulatory Networks*
  • Genes, Bacterial
  • Mycobacterium tuberculosis* / genetics
  • Transcription, Genetic