Omics of Brucella : Species-Specific sRNA-Mediated Gene Ontology Regulatory Networks Identified by Computational Biology

Abstract

Abstract

Brucella is an intracellular bacterium that causes the zoonotic infectious disease, brucellosis. Brucella species are currently intensively studied with a view to developing novel global health diagnostics and therapeutics. In this context, small RNAs (sRNAs) are one of the emerging topical areas; they play significant roles in regulating gene expression and cellular processes in bacteria. In the present study, we forecast sRNAs in three Brucella species that infect humans, namely Brucella melitensis, Brucella abortus, and Brucella suis, using a computational biology analysis. We combined two bioinformatic algorithms, SIPHT and sRNAscanner. In B. melitensis 16M, 21 sRNA candidates were identified, of which 14 were novel. Similarly, 14 sRNAs were identified in B. abortus, of which four were novel. In B. suis, 16 sRNAs were identified, and five of them were novel. TargetRNA2 software predicted the putative target genes that could be regulated by the identified sRNAs. The identified mRNA targets are involved in carbohydrate, amino acid, lipid, nucleotide, and coenzyme metabolism and transport, energy production and conversion, replication, recombination, repair, and transcription. Additionally, the Gene Ontology (GO) network analysis revealed the species-specific, sRNA-based regulatory networks in B. melitensis, B. abortus, and B. suis. Taken together, although sRNAs are veritable modulators of gene expression in prokaryotes, there are few reports on the significance of sRNAs in Brucella. This report begins to address this literature gap by offering a series of initial observations based on computational biology to pave the way for future experimental analysis of sRNAs and their targets to explain the complex pathogenesis of Brucella.