In silico genome-scale analysis reveals a putative TssM-like deubiquitinase as a virulence-associated marker in Burkholderia pseudomallei strain CM000113

Burkholderia pseudomallei produces a disease known as Melioidosis. Much of its genetic makeup remains undiscovered, including genes that code for what are called hypothetical and putative proteins. Uncharacterized proteins could uncover new mechanisms of virulence as well as reveal novel pathways and processes associated with pathogenesis. In this study, we present data on the B. pseudomallei CM000113 strain, which has 3,094 putative proteins (PPs), representing approximately 41% of its genome. Comparative sequence analysis using the Virulence Factor Database (VFDB) identified 20 PPs with >90% homology to known virulence determinants. Antigenicity profiling using VaxiJen v2.0 predicted a strong immunogenic potential for 18 of these PPs, underscoring their potential as vaccine candidates. Interestingly, one putative protein (IFOILCOA_05323) had a predicted structure that resembled TssM, a deubiquitinase. It also had several domain regions that were predicted to be associated with ubiquitin carboxyl-terminal hydrolase 14 open reading frame. Further in silico prediction of the protein sequences suggested that they participate in the bacterial intracellular immune evasion mechanism of the human host cell. It is predicted that these proteins will reside mainly in the periplasmic space and cytoplasm to fulfil their putative roles. Protein–protein docking, HADDOCK scoring, and molecular dynamics simulations demonstrated stable interactions with host HLA molecules, particularly HLA-DQB2, corroborated by host–pathogen interactome predictions. These integrative in silico analyses offer the first insights into the structural and functional attributes of these PPs, leading to their consideration for experimental analyses of vaccine and therapeutic strategies against melioidosis. Keywords: Burkholderia pseudomallei, putative proteins, virulence factors, functional prediction, in silico approaches, melioidosis