Biology subjects

Shastry, R. P.

Publications and source records attributed to Shastry, R. P..

3 recordsLinked to original sources

bioRxiv2023

Comparative genomics reveals the diversity of CRISPR-Cas systems among neonatal sepsis causing group B Streptococcus agalactiae

The pathogen Streptococcus agalactiae, or Group B Streptococcus (GBS) infection is the leading cause of neonatal sepsis and meningitis in neonates. In this study, we aimed to investigate the occurrence and diversity of the CRISPR-Cas system in S. agalactiae genomes using computational biology approaches. A total of 51 out of 52 complete genomes (98.07%) of S. agalactiae possess CRISPR arrays (75 CRISPR arrays) with 17 strains possessing multiple CRISPR arrays. There were only two CRISPR-Cas systems - type II-A system and type I-C system in S. agalactiae strains. RNA secondary structure analysis through direct repeat analysis showed that the analyzed strains could form stable secondary structures. The 16S rRNA phylogeny exhibited clustering of the strains into three major clades grouped on the type of CRISPR-Cas system. The anti-CRISPRs that contribute to CRISPR-Cas system diversity and prevent genome editing were also detected. These results provide valuable insights into elucidating the evolution, diversity, and function of CRISPR/Cas elements in this pathogen.

bioinformatics↗

bioRxiv2023

Functional network analysis identifies multiple virulence and antibiotic resistance systems in Stenotrophomonas maltophilia

Stenotrophomonas maltophilia, an emerging multidrug-resistant opportunistic bacterium in humans is of major concern for immunocompromised individuals for causing pneumonia and bloodborne infections. This bacterial pathogen is associated with a considerable fatality/case ratio, with up to 100%, when presented as hemorrhagic fever. It is resistant to commonly used drugs as well as to antibiotic combinations. In-silico based functional network analysis is a key approach to get novel insights into virulence and resistance in pathogenic organisms. This study included the protein-protein interaction (PPI) network analysis of 150 specific genes identified for antibiotic resistance mechanism and virulence pathways. Eight proteins, namely, pilL, fliA, Smlt2260, Smlt2267, cheW, Smlt2318, cheZ, and fliM were identified as hub proteins. Further docking studies of selected phytochemicals were performed against the identified hub proteins. Deoxytubulosine and Corosolic acid were found to be potent inhibitors of hub proteins of pathogenic S. maltophilia based on protein-ligand interactive study. Further pharmacophore studies are warranted with these molecules to develop them as novel antibiotics against S. maltophilia.

bioinformatics↗

bioRxiv2022

Prevalence and heterogeneity of antibiotic-resistant genes in Orientia tsutsugamushi and other rickettsial genomes

Despite a million infections every year and an estimated one billion people at risk, scrub typhus is regarded as a neglected tropical disease. The causative bacterium Orientia tsutsugamushi, a member of rickettsiae, seems to be intrinsically resistant to several classes of antibiotics. The emergence of antibiotic-resistant scrub typhus is likely to become a global public health concern. Yet, it is unknown as to how common antibiotic-resistant genes are in O. tsutsugamushi, and how variable these loci are among the genomes of rickettsiae. By using the comprehensive antibiotic resistance database, we explored 79 complete genomes from 24 species of rickettsiae for putative antibiotic-resistant loci. There were 244 unique antibiotic-resistant genes in rickettsiae. Both the total and unique antibiotic-resistant genes in O. tsutsugamushi were significantly less compared to other members of rickettsiae. However, antibiotic-resistant genes in O. tsutsugamushi genomes were more unique and highly variable. Many genes such as resistant versions of evgS, and vanS A/G were present in numerous copies. These results will have important implications in the context of antibiotic-resistant scrub typhus.

bioinformatics↗