Computational prediction of crucial genes involved in gonorrhea infection and neoplastic cell transformation: A multiomics approach

RAVINDRANATH, B.S.; ANANYA, G.; HEMA KUMAR, C.; RAMIREZ, D.C.; GOMEZ MEJIBA, S.E.

MICROBIAL PATHOGENESIS

ACADEMIC PRESS LTD-ELSEVIER SCIENCE LTD

Año: 2024 vol. 193

0882-4010

AbstractNeisseria gonorrheae, the causative agent of genitourinary infections, has beenassociated with asymptomatic or recurrent infections with the potential to form biofilmsand induce inflammation and cell transformation. Herein, we aimed to usecomputational analysis to highlight novel associations between chronic inflammationcaused by gonorrheal infection and neoplastic transformation. Prioritization and geneenrichment strategies based on virulence and resistance genes utilizing essentialgenes from the DEG and PANTHER databases were performed, respectively. Proteinproteininteraction networks were constructed with 55 nodes of bacterial proteins and72 nodes of proteins involved in the host immune response using the STRINGdatabase. MCODE and cytoHubba calculated 12 bacterial hub proteins (murA, murB,murC, murD, murE, purN, purL, thyA, uvrB, kdsB, lpxC, and ftsH) and 19 human hubproteins, of which TNF, STAT3 and AKT1 had high significance. The PPI networks arebased on the connectivity degree (K), betweenness centrality (BC), and closenesscentrality (CC) values. Hub genes are vital for cell survival and growth, and theirsignificance as potential drug targets is discussed. This computational study providesa comprehensive understanding of inflammation and carcinogenesis pathways thatare activated during gonorrheal infection.