Network Analysis For Identifying Potential Anti-Virulence Targets From Whole Transcriptome of Pseudomonas Aeruginosa and Staphylococcus Aureus Exposed to Certain Anti-Pathogenic Polyherbal Formulations

Abstract

The current study aimed to use in silico network analysis to identify 'hubs' that could serve as potential antibacterial targets based on previous investigation that has focused on differential-ly expressed genes of Pseudomonas aeruginosa and Staphylococcus aureus, which were ex-posed to polyherbal formulations Panchvalkal and Herboheal, respectively. The Whole tran-scriptome analysis revealed that Herboheal has shown its anti-infective potential against spe-cific genes associated with various cellular processes, such as haemolysis, virulence, enzy-matic activity, transport, RNA metabolism, quorum sensing, and transcriptional regulation, while Panchvalkal seemed to have its anti-virulence effect through generating nitrosative and oxidative stress, interfering with iron and molybdenum homeostasis, and disrupting QS ma-chinery. Present study focuses to identify genes that serve a significant part in the virulence and phys-iology of certain pathogens, which can be used as the starting point for a large-scale drug dis-covery program. To accomplish this, we utilized various stringent criteria, including node degrees, local network clustering analysis, and 12 different ranking methods from STRING and cytoHubba databases. Through this approach, we identified a set of genes that are crucial for the pathogenesis of these diseases. By targeting these genes, new therapies or drugs can be potentially developed to combat these diseases and improve the health outcomes of affect-ed individuals. Our findings serve as a crucial step towards finding a cure for these diseases and improving public health.