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. 2023 May 29:17:58-69.
doi: 10.33393/dti.2023.2595. eCollection 2023 Jan-Dec.

Network analysis for identifying potential anti-virulence targets from whole transcriptome of Pseudomonas aeruginosa and Staphylococcus aureus exposed to certain anti-pathogenic polyherbal formulations

Feny J Ruparel  1   2 , Siddhi K Shah  1   2 , Jhanvi H Patel  1   2 , Nidhi R Thakkar  1   2 , Gemini N Gajera  1   2 , Vijay O Kothari  1   2
Affiliations

Network analysis for identifying potential anti-virulence targets from whole transcriptome of Pseudomonas aeruginosa and Staphylococcus aureus exposed to certain anti-pathogenic polyherbal formulations

Feny J Ruparel et al. Drug Target Insights. .

Abstract

Introduction: Antimicrobial resistance (AMR) is a serious global threat. Identification of novel antibacterial targets is urgently warranted to help antimicrobial drug discovery programs. This study attempted identification of potential targets in two important pathogens Pseudomonas aeruginosa and Staphylococcus aureus.

Methods: Transcriptomes of P. aeruginosa and S. aureus exposed to two different quorum-modulatory polyherbal formulations were subjected to network analysis to identify the most highly networked differentially expressed genes (hubs) as potential anti-virulence targets.

Results: Genes associated with denitrification and sulfur metabolism emerged as the most important targets in P. aeruginosa. Increased buildup of nitrite (NO2) in P. aeruginosa culture exposed to the polyherbal formulation Panchvalkal was confirmed through in vitro assay too. Generation of nitrosative stress and inducing sulfur starvation seemed to be effective anti-pathogenic strategies against this notorious gram-negative pathogen. Important targets identified in S. aureus were the transcriptional regulator sarA, immunoglobulin-binding protein Sbi, serine protease SplA, the saeR/S response regulator system, and gamma-hemolysin components hlgB and hlgC.

Conclusion: Further validation of the potential targets identified in this study is warranted through appropriate in vitro and in vivo assays in model hosts. Such validated targets can prove vital to many antibacterial drug discovery programs globally.

Keywords: AMR (antimicrobial resistance); Anti-virulence; Network Analysis; Novel antibacterial targets; Polyherbal; Protein-Protein Interaction (PPI).

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Conflict of interest statement

Conflict of interest: The authors declare no conflict of interest.

Figures

Fig. 1 -
Fig. 1 -
A schematic of methodology for network analysis and hub identification.
Fig. 2 -
Fig. 2 -
Protein-Protein Interaction (PPI) network of downregulated genes in Panchvalkal-exposed Pseudomonas aeruginosa. Edges represent protein-protein associations that are meant to be specific and meaningful, that is, proteins jointly contribute to a shared function; this does not necessarily mean they are physically binding to each other. Network nodes represent proteins. Splice isoforms or post-translational modifications are collapsed, that is, each node represents all the proteins produced by a single, protein-coding gene locus.
Fig. 3 -
Fig. 3 -
Protein-Protein Interaction (PPI) network of top-ranked genes revealed through cytoHubba among downregulated differentially expressed genes (DEG) in Panchvalkal-exposed Pseudomonas aeruginosa.
Fig. 4 -
Fig. 4 -
Panchvalkal-treated Pseudomonas aeruginosa culture has higher extracellular accumulation of nitrite. While nitrite concentration in vehicle control (P. aeruginosa incubated in media supplemented with 0.5% v/v dimethylsulfoxide (DMSO)) was at par to that without DMSO, Panchvalkal caused nitrite concentration in P. aeruginosa culture supernatant to rise (A). Sodium nitroprusside used as positive control caused a dose-dependent 2.37 to 52.29-fold higher nitrite buildup in P. aeruginosa culture (B). Nitrite unit (i.e., nitrite concentration:cell density ratio) was calculated to nullify any effect of cell density on nitrite production. ***p<0.001.
Fig. 5 -
Fig. 5 -
Protein-Protein Interaction (PPI) network of up-regulated genes in Panchvalkal-exposed P. aeruginosa.
Fig. 6 -
Fig. 6 -
PPI network of top-ranked genes revealed through cytoHubba among up-regulated DEG in Panchvalkal-exposed P. aeruginosa.
Fig. 7 -
Fig. 7 -
Protein-Protein Interaction (PPI) network of upregulated and downregulated genes in Herboheal-exposed Staphylococcus aureus.
Fig. 8 -
Fig. 8 -
Protein-Protein Interaction (PPI) network of top-ranked genes revealed through cytoHubba among differentially expressed genes (DEG) in Herboheal-exposed Staphylococcus aureus.
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