Literature DB >> 31419460

Systems biology studies in Pseudomonas aeruginosa PA01 to understand their role in biofilm formation and multidrug efflux pumps.

Sravan Kumar Miryala1, Anand Anbarasu1, Sudha Ramaiah2.   

Abstract

The antimicrobial resistance (AMR) exhibited against broad spectrum and new generation antibiotics used for Pseudomonas infections is a major threat and renders the treatment ineffective. In our present study, we have used a computational approach to understand various drug resistance mechanisms which contribute to Multi-Drug Resistance (MDR) in P. aeruginosa. The interaction network of 60 AMR genes along with the 337 functional interactions was analyzed. Functional enrichment analysis of AMR genes has shown that the genes in the network are mainly associated with efflux pump mechanisms, alginate biosynthesis, biofilm formation, and ampC beta-lactamase biosynthesis. Interestingly, the genes phoP, phoQ, and cat genes are observed to have roles in more than one drug-resistant mechanism. The genes phoP and phoQ apart from their role in two-component regulatory systems also play major roles in multidrug efflux pumps and alteration in drug target. The gene cat involves in alteration of drug target and enzymatic inactivation. The interaction network analysis has shown that the AMR genes oprJ, oprM, oprN, ampC, gyrA, mexA, oprD, mexB and nfxB have higher number of direct interactors and they are considered as the hub nodes in the network and these genes can be used as potential drug targets for developing new drugs. The results from our study will be helpful in better understanding of the antibiotic resistance mechanisms in P. aeruginosa. The gene targets reported, can be used for new drug discovery against Pseudomonas infections.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Antimicrobial resistance genes; Clustering analysis; Functional enrichment analysis; Gene network; Multidrug resistance; Pseudomonas aeruginosa PA01

Mesh:

Year:  2019        PMID: 31419460     DOI: 10.1016/j.micpath.2019.103668

Source DB:  PubMed          Journal:  Microb Pathog        ISSN: 0882-4010            Impact factor:   3.738


  6 in total

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Authors:  P Priyamvada; Reetika Debroy; Anand Anbarasu; Sudha Ramaiah
Journal:  World J Microbiol Biotechnol       Date:  2022-07-05       Impact factor: 3.312

Review 2.  In silico Methods for Identification of Potential Therapeutic Targets.

Authors:  Xuting Zhang; Fengxu Wu; Nan Yang; Xiaohui Zhan; Jianbo Liao; Shangkang Mai; Zunnan Huang
Journal:  Interdiscip Sci       Date:  2021-11-26       Impact factor: 3.492

3.  A Shaving Proteomic Approach to Unveil Surface Proteins Modulation of Multi-Drug Resistant Pseudomonas aeruginosa Strains Isolated From Cystic Fibrosis Patients.

Authors:  Anna Lisa Montemari; Valeria Marzano; Nour Essa; Stefano Levi Mortera; Martina Rossitto; Simone Gardini; Laura Selan; Gianluca Vrenna; Andrea Onetti Muda; Lorenza Putignani; Ersilia Vita Fiscarelli
Journal:  Front Med (Lausanne)       Date:  2022-03-09

4.  Pseudomonas aeruginosa Initiates a Rapid and Specific Transcriptional Response during Surface Attachment.

Authors:  Christopher J Jones; Nikolas Grotewold; Daniel J Wozniak; Erin S Gloag
Journal:  J Bacteriol       Date:  2022-04-25       Impact factor: 3.476

Review 5.  The Revaluation of Plant-Derived Terpenes to Fight Antibiotic-Resistant Infections.

Authors:  Floriana Cappiello; Maria Rosa Loffredo; Cristina Del Plato; Silvia Cammarone; Bruno Casciaro; Deborah Quaglio; Maria Luisa Mangoni; Bruno Botta; Francesca Ghirga
Journal:  Antibiotics (Basel)       Date:  2020-06-13

6.  Amalgamation of 3D structure and sequence information for protein-protein interaction prediction.

Authors:  Kanchan Jha; Sriparna Saha
Journal:  Sci Rep       Date:  2020-11-05       Impact factor: 4.379

  6 in total

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