Literature DB >> 32542649

Gene interaction network approach to elucidate the multidrug resistance mechanisms in the pathogenic bacterial strain Proteus mirabilis.

Sravan K Miryala1, Anand Anbarasu1, Sudha Ramaiah1.   

Abstract

Proteus mirabilis is one among the most frequently identified pathogen in patients with the urinary tract infection. The multidrug resistance exhibited by P. mirabilis renders the treatment ineffective, and new progressive strategies are needed to overcome the antibiotic resistance (AR). We have analyzed the evolutionary relationship of 29 P. mirabilis strains available in the National Center for Biotechnology Information-Genome database. The antimicrobial resistance genes of P. mirabilis along with the enriched pathways and the Gene Ontology terms are analyzed using gene networks to understand the molecular basis of AR. The genes rpoB, tufB, rpsl, fusA, and rpoA could be exploited as potential drug targets as they are involved in regulating the vital functions within the bacterium. The drug targets reported in the present study will aid researchers in developing new strategies to combat multidrug-resistant P. mirabilis.
© 2020 Wiley Periodicals LLC.

Entities:  

Keywords:  Proteus mirabilis; clustering analysis; functional enrichment analysis; gene ontology; two-component system

Year:  2020        PMID: 32542649     DOI: 10.1002/jcp.29874

Source DB:  PubMed          Journal:  J Cell Physiol        ISSN: 0021-9541            Impact factor:   6.384


  3 in total

Review 1.  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

2.  Protein Integrated Network Analysis to Reveal Potential Drug Targets Against Extended Drug-Resistant Mycobacterium tuberculosis XDR1219.

Authors:  Noor Ul Ain Zahra; Faiza Jamil; Reaz Uddin
Journal:  Mol Biotechnol       Date:  2021-08-11       Impact factor: 2.695

3.  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

  3 in total

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