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Full title: Identification of potential drug targets against carbapenem resistant Enterobacteriaceae (CRE) strains using in silico gene network analysis
Baishya S, Kangsa Banik S, Das Talukdar A, , Bhattacharjee A, Dutta Choudhury M.
Published in Elsevier BV
2019
Volume: 14
   
Pages: 129 - 137
Abstract
In the era where issue of antibiotic resistance is increasing at an alarming rate and resistance to most antibiotics has occurred, carbapenems have been the choice of drug against most infection because of its unique structure. However due to lack of antibiotic policy carbapenems too have achieved resistance and led to the emergence of carbapenem resistant Enterobacteriaceae (CRE). Members of Enterobacteriaceae family produce New Delhi metallo-beta-lactamase (NDM), a type of carbapenemase that can cleave carbapenems. Therefore, new anti-microbial targets need to be identified and for this purpose a holistic model is designed in this approach in order to find out the influential genes that are liable in imparting carbapenem resistance owing to the presence of NDM. In this research approach, firstly genes associated with resistance owing to NDM are collected from NCBI database. A total of 419 genes from E. coli that have been obtained from NCBI were subjected to STRING for protein-protein interaction analysis. Out of 419 genes, only 59 genes showed interaction. STRING gave 1679 functional partners at different confidence levels. In the next stage, clustering analysis of the 1679 functional partners was done using MCODE app of Cytoscape software which generated 71 clusters. Topological properties of the 804 functional partners obtained from the 71 clusters were done using Network Analyser plugin of Cytoscape software. 797 functional partners were streamlined and they were subjected to functional enrichment analysis by DAVID Database. This database finally gave 21 genes from 15 clusters, thus indicating that these 15 genes might have a crucial role in the development of carbapenem resistance owing to NDM. These genes can be targeted for designing new anti-microbial drugs in future by the way of gene silencing or altering the genetic expression. © 2018 Elsevier Inc.
About the journal
JournalData powered by TypesetGene Reports
PublisherData powered by TypesetElsevier BV
ISSN2452-0144
Open Access0