Rekawad, B. and Khobragade, C. and Khobragade, S. (2018) Bioinformatics surveillance and digitalization of the multi-drug-resistant UTI pathogens isolated from hospitalized nosocomial patient. Chaos and Complexity Letters , 12 (1). pp. 17-38.

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Abstract

Clinical microbiologists are routinely engaged in the identification and taxonomic categorization of microorganisms having ‘morphological and genetic plasticity’ such as Enterobacter, Escherichia and Shigella responsible for urinary tract infections (UTI) in immunocompromised nosocomial patients. Nosocomial patients are amiable host for growth and spread of UTIs. Nonspecific uptake of medicines and over dosages of antibiotics either single or in combination with other drugs in diseased condition. Pathogens dominated during such diseased condition leads to development of multi-drug resistant pathogens (MDR). In this research work, nine bacteria were isolated from urine samples of hospitalized UTI patients. These bacteria were identified using 16S rRNA gene sequencing method. 16S rRNA gene sequences were used for the systematic creation of digital data on urinary tract infecting MDR pathogens. The 16S rRNA gene sequences of nine UTI pathogens were retrieved from NCBI repository. All datasets were generated through standalone and web-service based bioinformatics tools. The unique QR codes, CGR, CGPR and PCA were generated for each bacterium. GC/AT content was determined using ENDMEMO tool. Sequence of multidrug resistant Enterobacter cancerogenous strain MAB1 (MAB1) was translated into protein sequence using ExPASy tool. ExPASy and SWISS-MOEL tools were used to perform homology modeling of MAB1 virulent protein. The VirulentPred tool was used for prediction of nature of MAB1 protein. Results are interpreted in a systematic manner that helps to evaluate and compare similarity among the strains of UTI pathogens in addition to other wet laboratory methods. Hence, generated data on useful in further in-depth investigations and discriminations of UTI strains and their virulent proteins

Item Type:	Article
Depositing User:	Mr. Rameshwar Nema
Date Deposited:	17 Feb 2020 06:27
Last Modified:	17 Feb 2020 06:27
URI:	http://nccs.sciencecentral.in/id/eprint/666

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