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OJBTM

Online Journal of Bioinformatics

Volume 21(2): 128-131, 2020.


Bioinformatic tools to detect microbial resistance to sanitizers and antibiotics during coronavirus pandemic.

 

Dr. Anubha Dubey

 

Bioinformatics Gayatri Nagar, Katni, M.P. India.

ABSTRACT

 

Dubey A., Bioinformatic tools to detect microbial resistance to sanitizers and antibiotics during coronavirus pandemic, Onl J Bioinform., 21(2): 128-131, 2020. Extensive excessive use of sanitizers and antibiotics during the covid-19 viral pandemic may have implications for microbial resistance. Author describes bioinformatic tools to isolate resistance including genome sequencing, nucleic acid amplification, databases for microbe resistance phenotype genes (CARD), ResFinder, PointFinder, ARG-ANNOT, ARDB, MEGARes, Resfams, RAST, Bacterial Antimicrobial Resistance Reference Gene Database, Dream TB and MUBII-TB-DB. Software tools for detection of microbial resistance include WHONET for antimicrobial susceptibility, clinical management, infection control, outbreak detection and resistance epidemiology. Antibiotic Resistance Gene-ANNOTation (ARG-ANNOT) can reveal existing and putative new antibiotic resistance genes in bacterial genomes when used with BLAST allows analysis of sequences without web interface. Nucleotide and protein sequences retrieved from NCBI GenBank database can be analysed with BLAST to detect resistant genes in bacterial genomes. Access, watch, reserve tool (AWaRe) can predict appropriate narrow spectrum to prevent resistance. Automated Antimicrobial resistance surveillance systems (AMASS) allows hospitals to record patient with resistant bacteria and mortality for surveillance. AMR Finder can identify resistant genes from sequence data based on Hidden Markov Models wherein resistant protein sequences are curated.

 

Keywords: Antimicrobial resistance, COVID-19, Pandemic, Disease, Patients