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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