PeerJGenomicsPeer-reviewed journal article
Clinical considerations on antimicrobial resistance potential of complex microbiological samples
Norbert SolymosiiD, Adrienn Gréta TóthiD, Sára Ágnes NagyiD, István CsabaiiD, Csongor Feczkó, Tamás Reibling, Tibor NémethiD
Abstract
Antimicrobial resistance (AMR) is one of our greatest public health challenges. Targeted use of antibiotics (AB) can reduce the occurrence and spread of AMR and boost the effectiveness of treatment. This requires knowledge of the antibiotic susceptibility (AS) of the pathogens involved in the disease. Therapeutic recommendations based on classical antibiotic susceptibility testing (AST) are based on the analysis of only a fraction of the bacteria present in the disease process. Next and third generation sequencing technologies allow the identification of antimicrobial resistance genes (ARGs) present in a bacterial community. Using this genomic approach, we can map the antimicrobial resistance potential (AMRP) of a complex, multi-bacterial microbial sample. The same approach can be used to identify antibiotics without any ARGs in the sample that interfere with their activity. Our paper summarises the clinical interpretation opportunities of genomic analysis results from 574 Escherichia coli strains and a complex microbiological sample from canine external otitis. In clinical metagenomics, AMRP may be an important approach to make AB therapy more targeted and effective. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/594174v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@d84733org.highwire.dtl.DTLVardef@12aa447org.highwire.dtl.DTLVardef@873811org.highwire.dtl.DTLVardef@1721aba_HPS_FORMAT_FIGEXP M_FIG C_FIG
- assay: metagenomics
- research focus: benchmarking
- research focus: variant calling
- research focus: variant effect prediction
- research focus: drug response / drug discovery
- approach: statistical model
- Citations
- 2
- FWCI
- 0.56
- Field percentile
- top 46%
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