Herein, we combined different bioinformatics tools and databases (BV-BRC, ResFinder, RAST, and KmerResistance) to perform a prediction of antimicrobial resistance (AMR) in the genomic sequences of 107 Corynebacterium striatum isolates for which trustable antimicrobial susceptibility (AST) phenotypes could be retrieved. Then, the reliabilities of the AMR predictions were evaluated by different metrics: area under the ROC curve (AUC); Major Error Rates (MERs) and Very Major Error Rates (VMERs); Matthews Correlation Coefficient (MCC); F1-Score; and Accuracy. Out of 15 genes that were reliably detected in the C.
View Article and Find Full Text PDFInt J Antimicrob Agents
August 2024
Spectrochim Acta A Mol Biomol Spectrosc
October 2024
Antimicrobial resistance poses a significant challenge in modern medicine, affecting public health. Klebsiella pneumoniae infections compound this issue due to their broad range of infections and the emergence of multiple antibiotic resistance mechanisms. Efficient detection of its capsular serotypes is crucial for immediate patient treatment, epidemiological tracking and outbreak containment.
View Article and Find Full Text PDFInfection
December 2024
Gene sequencing in back of reverse transcription-quantitative polymerase chain reaction (RT-qPCR) is the current approach for discriminating infections produced by different severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants in the clinic. However, sequencing is often a time-consuming step, which hinders the deployment of a very fast response during a pandemic. Here, we propose to run a CRISPR-Cas12a reaction after completing the RT-qPCR and in the very same pot to detect with high specificity genetic marks characterizing variants of concern.
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