Sequencing-based methods and resources to study antimicrobial resistance
By Manish Boolchandani, Alaric W. D’Souza, Gautam Dantas. Nature reviews genetics, 2019
491 citations recorded by the source corpus.
Antimicrobial resistance extracts high morbidity, mortality and economic costs yearly by rendering bacteria immune to antibiotics. Identifying and understanding antimicrobial resistance are imperative for clinical practice to treat resistant infections and for public health efforts to limit the spread of resistance. Technologies such as next-generation sequencing are expanding our abilities to detect and study antimicrobial resistance. This Review provides a detailed overview of antimicrobial resistance identification and characterization methods, from traditional antimicrobial susceptibility testing to recent deep-learning methods. We focus on sequencing-based resistance discovery and discuss tools and databases used in antimicrobial resistance studies. Next-generation sequencing has improved the identification and characterization of antimicrobial resistance. Focusing on sequence-based discovery of antibiotic resistance genes, this Review discusses computational strategies and resources for resistance gene identification in genomic and metagenomic samples, including recent deep-learning approaches.
Subfields: Clinical Biochemistry, Molecular Biology, Molecular Medicine
View Paper: https://www.semanticscholar.org/paper/e6525d25254833d95321b83d8f4e5b72a1852868
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In Clinical Biochemistry
In Molecular Biology
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In Molecular Medicine
Citations in the corpus
- Using Genomics to Track Global Antimicrobial Resistance (2019, methodology): “KMA uses k-mer seeding to speed-up mapping and the Needleman-Wunsch algorithm to accurately align extensions from k-mer seeds.”
- CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database (2019, background): “Given the severity of the AMR crisis and the next-generation sequencing revolution, it is no surprise that there is a large diversity of AMR databases and software tools available (10,13).”