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Genomic Prediction of Antimicrobial Resistance: Ready or Not, Here It Comes!
Ransom, Eric M; Potter, Robert F; Dantas, Gautam; Burnham, Carey-Ann D.
Afiliación
  • Ransom EM; Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO.
  • Potter RF; The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO.
  • Dantas G; Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO.
  • Burnham CD; The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO.
Clin Chem ; 66(10): 1278-1289, 2020 10 01.
Article en En | MEDLINE | ID: mdl-32918462
BACKGROUND: Next-generation sequencing (NGS) technologies are being used to predict antimicrobial resistance. The field is evolving rapidly and transitioning out of the research setting into clinical use. Clinical laboratories are evaluating the accuracy and utility of genomic resistance prediction, including methods for NGS, downstream bioinformatic pipeline components, and the clinical settings in which this type of testing should be offered. CONTENT: We describe genomic sequencing as it pertains to predicting antimicrobial resistance in clinical isolates and samples. We elaborate on current methodologies and workflows to perform this testing and summarize the current state of genomic resistance prediction in clinical settings. To highlight this aspect, we include 3 medically relevant microorganism exemplars: Mycobacterium tuberculosis, Staphylococcus aureus, and Neisseria gonorrhoeae. Last, we discuss the future of genomic-based resistance detection in clinical microbiology laboratories. SUMMARY: Antimicrobial resistance prediction by genomic approaches is in its infancy for routine patient care. Genomic approaches have already added value to the current diagnostic testing landscape in specific circumstances and will play an increasingly important role in diagnostic microbiology. Future advancements will shorten turnaround time, reduce costs, and improve our analysis and interpretation of clinically actionable results.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Bacterias / ADN Bacteriano / Farmacorresistencia Bacteriana Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Clin Chem Asunto de la revista: QUIMICA CLINICA Año: 2020 Tipo del documento: Article Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Bacterias / ADN Bacteriano / Farmacorresistencia Bacteriana Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Clin Chem Asunto de la revista: QUIMICA CLINICA Año: 2020 Tipo del documento: Article Pais de publicación: Reino Unido