Use of online tools for antimicrobial resistance prediction by whole-genome sequencing in methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci (VRE).
Computational Biology
/ methods
Drug Resistance, Bacterial
Genes, Essential
Genome, Bacterial
Humans
Methicillin-Resistant Staphylococcus aureus
/ drug effects
Microbial Sensitivity Tests
Phenotype
Point Mutation
Prospective Studies
Sensitivity and Specificity
Vancomycin-Resistant Enterococci
/ drug effects
Web Browser
Whole Genome Sequencing
/ methods
Antimicrobial resistance
MRSA
Methicillin-resistant Staphylococcus aureus
VRE
Vancomycin-resistant enterococci
Whole-genome sequencing
Journal
Journal of global antimicrobial resistance
ISSN: 2213-7173
Titre abrégé: J Glob Antimicrob Resist
Pays: Netherlands
ID NLM: 101622459
Informations de publication
Date de publication:
12 2019
12 2019
Historique:
received:
23
02
2019
revised:
31
03
2019
accepted:
06
04
2019
pubmed:
22
4
2019
medline:
24
6
2020
entrez:
22
4
2019
Statut:
ppublish
Résumé
The antimicrobial resistance (AMR) crisis represents a serious threat to public health and has resulted in concentrated efforts to accelerate development of rapid molecular diagnostics for AMR. In combination with publicly available web-based AMR databases, whole-genome sequencing (WGS) offers the capacity for rapid detection of AMR genes. Here we studied the concordance between WGS-based resistance prediction and phenotypic susceptibility test results for methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci (VRE) clinical isolates using publicly available tools and databases. Clinical isolates prospectively collected at the University of Pittsburgh Medical Center between December 2016 and December 2017 underwent WGS. The AMR gene content was assessed from assembled genomes by BLASTn search of online databases. Concordance between the WGS-predicted resistance profile and phenotypic susceptibility as well as the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated for each antibiotic/organism combination, using the phenotypic results as gold standard. Phenotypic susceptibility testing and WGS results were available for 1242 isolate/antibiotic combinations. Overall concordance was 99.3%, with a sensitivity, specificity, PPV and NPV of 98.7% (95% CI 97.2-99.5%), 99.6% (95% CI 98.8-99.9%), 99.3% (95% CI 98.0-99.8%) and 99.2% (95% CI 98.3-99.7%), respectively. Additional identification of point mutations in housekeeping genes increased the concordance to 99.4%, sensitivity to 99.3% (95% CI 98.2-99.8%) and NPV to 99.4% (95% CI 98.4-99.8%). WGS can be used as a reliable predicator of phenotypic resistance both for MRSA and VRE using readily available online tools.
Identifiants
pubmed: 31005733
pii: S2213-7165(19)30095-5
doi: 10.1016/j.jgar.2019.04.006
pmc: PMC6800622
mid: NIHMS1527347
pii:
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
136-143Subventions
Organisme : NIAID NIH HHS
ID : R01 AI127472
Pays : United States
Organisme : NIAID NIH HHS
ID : R21 AI109459
Pays : United States
Informations de copyright
Copyright © 2019 International Society for Antimicrobial Chemotherapy. Published by Elsevier Ltd. All rights reserved.
Références
Antimicrob Agents Chemother. 2018 Dec 21;63(1):
pubmed: 30373801
Antimicrob Agents Chemother. 2013 Jul;57(7):3348-57
pubmed: 23650175
Clin Infect Dis. 2006 Jan 15;42 Suppl 2:S82-9
pubmed: 16355321
Antimicrob Agents Chemother. 2014;58(1):212-20
pubmed: 24145532
Nucleic Acids Res. 2016 Jul 8;44(W1):W242-5
pubmed: 27095192
RNA. 2009 Feb;15(2):327-36
pubmed: 19144912
Drug Resist Updat. 2014 Apr;17(1-2):1-12
pubmed: 24880801
Ann N Y Acad Sci. 2015 Sep;1354:32-53
pubmed: 26495887
J Clin Microbiol. 2013 Jan;51(1):281-3
pubmed: 23077121
J Antimicrob Chemother. 2017 Jan;72(1):104-114
pubmed: 27667325
Genome Res. 2013 Apr;23(4):653-64
pubmed: 23299977
J Clin Microbiol. 2017 Dec 26;56(1):
pubmed: 29118168
J Antimicrob Chemother. 2011 May;66(5):997-1000
pubmed: 21393177
Antimicrob Agents Chemother. 1995 Apr;39(4):797-805
pubmed: 7785974
Bioinformatics. 2014 May 1;30(9):1312-3
pubmed: 24451623
Nat Rev Genet. 2012 Sep;13(9):601-612
pubmed: 22868263
Clin Microbiol Infect. 2017 Jan;23(1):2-22
pubmed: 27890457
J Antimicrob Chemother. 2012 Nov;67(11):2640-4
pubmed: 22782487
J Antimicrob Chemother. 2013 Apr;68(4):771-7
pubmed: 23233485
Chem Rev. 2005 Feb;105(2):621-32
pubmed: 15700959
Proc Natl Acad Sci U S A. 2008 Mar 25;105(12):4886-91
pubmed: 18349144
Clin Infect Dis. 2005 Aug 1;41(3):327-33
pubmed: 16007529
Antimicrob Agents Chemother. 1998 Oct;42(10):2590-4
pubmed: 9756760
J Clin Microbiol. 2011 Jun;49(6):2272-3
pubmed: 21450951
N Engl J Med. 2012 Jun 14;366(24):2267-75
pubmed: 22693998
Clin Infect Dis. 2016 Jan 15;62(2):181-9
pubmed: 26409063
Antimicrob Agents Chemother. 1985 Sep;28(3):397-403
pubmed: 3878127
Drug Resist Updat. 2010 Dec;13(6):151-71
pubmed: 20833577
Proc Natl Acad Sci U S A. 1980 Jul;77(7):3974-7
pubmed: 7001450
J Comput Biol. 2012 May;19(5):455-77
pubmed: 22506599
Infect Control Hosp Epidemiol. 2019 Mar;40(3):314-319
pubmed: 30773168
Antimicrob Agents Chemother. 2009 Dec;53(12):5265-74
pubmed: 19752277
Clin Infect Dis. 2002 Feb 15;34(4):482-92
pubmed: 11797175
Clin Infect Dis. 2013 Dec;57 Suppl 3:S139-70
pubmed: 24200831
J Clin Microbiol. 2014 Apr;52(4):1182-91
pubmed: 24501024
Mol Biol Evol. 2016 Jul;33(7):1870-4
pubmed: 27004904
Antimicrob Agents Chemother. 2003 Dec;47(12):3675-81
pubmed: 14638464
Genome Med. 2016 Jul 01;8(1):73
pubmed: 27368373
J Biomed Inform. 2019 Mar;91:103126
pubmed: 30771483
Nat Commun. 2015 Dec 21;6:10063
pubmed: 26686880
Clin Infect Dis. 2001 Jun 1;32(11):1608-14
pubmed: 11340533
Clin Infect Dis. 2006 Jan 1;42 Suppl 1:S25-34
pubmed: 16323116