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Clin Infect Dis. 2017 Sep 1;65(5):738-745. doi: 10.1093/cid/cix417.

Whole-Genome Sequencing Accurately Identifies Resistance to Extended-Spectrum β-Lactams for Major Gram-Negative Bacterial Pathogens.

Author information

1
Department of Infectious Diseases, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America
2
Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
3
Center for Antimicrobial Resistance and Microbial Genomics, Division of Infectious Diseases, University of Texas McGovern Medical School at Houston.
4
Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas.
5
Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas.
6
Division of Infectious Diseases, Department of Internal Medicine, University of Texas McGovern Medical School at Houston.
7
Genomics and Resistant Microbes Group, Clinica Alemana, Universidad del Desarrollo, Santiago, Chile.
8
Department of Medicine, University of Pittsburgh, Pennsylvania.
9
Graduate Program in Diagnostic Genetics, School of Health Professions, University of Texas MD Anderson Cancer Center.
10
Department of Microbiology and Molecular Genetics, University of Texas McGovern Medical School at Houston.
11
Molecular Genetics and Antimicrobial Resistance Unit, International Center for Microbial Genomics, Universidad El Bosque, Bogota, Colombia.
12
Division of Pharmacy, MD Anderson Cancer Center, Houston.
13
Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA.
14
Microbiology, University of Texas Southwestern, Dallas.

Abstract

Background:

There is marked interest in using DNA-based methods to detect antimicrobial resistance (AMR), with targeted polymerase chain reaction (PCR) approaches increasingly being incorporated into clinical care. Whole-genome sequencing (WGS) could offer significant advantages over targeted PCR for AMR detection, particularly for species where mutations are major drivers of AMR.

Methods:

Illumina MiSeq WGS and broth microdilution (BMD) assays were performed on 90 bloodstream isolates of the 4 most common gram-negative bacteria causing bloodstream infections in neutropenic patients. The WGS data, including both gene presence/absence and detection of mutations in an array of AMR-relevant genes, were used to predict resistance to 4 β-lactams commonly used in the empiric treatment of neutropenic fever. The genotypic predictions were then compared to phenotypic resistance as determined by BMD and by commercial methods during routine patient care.

Results:

Of 133 putative instances of resistance to the β-lactams of interest identified by WGS, only 87 (65%) would have been detected by a typical PCR-based approach. The sensitivity, specificity, and positive and negative predictive values for WGS in predicting AMR were 0.87, 0.98, 0.97, and 0.91, respectively. Using BMD as the gold standard, our genotypic resistance prediction approach had a significantly higher positive predictive value compared to minimum inhibitory concentrations generated by commercial methods (0.97 vs 0.92; P = .025).

Conclusions:

These data demonstrate the potential feasibility of using WGS to guide antibiotic treatment decisions for patients with life-threatening infections for an array of medically important pathogens.

KEYWORDS:

antimicrobial resistance; bacteremia; gram-negative bacteria; neutropenic fever; whole-genome sequencing

PMID:
28472260
PMCID:
PMC5850535
DOI:
10.1093/cid/cix417
[Indexed for MEDLINE]
Free PMC Article

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