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ARS Home » Plains Area » Clay Center, Nebraska » U.S. Meat Animal Research Center » Meat Safety & Quality Research » Research » Publications at this Location » Publication #316053

Research Project: Exploring Genomic Differences and Ecological Reservoirs To Control Foodborne Pathogens

Location: Meat Safety & Quality Research

Title: WGS accurately predicts antimicrobial resistance in Escherichia coli

Author
item Tyson, Gregory - U.s. Food & Drug Administration (FDA)
item Mcdermott, Patrick - U.s. Food & Drug Administration (FDA)
item Li, Cong - U.s. Food & Drug Administration (FDA)
item Chen, Yuansha - U.s. Food & Drug Administration (FDA)
item Tadesse, Daniel - U.s. Food & Drug Administration (FDA)
item Mukherjee, Sampa - U.s. Food & Drug Administration (FDA)
item Bodeis-jones, Sonya - U.s. Food & Drug Administration (FDA)
item Kabera, Claudine - U.s. Food & Drug Administration (FDA)
item Gaines, Stuart - U.s. Food & Drug Administration (FDA)
item Loneragan, Guy - U.s. Food & Drug Administration (FDA)
item Edrington, Thomas
item Torrence, Mary - U.s. Food & Drug Administration (FDA)
item Harhay, Dayna
item Zhao, Shaohua - U.s. Food & Drug Administration (FDA)

Submitted to: Antimicrobial Chemotherapy
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/10/2015
Publication Date: 7/3/2015
Publication URL: http://handle.nal.usda.gov/10113/61663
Citation: Tyson, G.H., McDermott, P., Li, C., Chen, Y., Tadesse, D.A., Mukherjee, S., Bodeis-Jones, S., Kabera, C., Gaines, S.A., Loneragan, G.H., Edrington, T.S., Torrence, M., Harhay, D.M., Zhao, S. 2015. WGS accurately predicts antimicrobial resistance in Escherichia coli. Journal of Antimicrobial Chemotherapy. July 2015:1-7.

Interpretive Summary: It is widely expected that technological advancements and decreased sequencing costs soon will allow whole-genome sequencing (WGS) to replace a number of traditional microbiology laboratorymethods. The operational processes for WGS are relatively undemanding and soon will be a routine part of laboratory workflow. Antimicrobial resistance phenotyping is a time-consuming and expensive process that may be replaced with WGS based genotyping methods. These methods rely on the identification of specific genes and mutations conferring antibiotic resistance, and therefore, could result in a more consistent measure of resistance. In order to examine the utility of WGS for predicting resistance phenotype, we determined 1) the resistance genotypes of seventy-six multidrug-resistant Escherichia coli and 2) the correlation of genotype with observed phenotype. We found that WGS can provide comprehensive resistance genotypes, and is capable of accurately predicting resistance phenotypes, making it a valuable tool for surveillance.

Technical Abstract: Objectives: To determine the effectiveness of whole-genome sequencing (WGS) in identifying resistance genotypes of multidrug-resistant Escherichia coli (E. coli) and whether these correlate with observed phenotypes. Methods: Seventy-six E. coli strains were isolated from farm cattle and measured for phenotypic resistance to 15 antimicrobials with the Sensititre® system. Isolates with resistance to at least three classes of antibiotics were selected for WGS using an Illumina MiSeq. Genotypic analysis was conducted with in-house Perl scripts using BLAST analysis to identify known genes and mutations associated with clinical resistance. Results: Over 30 resistance genes and a number of resistance mutations were identified among the E. coli isolates. Resistance genotypes correlated with 97.8% specificity and 99.6% sensitivity to the identified phenotypes. A majority of discordant results were attributable to the aminoglycoside streptomycin, whereas there was a perfect genotypic-phenotypic correlation for most antibiotic classes such as tetracyclines, quinolones, and phenicols. Additional information was gained about rare resistance mechanisms, such as structural mutations in chromosomal copies of ampC conferring third-generation cephalosporin resistance. Conclusions: Whole-genome sequencing can provide comprehensive resistance genotypes, and is capable of accurately predicting resistance phenotypes, making it a valuable tool for surveillance. Moreover, the data presented here showing the ability to accurately predict resistance suggests that WGS may be used to as a screening tool in selecting anti-infective therapy, especially as costs drop and methods improve.