ANTIMICROBIAL RESISTANCE IN NON-TYPHODIAL SALMONELLA FROM HUMAN AND RETAIL MEATS–UNITED STATES, 2009-2018

Background: Non-typhoidal Salmonella (NTS) is a leading cause of foodborne illnesses in the United States. Antimicrobial-resistant NTS infections are associated with more bloodstream infections, longer hospitalizations, and higher mortality. Contaminated foods of animal origin are an important source of NTS infections in human. The imprudent use of antimicrobials in animal agriculture could lead to the emergence and spread of resistant NTS, which can be transmitted from retail meat products to humans. The FDA has established regulations to guide and monitor the use of clinically important antimicrobials in food animals. In recent years, whole genome sequencing (WGS) has become a standard tool in NTS outbreak investigations due to its accuracy and cost-effectiveness. However, little has been done to quantify the association between antimicrobial use in food animals and observed resistance in retail meats. Also, more information is needed on how to better use and interpret the results of WGS in routine surveillance of resistant NTS.

Methods: The first study used a subset of the publicly available NARMS national clinical and retail meat datasets from 2009 to 2018 (16,741 isolates from humans and 4,318 isolates from retail meats), which contain isolate level MIC data. Fluoroquinolone sales from 2013 to 2018 in food-producing animals reported by the FDA were used as a proxy for fluoroquinolone use. The second study used all the Salmonella Typhimurium data (577 isolates from humans and 106 isolates from retail meats) in the publicly available NARMS national clinical and retail meat datasets from 2016 to 2018. In study 1, the Pearson’s correlation was used to examine the correlation between normalized fluoroquinolone sales and the prevalence of quinolone-resistant Salmonella in retail meats. Differences in quinolone resistance between years were assessed using chi square tests or fisher’s exact tests. In study 2, Staramr (0.5.1) on GalaxyTrakr platform was used to identify AMR determinants and predictive resistance. Sensitivity and specificity of WGS method were calculated with phenotypic resistance results as the reference. SNP-based cluster analysis was used to examine the genetic relatedness of a collection of MDR and pan-susceptible S. Typhimurium isolates recovered from retail chickens.

Results: In study 1, the prevalence of quinolone resistant NTS in retail meats was positively but insignificantly correlated with the normalized fluoroquinolone sales in food animals (r=0.67, p=0.1449); and were also positively and significantly correlated with the prevalence of quinolone resistant NTS isolates from human (r=0.92, p=0.0002). The increase of quinolone resistant isolates in retail meats since 2016 were mostly related to Salmonella Infantis and Salmonella Enteritidis. In study 2, the overall sensitivity of WGS was 96.47% and the overall specificity was 100.00%. The disagreement between phenotypic and genotypic results were mostly related to streptomycin. The MDR isolates differed by an average of 73 SNPs from each other, while the pan-susceptible isolates differed by an average of 473 SNPs (p<0.0001). The nearest distance between a pan-susceptible and an MDR isolate was 547 SNPs. MDR isolates and pan-susceptible isolates distinctly clustered on a phylogenetic tree.

Conclusions: Fluoroquinolone sales in food animals were positively associated with the prevalence of quinolone resistance of NTS in retail meat products and humans. WGS is reliable in predicting antibiotic resistance, and is able to provide genetic information for better understanding the evolution of MDR isolates. Continuous surveillance of antimicrobial use in agriculture and clinical settings with WGS is necessary.

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Work Title ANTIMICROBIAL RESISTANCE IN NON-TYPHODIAL SALMONELLA FROM HUMAN AND RETAIL MEATS–UNITED STATES, 2009-2018
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Creators
  1. Xin Yin
License In Copyright (Rights Reserved)
Work Type Dissertation
Acknowledgments
  1. Casey Pinto
  2. Nkuchia Mikanatha
  3. Edward Dudley
  4. Duanping Liao
  5. Jasna Kovac
Publication Date 2021
Deposited June 16, 2021

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