Prediction of Phenotypic Antimicrobial Resistance Profiles From Whole Genome Sequences of Non-typhoidal Salmonella enterica

Abstract

Surveillance of antimicrobial resistance (AMR) in non-typhoidal Salmonella enterica (NTS), is essential for monitoring transmission of resistance from the food chain to humans, and for establishing effective treatment protocols. We evaluated the prediction of phenotypic resistance in NTS from genotypic profiles derived from whole genome sequencing (WGS). Genes and chromosomal mutations responsible for phenotypic resistance were sought in WGS data from 3,491 NTS isolates received by Public Health England’s Gastrointestinal Bacteria Reference Unit between April 2014 and March 2015. Inferred genotypic AMR profiles were compared with phenotypic susceptibilities determined for fifteen antimicrobials using EUCAST guidelines. Discrepancies between phenotypic and genotypic profiles for one or more antimicrobials were detected for 76 isolates (2.18%) although only 88/52,365 (0.17%) isolate/antimicrobial combinations were discordant. Of the discrepant results, the largest number were associated with streptomycin (67.05%, n = 59). Pan-susceptibility was observed in 2,190 isolates (62.73%). Overall, resistance to tetracyclines was most common (26.27% of isolates, n = 917) followed by sulphonamides (23.72%, n = 828) and ampicillin (21.43%, n = 748). Multidrug resistance (MDR), i.e., resistance to three or more antimicrobial classes, was detected in 848 isolates (24.29%) with resistance to ampicillin, streptomycin, sulphonamides and tetracyclines being the most common MDR profile (n = 231; 27.24%). For isolates with this profile, all but one were S. Typhimurium and 94.81% (n = 219) had the resistance determinants blaTEM-1, strA-strB, sul2 and tet(A). Extended-spectrum β-lactamase genes were identified in 41 isolates (1.17%) and multiple mutations in chromosomal genes associated with ciprofloxacin resistance in 82 isolates (2.35%). This study showed that WGS is suitable as a rapid means of determining AMR patterns of NTS for public health surveillance.

Salmonella enterica subsp. enterica Serovar Heidelberg Food Isolates Associated with a Salmonellosis Outbreak Have Enhanced Stress Tolerance Capabilities

“…All isolates, regardless of their phenotypic antibiotic resistance profile, contained aminoglycoside resistance gene aac(6=)-Iaa, which codes for a deactivator of kanamycin and amikacin (40). However, this gene does not provide clinical-level resistance to kanamycin or amikacin (40); in fact, this class of aminoglycoside resistance genes is often not expressed in S. enterica (41,42). Consequently, its presence alone does not adequately explain the high levels of amikacin resistance that we uncovered when attempting to use amikacin for cell invasion assays.…”

Food Security: Microbiological and Chemical Risks

“…One of the valuable WGS applications is the ability to predict phenotypic AMR profile with WGS-based genotypic AMR profile. This application has been demonstrated by several groups in S. enterica [107][108][109], E. coli [110,111], Campylobacter spp. [112], Staphylococcus aureus [113] and Mycobacterium tuberculosis [114,115] and high resistance phenotype-genotype correlation (>97%) is commonly seen.…”

The importance of public health genomics for ensuring health security for Australia

“…For example, when applied to surveillance of Shiga toxin‐producing Escherichia coli serotype O157, whole genome sequencing detected twice as many disease clusters than traditional typing methods, including common source outbreaks that were geographically distributed across the country . Similarly, routine whole genome sequencing of Salmonella enterica and Shigella isolates in England and Wales has generated a rich repository of genomic data, providing unparalleled levels of strain discrimination and a wealth of information on the emergence and spread of antimicrobial‐resistant pathogens …”

“…8 Similarly, routine whole genome sequencing of Salmonella enterica and Shigella isolates in England and Wales has generated a rich repository of genomic data, providing unparalleled levels of strain discrimination and a wealth of information on the emergence and spread of antimicrobial-resistant pathogens. 9,10…”