Using whole-genome sequencing to determine appropriate streptomycin epidemiological cutoffs for Salmonella and Escherichia coli

Conventionally Reared Wallon Meat Lambs Carry Transiently Multi-Drug-Resistant Escherichia coli with Reduced Sensitivity to Colistin Before Slaughter

Major efforts have been made to reduce the use of colistin in livestock since the discovery of the plasmid-borne mobile colistin resistance (mcr) gene in E. coli a decade ago, to curb the burden of its potential transmission to other bacterial species, spread between animals, humans and the environment. This study explored the longitudinal prevalence and characteristics of colistin-resistant and extended-spectrum beta-lactamase-producing (ESBL) E. coli via in vivo fecal and ex vivo carcass swabs from two batches of conventional indoor and organic outdoor Wallon meat sheep from birth to slaughter in 2020 and 2021. Antimicrobial susceptibility testing via broth microdilution revealed that n = 16/109 (15%) E. coli isolates from conventional meat lamb fecal samples had a reduced colistin sensitivity (MIC = 0.5 μg/mL) and thereof, n = 9/109 (8%) were multi-drug-resistant E. coli, while no resistant isolates were recovered from their carcasses. Sequencing revealed causative pmrB genes, indicating that the reduced sensitivity to colistin was not plasmid-borne. While the sample size was small (n = 32), no colistin-resistant and ESBL-producing E. coli were isolated from the organic meat sheep and their carcasses, potentially due to the different husbandry conditions. Prudent and judicious antimicrobial use and strict slaughter hygiene remain imperative for effective risk management to protect consumers in a sustainable One Health approach.

Comparison of genotypic and phenotypic antimicrobial resistance profiles of Salmonella enterica isolates from poultry diagnostic specimens

The spread of antimicrobial-resistant bacteria is a significant concern, as it can lead to increased morbidity and mortality in both humans and animals. Whole-genome sequencing (WGS) is a powerful tool that can be used to conduct a comprehensive analysis of the genetic basis of antimicrobial resistance (AMR). We compared the phenotypic and genotypic AMR profiles of 97 Salmonella isolates derived from chicken and turkey diagnostic samples. We focused AMR analysis on 5 antimicrobial classes: aminoglycoside, beta-lactam, phenicol, tetracycline, and trimethoprim. The overall sensitivity and specificity of WGS in predicting phenotypic antimicrobial resistance in the Salmonella isolates were 93.4% and 99.8%, respectively. There were 16 disagreement instances, including 15 that were phenotypically resistant but genotypically susceptible; the other instance involved phenotypic susceptibility but genotypic resistance. Of the isolates examined, 67 of 97 (69%) carried at least 1 resistance gene, with 1 isolate carrying as many as 12 resistance genes. Of the 31 AMR genes analyzed, 16 were identified as aminoglycoside-resistance genes, followed by 4 beta-lactam-resistance, 3 tetracycline-resistance, 2 sulfonamide-resistance, and 1 each of fosfomycin-, quinolone-, phenicol-, trimethoprim-, bleomycin-, and colistin-resistance genes. Most of the resistance genes found were located on plasmids.

A National Antimicrobial Resistance Monitoring System Survey of Antimicrobial-Resistant Foodborne Bacteria Isolated from Retail Veal in the United States

ABSTRACT

Little is known about the prevalence of antimicrobial-resistant (AMR) bacteria in veal meat in the United States. We estimated the prevalence of bacterial contamination and AMR in various veal meats collected during the 2018 U.S. National Antimicrobial Resistance Monitoring System (NARMS) survey of retail outlets in nine states and compared the prevalence with the frequency of AMR bacteria from other cattle sources sampled for NARMS. In addition, we identified genes associated with resistance to medically important antimicrobials and gleaned other genetic details about the resistant organisms. The prevalence of Campylobacter, Salmonella, Escherichia coli, and Enterococcus in veal meats collected from grocery stores in nine states was 0% (0 of 358), 0.6% (2 of 358), 21.1% (49 of 232), and 53.5% (121 of 226), respectively, with ground veal posing the highest risk for contamination. Both Salmonella isolates were resistant to at least one antimicrobial agent as were 65.3% (32 of 49) of E. coli and 73.6% (89 of 121) of Enterococcus isolates. Individual drug and multiple drug resistance levels were significantly higher (P < 0.05) in E. coli and Enterococcus from retail veal than in dairy cattle ceca and retail ground beef samples from 2018 NARMS data. Whole genome sequencing was conducted on select E. coli and Salmonella from veal. Cephalosporin resistance (blaCMY and blaCTX-M), macrolide resistance (mph), and plasmid-mediated quinolone resistance (qnr) genes and gyrA mutations were found. We also identified heavy metal resistance genes ter, ars, mer, fieF, and gol and disinfectant resistance genes qac and emrE. An stx1a-containing E. coli was also found. Sequence types were highly varied among the nine E. coli isolates that were sequenced. Several plasmid types were identified in E. coli and Salmonella, with the majority (9 of 11) of isolates containing IncF. This study illustrates that veal meat is a carrier of AMR bacteria.

HIGHLIGHTS

Antimicrobial resistance studies in staphylococci and streptococci isolated from cows with mastitis in Argentina

BACKGROUND

Staphylococcus aureus and Streptococcus agalactiae are the main cause of clinical mastitis in dairy cattle in Argentina, whereas coagulase-negative staphylococci (CNS) and environmental streptococci are the main cause of subclinical mastitis. Bacteria isolated from infected animals show increasing antimicrobial resistance.

OBJECTIVES

This study aims to determine the antimicrobial resistance of staphylococci and streptococci isolated from milk with mastitis, and to genotypically characterize the methicillin-resistant (MR) staphylococci.

METHODS

Isolation was performed on blood agar and identification was based on biochemical reactions. Antimicrobial susceptibility was according to the Clinical and Laboratory Standards Institute guidelines. The antimicrobial resistance genes, SCCmec type and spa type were detected by the polymerase chain reaction method.

RESULTS

We isolated a total of 185 staphylococci and 28 streptococci from 148 milk samples. Among the staphylococcal isolates, 154 were identified as CNS and 31 as S. aureus. Among the 154 CNS, 24.6% (n = 38) were resistant to penicillin, 14.9% (n = 23) to erythromycin, 17.5% (n = 27) to clindamycin, 6.5% (n = 10) to cefoxitin and oxacillin. Among the S. aureus isolates, 16.1% (n = 5) were resistant to penicillin, 3.2% (n = 1) to cefoxitin and oxacillin (MRSA). Six MR isolates (5 CNS and 1 MRSA) were positive to the mecA gene, and presented the SCCmec IVa. The MRSA strain presented the sequence type 83 and the spa type 002. Among the 28 streptococcal isolates, 14.3% (n = 4) were resistant to penicillin, 10.7% (n = 3) to erythromycin and 14.3% (n = 4) to clindamycin.

CONCLUSIONS

The present findings of this study indicate a development of antimicrobial resistance in main bacteria isolated from cows with mastitis in Argentina.

High-Resolution Genomic Comparisons within Salmonella enterica Serotypes Derived from Beef Feedlot Cattle: Parsing the Roles of Cattle Source, Pen, Animal, Sample Type, and Production Period

Salmonella enterica is a major foodborne pathogen, and contaminated beef products have been identified as one of the primary sources of Salmonella-related outbreaks. Pathogenicity and antibiotic resistance of Salmonella are highly serotype and subpopulation specific, which makes it essential to understand high-resolution Salmonella population dynamics in cattle. Time of year, source of cattle, pen, and sample type (i.e., feces, hide, or lymph nodes) have previously been identified as important factors influencing the serotype distribution of Salmonella (e.g., Anatum, Lubbock, Cerro, Montevideo, Kentucky, Newport, and Norwich) that were isolated from a longitudinal sampling design in a research feedlot. In this study, we performed high-resolution genomic comparisons of Salmonella isolates within each serotype using both single-nucleotide polymorphism-based maximum-likelihood phylogeny and hierarchical clustering of core-genome multilocus sequence typing. The importance of the aforementioned features in clonal Salmonella expansion was further explored using a supervised machine learning algorithm. In addition, we identified and compared the resistance genes, plasmids, and pathogenicity island profiles of the isolates within each subpopulation. Our findings indicate that clonal expansion of Salmonella strains in cattle was mainly influenced by the randomization of block and pen, as well as the origin/source of the cattle, i.e., regardless of sampling time and sample type (i.e., feces, lymph node, or hide). Further research is needed concerning the role of the feedlot pen environment prior to cattle placement to better understand carryover contributions of existing strains of Salmonella and their bacteriophages. IMPORTANCE Salmonella serotypes isolated from outbreaks in humans can also be found in beef cattle and feedlots. Virulence factors and antibiotic resistance are among the primary defense mechanisms of Salmonella, and are often associated with clonal expansion. This makes understanding the subpopulation dynamics of Salmonella in cattle critical for effective mitigation. There remains a gap in the literature concerning subpopulation dynamics within Salmonella serotypes in feedlot cattle from the beginning of feeding up until slaughter. Here, we explore Salmonella population dynamics within each serotype using core-genome phylogeny and hierarchical classifications. We used machine learning to quantitatively parse the relative importance of both hierarchical and longitudinal clustering among cattle host samples. Our results reveal that Salmonella populations in cattle are highly clonal over a 6-month study period and that clonal dissemination of Salmonella in cattle is mainly influenced spatially by experimental block and pen, as well by the geographical origin of the cattle.

Comparison of Antimicrobial Resistance Profiles in Salmonella spp. from Swine Upon Arrival and Postslaughter at the Abattoir

Antimicrobial resistance (AMR) developed by Salmonella within animals used for food products is a major global issue. Monitoring AMR in animals destined for slaughter is, therefore, critical. Abattoirs may serve as potential candidate checkpoints for monitoring resistance patterns on farms. A complicating factor, however, is the impact of lairage on Salmonella detected in pigs at slaughter. This study sought to compare AMR patterns in Salmonella spp. in swine collected upon arrival (fecal samples) at the abattoir with those at postslaughter (cecal samples) and evaluate the feasibility of using slaughterhouse samples for surveillance of prevailing AMR Salmonella on farms. Eighty-four Salmonella isolates were recovered from a large, midwestern U.S. abattoir between September and November 2013. Isolates were tested for phenotypic AMR to 12 antimicrobials using the broth microdilution assay. Whole-genome sequencing identified the AMR genes harbored by the strains. Significant differences were observed in the isolate phenotypes and genotypes; however, no significant difference was observed in genotypic resistance patterns. Hence, the AMR profiles of Salmonella spp. postslaughter cannot be predicted from preslaughter samples. Further research considering the genetic diversity of isolates and statistical power of the genotypic analysis is warranted to improve the performance of WGS-inferred antimicrobial susceptibility.

Antimicrobial Susceptibility Patterns and Wild-Type MIC Distributions of Anaerobic Bacteria at a German University Hospital: A Five-Year Retrospective Study (2015-2019)

Local antimicrobial susceptibility surveys are crucial for optimal empirical therapy guidelines and for aiding in antibiotic stewardship and treatment decisions. For many laboratories, a comprehensive overview of local antimicrobial susceptibility patterns of anaerobic bacteria is still lacking due to the long incubation time and effort involved. The present study investigates the antimicrobial susceptibility patterns and related clinical and demographic data of 2856 clinical isolates of anaerobic bacteria that were submitted for analysis to the Institute for Medical Microbiology and Hygiene of the Freiburg University Medical Center (a tertiary university medical center in Southern Germany) between 2015 and 2019. Antimicrobial susceptibility testing has been carried out according to the European Committee on Antimicrobial Susceptibility Testing (EUCAST) guideline. Minimum inhibitory concentration (MIC)₅₀ and MIC₉₀ for penicillin, metronidazole, moxifloxacin, and clindamycin were established for Gram-positive anaerobes and for ampicillin-sulbactam, meropenem, metronidazole, moxifloxacin, and clindamycin for Gram-negative anaerobes. The distribution of MIC-values for various antibiotics against anaerobic bacteria was also established, especially for those having no specific breakpoints according to EUCAST guidelines. Most clinically relevant anaerobic bacteria originated from general surgery, neurological, and orthopedic wards. A high proportion of isolates were resistant to moxifloxacin and clindamycin indicating the importance of their susceptibility testing before administration. Based on our study metronidazole and other β-lactam/β-lactamase inhibitor combinations such as ampicillin-sulbactam remain suitable for empirical treatment of infections with anaerobic bacteria.

Tentative epidemiologic cut-off value and resistant characteristic detection of apramycin against Escherichia coli from chickens

Escherichia coli are important foodborne zoonotic pathogens. Apramycin is a key aminoglycoside antibiotic used by veterinarians against E. coli. This study was conducted to establish the epidemiological cut-off value (ECV) and resistant characteristics of apramycin against E. coli. In this study, 1412 clinical isolates of E. coli from chickens in China were characterized. Minimum inhibitory concentrations (MICs) of apramycin were assessed by broth microdilution method. MIC50 and MIC90 for apramycin against E. coli (0.5-256 µg/mL) were 8 and 16 µg/mL, respectively. In this study, the tentative ECV was determined to be 16 µg/mL by the statistical method and 32 µg/mL by ECOFFinder software. Besides, the percentages of aac(3)-IV positive strains ascended with the increase of MIC values of apramycin, and the gene npmA was detected in strains with higher MICs. Sixteen apramycin highly resistant strains displayed multiple drug resistance (100%) to amoxicillin, ampicillin, gentamicin, doxycycline, tetracycline, trimethoprim and florfenicol, while most of them were susceptible to amikacin and spectinomycin. In summary, the tentative ECV of apramycin against E. coli was recommended to be 16 µg/mL.

Genomic analyses of multidrug-resistant Salmonella Indiana, Typhimurium, and Enteritidis isolates using MinION and MiSeq sequencing technologies

We sequenced 25 isolates of phenotypically multidrug-resistant Salmonella Indiana (n = 11), Typhimurium (n = 8), and Enteritidis (n = 6) using both MinION long-read [SQK-LSK109 and flow cell (R9.4.1)] and MiSeq short-read (Nextera XT and MiSeq Reagent Kit v2) sequencing technologies to determine the advantages of each approach in terms of the characteristics of genome structure, antimicrobial resistance (AMR), virulence potential, whole-genome phylogeny, and pan-genome. The MinION reads were base-called in real-time using MinKnow 3.4.8 integrated with Guppy 3.0.7. The long-read-only assembly, Illumina-only assembly, and hybrid assembly pipelines of Unicycler 0.4.8 were used to generate the MinION, MiSeq, and hybrid assemblies, respectively. The MinION assemblies were highly contiguous compared to the MiSeq assemblies but lacked accuracy, a deficiency that was mitigated by adding the MiSeq short reads through the Unicycler hybrid assembly which corrected erroneous single nucleotide polymorphisms (SNPs). The MinION assemblies provided similar predictions of AMR and virulence potential compared to the MiSeq and hybrid assemblies, although they produced more total false negatives of AMR genotypes, primarily due to failure in identifying tetracycline resistance genes in 11 of the 19 MinION assemblies of tetracycline-resistant isolates. The MinION assemblies displayed a large genetic distance from their corresponding MiSeq and hybrid assemblies on the whole-genome phylogenetic tree, indicating that the lower read accuracy of MinION sequencing caused incorrect clustering. The pan-genome of the MinION assemblies contained significantly more accessory genes and less core genes compared to the MiSeq and hybrid assemblies, suggesting that although these assemblies were more contiguous, their sequencing errors reduced accurate genome annotations. Our research demonstrates that MinION sequencing by itself provides an efficient assessment of the genome structure, antimicrobial resistance, and virulence potential of Salmonella; however, it is not sufficient for whole-genome phylogenetic and pan-genome analyses. MinION in combination with MiSeq facilitated the most accurate genomic analyses.

Prevalence and distribution of antimicrobial resistance determinants of Escherichia coli isolates obtained from meat in South Africa

OBJECTIVE

This study aimed to characterise antibiotics resistance of Escherichia coli isolates from the formal meat sector (FMS) and informal meat sectors (INMS).

METHOD

A total of 162 and 102 E. coli isolates from the FMS, and INMS respectively were isolated by standard culture-based, and biochemical reactions. The isolates were further confirmed by polymerase chain reaction (PCR). The disc diffusion method was used to screen for antimicrobial susceptibility against 19 different antibiotics. The presence of class 1-2 integrons in each E. coli isolates was assessed using 3'-CS and 5'-CS regions specific primers.

RESULT

Among the 19 antimicrobials, resistance to tetracyclines, aminoglycosides, cephalosporins, and nitrofurans were found to be more frequent than carbapenems and chloramphenicol. The number of multi-drug resistance ranged from three to ten antimicrobials. The resistant determinants with the highest prevalence in the FMS and INMS were; [aminoglycosides: aadA (40.6%; 31.9%), and strA (6.5%; 9.4%)], [β-lactams: ampC (20%; 45%),], [Chloramphenicol: catI (1.7%; 1.7%), and [tetracyclines: tetB (11.5%; 24%),], and [sulfonamides: sul1 (22.2%; 26.7%),].

CONCLUSION

Higher phenotypic resistance to cephalosporins and carbapenems were found in the FMS than in INMS. The multiple antibiotic resistance (MAR) indexes for FMS and INMS ranged from 0.2-0.5. The results reveal a high prevalence of multidrug-resistant E. coli isolates and resistance determinants, suggesting that consumers and handlers of such meat are at risk of contracting antibiotic-resistant E. coli-related foodborne disease.

Systematic Evaluation of Whole Genome Sequence-Based Predictions of Salmonella Serotype and Antimicrobial Resistance

Whole-genome sequencing (WGS) is used increasingly in public-health laboratories for typing and characterizing foodborne pathogens. To evaluate the performance of existing bioinformatic tools for in silico prediction of antimicrobial resistance (AMR) and serotypes of Salmonella enterica, WGS-based genotype predictions were compared with the results of traditional phenotyping assays. A total of 111 S. enterica isolates recovered from a Canadian baseline study on broiler chicken conducted in 2012-2013 were selected based on phenotypic resistance to 15 different antibiotics and isolates were subjected to WGS. Both SeqSero2 and SISTR accurately determined S. enterica serotypes, with full matches to laboratory results for 87.4 and 89.2% of isolates, respectively, and partial matches for the remaining isolates. Antimicrobial resistance genes (ARGs) were identified using several bioinformatics tools including the Comprehensive Antibiotic Resistance Database – Resistance Gene Identifier (CARD-RGI), Center for Genomic Epidemiology (CGE) ResFinder web tool, Short Read Sequence Typing for Bacterial Pathogens (SRST2 v 0.2.0), and k-mer alignment method (KMA v 1.17). All ARG identification tools had ≥ 99% accuracy for predicting resistance to all antibiotics tested except streptomycin (accuracy 94.6%). Evaluation of ARG detection in assembled versus raw-read WGS data found minimal observable differences that were gene- and coverage- dependent. Where initial phenotypic results indicated isolates were sensitive, yet ARGs were detected, repeat AMR testing corrected discrepancies. All tools failed to find resistance-determining genes for one gentamicin- and two streptomycin-resistant isolates. Further investigation found a single nucleotide polymorphism (SNP) in the nuoF coding region of one of the isolates which may be responsible for the observed streptomycin-resistant phenotype. Overall, WGS-based predictions of AMR and serotype were highly concordant with phenotype determination regardless of computational approach used.

Population Dynamics of Salmonella enterica within Beef Cattle Cohorts Followed from Single-Dose Metaphylactic Antibiotic Treatment until Slaughter

Antibiotic use in cattle can select for multidrug-resistant Salmonella enterica, which is considered a serious threat by the U.S. Centers for Disease Control and Prevention. A randomized controlled longitudinal field trial was designed to determine the long-term effects of a single dose of ceftiofur or tulathromycin on Salmonella population characteristics in cattle feces and peripheral lymph nodes and on hides. A total of 134 beef cattle from two sources were divided among 12 pens, with cattle in each of the 3-pen blocks receiving a single dose of either ceftiofur or tulathromycin or neither (control) on day 0. Fecal samples were collected before treatment (day 0) and repeatedly following treatment until slaughter (day 99+). Hide and lymph node samples were collected at slaughter age. Salmonella prevalence, phenotypic antimicrobial resistance, serotype, and phylogenetic relationships were examined. Multilevel mixed logistic regression models indicated no significant effects (P ≥ 0.218) of metaphylactic antibiotics on the prevalence of Salmonella across sample types. However, there was a significant time effect observed, with prevalence increasing from spring through the midsummer months (P < 0.0001) in feces. The majority of Salmonella isolates were pansusceptible to a panel of 14 antibiotics both before and after treatment. Highly prevalent Salmonella serotypes were Salmonella enterica serovar Montevideo, Salmonella enterica serovar Anatum, Salmonella enterica serovar Cerro, and Salmonella enterica serovar Lubbock across all sample types. Strong pen and cattle source serotype clustering effects were observed among Salmonella isolates originating from fecal, lymph node, and hide samples; however, the potential role of Salmonella isolates from the pen environment prior to animal placement was not assessed in this study.IMPORTANCE Salmonella is a leading bacterial foodborne pathogen, causing a significant number of human infections and deaths every year in the United States. Macrolides and 3rd-generation cephalosporins play critical roles in the treatment of human salmonellosis. Use of these antibiotics in beef cattle can select for resistant bacteria that may enter the food chain or spread from the farm via manure. There is a lack of longitudinal research concerning the long-term effects of metaphylactic antibiotic administration. Here, we assessed Salmonella population dynamics during the feeding period until slaughter following single-dose antibiotic treatment. We found no long-term effects of antibiotic use early in the cattle-feeding period on Salmonella prevalence and antimicrobial resistance at slaughter. We identified the pens in which cattle were housed as the factor that contributed most to Salmonella serotypes being shared; importantly, the dominant strain in each pen changed repeatedly over the entire feeding period.

Validating the AMRFinder Tool and Resistance Gene Database by Using Antimicrobial Resistance Genotype-Phenotype Correlations in a Collection of Isolates

Antimicrobial resistance (AMR) is a major public health problem that requires publicly available tools for rapid analysis. To identify AMR genes in whole-genome sequences, the National Center for Biotechnology Information (NCBI) has produced AMRFinder, a tool that identifies AMR genes using a high-quality curated AMR gene reference database. The Bacterial Antimicrobial Resistance Reference Gene Database consists of up-to-date gene nomenclature, a set of hidden Markov models (HMMs), and a curated protein family hierarchy. Currently, it contains 4,579 antimicrobial resistance proteins and more than 560 HMMs. Here, we describe AMRFinder and its associated database. To assess the predictive ability of AMRFinder, we measured the consistency between predicted AMR genotypes from AMRFinder and resistance phenotypes of 6,242 isolates from the National Antimicrobial Resistance Monitoring System (NARMS). This included 5,425 Salmonella enterica, 770 Campylobacter spp., and 47 Escherichia coli isolates phenotypically tested against various antimicrobial agents. Of 87,679 susceptibility tests performed, 98.4% were consistent with predictions. To assess the accuracy of AMRFinder, we compared its gene symbol output with that of a 2017 version of ResFinder, another publicly available resistance gene detection system. Most gene calls were identical, but there were 1,229 gene symbol differences (8.8%) between them, with differences due to both algorithmic differences and database composition. AMRFinder missed 16 loci that ResFinder found, while ResFinder missed 216 loci that AMRFinder identified. Based on these results, AMRFinder appears to be a highly accurate AMR gene detection system.

Emergence of Multidrug-Resistant Salmonella enterica Serovar Goldcoast Strains in Taiwan and International Spread of the ST358 Clone

Salmonella enterica serovar Goldcoast infection was rare in Taiwan; it was not detected in routine surveillance from 2004 to 2013. This serovar was first identified in 2014, but the frequency of infection remained low until 2017. From 2014 to 2016, all but one isolate was pan-susceptible. S Goldcoast infections abruptly increased in 2018, and all isolates were multidrug-resistant (MDR). All MDR isolates harbored an IncHI2 plasmid, and the majority carried 14 antimicrobial resistance genes, aac(3)-IId, aadA22, aph(3')-Ia, aph(6)-Id, blaTEM-1B, blaCTX-M-55, lnu(F), floR, qnrS13, arr-2, sul2, sul3, tet(A), and dfrA14. S Goldcoast strains recovered in Taiwan and 96 of 99 strains from Germany, the Netherlands, the United Kingdom, and the United States belonged to sequence type 358 (ST358). Whole-genome single-nucleotide polymorphism and core genome multilocus sequence type analyses revealed that all strains of the ST358 clone shared a high degree of genetic relatedness. The present study highlighted that a dramatic increase in S Goldcoast infections followed the emergence of MDR strains and indicated that a genetically closely related S Goldcoast ST358 clone may have widespread significance internationally.

Determining antimicrobial susceptibility in Salmonella enterica serovar Typhimurium through whole genome sequencing: a comparison against multiple phenotypic susceptibility testing methods

Background

UK public health organisations perform routine antimicrobial susceptibility tests (ASTs) to characterise the potential for antimicrobial resistance in Salmonella enterica serovars. Genetic determinants of these resistance mechanisms are detectable by whole genome sequencing (WGS), however the viability of WGS-based genotyping as an alternative resistance screening tool remains uncertain. We compared WGS-based genotyping, disk diffusion and agar dilution to the broth microdilution reference AST for 102 Salmonella enterica serovar Typhimurium (S. Typhimurium) isolates across 11 antimicrobial compounds.

Results

Genotyping concordance, interpreted using epidemiological cut-offs (ECOFFs), was 89.8% (1007/1122) with 0.83 sensitivity and 0.96 specificity. For seven antimicrobials interpreted using Salmonella clinical breakpoints, genotyping produced 0.84 sensitivity and 0.88 specificity. Although less accurate than disk diffusion (0.94 sensitivity, 0.93 specificity) and agar dilution (0.83 sensitivity, 0.98 specificity), genotyping performance improved to 0.89 sensitivity and 0.97 specificity when two antimicrobials with relatively high very major error rates were excluded (streptomycin and sulfamethoxazole).

Conclusions

An 89.8% concordance from WGS-based AST predictions using ECOFF interpretations suggest that WGS would serve as an effective screening tool for the tracking of antimicrobial resistance mechanisms in S. Typhimurium. For use as a standalone clinical diagnostic screen, further work is required to reduce the error rates for specific antimicrobials.

Electronic supplementary material

The online version of this article (10.1186/s12866-019-1520-9) contains supplementary material, which is available to authorized users.

Comparative Genomic Analysis of Virulence, Antimicrobial Resistance, and Plasmid Profiles of Salmonella Dublin Isolated from Sick Cattle, Retail Beef, and Humans in the United States

Salmonella enterica serovar Dublin is a host-adapted serotype associated with typhoidal disease in cattle. While rare in humans, it usually causes severe illness, including bacteremia. In the United States, Salmonella Dublin has become one of the most multidrug-resistant (MDR) serotypes. To understand the genetic elements that are associated with virulence and resistance, we sequenced 61 isolates of Salmonella Dublin (49 from sick cattle and 12 from retail beef) using the Illumina MiSeq and closed 5 genomes using the PacBio sequencing platform. Genomic data of eight human isolates were also downloaded from NCBI (National Center for Biotechnology Information) for comparative analysis. Fifteen Salmonella pathogenicity islands (SPIs) and a spv operon (spvRABCD), which encodes important virulence factors, were identified in all 69 (100%) isolates. The 15 SPIs were located on the chromosome of the 5 closed genomes, with each of these isolates also carrying 1 or 2 plasmids with sizes between 36 and 329 kb. Multiple antimicrobial resistance genes (ARGs), including bla_CMY-2, bla_TEM-1B, aadA12, aph(3')-Ia, aph(3')-Ic, strA, strB, floR, sul1, sul2, and tet(A), along with spv operons were identified on these plasmids. Comprehensive antimicrobial resistance genotypes were determined, including 17 genes encoding resistance to 5 different classes of antimicrobials, and mutations in the housekeeping gene (gyrA) associated with resistance or decreased susceptibility to fluoroquinolones. Together these data revealed that this panel of Salmonella Dublin commonly carried 15 SPIs, MDR/virulence plasmids, and ARGs against several classes of antimicrobials. Such genomic elements may make important contributions to the severity of disease and treatment failures in Salmonella Dublin infections in both humans and cattle.

Retrospective whole-genome sequencing analysis distinguished PFGE and drug-resistance-matched retail meat and clinical Salmonella isolates

Non-typhoidal Salmonella is a leading cause of outbreak and sporadic-associated foodborne illnesses in the United States. These infections have been associated with a range of foods, including retail meats. Traditionally, pulsed-field gel electrophoresis (PFGE) and antibiotic susceptibility testing (AST) have been used to facilitate public health investigations of Salmonella infections. However, whole-genome sequencing (WGS) has emerged as an alternative tool that can be routinely implemented. To assess its potential in enhancing integrated surveillance in Pennsylvania, USA, WGS was used to directly compare the genetic characteristics of 7 retail meat and 43 clinical historic Salmonella isolates, subdivided into 3 subsets based on PFGE and AST results, to retrospectively resolve their genetic relatedness and identify antimicrobial resistance (AMR) determinants. Single nucleotide polymorphism (SNP) analyses revealed that the retail meat isolates within S. Heidelberg, S. Typhimurium var. O5- subset 1 and S. Typhimurium var. O5- subset 2 were separated from each primary PFGE pattern-matched clinical isolate by 6-12, 41-96 and 21-81 SNPs, respectively. Fifteen resistance genes were identified across all isolates, including fosA7, a gene only recently found in a limited number of Salmonella and a ≥95 % phenotype to genotype correlation was observed for all tested antimicrobials. Moreover, AMR was primarily plasmid-mediated in S. Heidelberg and S. Typhimurium var. O5- subset 2, whereas AMR was chromosomally carried in S. Typhimurium var. O5- subset 1. Similar plasmids were identified in both the retail meat and clinical isolates. Collectively, these data highlight the utility of WGS in retrospective analyses and enhancing integrated surveillance for Salmonella from multiple sources.

Present and Future Surveillance of Antimicrobial Resistance in Animals: Principles and Practices

There is broad consensus internationally that surveillance of the levels of antimicrobial resistance (AMR) occurring in various systems underpins strategies to address the issue. The key reasons for surveillance of resistance are to determine (i) the size of the problem, (ii) whether resistance is increasing, (iii) whether previously unknown types of resistance are emerging, (iv) whether a particular type of resistance is spreading, and (v) whether a particular type of resistance is associated with a particular outbreak. The implications of acquiring and utilizing this information need to be considered in the design of a surveillance system. AMR surveillance provides a foundation for assessing the burden of AMR and for providing the necessary evidence for developing efficient and effective control and prevention strategies. The codevelopment of AMR surveillance programs in humans and animals is essential, but there remain several key elements that make data comparisons between AMR monitoring programs, and between regions, difficult. Currently, AMR surveillance relies on uncomplicated in vitro antimicrobial susceptibility methods. However, the lack of harmonization across programs and the limitation of genetic information of AMR remain the major drawbacks of these phenotypic methods. The future of AMR surveillance is moving toward genotypic detection, and molecular analysis methods are expected to yield a wealth of information. However, the expectation that these molecular techniques will surpass phenotypic susceptibility testing in routine diagnosis and monitoring of AMR remains a distant reality, and phenotypic testing remains necessary in the detection of emerging resistant bacteria, new resistance mechanisms, and trends of AMR.

Genome wide characterization of enterotoxigenic Escherichia coli serogroup O6 isolates from multiple outbreaks and sporadic infections from 1975-2016

Enterotoxigenic Escherichia coli (ETEC) are an important cause of diarrhea globally, particularly among children under the age of five in developing countries. ETEC O6 is the most common ETEC serogroup, yet the genome wide population structure of isolates of this serogroup is yet to be determined. In this study, we have characterized 40 ETEC O6 isolates collected between 1975–2016 by whole genome sequencing (WGS) and by phenotypic antimicrobial susceptibility testing. To determine the relatedness of isolates, we evaluated two methods—whole genome high-quality single nucleotide polymorphism (whole genome-hqSNP) and core genome SNP analyses using Lyve-SET and Parsnp respectively. All isolates were tested for antimicrobial susceptibility using a panel of 14 antibiotics. ResFinder 2.1 and a custom quinolone resistance determinants workflow were used for resistance determinant detection. VirulenceFinder 1.5 was used for prediction of the virulence genes. Thirty-seven isolates clustered into three major clades (I, II, III) by whole genome-hqSNP and core genome SNP analyses, while three isolates included in the whole genome-hqSNP analysis only did not cluster with clades I-III by both analyses and formed a distantly related outgroup, designated clade IV. Median number of pairwise whole genome-hqSNPs in clonal ETEC O6 outbreaks ranged from 0 to 5. Of the 40 isolates tested for antimicrobial susceptibility, 18 isolates were pansusceptible. Twenty-two isolates were resistant to at least one antibiotic, nine of which were multidrug resistant. Phenotypic antimicrobial resistance (AR) correlated with AR determinants in 22 isolates. Thirty-two isolates harbored both enterotoxin virulence genes while the remaining 8 isolates had only one of the two virulence genes. In summary, whole genome-hqSNP and core genome SNP analyses from this study revealed similar evolutionary relationships and an overall diversity of ETEC O6 isolates independent of time of isolation. Less than 5 pairwise hqSNPs between ETEC O6 isolates is circumstantially indicative of an outbreak cluster. Findings from this study will be a basis for quicker outbreak detection and control by efficient subtyping by WGS.

The Present and Future of Whole Genome Sequencing (WGS) and Whole Metagenome Sequencing (WMS) for Surveillance of Antimicrobial Resistant Microorganisms and Antimicrobial Resistance Genes across the Food Chain

Antimicrobial resistance (AMR) surveillance is a critical step within risk assessment schemes, as it is the basis for informing global strategies, monitoring the effectiveness of public health interventions, and detecting new trends and emerging threats linked to food. Surveillance of AMR is currently based on the isolation of indicator microorganisms and the phenotypic characterization of clinical, environmental and food strains isolated. However, this approach provides very limited information on the mechanisms driving AMR or on the presence or spread of AMR genes throughout the food chain. Whole-genome sequencing (WGS) of bacterial pathogens has shown potential for epidemiological surveillance, outbreak detection, and infection control. In addition, whole metagenome sequencing (WMS) allows for the culture-independent analysis of complex microbial communities, providing useful information on AMR genes occurrence. Both technologies can assist the tracking of AMR genes and mobile genetic elements, providing the necessary information for the implementation of quantitative risk assessments and allowing for the identification of hotspots and routes of transmission of AMR across the food chain. This review article summarizes the information currently available on the use of WGS and WMS for surveillance of AMR in foodborne pathogenic bacteria and food-related samples and discusses future needs that will have to be considered for the routine implementation of these next-generation sequencing methodologies with this aim. In particular, methodological constraints that impede the use at a global scale of these high-throughput sequencing (HTS) technologies are identified, and the standardization of methods and protocols is suggested as a measure to upgrade HTS-based AMR surveillance schemes.

Establishing Genotypic Cutoff Values To Measure Antimicrobial Resistance in Salmonella

Whole-genome sequencing (WGS) has transformed our understanding of antimicrobial resistance, helping us to better identify and track the genetic mechanisms underlying phenotypic resistance. Previous studies have demonstrated high correlations between phenotypic resistance and the presence of known resistance determinants. However, there has never been a large-scale assessment of how well resistance genotypes correspond to specific MICs. We performed antimicrobial susceptibility testing and WGS of 1,738 nontyphoidal Salmonella strains to correlate over 20,000 MICs with resistance determinants. Using these data, we established what we term genotypic cutoff values (GCVs) for 13 antimicrobials against Salmonella For the drugs we tested, we define a GCV as the highest MIC of isolates in a population devoid of known acquired resistance mechanisms. This definition of GCV is distinct from epidemiological cutoff values (ECVs or ECOFFs), which currently differentiate wild-type from non-wild-type strains based on MIC distributions alone without regard to genetic information. Due to the large number of isolates involved, we observed distinct MIC distributions for isolates with different resistance gene alleles, including for ciprofloxacin and tetracycline, suggesting the potential to predict MICs based on WGS data alone.

Whole-Genome Sequencing for Detecting Antimicrobial Resistance in Nontyphoidal Salmonella

Laboratory-based in vitro antimicrobial susceptibility testing is the foundation for guiding anti-infective therapy and monitoring antimicrobial resistance trends. We used whole-genome sequencing (WGS) technology to identify known antimicrobial resistance determinants among strains of nontyphoidal Salmonella and correlated these with susceptibility phenotypes to evaluate the utility of WGS for antimicrobial resistance surveillance. Six hundred forty Salmonella of 43 different serotypes were selected from among retail meat and human clinical isolates that were tested for susceptibility to 14 antimicrobials using broth microdilution. The MIC for each drug was used to categorize isolates as susceptible or resistant based on Clinical and Laboratory Standards Institute clinical breakpoints or National Antimicrobial Resistance Monitoring System (NARMS) consensus interpretive criteria. Each isolate was subjected to whole-genome shotgun sequencing, and resistance genes were identified from assembled sequences. A total of 65 unique resistance genes, plus mutations in two structural resistance loci, were identified. There were more unique resistance genes (n = 59) in the 104 human isolates than in the 536 retail meat isolates (n = 36). Overall, resistance genotypes and phenotypes correlated in 99.0% of cases. Correlations approached 100% for most classes of antibiotics but were lower for aminoglycosides and beta-lactams. We report the first finding of extended-spectrum β-lactamases (ESBLs) (blaCTX-M1 and blaSHV2a) in retail meat isolates of Salmonella in the United States. Whole-genome sequencing is an effective tool for predicting antibiotic resistance in nontyphoidal Salmonella, although the use of more appropriate surveillance breakpoints and increased knowledge of new resistance alleles will further improve correlations.