Antimicrobial Resistance Genes, Cassettes, and Plasmids Present in Salmonella enterica Associated With United States Food Animals

The ability of antimicrobial resistance (AR) to transfer, on mobile genetic elements (MGEs) between bacteria, can cause the rapid establishment of multidrug resistance (MDR) in bacteria from animals, thus creating a foodborne risk to human health. To investigate MDR and its association with plasmids in Salmonella enterica, whole genome sequence (WGS) analysis was performed on 193 S. enterica isolated from sources associated with United States food animals between 1998 and 2011; 119 were resistant to at least one antibiotic tested. Isolates represented 86 serotypes and variants, as well as diverse phenotypic resistance profiles. A total of 923 AR genes and 212 plasmids were identified among the 193 strains. Every isolate contained at least one AR gene. At least one plasmid was detected in 157 isolates. Genes were identified for resistance to aminoglycosides (n = 472), β-lactams (n = 84), tetracyclines (n = 171), sulfonamides (n = 91), phenicols (n = 42), trimethoprim (n = 8), macrolides (n = 5), fosfomycin (n = 48), and rifampicin (n = 2). Plasmid replicon types detected in the isolates were A/C (n = 32), ColE (n = 76), F (n = 43), HI1 (n = 4), HI2 (n = 20), I1 (n = 62), N (n = 4), Q (n = 7), and X (n = 35). Phenotypic resistance correlated with the AR genes identified in 95.4% of cases. Most AR genes were located on plasmids, with many plasmids harboring multiple AR genes. Six antibiotic resistance cassette structures (ARCs) and one pseudo-cassette were identified. ARCs contained between one and five resistance genes (ARC1: sul2, strAB, tetAR; ARC2: aac3-iid; ARC3: aph, sph; ARC4: cmy-2; ARC5: floR; ARC6: tetB; pseudo-ARC: aadA, aac3-VIa, sul1). These ARCs were present in multiple isolates and on plasmids of multiple replicon types. To determine the current distribution and frequency of these ARCs, the public NCBI database was analyzed, including WGS data on isolates collected by the USDA Food Safety and Inspection Service (FSIS) from 2014 to 2018. ARC1, ARC4, and ARC5 were significantly associated with cattle isolates, while ARC6 was significantly associated with chicken isolates. This study revealed that a diverse group of plasmids, carrying AR genes, are responsible for the phenotypic resistance seen in Salmonella isolated from United States food animals. It was also determined that many plasmids carry similar ARCs

Poultry Processing Interventions Reduce Salmonella Serovar Complexity on Postchill Young Chicken Carcasses as Determined by Deep Serotyping

Nearly 20% of salmonellosis cases are attributed to broilers, with renewed efforts to reduce Salmonella during broiler production and processing. A limitation to Salmonella culture is that often a single colony is picked for characterization, favoring isolation of the most abundant serovar found in a sample, while low abundance serovars can remain undetected. We used a deep serotyping approach, CRISPR-SeroSeq (serotyping by sequencing the clustered regularly interspaced palindromic repeats), to assess Salmonella serovar complexity during broiler processing and to determine the impact of antimicrobial interventions upon serovar population dynamics. Paired hot rehang and postchill young chicken carcasses were collected from establishments across the United States from August to November 2022. CRISPR-SeroSeq was performed on Salmonella culture-positive hot rehang (n = 153) and postchill (n = 38) samples, including 31 paired hot rehang and postchill samples. Multiple serovars were detected in 48.4% (74/153) and 7.9% (3/38) of hot rehang and postchill samples, respectively. On average, hot rehang carcasses contained 1.6 serovars, compared to 1.1 serovars at postchill (Mann Whitney U, p = 0.00018). Nineteen serovars were identified with serovar Kentucky the most common at hot rehang (72.5%; 111/153) and postchill (73.7%; 28/38). Serovar Infantis prevalence was higher at hot rehang (39.9%; 61/153) than in postchill (7.9%; 3/38). At hot rehang, serovar Enteritidis was outnumbered by other serovars 81.3% (13/16) of the time but was always the single or most abundant serovar detected when it was present at postchill (n = 5). We observed 98.4% (188/191) concordance between traditional isolation with serotyping and CRISPR-SeroSeq. Deep serotyping was able to explain serovar discrepancies between paired hot rehang and postchill samples when only traditional isolation and serotyping methods were used. These data demonstrate that processing interventions are effective in reducing Salmonella serovar complexity

Core Genome MLST for Source Attribution of Campylobacter coli

Campylobacter species are among the leading foodborne bacterial agents of human diarrheal illness. The majority of campylobacteriosis has been attributed to Campylobacter jejuni (85% or more), followed by Campylobacter coli (5–10%). The distribution of C. jejuni and C. coli varies by host organism, indicating that the contribution to human infection may differ between isolation sources. To address the relative contribution of each source to C. coli infections in humans, core genome multilocus sequence type with a 200-allele difference scheme (cgMLST200) was used to determine cgMLST type for 3,432 C. coli isolated from food animals (n = 2,613), retail poultry meats (n = 389), human clinical settings (n = 285), and environmental sources (n = 145). Source attribution was determined by analyzing the core genome with a minimal multilocus distance methodology (MMD). Using MMD, a higher proportion of the clinical C. coli population was attributed to poultry (49.6%) and environmental (20.9%) sources than from cattle (9.8%) and swine (3.2%). Within the population of C. coli clinical isolates, 70% of the isolates that were attributed to non-cecal retail poultry, dairy cattle, beef cattle and environmental waters came from two cgMLST200 groups from each source. The most common antibiotic resistance genes among all C. coli were tetO (65.6%), blaOXA–193 (54.2%), aph(3′)-IIIa (23.5%), and aadE-Cc (20.1%). Of the antibiotic resistance determinants, only one gene was isolated from a single source: blaOXA–61 was only isolated from retail poultry. Within cgMLST200 groups, 17/17 cgMLST200-435 and 89/92 cgMLST200-707 isolates encoded for aph(3’)-VIIa and 16/16 cgMLST200-319 harbored aph(2’)-If genes. Distribution of blaOXA alleles showed 49/50 cgMLST200-5 isolates contained blaOXA–498 while blaOXA–460 was present in 37/38 cgMLST200-650 isolates. The cgMLST200-514 group revealed both ant(6)-Ia and sat4 resistance genes in 23/23 and 22/23 isolates, respectively. Also, cgMLST200-266 and cgMLST200-84 had GyrAT86I mutation with 16/16 (100%) and 14/15 (93.3%), respectively. These findings illustrate how cgMLST and MMD methods can be used to evaluate the relative contribution of known sources of C. coli to the human burden of campylobacteriosis and how cgMLST typing can be used as an indicator of antimicrobial resistance in C. coli.This article is published as Harrison, Lucas, Sampa Mukherjee, Chih-Hao Hsu, Shenia Young, Errol Strain, Qijing Zhang, Glenn E. Tillman, Cesar Morales, Jovita Haro, and Shaohua Zhao. "Core Genome MLST for Source Attribution of Campylobacter coli." Frontiers in Microbiology 12 (2021): 703890. DOI: 10.3389/fmicb.2021.703890. Works produced by employees of the U.S. Government as part of their official duties are not copyrighted within the U.S. The content of this document is not copyrighted

Benchmark datasets for phylogenomic pipeline validation, applications for foodborne pathogen surveillance

Background As next generation sequence technology has advanced, there have been parallel advances in genome-scale analysis programs for determining evolutionary relationships as proxies for epidemiological relationship in public health. Most new programs skip traditional steps of ortholog determination and multi-gene alignment, instead identifying variants across a set of genomes, then summarizing results in a matrix of single-nucleotide polymorphisms or alleles for standard phylogenetic analysis. However, public health authorities need to document the performance of these methods with appropriate and comprehensive datasets so they can be validated for specific purposes, e.g., outbreak surveillance. Here we propose a set of benchmark datasets to be used for comparison and validation of phylogenomic pipelines. Methods We identified four well-documented foodborne pathogen events in which the epidemiology was concordant with routine phylogenomic analyses (reference-based SNP and wgMLST approaches). These are ideal benchmark datasets, as the trees, WGS data, and epidemiological data for each are all in agreement. We have placed these sequence data, sample metadata, and “known” phylogenetic trees in publicly-accessible databases and developed a standard descriptive spreadsheet format describing each dataset. To facilitate easy downloading of these benchmarks, we developed an automated script that uses the standard descriptive spreadsheet format. Results Our “outbreak” benchmark datasets represent the four major foodborne bacterial pathogens (Listeria monocytogenes, Salmonella enterica, Escherichia coli, and Campylobacter jejuni) and one simulated dataset where the “known tree” can be accurately called the “true tree”. The downloading script and associated table files are available on GitHub: https://github.com/WGS-standards-and-analysis/datasets. Discussion These five benchmark datasets will help standardize comparison of current and future phylogenomic pipelines, and facilitate important cross-institutional collaborations. Our work is part of a global effort to provide collaborative infrastructure for sequence data and analytic tools—we welcome additional benchmark datasets in our recommended format, and, if relevant, we will add these on our GitHub site. Together, these datasets, dataset format, and the underlying GitHub infrastructure present a recommended path for worldwide standardization of phylogenomic pipelines

Carriage and Gene Content Variability of the pESI-Like Plasmid Associated with Salmonella Infantis Recently Established in United States Poultry Production

Salmonella Infantis carrying extended spectrum β-lactamase blaCTX-M-65 on a pESI-like megaplasmid has recently emerged in United States poultry. In order to determine the carriage rate and gene content variability of this plasmid in U.S. Salmonella Infantis, whole genome sequences of Salmonella isolates from humans and animals in the U.S. and internationally containing the pESI-like plasmid were analyzed. The U.S. Department of Agriculture Food Safety and Inspection Service (FSIS) identified 654 product sampling isolates containing pESI-like plasmids through hazard analysis and critical control point (HACCP) verification testing in 2017 and 2018. The Centers for Disease Control and Prevention identified 55 isolates with pESI-like plasmids in 2016–2018 through the National Antimicrobial Resistance Monitoring System. Approximately 49% of pESI-like plasmids from FSIS verification isolates and 71% from CDC NARMS contained blaCTX-M-65. Pan-plasmid genome analysis was also performed. All plasmids contained traN and more than 95% contained 172 other conserved genes; 61% contained blaCTX-M-65. In a hierarchical clustering analysis, some plasmids from U.S. animal sources clustered together and some plasmids from South America clustered together, possibly indicating multiple plasmid lineages. However, most plasmids contained similar genes regardless of origin. Carriage of the pESI-like plasmid in U.S. appears to be limited to Salmonella Infantis and carriage rates increased from 2017 to 2018

AMRFinderPlus and the Reference Gene Catalog facilitate examination of the genomic links among antimicrobial resistance, stress response, and virulence

Abstract Antimicrobial resistance (AMR) is a significant public health threat. With the rise of affordable whole genome sequencing, in silico approaches to assessing AMR gene content can be used to detect known resistance mechanisms and potentially identify novel mechanisms. To enable accurate assessment of AMR gene content, as part of a multi-agency collaboration, NCBI developed a comprehensive AMR gene database, the Bacterial Antimicrobial Resistance Reference Gene Database and the AMR gene detection tool AMRFinder. Here, we describe the expansion of the Reference Gene Database, now called the Reference Gene Catalog, to include putative acid, biocide, metal, stress resistance genes, in addition to virulence genes and species-specific point mutations. Genes and point mutations are classified by broad functions, as well as more detailed functions. As we have expanded both the functional repertoire of identified genes and functionality, NCBI released a new version of AMRFinder, known as AMRFinderPlus. This new tool allows users the option to utilize only the core set of AMR elements, or include stress response and virulence genes, too. AMRFinderPlus can detect acquired genes and point mutations in both protein and nucleotide sequence. In addition, the evidence used to identify the gene has been expanded to include whether nucleotide or protein sequence was used, its location in the contig, and presence of an internal stop codon. These database improvements and functional expansions will enable increased precision in identifying AMR genes, linking AMR genotypes and phenotypes, and determining possible relationships between AMR, virulence, and stress response

The Poultry-Associated Microbiome: Network Analysis and Farm-to-Fork Characterizations

<div><p>Microbial communities associated with agricultural animals are important for animal health, food safety, and public health. Here we combine high-throughput sequencing (HTS), quantitative-PCR assays, and network analysis to profile the poultry-associated microbiome and important pathogens at various stages of commercial poultry production from the farm to the consumer. Analysis of longitudinal data following two flocks from the farm through processing showed a core microbiome containing multiple sequence types most closely related to genera known to be pathogenic for animals and/or humans, including <i>Campylobacter, Clostridium</i>, and <i>Shigella</i>. After the final stage of commercial poultry processing, taxonomic richness was ca. 2–4 times lower than the richness of fecal samples from the same flocks and <i>Campylobacter</i> abundance was significantly reduced. Interestingly, however, carcasses sampled at 48 hr after processing harboured the greatest proportion of unique taxa (those not encountered in other samples), significantly more than expected by chance. Among these were anaerobes such as <i>Prevotella</i>, <i>Veillonella</i>, <i>Leptrotrichia</i>, and multiple <i>Campylobacter</i> sequence types. Retail products were dominated by <i>Pseudomonas</i>, but also contained 27 other genera, most of which were potentially metabolically active and encountered in on-farm samples. Network analysis was focused on the foodborne pathogen <i>Campylobacter</i> and revealed a majority of sequence types with no significant interactions with other taxa, perhaps explaining the limited efficacy of previous attempts at competitive exclusion of <i>Campylobacter</i>. These data represent the first use of HTS to characterize the poultry microbiome across a series of farm-to-fork samples and demonstrate the utility of HTS in monitoring the food supply chain and identifying sources of potential zoonoses and interactions among taxa in complex communities.</p> </div