Multidrug resistance and virulence genes carried by mobile genomic elements in Salmonella enterica isolated from live food animals, processed, and retail meat in North Carolina, 2018–2019

Hull, Dawn; Harrell, Erin; Harden, Lyndy; Thakur, Siddhartha

doi:10.1016/j.ijfoodmicro.2022.109821

Cited by 17 publications

(8 citation statements)

References 24 publications

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“…Using our Kraken classifier predictor, the median number of chromosome-carrying ARGs of each strain was one (95% CI: 1-7), and the median number of plasmid-borne ARGs was three (95% CI: [1][2][3][4][5][6][7][8][9][10][11][12][13][14]. This is a significant difference in ARG distribution between chromosomes and plasmids in these Salmonella strains (P value <0.001, Kolmogorov-Smirnov test) (Figure 2F).…”

Section: Analysis Of Plasmid Carrying Prevalence and Plasmid Carrying...mentioning

confidence: 99%

“…Salmonella is an important intestinal pathogen of foodborne disease, causing enteritis and bloodstream infections, among other serious consequences, transmitted by food and water. Plasmid genome sizes in Salmonella enterica are generally between 2 kb and 200 kb and are biased based on serotype (1). As an important mobile genetic element (MGE), plasmids in Salmonella endow strains with many biological characteristics, including toxin production, resistance to heavy metals, antibiotic resistance genes (ARGs), and prophage integration (2)(3)(4).…”

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confidence: 99%

“…Plasmid genome sizes in Salmonella enterica are generally between 2 kb and 200 kb and are biased based on serotype ( 1 ). As an important mobile genetic element (MGE), plasmids in Salmonella endow strains with many biological characteristics, including toxin production, resistance to heavy metals, antibiotic resistance genes (ARGs), and prophage integration ( 2 - 4 ). The spread of plasmid-borne ARGs has become a global public health problem, and plasmids, as reservoirs of ARGs, can spread rapidly between different species, including human pathogens ( 5 - 6 ).…”

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confidence: 99%

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The Establishment and Application of a Kraken Classifier for <i>Salmonella</i> Plasmid Sequence Prediction

Li¹,

Pang²,

Lü³

et al. 2022

China CDC Weekly

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Introduction: Salmonella is a key intestinal pathogen of foodborne disease, and the plasmids in Salmonella are related to many biological characteristics, including virulence and drug resistance. A large number of plasmid contigs have been sequenced in bacterial draft genomes, however, these are often difficult to distinguish from chromosomal contigs.Methods: In this study, three different customized Kraken databases were used to build three different Kraken classifiers. Complete genome benchmark datasets and simulated draft genome benchmark datasets were constructed. Five-fold cross-validation was used to evaluate the performance of the three different Kraken classifiers by two benchmark datasets.Results: The predictive performance of the classifier based on all National Center for Biotechnology Information plasmids and Salmonella complete genomes was optimal. This optimal Kraken classifier was performed with Salmonella isolated in China. The plasmid carrying rate of Salmonella in

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Section: Analysis Of Plasmid Carrying Prevalence and Plasmid Carrying...mentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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The Establishment and Application of a Kraken Classifier for <i>Salmonella</i> Plasmid Sequence Prediction

Li¹,

Pang²,

Lü³

et al. 2022

China CDC Weekly

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“…In this context, mobile genetic elements are involved in the ability of the bacteria to adapt to stress pressures ( Hull et al, 2022 ). Despite this, the relationship of Salmonella and these elements within the production line environment of a chicken farm remains understudied.…”

Section: Introductionmentioning

confidence: 99%

Mobile genetic elements drive the multidrug resistance and spread of Salmonella serotypes along a poultry meat production line

Krüger

Pardo-Esté²,

Zepeda³

et al. 2023

Front. Microbiol.

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The presence of mobile genetic elements in Salmonella isolated from a chicken farm constitutes a potential risk for the appearance of emerging bacteria present in the food industry. These elements contribute to increased pathogenicity and antimicrobial resistance through genes that are related to the formation of biofilms and resistance genes contained in plasmids, integrons, and transposons. One hundred and thirty-three Salmonella isolates from different stages of the production line, such as feed manufacturing, hatchery, broiler farm, poultry farm, and slaughterhouse, were identified, serotyped and sequenced. The most predominant serotype was Salmonella Infantis. Phylogenetic analyses demonstrated that the diversity and spread of strains in the pipeline are serotype-independent, and that isolates belonging to the same serotype are very closely related genetically. On the other hand, Salmonella Infantis isolates carried the pESI IncFIB plasmid harboring a wide variety of resistance genes, all linked to mobile genetic elements, and among carriers of these plasmids, the antibiograms showed differences in resistance profiles and this linked to a variety in plasmid structure, similarly observed in the diversity of Salmonella Heidelberg isolates carrying the IncI1-Iα plasmid. Mobile genetic elements encoding resistance and virulence genes also contributed to the differences in gene content. Antibiotic resistance genotypes were matched closely by the resistance phenotypes, with high frequency of tetracycline, aminoglycosides, and cephalosporins resistance. In conclusion, the contamination in the poultry industry is described throughout the entire production line, with mobile genetic elements leading to multi-drug resistant bacteria, thus promoting survival when challenged with various antimicrobial compounds.

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“…Since publication, MEGARes v1.0 has been cited in more than 250 manuscripts, and MEGARes v2.0 has been cited in >120 papers. These citations relate to a variety of applications, such as research targeting AMR in aquatic environments ( 3 , 4 ), agricultural production ( 5–7 ), animals ( 8 , 9 ), and humans ( 10–12 ).…”

Section: Introductionmentioning

confidence: 99%

MEGARes and AMR++, v3.0: an updated comprehensive database of antimicrobial resistance determinants and an improved software pipeline for classification using high-throughput sequencing

Bonin

Doster

Worley

et al. 2022

Nucleic Acids Research

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Antimicrobial resistance (AMR) is considered a critical threat to public health, and genomic/metagenomic investigations featuring high-throughput analysis of sequence data are increasingly common and important. We previously introduced MEGARes, a comprehensive AMR database with an acyclic hierarchical annotation structure that facilitates high-throughput computational analysis, as well as AMR++, a customized bioinformatic pipeline specifically designed to use MEGARes in high-throughput analysis for characterizing AMR genes (ARGs) in metagenomic sequence data. Here, we present MEGARes v3.0, a comprehensive database of published ARG sequences for antimicrobial drugs, biocides, and metals, and AMR++ v3.0, an update to our customized bioinformatic pipeline for high-throughput analysis of metagenomic data (available at MEGLab.org). Database annotations have been expanded to include information regarding specific genomic locations for single-nucleotide polymorphisms (SNPs) and insertions and/or deletions (indels) when required by specific ARGs for resistance expression, and the updated AMR++ pipeline uses this information to check for presence of resistance-conferring genetic variants in metagenomic sequenced reads. This new information encompasses 337 ARGs, whose resistance-conferring variants could not previously be confirmed in such a manner. In MEGARes 3.0, the nodes of the acyclic hierarchical ontology include 4 antimicrobial compound types, 59 resistance classes, 233 mechanisms and 1448 gene groups that classify the 8733 accessions.

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Multidrug resistance and virulence genes carried by mobile genomic elements in Salmonella enterica isolated from live food animals, processed, and retail meat in North Carolina, 2018–2019

Cited by 17 publications

References 24 publications

The Establishment and Application of a Kraken Classifier for <i>Salmonella</i> Plasmid Sequence Prediction

The Establishment and Application of a Kraken Classifier for <i>Salmonella</i> Plasmid Sequence Prediction

Mobile genetic elements drive the multidrug resistance and spread of Salmonella serotypes along a poultry meat production line

MEGARes and AMR++, v3.0: an updated comprehensive database of antimicrobial resistance determinants and an improved software pipeline for classification using high-throughput sequencing

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