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Strain, E. A.

Publications and source records attributed to Strain, E. A..

5 recordsLinked to original sources

Paired metagenomic and chemical evaluation of an aflatoxin contaminated dog kibble

Identification of chemical toxins from complex or highly processed foods can present needle in the haystack challenges for chemists. Metagenomic data can guide chemical toxicity evaluations with DNA-based description of the wholistic composition (bacterial, eukaryotic, protozoal, viral, and antimicrobial resistance) of any food suspected to harbor toxins, allergens, or pathogens. This approach can focus chemistry-based diagnostics, improve risk assessment, and address data gaps. There is increasing recognition that simultaneously co-occurring mycotoxins, either from single or multiple species, can impact dietary toxicity. Here we evaluate an aflatoxin contaminated kibble with known levels of specific mycotoxins and demonstrate that the abundance of DNA from putative aflatoxigenic Aspergillus spp. correlated with levels of aflatoxin quantified by Liquid Chromatography Mass Spectrometry (LCMS). Metagenomic data also identified an expansive range of co-occurring fungal taxa which may produce additional mycotoxins. Metagenomic data paired with chemical data provides a novel modality to address current data gaps pertaining to mycotoxin toxicity exposures, toxigenic fungal taxonomy, and mycotoxins of emerging concern.

microbiology↗

The spread of pESI-mediated extended-spectrum cephalosporin resistance in Salmonella serovars - Infantis, Senftenberg, and Alachua isolated from food animal sources in the United States

The goal of this study is to investigate the origin, prevalence, and evolution of the pESI megaplasmid in Salmonella isolated from animals, foods, and humans. We queried 510,097 Salmonella genomes under the National Center for Biotechnology Information (NCBI) Pathogen Detection (PD) database for the presence of potential sequences containing the pESI plasmid in animal, food, and environmental sources. The presence of the pESI megaplasmid was confirmed by using seven plasmid-specific markers (rdA, pilL, SogS, TrbA, ipf, ipr2 and IncFIB(pN55391)). The plasmid and chromosome phylogeny of these isolates was inferred from single nucleotide polymorphisms (SNPs). Our search resolved six Salmonella clusters carrying the pESI plasmid. Four were emergent Salmonella Infantis clusters, and one each belonged to serovar Senftenberg and Alachua. The Infantis cluster with a pESI plasmid carrying blaCTX-M-65 gene was the biggest of the four emergent Infantis clusters, with over 10,000 isolates. This cluster was first detected in South America and has since spread widely in United States. Over time the composition of pESI in United States has changed with the average number of resistance genes showing a decrease from 9 in 2014 to 5 in 2022, resulting from changes in gene content in two integrons present in the plasmid. A recent and emerging cluster of Senftenberg, which carries the blaCTX-M-65 gene and is primarily associated with turkey sources, was the second largest in the United States. SNP analysis showed that this cluster likely originated in North Carolina with the recent acquisition of the pESI plasmid. A single Alachua isolate from turkey was also found to carry the pESI plasmid containing blaCTX-M-65 gene. The study of the pESI plasmid, its evolution and mechanism of spread can help us in developing appropriate strategies for the prevention and further spread of this multi-drug resistant plasmid in Salmonella in poultry and humans.

genomics↗

Fecal microbiomes of laboratory beagles receiving antiparasitic formulations in an experimental setting

Here we describe the fecal microbiome of laboratory beagles in a non-invasive and humane experiment designed to contrast in vivo versus invitro bioequivalence in response to antiparasitic drug administration. The experiment provided a unique opportunity to describe the fecal microbiota of dogs in an experimental setting prior to their adoption. These data are contributed as a resource for the scientific community by the Center for Veterinary Medicine (CVM) of the U.S. Food and Drug Administration (FDA).

microbiology↗

Metagenomic survey of antimicrobial resistance (AMR) in Maryland surface waters differentiated by high and low human impact

In alignment with the One Health paradigm, surface waters are being evaluated as a modality to better understand baseline antimicrobial resistance (AMR) across the environment to supplement existing AMR monitoring in pathogens associated with humans, foods, and animals. Here, we use metagenomic and quasimetagenomic sequence data to describe AMR in Maryland surface waters from developed (high human impact) and natural (low human impact) classifications by the National Land Cover Database (NLCD). Critically important {beta}-lactamase genes were observed in twice as many high human impact zones. All data are available under BioProject PRJNA79347. https://www.ncbi.nlm.nih.gov/bioproject/794347

microbiology↗

Application of Quasimetagenomics Methods to Define Microbial Diversity and Subtype Listeria monocytogenes in Dairy and Seafood Production Facilities

Microorganisms frequently colonize surfaces and equipment within food production facilities. Listeria monocytogenes is a ubiquitous foodborne pathogen widely distributed in food production environments and is the target of numerous control and prevention procedures. Detection of L. monocytogenes in a food production setting requires culture dependent methods, but the complex dynamics of bacterial interactions within these environments and their impact on pathogen detection remains largely unexplored. To address this challenge, we applied both 16S rRNA and shotgun quasimetagenomic (enriched microbiome) sequencing of swab culture enrichments from seafood and dairy production environments. Utilizing 16S rRNA amplicon sequencing, we observed variability between samples taken from different production facilities and a distinctive microbiome for each environment. With shotgun quasimetagenomic sequencing, we were able to assemble L. monocytogenes metagenome assembled genomes (MAGs) and compare these MAGSs to their previously sequenced whole genome sequencing (WGS) assemblies, which resulted in two polyphyletic clades (lineages I and II). Using these same datasets together with in silico downsampling to produce a titration series of proportional abundances of L. monocytogenes, we were able to begin to establish limits for Listeria detection and subtyping using shotgun quasimetagenomics. This study contributes to the understanding of microbial diversity within food production environments and presents insights into how many reads or relative abundance is needed in a metagenome sequencing dataset to detect, subtype, and source track at a SNP level, as well as providing an important foundation for utilizing metagenomics to mitigate unfavorable occurrences along the farm to fork continuum. IMPORTANCEIn developed countries, the human diet is predominantly food commodities, which have been manufactured, processed, and stored in a food production facility. It is well known that the pathogen Listeria monocytogenes is frequently isolated from food production facilities and can cause serious illness to susceptible populations. Multistate outbreaks of L. monocytogenes over the last 10 years have been attributed to food commodities manufactured and processed in production facilities, especially those dealing with dairy products such as cheese and ice cream. A myriad of recalls due to possible L. monocytogenes contamination have also been issued for seafood commodities originating from production facilities. It is critical to public health that the means of growth, survival and spread of Listeria in food production ecosystems is investigated with developing technologies, such as 16S rRNA and quasimetagenomic sequencing, to aid in the development of effective control methods.

microbiology↗