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Grim, C. J.

Publications and source records attributed to Grim, C. J..

2 recordsLinked to original sources

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↗