Biology subjects

Kocurek, B. J.

Publications and source records attributed to Kocurek, B. J..

6 recordsLinked to original sources

bioRxiv2026

Ultra processed microbiome: Effects of dietary Stable Carbonyl adducts (SCars) on developing microbiota of mice

Consumption of ultra-processed food (UPF) is increasing and is causally linked with noncommunicable disease onset, however specific compounds within UPFs that influence disease risk remain poorly defined. The acronym 'SCars', for Stable Carbonyl Adducts, is introduced herein as an umbrella term encompassing advanced glycation end-products (AGEs), advanced lipoxidation end-products (ALEs), and other carbonyl-derived modifications. These molecules arise as products of spontaneous carbonyl chemistry, a reaction accelerated by industrial food processing. Dietary SCars have been associated with metabolic dysfunction; however, their impact on microbiome composition during windows of developmental vulnerability has not been well studied. Puberty in mice represents a period of developmental plasticity during which the gut microbiome is susceptible to dietary exposures. We tested whether transient exposure to high levels of dietary SCars during puberty remodels the developing gut microbiome. Using metagenomic sequencing of fecal samples from mice exposed to high-SCars or control diets, we found that high-SCars exposure profoundly impacted microbial community structure and metabolic potential. Dietary SCars reduced microbial diversity and depleted short-chain fattyacid producing taxa while enriching pathways related to membrane remodeling, branched-chain amino acid biosynthesis, and nucleotide anabolism. These data identify SCars as features of UPFs capable of reprogramming the developing gut microbiota.

microbiology↗

bioRxiv2025

Breaking the culture habit: metagenomic diagnosis of companion animal skin infections

BackgroundSkin infections have been described as the primary cause for presentation in veterinary small animal practices and they frequently result in prescription of both topical and systemic antibiotics. Because such infections are often secondary complications of other underlying pathologies, recurrent infections are common and can lead to multiple antibiotic exposures. This scenario creates steady selection pressure toward antibiotic resistance at the confluence of the skin (the largest mammalian organ), the bloodstream, and shared human and animal environments. This case study compares metagenomic (MGX) data with aerobic culture to evaluate diagnostic utility for simultaneous identification and characterization of pathogens, microbiomes, and resistomes of companion animal skin infections. ResultsOne feline and eight canine skin swabs were analyzed with aerobic culture and traditional antimicrobial susceptibility testing (AST) and compared with MGX profiling. Veterinary laboratory diagnostic (VDL) culture and AST identified Staphylococcus aureus, S. pseudintermedius, S. schleiferi, methicillin resistant (MR) S. schleiferi (MRSS), MR S. pseudintermedius (MRSP) and Pseudomonas aeruginosa from skin swabs. MGX data described the identical bacterial pathogens recovered by aerobic culture and methicillin resistance genes mecA, mecI, mecR1 in samples for which AST confirmed MRSP and MRSS. MGX data also identified mec genes in samples without culture-based confirmation of MR phenotypes. MGX data also described multi-domain composition of microbiomes of infected skin including bacteria, fungi, viruses, phages, AMR, plasmids, and metabolic features associated with skin infections. ConclusionsMGX data identified the identical pathogens and inferred AMR phenotypes as culture-based diagnostic testing, and additionally characterizedo multi-domain microbiota, mobile AMR elements, and metabolic features. Efforts to accelerate cures by precision medical responses depend on accelerated precision diagnostics. Challenges remain for the implementation of MGX data into veterinary diagnostic laboratory investigation and response. We demonstrate with a small case study, that MGX data can be used to complement current state of the art VDL results and potentially advance a judicious veterinary medical response regarding antibiotic administration for companion animal skin infections. In the future, simultaneous description of the polymicrobial ecology of skin infections (bacterial, viruses, phages, fungi, and even functional metabolomic features) provided by MGX data can advance epidemiology, develop new treatment strategies, accelerate diagnostics and provide data for artificial intelligence (AI) models focused on advancing veterinary diagnostics and medical treatments.

microbiology↗

bioRxiv2025

DNA data (genome skims and metabarcodes) paired with chemical data demonstrate utility for retrospective analysis of forage linked to fatal poisoning of cattle

Prepared and stored feeds, fodder, silage, and hay may be contaminated by toxic plants resulting in the loss of livestock. Several poisonous plants have played significant roles in livestock deaths from forage consumption in recent years in the Western United States including Salvia reflexa. Metagenomic data, genome skims and metabarcodes, have been used for identification and characterization of plants in complex matrices including diet composition of animals, mixed forages, and herbal products. Here, chemistry, genome skims, and metabarcoding were used to retrospectively describe the composition of contaminated alfalfa hay from a case of Salvia reflexa poisoning that killed 165 cattle. Genome skims and metabarcoding provided similar estimates of the relative abundance of the Salvia in the hay samples when compared to chemical methods. Additionally, genome skims and metabarcoding provided similar estimates of species composition in the contaminated hay and rumen contents of poisoned animals. The data demonstrate that genome skims and DNA metabarcoding may provide useful tools for plant poisoning investigations.

genomics↗

bioRxiv2024

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↗

bioRxiv2023

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↗

bioRxiv2022

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↗