Ontology highlight
ABSTRACT:
PROVIDER: PRJNA880884 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:FDA CVM NARMS - EPA One Health Surface Water Study
| PRJNA884092 | ENA
Project description:FDA CVM NARMS - EPA One Health Surface Water Study Metagenomes
| PRJNA1177841 | ENA
Project description:Early detection of spoilage microorganisms and food pathogens is of major importance in preventing food recalls and foodborne outbreaks. Although constant effort is invested in developing sensitive methods for rapid microbial detection, none of the current methods enables the detection of food pathogens within a few hours; therefore, development of innovative early-warning food-testing strategies are needed. Herein, we assessed a novel strategy that harnesses the microbiome signature of a food product to determine deviations in the abundance of particular community members and detect production defects. Employing the production process of barbecued (BarBQ) pastrami as a model, we characterized the microbiome profiles of the product along the production line using next-generation sequencing of the 16S rRNA gene, concentrating on the live microbiota. Following the establishment of a microbiome dataset representing a properly produced product, we were able to identify shifts in the microbiome profile of a defective batch produced under potassium lactate deficiency. With the identification of Vibrio and Lactobacillus as potential indicator bacteria for potassium lactate deficiency, rapid qPCR assays were designed for their quantification. Aligned with the microbiome profiling results, these qPCR assays were effective for rapid identification of a defective production event. This implies the use of rapid quantification targeting microbiome profile-derived indicator bacteria for in-house detection of defective batches and identification of food-safety and quality events with results obtained on the same day. The suggested strategy should pave the way toward safer and more efficient food-production systems.
2024-08-27 | GSE255249 | GEO
Project description:enzymes. However, many genes in the microbiome remain uncharacterized due to the challenge in culturing intestinal strains in vitro, which limits the identification of target enzymes. To address this issue, we developed an effective Activity-Based MetaProteomics (ABMP) strategy using a specific activity-based probe (ABP) to screen the entire gut microbiome for target enzymes, without the need to isolate and culture bacterial strains individually. α-Galactosidases (AGALs) are widely distributed in gut microbiota, plant, and animal kingdoms of life and have multiple applications in industries such as food, animal feed, and biomedical sectors. Despite the rich source of AGALs in the gut microbiome, many AGAL genes lack functional annotations. Using an activity-based cyclophellitol aziridine probe specific to AGAL, we successfully identified and characterized several new enzymes possessing AGAL activities from the gut microbiome.
2023-08-25 | PXD044848 |
Project description:We combined an experimental microbiome of 11 bacterial strains isolated from the gut of native Caenorhabditis elegans. C. elegans were maintained on the experimental microbiome, Escherichia coli OP50 (control food source), or OP50 supplemented with cell-free media (CFM) from the experimental microbiome. For each of the three feeding conditions, RNA-seq was performed for wildtype (N2) worms or transgenic worms expressing amyloid beta 1-42 in their body wall muscle (GMC101).
2022-06-23 | E-MTAB-10693 | biostudies-arrayexpress
Project description:Companion Animal Food Metagenome
| PRJNA1062328 | ENA
Project description:FDA metagenomic data sets related to food safety
| PRJNA390622 | ENA
Project description:The capability of the U.S. Food and Drug Administration Enteric Viruses tiling microarray (FDA-EVIR) was assessed for rapid molecular identification of human norovirus (NoV) and hepatitis A virus (HAV) extracted from artificially inoculated fresh produce. Two published viral extraction strategies, total RNA extraction or virus particle isolation, were employed to prepare the viral targets. We also assessed the amount of viral RNA extracted from celery by three commercially-available kits and how well that RNA performed on the FDA-EVIR. Our results confirm that FDA-EVIR can correctly identify common enteric viruses isolated from fresh produce and is capable of identifying single and mixed species of viruses, as well as distinguishing among genotypes. Extending microarray methods to other food matrices should provide important support to surveillance and outbreak investigations.
2020-04-01 | GSE140351 | GEO