Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Food metagenome

ABSTRACT: The impact of vegan production on the kimchi microbiome

PROVIDER: PRJNA418790 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR6304540_1.fastq.gz	Fastqsanger.gz
	SRR6304540_2.fastq.gz	Fastqsanger.gz
	SRR6304550_1.fastq.gz	Fastqsanger.gz
	SRR6304550_2.fastq.gz	Fastqsanger.gz
	SRR6304560_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 148

Similar Datasets

microbiome

Project description:The impact of vegan production on the kimchi microbiome

| PRJNA418783 | ENA

food metagenome

Project description:Metagenome isolated from kimchi

| PRJNA50815 | ENA

food metagenome

Project description:Studies of Kimchi microbial community

| PRJNA170723 | ENA

food fermentation metagenome

Project description:Buddhist temple kimchi fermentation metagenome

| PRJNA431117 | ENA

food metagenome

Project description:Kimchi (fermented food) with saccharides Targeted loci

| PRJNA400652 | ENA

food fermentation metagenome

Project description:Bacterial communities in kimchi manufacturing process

| PRJDB5218 | ENA

food fermentation metagenome

Project description:Fermented food (kimchi) Metagenome Targeted Locus (Loci)

| PRJNA255141 | ENA

food metagenome

Project description:Metatranscriptomic Analysis of Lactic Acid Bacterial Gene Expressions during Kimchi Fermentation

| PRJNA306639 | ENA

Early detection of food safety and spoilage incidents based on live microbiome profiling and qPCR-based monitoring of indicators

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

food fermentation metagenome

Project description:Impact of container type on microbiome of Airag, a Mongolian fermented mare's milk

| PRJDB17651 | ENA