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Metagenomics Food safety

ABSTRACT: The study compares 16S rDNA amplicon and metagenomics sequencing for Pathogen detection in Food safety

PROVIDER: PRJEB33186 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	ERR3414570_1.fastq.gz	Fastqsanger.gz
	ERR3414570_2.fastq.gz	Fastqsanger.gz
	ERR3413871_1.fastq.gz	Fastqsanger.gz
	ERR3413871_2.fastq.gz	Fastqsanger.gz
	ERR3413872_1.fastq.gz	Fastqsanger.gz

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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.

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A multidimensional 1H NMR lipidomics workflow to address chemical food safety issues

Project description:INTRODUCTION: Although it is still at a very early stage compared to its mass spectrometry (MS) counterpart, proton nuclear magnetic resonance (NMR) lipidomics is worth being investigated as an original and complementary solution for lipidomics. Dedicated sample preparation protocols and adapted data acquisition methods have to be developed to set up an NMR lipidomics workflow; in particular, the considerable overlap observed for lipid signals on 1D spectra may hamper its applicability.OBJECTIVES: The study describes the development of a complete proton NMR lipidomics workflow for application to serum fingerprinting. It includes the assessment of fast 2D NMR strategies, which, besides reducing signal overlap by spreading the signals along a second dimension, offer compatibility with the high-throughput requirements of food quality characterization.METHOD: The robustness of the developed sample preparation protocol is assessed in terms of repeatability and ability to provide informative fingerprints; further, different NMR acquisition schemes—including classical 1D, fast 2D based on non-uniform sampling or ultrafast schemes—are evaluated and compared. Finally, as a proof of concept, the developed workflow is applied to characterize lipid profiles disruption in serum from β-agonists diet fed pigs.RESULTS: Our results show the ability of the workflow to discriminate efficiently sample groups based on their lipidic profile, while using fast 2D NMR methods in an automated acquisition framework.CONCLUSION: This work demonstrates the potential of fast multidimensional 1H NMR—suited with an appropriate sample preparation—for lipidomics fingerprinting as well as its applicability to address chemical food safety issues.

2018-09-10 | MTBLS643 | MetaboLights

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