ArticleMicrobiome2015
Amplicon sequencing for the quantification of spoilage microbiota in complex foods including bacterial spores.
Article in Microbiome, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Emerging Microbiological and Sensor-Based Approaches for Biofilm Detection in Meat and Poultry Processing Environments.Foods (Basel, Switzerland) · 2026Review
- Deciphering the Microbe-Metabolite Network in Irradiated Chicken Breast Meat: Multi-Omics Characterization of Differential Quality Response Mechanisms to Stepwise Irradiation Doses.Microorganisms · 2026Article
- Nanopore-based amplicon sequencing for rapid detection and identification ofFrontiers in microbiology · 2025Article
- Exploring the Feasibility of 16S rRNA Short Amplicon Sequencing-Based Microbiota Analysis for Microbiological Safety Assessment of Raw Oyster.Journal of microbiology and biotechnology · 2023Article
- Identification of Bulgarian Sourdough Microbiota by Metagenomic Approach Using Three Commercially Available DNA Extraction Protocols.Food technology and biotechnology · 2023Article
- Model Selection Reveals the Butyrate-Producing Gut BacteriumFrontiers in microbiology · 2021Article
- The use of next generation sequencing for improving food safety: Translation into practice.Food microbiology · 2019Review
- A benchmark study on error-correction by read-pairing and tag-clustering in amplicon-based deep sequencing.BMC genomics · 2016Article
- Flow Cytometric and 16S Sequencing Methodologies for Monitoring the Physiological Status of the Microbiome in Powdered Infant Formula Production.Frontiers in microbiology · 2016Article
- Mitigation of Biofilm Formation on Corrugated Cardboard Fresh Produce Packaging Surfaces Using a Novel Thiazolidinedione Derivative Integrated in Acrylic Emulsion Polymers.Frontiers in microbiology · 2016Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSpoilage of food products is frequently caused by bacterial spores and lactic acid bacteria. Identification of these organisms by classic cultivation methods is limited by their ability to form colonies on nutrient agar plates. In this study, we adapted and optimized 16S rRNA amplicon sequencing for quantification of bacterial spores in a canned food matrix and for monitoring the outgrowth of spoilage microbiota in a ready-to-eat food matrix.
resultsThe detection limit of bar-coded 16S rRNA amplicon sequencing was determined for the number of bacterial spores in a canned food matrix. Analysis of samples from a canned food matrix spiked with a mixture of equinumerous spores from the thermophiles, Geobacillus stearothermophilus and Geobacillus thermoglucosidans, and the mesophiles, Bacillus sporothermodurans, Bacillus cereus, and Bacillus subtilis, led to the detection of these spores with an average limit of 2 × 10(2) spores ml(-1). The data were normalized by setting the number of sequences resulting from DNA of an inactivated bacterial species, present in the matrix at the same concentration in all samples, to a fixed value for quantitative sample-to-sample comparisons. The 16S rRNA amplicon sequencing method was also employed to monitor population dynamics in a ready-to-eat rice meal, incubated over a period of 12 days at 7 °C. The most predominant outgrowth was observed by the genera Leuconostoc, Bacillus, and Paenibacillus. Analysis of meals pre-treated with weak acids showed inhibition of outgrowth of these three genera. The specificity of the amplicon synthesis was improved by the design of oligonucleotides that minimize the amplification of 16S rRNA genes from chloroplasts originating from plant-based material present in the food.
conclusionThis study shows that the composition of complex spoilage populations, including bacterial spores, can be monitored in complex food matrices by bar-coded amplicon sequencing in a quantitative manner. In order to allow sample-to-sample comparisons, normalizations based on background DNA are described. This method offers a solution for the identification and quantification of spoilage microbiota, which cannot be cultivated under standard laboratory conditions. The study indicates variable detection limits among species of bacterial spores resulting from differences in DNA extraction efficiencies.
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