Browsing Food Biosciences by Funder "2012205"
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High-throughput DNA sequencing to survey bacterial histidine and tyrosine decarboxylases in raw milk cheesesBackground: The aim of this study was to employ high-throughput DNA sequencing to assess the incidence of bacteria with biogenic amine (BA; histamine and tyramine) producing potential from among 10 different cheeses varieties. To facilitate this, a diagnostic approach using degenerate PCR primer pairs that were previously designed to amplify segments of the histidine (hdc) and tyrosine (tdc) decarboxylase gene clusters were employed. In contrast to previous studies in which the decarboxylase genes of specific isolates were studied, in this instance amplifications were performed using total metagenomic DNA extracts. Results: Amplicons were initially cloned to facilitate Sanger sequencing of individual gene fragments to ensure that a variety of hdc and tdc genes were present. Once this was established, high throughput DNA sequencing of these amplicons was performed to provide a more in-depth analysis of the histamine- and tyramine-producing bacteria present in the cheeses. High-throughput sequencing resulted in generation of a total of 1,563,764 sequencing reads and revealed that Lactobacillus curvatus, Enterococcus faecium and E. faecalis were the dominant species with tyramine producing potential, while Lb. buchneri was found to be the dominant species harbouring histaminogenic potential. Commonly used cheese starter bacteria, including Streptococcus thermophilus and Lb. delbreueckii, were also identified as having biogenic amine producing potential in the cheese studied. Molecular analysis of bacterial communities was then further complemented with HPLC quantification of histamine and tyramine in the sampled cheeses. Conclusions: In this study, high-throughput DNA sequencing successfully identified populations capable of amine production in a variety of cheeses. This approach also gave an insight into the broader hdc and tdc complement within the various cheeses. This approach can be used to detect amine producing communities not only in food matrices but also in the production environment itself.