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Methods for detection and identification of beer-spoilage microbes.
Oldham, Ryanne C; Held, Michael A.
Afiliação
  • Oldham RC; Department of Chemistry and Biochemistry, Ohio University, Athens, OH, United States.
  • Held MA; Quality Assurance and Quality Control Laboratory, Jackie O's Brewery, Athens, OH, United States.
Front Microbiol ; 14: 1217704, 2023.
Article em En | MEDLINE | ID: mdl-37637116
It is critical that breweries of all sizes routinely monitor the microbiome of their process to limit financial losses due to microbial contamination. Contamination by beer-spoiling microbes (BSMs) at any point during the brewing process may lead to significant losses for breweries if gone undetected and allowed to spread. Testing and detection of BSMs must be routine and rapid, and because even small breweries need the capability of BSM detection and identification, the method also needs to be affordable. Lactic acid bacteria (LAB) are responsible for most spoilage incidents, many of which have been shown to enter the viable but nonculturable (VBNC) state under conditions present in beer such as cold or oxidative stress. These bacteria are invisible to traditional methods of detection using selective media. This article describes several methods of BSM detection and identification that may be useful in the majority of craft breweries. While there are several genomic methods that meet some or many qualifications of being useful in craft breweries, real-time quantitative polymerase chain reaction (qPCR) currently best meets the desired method characteristics and holds the most utility in this industry, specifically SYBR Green qPCR. qPCR is a targeted method of detection and identification of microbes that is affordable, rapid, specific, sensitive, quantitative, and reliable, and when paired with valid DNA extraction techniques can be used to detect BSMs, including those in the VBNC state.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article