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Record W2083517753 · doi:10.1094/asbcj-2007-0611-01

<i>horA</i>-Specific Real-Time PCR for Detection of Beer-Spoilage Lactic Acid Bacteria

2007· article· en· W2083517753 on OpenAlex
Monique Haakensen, L. Butt, Bonnie Chaban, Harry Deneer, Barry Ziola, Teri Dowgiert

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of the American Society of Brewing Chemists · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFermentation and Sensory Analysis
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsFood spoilagePediococcusBacteriaBiologyLactobacillusFood scienceLactic acidLactobacillus brevisMicrobiologyGenetics

Abstract

fetched live from OpenAlex

AbstractBeer-spoilage bacteria have long been a problem for brewers. Among the most problematic beer spoilers are several species of the Gram-positive genera Lactobacillus and Pediococcus. Current methods of detecting and identifying these organisms are time-consuming and do not differentiate between bacteria capable of spoiling beer and benign bacteria. The horA-specific real-time polymerase chain reaction (rPCR) described here identifies beer-spoilage organisms based not on their identity, but on the presence of a gene that we show to be highly correlated with the ability of an organism to grow in beer. The horA hop-resistance gene has been shown to be associated with beer spoilage by isolates from four Lactobacillus spp. and one Pediococcus sp. We document the presence of the horA gene in one additional genus and 11 additional species, with many of these bacteria commonly found as beer spoilers. The use of horA-specific rPCR allows for a substantial reduction in the time required for detection of potential beer spoilage bacteria and efficiently discriminates between those organisms that have the horA gene (highly likely to spoil beer) and those organisms that do not have the gene (much less likely to spoil beer).RESUMENLas bacterias dañinas a la cerveza han sido un problema para cerveceros por mucho tiempo. Entre la más problemática organismos dañinas a la cerveza son varias especies Gram-positiva del género Lactobacillus y Pediococcus. Los métodos actuales de detectar y de identificar estos organismos son desperdiciadores de tiempo y no distinguen entre las bacterias capaces de deteriorar la cerveza y bacterias benignas. La horA-específica reacción en cadena de la polimerasa en tiempo real (rPCR) descrita aquí identifica los organismos dañinos a la cerveza basada no en su identidad, sino en la presencia de un gene que demostremos para ser correlacionados fuertemente con la capacidad de un organismo de crecer en cerveza. El gene horA de lúpulo-resistencia se ha demostrado para ser asociado con la deterioración de cerveza por los aislados de cuatro especies de Lactobacillus y una especie de Pediococcus. Documentamos la presencia del gene horA en un género adicional y 11 especies adicionales, con muchas de estas bacterias encontradas comúnmente como bacterias dañinas a la cerveza. El uso del rPCR horA-específico permite una reducción substancial en el tiempo requerido para la detección de las bacterias con potencial a deteriorar la cerveza y discrimina eficientemente entre esos organismos que tengan el gene horA (altamente probable estropear la cerveza) y esos organismos que no tienen el gene (mucho menos probable estropear la cerveza).KeywordsBeer spoilageHop resistancehorALactic acid bacteriaReal-time PCRPalabras clave: Bacterias ácido-lácticasDeterioración de la cervezahorAPCR en tiempo realResistencia de lúpuloView correction statement:Erratum

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.154

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.246
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it