MétaCan
Menu
Back to cohort
Record W1997554454 · doi:10.1094/asbcj-2010-0308-02

Rapid Screening for Gram-Negative and Gram-Positive Beer-Spoilage <i>Firmicutes</i> Using a Real-Time Multiplex PCR

2010· article· en· W1997554454 on OpenAlex
Vanessa Pittet, Monique Haakensen, Barry Ziola

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 · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFermentation and Sensory Analysis
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsFirmicutesFood spoilageMultiplexMicrobiologyBiologyBacteriaGramGram-positive bacteriaFood science16S ribosomal RNAGeneticsAntibiotics

Abstract

fetched live from OpenAlex

AbstractCurrent methods for detection and identification of beer-spoilage bacteria can be time-consuming and may not encompass all beer-spoilage isolates due to targeting of specific species. As such, a rapid method that targets a broader spectrum of beer-spoilage bacteria is likely to be more efficient for initial detection of contamination. Building on our previous real-time PCR (rltPCR) that detects Firmicutes, we created a system that enables concurrent detection and differentiation of gram-negative and -positive brewery-associated Firmicutes. Our two previously described rltPCR hydrolysis probes, which are able to detect all bacteria and Firmicutes, were used in combination with a newly developed probe (GmNeg) that detects only gramnegative brewery-associated Firmicutes. In silico analysis performed to determine the specificity of the GmNeg probe predicted that the probe would detect all gram-negative brewery-associated Firmicutes. This was confirmed by rltPCR analysis of brewery-associated bacteria, with the GmNeg probe showing specificity for gram-negative Firmicutes but not for gram-positive Firmicutes or any non-Firmicutes. The sensitivity of this rltPCR system was 35 fg of DNA per reaction, corresponding to approx. 10–20 bacteria. This multiplex rltPCR will enable brewery quality control laboratories to rapidly screen for brewery-associated Firmicutes, with identification of a contaminant as either a gram-negative or -positive bacterium.RESUMENLos métodos actuales de detectión e identificatión de bacterias de deterioro de cerveza puede ser mucho tiempo y no puede abarcar todos los aislados de bacterias de deterioro de cerveza debido a la orientatión de determinadas especies. Como tal, un método rápido que se dirige a un amplio espectro de bacterias de deterioro de cerveza es probable que sea más eficiente para la detección inicial de contaminación. Basándonos en nuestra anterior en tiempo real PCR (rltPCR) que detecta Firmicutes, hemos creado un sistema que permite la detección y la diferenciación simultánea de bacterias gram-negativos y gram-positivos Firmicutes asociada con la cervecería. Nuestros dos descritos anteriormente rltPCR sondas de hidrólisis, que son capaces de detectar todas las bacterias y Firmicutes, se utiliza en combinación con una sonda de nuevo desarrollo (GmNeg) que detecta sólo gram-negativos Firmicutes asociados con la cervecería. Análisis en silico realiza para determinar la especificidad de la sonda GmNeg predijo que la sonda detecta todos los gram-negativos Firmicutes asociados con la cervecería. Esto fue confirmado por análisis rltPCR de las bacterias asociadas con la cervecería, con la sonda GmNeg muestra especificidad por gram-negativos Firmicutes pero no para gram-positivas Firmicutes o de otra índole Firmicutes. La sensibilidad de este sistema de rltPCR fue de 35 fg de ADN por reacción, que corresponde a aprox. 10–20 bacterias. Esta rltPCR múltiplex permitirá que los laboratorios de control de calidad de la cervecería a rápidamente la pantalla para Firmicutes asociada con la cervecería, con la identificación de un contaminante, ya sea como bacterias gram-negativos o gram-positivos.KeywordsBeer-spoilage organismsFirmicutesGram-negativeGram-positiveMultiplex real-time PCRRapid screeningPalabras clave: Bacterias de deterioro de cervezaFirmicutesGram-negativasGram-positivasPCR múltiplex en tiempo realRapida detección

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)0.000
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 score0.089
Threshold uncertainty score0.230

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.027
GPT teacher head0.263
Teacher spread0.237 · 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