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Record W2037779253 · doi:10.1186/1471-2180-8-86

Rapid identification of Brucella isolates to the species level by real time PCR based single nucleotide polymorphism (SNP) analysis

2008· article· en· W2037779253 on OpenAlex

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBMC Microbiology · 2008
Typearticle
Languageen
FieldVeterinary
TopicBrucella: diagnosis, epidemiology, treatment
Canadian institutionsnot available
FundersUniversity of WaterlooDepartment for Environment, Food and Rural Affairs, UK Government
KeywordsBiologyBrucellaGeneticsSingle-nucleotide polymorphismPhylogenetic treeGenotypeBrucellosis16S ribosomal RNAPolymerase chain reactionMicrobiologyGeneVirology

Abstract

fetched live from OpenAlex

BACKGROUND: Brucellosis, caused by members of the genus Brucella, remains one of the world's major zoonotic diseases. Six species have classically been recognised within the family Brucella largely based on a combination of classical microbiology and host specificity, although more recently additional isolations of novel Brucella have been reported from various marine mammals and voles. Classical identification to species level is based on a biotyping approach that is lengthy, requires extensive and hazardous culturing and can be difficult to interpret. Here we describe a simple and rapid approach to identification of Brucella isolates to the species level based on real-time PCR analysis of species-specific single nucleotide polymorphisms (SNPs) that were identified following a robust and extensive phylogenetic analysis of the genus. RESULTS: Seven pairs of short sequence Minor Groove Binding (MGB) probes were designed corresponding to SNPs shown to possess an allele specific for each of the six classical Brucella spp and the marine mammal Brucella. Assays were optimised to identical reaction parameters in order to give a multiple outcome assay that can differentiate all the classical species and Brucella isolated from marine mammals. The scope of the assay was confirmed by testing of over 300 isolates of Brucella, all of which typed as predicted when compared to other phenotypic and genotypic approaches. The assay is sensitive being capable of detecting and differentiating down to 15 genome equivalents. We further describe the design and testing of assays based on three additional SNPs located within the 16S rRNA gene that ensure positive discrimination of Brucella from close phylogenetic relatives on the same platform. CONCLUSION: The multiple-outcome assay described represents a new tool for the rapid, simple and unambiguous characterisation of Brucella to the species level. Furthermore, being based on a robust phylogenetic framework, the assay provides a platform that can readily be extended in the future to incorporate newly identified Brucella groups, to further type at the subspecies level, or to include markers for additional useful characteristics.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.356
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.111
GPT teacher head0.296
Teacher spread0.185 · 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