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Record W2118529479 · doi:10.1139/w02-089

Phylogenetic study and identification of human pathogenic<i>Vibrio</i>species based on partial<i>hsp</i>60 gene sequences

2002· article· en· W2118529479 on OpenAlexafffundvenue
Anita Kwok, Jason T Wilson, Michael B. Coulthart, Lai-King Ng, Lucy M. Mutharia, Anthony W. Chow

Bibliographic record

VenueCanadian Journal of Microbiology · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVibrio bacteria research studies
Canadian institutionsUniversity of British Columbia
FundersVancouver Foundation
KeywordsBiologyVibrioVibrio alginolyticusPhylogenetic treeMicrobiologyGeneticsGeneSequence analysisVibrio parahaemolyticusVibrionaceaeAeromonas hydrophilaPhylogeneticsBacteria

Abstract

fetched live from OpenAlex

The use of hsp60 gene sequences for phylogenetic study and identification of pathogenic marine vibrios was investigated. A 600-bp partial hsp60 gene was amplified by PCR and sequenced from 29 strains representing 15 Vibrio species within the family Vibrionaceae. Sequence comparison of the amplified partial hsp60 gene revealed 71-82% sequence identity among different Vibrio species and 96-100% sequence identity among epidemiologically distinct strains with the same species designation. This degree of discrimination allows unambiguous differentiation of all Vibrio species included in the current study from each other, as well as from Aeromonas hydrophila and Plesiomonas shigelloides, which are often misidentified as Vibrio species by conventional biochemical methods. Based on the hsp60 gene sequences, two previously unidentified shrimp isolates were found to be more closely related to Vibrio alginolyticus (93-94% sequence identity) than to Vibrio parahaemolyticus (89% sequence identity), whereas 16S rRNA gene analysis was unable to differentiate among these closely related species (95-97% sequence identity). Our results indicate that the hsp60 gene may be a useful alternative target for phylogenetic analysis and species identification of marine Vibrios to complement more conventional identification systems.

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.

How this classification was reachedexpand

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 score0.058
Threshold uncertainty score0.528

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.022
GPT teacher head0.248
Teacher spread0.225 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations65
Published2002
Admission routes3
Has abstractyes

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