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Record W2107048632 · doi:10.1186/1471-2164-7-43

Comparative genomics profiling of clinical isolates of Aeromonas salmonicida using DNA microarrays

2006· article· en· W2107048632 on OpenAlexafffund
John H. E. Nash, Wendy A. Findlay, Christian Luebbert, Oksana Mykytczuk, Simon Foote, Eduardo N. Taboada, Catherine D. Carrillo, Jessica M. Boyd, Duncan J. Colquhoun, Michael Reith, Laura L. Brown

Bibliographic record

VenueBMC Genomics · 2006
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAquaculture disease management and microbiota
Canadian institutionsInstitute for Marine BiosciencesNational Research Council CanadaInstitute for Biological Sciences
FundersCenters for Disease Control and PreventionFisheries and Oceans CanadaGenomic Health
KeywordsVirulenceBiologyAeromonas salmonicidaGenomeDNA microarrayGeneGeneticsComparative genomicsAeromonasMicroarrayGenomicsPlasmidBacteriaGene expression

Abstract

fetched live from OpenAlex

BACKGROUND: Aeromonas salmonicida has been isolated from numerous fish species and shows wide variation in virulence and pathogenicity. As part of a larger research program to identify virulence genes and candidates for vaccine development, a DNA microarray was constructed using a subset of 2024 genes from the draft genome sequence of A. salmonicida subsp. salmonicida strain A449. The microarray included genes encoding known virulence-associated factors in A. salmonicida and homologs of virulence genes of other pathogens. We used microarray-based comparative genomic hybridizations (M-CGH) to compare selected A. salmonicida sub-species and other Aeromonas species from different hosts and geographic locations. RESULTS: Results showed variable carriage of virulence-associated genes and generally increased variation in gene content across sub-species and species boundaries. The greatest variation was observed among genes associated with plasmids and transposons. There was little correlation between geographic region and degree of variation for all isolates tested. CONCLUSION: We have used the M-CGH technique to identify subsets of conserved genes from amongst this set of A. salmonicida virulence genes for further investigation as potential vaccine candidates. Unlike other bacterial characterization methods that use a small number of gene or DNA-based functions, M-CGH examines thousands of genes and/or whole genomes and thus is a more comprehensive analytical tool for veterinary or even human health research.

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 score0.009
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.056
GPT teacher head0.310
Teacher spread0.254 · 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

Citations41
Published2006
Admission routes2
Has abstractyes

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