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Record W2726979008 · doi:10.3389/fmicb.2017.01283

Prophage Integrase Typing Is a Useful Indicator of Genomic Diversity in Salmonella enterica

2017· article· en· W2726979008 on OpenAlexafffund
Anna Colavecchio, Yasmin D’Souza, Elizabeth Tompkins, Julie Jeukens, Luca Freschi, Jean-Guillaume Emond-Rheault, Irena Kukavica‐Ibrulj, Brian Boyle, Sadjia Békal, Sandeep Tamber, Roger C. Lévesque, Lawrence Goodridge

Bibliographic record

VenueFrontiers in Microbiology · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsSte. Anne's HospitalHealth CanadaUniversité LavalMcGill University
FundersGénome QuébecGenome Canada
KeywordsProphageIntegraseBiologySalmonella entericaGenomeGeneticsGeneVirologyBacteriophageMicrobiologyEscherichia coli

Abstract

fetched live from OpenAlex

Salmonella enterica is a bacterial species that is a major cause of illness in humans and food-producing animals. S. enterica exhibits considerable inter-serovar diversity, as evidenced by the large number of host adapted serovars that have been identified. The development of methods to assess genome diversity in S. enterica will help to further define the limits of diversity in this foodborne pathogen. Thus, we evaluated a PCR assay, which targets prophage integrase genes, as a rapid method to investigate S. enterica genome diversity. To evaluate the PCR prophage integrase assay, 49 isolates of S. enterica were selected, including 19 clinical isolates from clonal serovars (Enteritidis and Heidelberg) that commonly cause human illness, and 30 isolates from food-associated Salmonella serovars that rarely cause human illness. The number of integrase genes identified by the PCR assay was compared to the number of integrase genes within intact prophages identified by whole genome sequencing and phage finding program PHASTER. The PCR assay identified a total of 147 prophage integrase genes within the 49 S. enterica genomes (79 integrase genes in the food-associated Salmonella isolates, 50 integrase genes in S. Enteritidis, and 18 integrase genes in S. Heidelberg). In comparison, whole genome sequencing and PHASTER identified a total of 75 prophage integrase genes within 102 intact prophages in the 49 S. enterica genomes (44 integrase genes in the food-associated Salmonella isolates, 21 integrase genes in S. Enteritidis, and 9 integrase genes in S. Heidelberg). Collectively, both the PCR assay and PHASTER identified the presence of a large diversity of prophage integrase genes in the food-associated isolates compared to the clinical isolates, thus indicating a high degree of diversity in the food-associated isolates, and confirming the clonal nature of S. Enteritidis and S. Heidelberg. Moreover, PHASTER revealed a diversity of 29 different types of prophages and 23 different integrase genes within the food-associated isolates, but only identified 4 different phages and integrase genes within clonal isolates of S. Enteritidis and S. Heidelberg. These results demonstrate the potential usefulness of PCR based detection of prophage integrase genes as a rapid indicator of genome diversity in S. enterica.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.234
Teacher spread0.207 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations38
Published2017
Admission routes2
Has abstractyes

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