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Record W2900380467 · doi:10.3390/v10110616

Characterization of the Escherichia coli Virulent Myophage ST32

2018· article· en· W2900380467 on OpenAlexafffund
H. Liu, Hany Geagea, Geneviève M. Rousseau, Simon J. Labrie, Denise M. Tremblay, Xinchun Liu, Sylvain Moineau

Bibliographic record

VenueViruses · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsUniversité Laval
FundersChina Scholarship CouncilNational Natural Science Foundation of ChinaCanada Research Chairs
KeywordsORFSMyoviridaeBiologySiphoviridaePhylogenetic treeVirulenceEscherichia coliBacteriophageGeneticsCapsidGenomeOpen reading frameMicrobiologyGenePeptide sequence

Abstract

fetched live from OpenAlex

The virulent phage ST32 that infects the Escherichia coli strain ST130 was isolated from a wastewater sample in China and analyzed. Morphological observations showed that phage ST32 belongs to the Myoviridae family, as it has an icosahedral capsid and long contractile tail. Host range analysis showed that it exhibits a broad range of hosts including non-pathogenic and pathogenic E. coli strains. Interestingly, phage ST32 had a much larger burst size when amplified at 20 °C as compared to 30 °C or 37 °C. Its double-stranded DNA genome was sequenced and found to contain 53,092 bp with a GC content of 44.14%. Seventy-nine open reading frames (ORFs) were identified and annotated as well as a tRNA-Arg. Only nineteen ORFs were assigned putative functions. A phylogenetic tree using the large terminase subunit revealed a close relatedness with four unclassified Myoviridae phages. A comparative genomic analysis of these phages showed that the Enterobacteria phage phiEcoM-GJ1 is the closest relative to ST32 and shares the same new branch in the phylogenetic tree. Still, these two phages share only 47 of 79 ORFs with more than 90% identity. Phage ST32 has unique characteristics that make it a potential biological control agent under specific conditions.

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 categoriesInsufficient payload (model declined to judge)
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 score0.391
Threshold uncertainty score0.995

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)0.0060.001

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 head0.015
GPT teacher head0.241
Teacher spread0.227 · 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.

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

Citations25
Published2018
Admission routes2
Has abstractyes

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