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Record W3000799580 · doi:10.7939/r3-v0vd-bc72

Physiological and genomic characterization of six virulent bacteriophages of Shiga toxin-producing Escherichia coli O157:H7 for biocontrol and detection applications

2019· article· en· W3000799580 on OpenAlexaboutno aff
Beatriz Iara Cabral e Pacheco

Bibliographic record

VenueUniversity of Alberta Library · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsnot available
Fundersnot available
KeywordsVirulenceEscherichia coliMicrobiologyShiga toxinBiologyToxinVirologyGeneticsGene

Abstract

fetched live from OpenAlex

Despite multiple control strategies in all steps of the food production chain, outbreaks of foodborne pathogens are common worldwide. More effective ways to prevent, eliminate or at least detect their presence before products reach consumers are of great interest to the general public, the food industry, and public health agencies. A promising approach is the use of bacteriophages (phages), viruses that specifically infect bacteria, in the biocontrol and detection of these pathogens. Escherichia coli O157:H7 is an important bacterial pathogen commonly associated with the contamination of vegetables, meat and other animal products. Healthy cattle are the primary reservoir of E. coli O157:H7 and consequently of its predators, phages. In the present work, six E. coli O157:H7 phages previously isolated from commercial feedlots in Southern Alberta were characterized in terms of morphology, host range and lytic capability, adsorption kinetics, and virulence dynamics. The six phages belong to the Siphoviridae family. The screening of 30 different E. coli O157:H7 strains against all phages revealed that at least 22 were susceptible to all six phages, with 14 being extremely sensitive. Adsorption kinetics results combined with two different reaction models (single-step and sequential adsorption) indicated adsorption occurred in two steps: an initial reversible binding followed by an irreversible one. Moreover, the phage genomes were sequenced and analyzed. The six phages shared high genomic similarity between themselves and with other viruses isolated from the same trial but at different geographical locations and collected at different sampling times. We thus hypothesize these phages represent different variants of the dominant E. coli O157:H7 phage in their ecological niche. Furthermore, although the genomes of five of the six phages shared 99.9% pairwise similarity, their host range and lytic capability, adsorption kinetics, and infection dynamics differed. Twelve nonsynonymous point mutations differentiated the genetic codes of these phages and, notably, six of these mutations were located in genes encoding putative tail fibers, responsible for host recognition and binding. Thus, these point mutations are likely causes of differences in the phage phenotypes observed, and would be represent interesting locations for phage genetic engineering to tailor host specificity. The present work sets a framework for the identification and selection of phages with potential for biocontrol and/or detection of E. coli O157:H7, provides valuable insights on phage host relationship mechanisms, and suggests genetic basis for traits of interest.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.005
GPT teacher head0.167
Teacher spread0.163 · 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 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

Citations0
Published2019
Admission routes1
Has abstractyes

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