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Record W4319827940 · doi:10.1111/jfs.13044

Use of a phage cocktail to reduce the numbers of seven <i>Escherichia coli</i> strains belonging to different <scp>STEC</scp> serogroups applied to fresh produce and seeds

2023· article· en· W4319827940 on OpenAlex
Yiran Ding, Yuchen Nan, Yang Qiu, Dongyan Niu, Kim Stanford, Rick Holley, Tim A. McAllister, Claudia Narváez‐Bravo

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Food Safety · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of LethbridgeUniversity of CalgaryUniversity of Manitoba
FundersMinistry of Agriculture, Food and Rural AffairsOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsEscherichia coliFood scienceBiologyMicrobiology

Abstract

fetched live from OpenAlex

Abstract The aims of this research were to evaluate the effectiveness of a phage cocktail at reducing seven Shiga toxigenic Escherichia coli (STEC) serogroups on different food matrixes: mung bean sprouts (MBP), lettuce, and mung bean seeds (MBS) and to test the phage cocktail effectiveness to reduce E. coli O157 on Romaine and iceberg lettuce. To study the effect of the type of food matrix on the STEC phage cocktail effectiveness, a mixture of seven highly sensitive STEC strains designated as phage propagation strains (PPS) were used to adulterate Romaine lettuce, MBP, and MBS matrixes at a concentration of 10 5 logs CFU/g. A subsample of the treated MBS was germinated to assess STEC survival. Recovered STEC strains were confirmed using latex agglutination and PCR. To test the phage cocktail effectiveness to reduce E. coli O157:H7 on Romaine and iceberg lettuce, a mixture of four STEC strains (different than phage propagation strains, non‐PPS) at both low (10 3 CFU/g) and high (10 5 CFU/g) concentrations were used to spike the samples in scaled up trials for the purpose of potential commercialization. Phage treatments including a combination of STEC phage cocktail and chlorinated water treatment were then applied to lettuce in a simulated scaled‐up trial. STEC was assessed on the treated samples at different storage time and temperatures (0, 24, 48, and 72 hr at 2, 10 and 25°C). In the food matrix trial, the combination of STEC phage cocktail and chlorinated water‐reduced PPS ( p &lt; 0.001) STEC on lettuce by 2.1 log 10 CFU/g and on MBP by 2.2 log 10 CFU/g. However, isolates from all 7 STEC serogroups remained viable after phage treatment in both lettuce and MBP; particularly those associated with serogroup O111, O121, O103, and O145, while only a few colonies of serogroup O26, O45, and O157 were detected. Lettuce adulterated with low levels of 4 non‐PPS E. coli O157:H7 (10 3 CFU/g) achieved a reduction of 2.6–3.2 logs. While a reduction 1.7–2.3 logs was achieved by the phage cocktail when lettuce was inoculated with 10 5 CFU/g. Overall phage performance was more effective at 2 and 10°C and improved over storage time up to 72 hr. However, for MBS, the phage cocktail was not able to kill any of the STEC populations as all of them recovered during germination.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.697
Threshold uncertainty score0.510

Codex and Gemma teacher scores by category

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

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 head0.020
GPT teacher head0.245
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