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Record W4376610637 · doi:10.1128/spectrum.00183-23

Comparative Genomic Analyses of Escherichia coli from a Meat Processing Environment in Relation to Their Biofilm Formation and Persistence

2023· article· en· W4376610637 on OpenAlexafffund
Xianqin Yang, Frances Tran, Peipei Zhang

Bibliographic record

VenueMicrobiology Spectrum · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial biofilms and quorum sensing
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaBeef Cattle Research Council
KeywordsEscherichia coliBiologyBiofilmCelluloseGeneGenomeGeneticsMicrobiologyBacteriaBiochemistry

Abstract

fetched live from OpenAlex

The persistence of potentially hazardous bacteria is a major challenge for meat processing environments, which are conducive for biofilm formation. Marker genes/phenotypes are commonly used to differentiate biofilm forming E. coli strains from their nonbiofilm forming counterparts. We took a comparative genomic analysis approach to analyze E. coli strains that were from the same environment but were differentiated by their biofilm forming ability. A diversification of the genes involved in the biofilm formation of E. coli was observed. Even though there is a correlation on the population level between biofilm formation and the expression of curli and cellulose, uncertainties exist on the individual strain level. Novel substrate utilization and iron acquisition could contribute to the persistence of E. coli. These findings not only advance our understanding of the ecology of E. coli with respect to its persistence but also show that a marker gene/phenotype driven approach for the biofilm control of E. coli may not be prudent.

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 score0.060
Threshold uncertainty score0.402

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)0.0000.000

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 head0.030
GPT teacher head0.250
Teacher spread0.220 · 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

Citations10
Published2023
Admission routes2
Has abstractyes

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