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Record W2884337696 · doi:10.3390/microorganisms6030074

Variability in Characterizing Escherichia coli from Cattle Feces: A Cautionary Tale

2018· article· en· W2884337696 on OpenAlexafffundabout
Kim Stanford, Tim Reuter, Jennyka Hallewell, Renata Tostes, Trevor W. Alexander, Tim A. McAllister

Bibliographic record

VenueMicroorganisms · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEscherichia coli research studies
Canadian institutionsAgriculture and Agri-Food Canada
FundersAlberta InnovatesAlberta Innovates Bio SolutionsAlberta Livestock and Meat Agency
KeywordsSTX2SerotypeEscherichia coliBiologyFecesMicrobiologyImmunomagnetic separationPolymerase chain reactionPrimer (cosmetics)VirulenceShiga toxinGeneChemistryGenetics

Abstract

fetched live from OpenAlex

Shiga toxin-producing Escherichia coli (STEC) are diverse bacteria, with seven serogroups (O26, O45, O103, O111, O121, O145, O157; “Top 7”) of interest due to their predominance in human disease. Confirmation of STEC relies on a combination of culturing, immunological and molecular assays, but no single gold standard for identification exists. In this study, we compared analysis of STEC between three independent laboratories (LAB) using different methodologies. In LAB A, colonies of Top 7 were picked after serogroup-specific immunomagnetic separation of feces from western-Canadian slaughter cattle. A fraction of each colony was tested by PCR (stx1, stx2, eae, O group), and Top 7 isolates were saved as glycerol stocks (n = 689). In LAB B, a subsample of isolates (n = 171) were evaluated for stx1 and stx2 using different primer sets. For this, approximately half of the PCR were performed using original DNA template provided by LAB A and half using DNA extracted from sub-cultured isolates. All Top 7 isolates were sub-cultured by LAB A and shipped to LAB C for traditional serotyping (TS) to determine O and H groups, with PCR-confirmation of virulence genes using a third set of primers. By TS, 76% of O groups (525/689) matched PCR-determined O groups. Lowest proportions (p < 0.05) of O group matches between PCR and TS (62.6% and 69.8%) occurred for O26 and O45 serogroups, respectively. PCR-detection of stx differed most between LAB A and LAB C. Excluding isolates where O groups by PCR and TS did not match, detection of stx1 was most consistent (p < 0.01) for O111 and O157:H7/NM. In contrast, for O45 and O103, stx1 was detected in >65% of isolates by LAB A and <5% by LAB C. Stx2 was only detected by LAB C in isolates of serogroups O121, O145, and O157:H7/NM. LAB B also detected stx2 in O26 and O157:H12/H29, while LAB A detected stx2 in all serogroups. Excluding O111 and O157:H7/NM, marked changes in stx detection were observed between initial isolation and sub-cultures of the same isolate. While multiple explanations exist for discordant O-typing between PCR and TS and for differences in stx detection across labs, these data suggest that assays for STEC classification may require re-evaluation and/or standardization.

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 score0.192
Threshold uncertainty score0.713

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 head0.010
GPT teacher head0.256
Teacher spread0.245 · 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

Citations8
Published2018
Admission routes3
Has abstractyes

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