MétaCan
Menu
Back to cohort
Record W2068055092 · doi:10.1002/pmic.200500523

Proteomic analysis of the binding partners to enteropathogenic <b><i>Escherichia coli</i></b> virulence proteins expressed in <b><i>Saccharomyces cerevisiae</i></b>

2006· article· en· W2068055092 on OpenAlexaff
Philip R. Hardwidge, Sam Donohoe, Ruedi Aebersold, B. Brett Finlay

Bibliographic record

VenuePROTEOMICS · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEscherichia coli research studies
Canadian institutionsCanada's Michael Smith Genome Sciences CentreUniversity of British Columbia
Fundersnot available
KeywordsVirulenceEnteropathogenic Escherichia coliBiologySaccharomyces cerevisiaeEscherichia coliMicrobiologyEffectorSecretionEukaryoteBacterial adhesinYeastGeneBiochemistryGenome

Abstract

fetched live from OpenAlex

Enteropathogenic Escherichia coli (EPEC) is an enteric human pathogen responsible for much worldwide morbidity and mortality. EPEC uses a type III secretion system to inject bacterial proteins into the cytosol of intestinal epithelial cells to cause diarrheal disease. We are interested in determining the host proteins to which EPEC translocator and effector proteins bind during infection. To facilitate protein enrichment, we created fusions between GST and EPEC virulence proteins, and expressed these fusions individually in Saccharomyces cerevisiae. The biology of S. cerevisiae is well understood and often employed as a model eukaryote to study the function of bacterial virulence factors. We isolated the yeast proteins that interact with individual EPEC proteins by affinity purifying against the GST tag. These complexes were subjected to ICAT combined with ESI-MS/MS. Database searching of sequenced peptides provided a list of proteins that bound specifically to each EPEC virulence protein. The dataset suggests several potential mammalian targets of these proteins that may guide future experimentation.

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)0.001
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 score0.020
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.012
GPT teacher head0.271
Teacher spread0.259 · 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

Citations18
Published2006
Admission routes1
Has abstractyes

Explore more

Same venuePROTEOMICSSame topicEscherichia coli research studiesFrench-language works237,207