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Record W2741349589 · doi:10.1002/1873-3468.12770

The type IV secretion system core component VirB8 interacts via the β1‐strand with VirB10

2017· letter· en· W2741349589 on OpenAlexafffund
Mahzad Sharifahmadian, Ingrid Um Nlend, Lauriane Lecoq, James G. Omichinski, Christian Baron

Bibliographic record

VenueFEBS Letters · 2017
Typeletter
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsUniversité de Montréal
FundersFonds de Recherche du Québec - SantéNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationCanadian Institutes of Health ResearchBristol-Myers Squibb
KeywordsSecretionChemistryCell biologyBiologyBiochemistry

Abstract

fetched live from OpenAlex

In this work, we provide evidence for the interactions between VirB8 and VirB10, two core components of the type IV secretion system (T4SS). Using nuclear magnetic resonance experiments, we identified residues on the β1-strand of Brucella VirB8 that undergo chemical shift changes in the presence of VirB10. Bacterial two-hybrid experiments confirm the importance of the β1-strand, whereas phage display experiments suggest that the α2-helix of VirB8 may also contribute to the interaction with VirB10. Conjugation assays using the VirB8 homolog TraE as a model show that several residues on the β1-strand of TraE are important for T4SS function. Together, our results suggest that the β1-strand of VirB8-like proteins is essential for their interaction with VirB10 in the T4SS complex.

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)0.002
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 score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0030.004

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 head0.013
GPT teacher head0.220
Teacher spread0.207 · 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

Citations8
Published2017
Admission routes2
Has abstractyes

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