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Record W3025162606 · doi:10.1101/2020.05.12.089201

Structures of the stator complex that drives rotation of the bacterial flagellum

2020· preprint· en· W3025162606 on OpenAlexafffund
Justin C. Deme, Steven Johnson, Owen N. Vickery, Amy Muellbauer, Holly Monkhouse, Thomas Griffiths, Rory Hennell James, Ben C. Berks, James W. Coulton, Phillip J. Stansfeld, Susan M. Lea

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2020
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Genetics and Biotechnology
Canadian institutionsUniversité de MontréalMcGill University
FundersBiotechnology and Biological Sciences Research CouncilEngineering and Physical Sciences Research CouncilCanadian Institutes of Health ResearchMedical Research CouncilWolfson FoundationWellcome Trust
KeywordsFlagellumStatorRotor (electric)PropellerRotation (mathematics)Protein subunitTorqueMembranePhysicsChemistryBiophysicsBiologyEngineeringComputer scienceBiochemistry

Abstract

fetched live from OpenAlex

Summary The bacterial flagellum is the proto-typical protein nanomachine and comprises a rotating helical propeller attached to a membrane-embedded motor complex 1 . The motor consists of a central rotor surround by stator units that couple ion flow across the cytoplasmic membrane to torque generation. Here we present the structures of stator complexes from multiple bacterial species, allowing interpretation of the extensive body of data on stator mechanism. The structures reveal an unexpected asymmetric A 5 B 2 subunit assembly in which the five A subunits enclose the two B subunits. Comparison to novel structures of other ion-driven motors indicates that this A 5 B 2 architecture is fundamental to bacterial systems that couple energy from ion-flow to generate mechanical work at a distance, and suggests that such events involve rotation in the motor structures.

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 score0.167
Threshold uncertainty score0.929

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 science0.0010.001
Research integrity0.0010.000
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 head0.015
GPT teacher head0.212
Teacher spread0.197 · 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

Citations23
Published2020
Admission routes2
Has abstractyes

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