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Record W4404140553 · doi:10.1128/jb.00359-24

Building permits—control of type IV pilus assembly by PilB and its cofactors

2024· review· en· W4404140553 on OpenAlexafffund
Nathan Roberge, Lori L. Burrows

Bibliographic record

VenueJournal of Bacteriology · 2024
Typereview
Languageen
FieldEnvironmental Science
TopicMicrobial Fuel Cells and Bioremediation
Canadian institutionsMcMaster University
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsBiologyPilusCofactorType (biology)MicrobiologyGeneticsBiochemistryEscherichia coliEnzymeGeneEcology

Abstract

fetched live from OpenAlex

Many bacteria produce type IV pili (T4P), surfaced-exposed protein filaments that enable cells to interact with their environment and transition from planktonic to surface-adapted states. T4P are dynamic, undergoing rapid cycles of filament extension and retraction facilitated by a complex protein nanomachine powered by cytoplasmic motor ATPases. Dedicated assembly motors drive the extension of the pilus fiber into the extracellular space, but like any machine, this process is tightly organized. These motors are coordinated by various ligands and binding partners, which control or optimize their functional associations with T4P machinery before cells commit to the crucial first step of building a pilus. This review focuses on the molecular mechanisms that regulate T4P extension motor function. We discuss secondary messenger-dependent transcriptional or post-translational regulation acting both directly on the motor and through protein effectors. We also discuss the recent discoveries of naturally occurring extension inhibitors as well as alternative mechanisms of pilus assembly and motor-dependent signaling pathways. Given that T4P are important virulence factors for many bacterial pathogens, studying these motor regulatory systems will provide new insights into T4P-dependent physiology and efficient strategies to disable them.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score0.577

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.019
GPT teacher head0.280
Teacher spread0.261 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations12
Published2024
Admission routes2
Has abstractyes

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