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Cleavage of preflagellins by an aspartic acid signal peptidase is essential for flagellation in the archaeon <i>Methanococcus voltae</i>

2003· article· en· W2171476409 on OpenAlexaff
Sonia L. Bardy, Ken F. Jarrell

Bibliographic record

VenueMolecular Microbiology · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtist diversity and phylogeny
Canadian institutionsQueen's University
Fundersnot available
KeywordsBiologyFlagellumMethanococcusFlagellinMutantPilusBiochemistrySignal peptidaseSignal peptidePeptide sequenceEscherichia coliGene

Abstract

fetched live from OpenAlex

The differences between archaeal and bacterial flagella are becoming more apparent as research on the archaeal structure progresses. One crucial difference is the presence of a leader peptide on archaeal preflagellins, which is removed from the flagellin prior to its incorporation into the flagellar filament. The enzyme responsible for the removal of the flagellin leader peptide was identified as FlaK. FlaK of Methanococcus voltae retains its preflagellin peptidase activity when expressed in Escherichia coli and used in an in vitro assay. Homologous recombination of an integration vector into the chromosomal copy of flaK resulted in a non-motile, non-flagellated phenotype. The flagellins of the mutant had larger molecular weights than their wild-type counterparts, as expected if they retained their 11- to 12-amino-acid leader peptide. Membranes of the flaK mutant were unable to process preflagellin in the in vitro assay. Site-directed mutagenesis demonstrated that two aspartic acid residues conserved with ones in type IV prepilin peptidases were necessary for proper recognition or processing of the preflagellin. As bacterial flagellins lack a leader peptide and a peptidase is not required for export and assembly, the requirement for FlaK further emphasizes the similarity archaeal flagella have with type IV pili, rather than with bacterial flagella.

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 score0.040
Threshold uncertainty score0.613

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 head0.008
GPT teacher head0.236
Teacher spread0.228 · 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

Citations118
Published2003
Admission routes1
Has abstractyes

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