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Record W2111809875 · doi:10.1186/1471-2121-4-11

Chlamydomonas fla mutants reveal a link between deflagellation and intraflagellar transport

2003· article· en· W2111809875 on OpenAlexafffund
Jeremy Parker, Lynne M. Quarmby

Bibliographic record

VenueBMC Cell Biology · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and Kidney Cyst Diseases
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFlagellumIntraflagellar transportChlamydomonasAxonemeCiliumCell biologyBiologyMutantMicrotubuleGeneticsGene

Abstract

fetched live from OpenAlex

BACKGROUND: Cilia and flagella are often lost in anticipation of mitosis or in response to stress. There are two ways that a cell can lose its flagella: resorption or deflagellation. Deflagellation involves active severing of the axoneme at the base of the flagellum; this process is defective in Chlamydomonas fa mutants. In contrast, resorption has been thought to occur as a consequence of constitutive disassembly at the tip in the absence of continued assembly, which requires intraflagellar transport (IFT). Chlamydomonas fla mutants are unable to build and maintain flagella due to defects in IFT. RESULTS: fla10 cells, which are defective in kinesin-II, the anterograde IFT motor, resorb their flagella at the restrictive temperature (33 degrees C), as previously reported. We find that in standard media containing approximately 300 microM calcium, fla10 cells lose flagella by deflagellation at 33 degrees C. This temperature-induced deflagellation of a fla mutant is not predicted by the IFT-based model for flagellar length control. Other fla mutants behave similarly, losing their flagella by deflagellation instead of resorption, if adequate calcium is available. These data suggest a new model whereby flagellar resorption involves active disassembly at the base of the flagellum via a mechanism with components in common with the severing machinery of deflagellation. As predicted by this model, we discovered that deflagellation stimuli induce resorption if deflagellation is blocked either by mutation in a FA gene or by lack of calcium. Further support for this model comes from our discovery that fla10-fa double mutants resorb their flagella more slowly than fla10 mutants. CONCLUSIONS: Deflagellation of the fla10 mutant at the restrictive temperature is indicative of an active disassembly signal, which can manifest as either resorption or deflagellation. We propose that when IFT is halted by either an inactivating mutation or a cellular signal, active flagellar disassembly is initiated. This active disassembly is distinct from the constitutive disassembly which plays a role in flagellar length control.

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)0.000
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 score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.011
GPT teacher head0.233
Teacher spread0.222 · 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

Citations53
Published2003
Admission routes2
Has abstractyes

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