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Record W4301394708 · doi:10.1016/j.celrep.2022.111442

MICAL1 activation by PAK1 mediates actin filament disassembly

2022· article· en· W4301394708 on OpenAlexafffund
David J. McGarry, Giovanni Francesco Castino, Sérgio Lilla, Alexandre Carnet, Loughlin Kelly, Katarina Micovic, Sara Zanivan, Michael F. Olson

Bibliographic record

VenueCell Reports · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular Mechanics and Interactions
Canadian institutionsToronto Metropolitan University
FundersMedical Research CouncilCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaCancer Research UK
KeywordsPAK1GTPaseCell biologyPhosphorylationCDC42RabActin cytoskeletonActinBiologyCytoskeletonGTPase-activating proteinActin remodelingSignal transductionChemistryBiochemistryG proteinCell

Abstract

fetched live from OpenAlex

The MICAL1 monooxygenase is an important regulator of filamentous actin (F-actin) structures. Although MICAL1 has been shown to be regulated via protein-protein interactions at the autoinhibitory carboxyl terminus, a link between actin-regulatory RHO GTPase signaling pathways and MICAL1 has not been established. We show that the CDC42 GTPase effector PAK1 associates with and phosphorylates MICAL1 on two serine residues, leading to accelerated F-actin disassembly. PAK1 binds to the amino-terminal catalytic monooxygenase and calponin homology domains, distinct from the autoinhibitory carboxyl terminus. Extracellular ligand stimulation leads to PAK-dependent phosphorylation, linking external signals to MICAL1 phosphorylation. Mass spectrometry indicates that MICAL1 co-expression with CDC42 and PAK1 increases MICAL1 association with hundreds of proteins, including the previously described MICAL1-interacting proteins RAB10 and RAB7A. These results provide insights into a redox-mediated pathway linking extracellular signals to cytoskeleton regulation via a RHO GTPase and indicate a means of communication between RHO and RAB GTPases.

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 score0.332
Threshold uncertainty score0.538

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 head0.006
GPT teacher head0.221
Teacher spread0.215 · 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

Citations26
Published2022
Admission routes2
Has abstractyes

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