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Record W4321104292 · doi:10.1101/2023.02.15.528749

Endocytosis is regulated through the pH-dependent phosphorylation of Rab GTPases by Parkinson’s kinase LRRK2

2023· preprint· en· W4321104292 on OpenAlexaff
Michelle E. Maxson, Kassidy K. Huynh, Sergio Grinstein

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2023
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular transport and secretion
Canadian institutionsUniversity of TorontoHospital for Sick Children
Fundersnot available
KeywordsRabGTPaseCell biologyEndocytic cycleVacuoleBiologyEndocytosisPhosphorylationLRRK2KinaseChemistryBiochemistryCytoplasmMutation

Abstract

fetched live from OpenAlex

ABSTRACT While it has been known for decades that luminal acidification is required for normal traffic along the endocytic pathway, the precise underlying mechanism(s) remain unknown. We found that dissipation of the endomembrane pH gradient resulted in acute formation of large Rab5- or Rab7-positive vacuoles. Vacuole formation was associated with and required hyperactivation of the Rabs, which was attributable to impaired GTPase activity, despite normal recruitment of cognate GAPs. Surprisingly, LRRK2 –a kinase linked to Parkinson’s disease–was recruited to endomembranes and markedly activated upon dissipation of luminal acidification. LRRK2 phosphorylated Rab GTPases, rendering them insensitive to deactivation. Importantly, genetic deletion of LRRK2 prevented the ΔpH-induced vacuolation, implying that the kinase is required to modulate vesicular traffic. We propose that by dictating the state of activation of LRRK2 and in turn that of Rab GTPases, the development of a progressive luminal acidification serves as a timing device to control endocytic maturation.

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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.014
GPT teacher head0.217
Teacher spread0.202 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)→Same topicCellular transport and secretion→French-language works237,207→