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Record W1893312779 · doi:10.1083/jcb.201409071

Calcium release through P2X4 activates calmodulin to promote endolysosomal membrane fusion

2015· article· en· W1893312779 on OpenAlexafffund
Qi Cao, Xi Zhong, Yuanjie Zou, Ruth D. Murrell‐Lagnado, Michael X. Zhu, Xian‐Ping Dong

Bibliographic record

VenueThe Journal of Cell Biology · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCalcium signaling and nucleotide metabolism
Canadian institutionsDalhousie University
FundersNational Institute of General Medical SciencesCanadian Institutes of Health ResearchDalhousie University
KeywordsCell biologyBiologyCalmodulinLipid bilayer fusionVacuoleAdenosine triphosphateBiochemistryMembraneCytoplasm

Abstract

fetched live from OpenAlex

Intra-endolysosomal Ca(2+) release is required for endolysosomal membrane fusion with intracellular organelles. However, the molecular mechanisms for intra-endolysosomal Ca(2+) release and the downstream Ca(2+) targets involved in the fusion remain elusive. Previously, we demonstrated that endolysosomal P2X4 forms channels activated by luminal adenosine triphosphate in a pH-dependent manner. In this paper, we show that overexpression of P2X4, as well as increasing endolysosomal P2X4 activity by alkalinization of endolysosome lumen, promoted vacuole enlargement in cells and endolysosome fusion in a cell-free assay. These effects were prevented by inhibiting P2X4, expressing a dominant-negative P2X4 mutant, and disrupting the P2X4 gene. We further show that P2X4 and calmodulin (CaM) form a complex at endolysosomal membrane where P2X4 activation recruits CaM to promote fusion and vacuolation in a Ca(2+)-dependent fashion. Moreover, P2X4 activation-triggered fusion and vacuolation were suppressed by inhibiting CaM. Our data thus suggest a new molecular mechanism for endolysosomal membrane fusion involving P2X4-mediated endolysosomal Ca(2+) release and subsequent CaM activation.

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)0.001
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 score0.099
Threshold uncertainty score0.447

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.026
GPT teacher head0.279
Teacher spread0.253 · 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

Citations136
Published2015
Admission routes2
Has abstractyes

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