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Record W2884390408 · doi:10.1083/jcb.201804111

Competitive organelle-specific adaptors recruit Vps13 to membrane contact sites

2018· article· en· W2884390408 on OpenAlexafffund
Björn D. M. Bean, Samantha K. Dziurdzik, Kathleen Kolehmainen, Claire Fowler, Waldan K. Kwong, Leslie I. Grad, Michael Davey, Cayetana Schluter, Elizabeth Conibear

Bibliographic record

VenueThe Journal of Cell Biology · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPhotosynthetic Processes and Mechanisms
Canadian institutionsBC Children's HospitalUniversity of British Columbia
FundersCanadian Institutes of Health ResearchCanada Foundation for Innovation
KeywordsCell biologySignal transducing adaptor proteinSorting nexinEndosomeOrganelleBiologyTransport proteinMembraneVacuoleCytoplasmSignal transductionBiochemistry

Abstract

fetched live from OpenAlex

The regulated expansion of membrane contact sites, which mediate the nonvesicular exchange of lipids between organelles, requires the recruitment of additional contact site proteins. Yeast Vps13 dynamically localizes to membrane contacts that connect the ER, mitochondria, endosomes, and vacuoles and is recruited to the prospore membrane in meiosis, but its targeting mechanism is unclear. In this study, we identify the sorting nexin Ypt35 as a novel adaptor that recruits Vps13 to endosomal and vacuolar membranes. We characterize an interaction motif in the Ypt35 N terminus and identify related motifs in the prospore membrane adaptor Spo71 and the mitochondrial membrane protein Mcp1. We find that Mcp1 is a mitochondrial adaptor for Vps13, and the Vps13-Mcp1 interaction, but not Ypt35, is required when ER-mitochondria contacts are lost. All three adaptors compete for binding to a conserved six-repeat region of Vps13 implicated in human disease. Our results support a competition-based model for regulating Vps13 localization at cellular membranes.

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 score0.003
Threshold uncertainty score0.012

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 communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.017
GPT teacher head0.251
Teacher spread0.233 · 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

Citations157
Published2018
Admission routes2
Has abstractyes

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