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Record W1529175255 · doi:10.1113/jphysiol.2014.280636

Charge at the 46th residue of connexin 50 is crucial for the gap‐junctional unitary conductance and transjunctional voltage‐dependent gating

2014· article· en· W1529175255 on OpenAlexaff
Xiaoling Tong, Hiroshi Aoyama, Tomitake Tsukihara, Donglin Bai

Bibliographic record

VenueThe Journal of Physiology · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnexins and lens biology
Canadian institutionsWestern University
Fundersnot available
KeywordsConnexinGatingConductanceGap junctionChemistryBiophysicsCharge (physics)Residue (chemistry)PhysicsBiologyIntracellularCondensed matter physicsBiochemistryQuantum mechanics

Abstract

fetched live from OpenAlex

Key points Gap‐junction (GJ) channels provide direct intercellular communication and are twice the length of most membrane channels, yet they often have high efficiency in permeation of ions, which is reflected by large unitary channel conductance (γj). To reveal the key factors in determining the γj of a lens GJ channel, we studied connexin 50 mutant GJ channels, where a negatively or positively charged residue was introduced into a pore‐lining domain. The results indicate that the pore surface electrostatic potential is a dictating factor for the connexin 50 GJ channel γj. A change in the local resistance of the channel pore associated with these mutant channels is an important factor for their voltage‐dependent gating properties. The combination of dual patch clamp and homology structure modelling is a powerful approach in revealing molecular mechanisms of GJ gating and ion permeation. Abstract Gap‐junction (GJ) channels are twice the length of most membrane channels, yet they often have large unitary channel conductance (γj). What factors make this possibly the longest channel so efficient in passing ions are not fully clear. Here we studied the lens connexin (Cx) 50 GJs, which display one of the largest γj and the most sensitive transjunctional voltage‐dependent gating (Vj gating) among all GJ channels. Introduction of charged residues into a putative pore‐lining domain (the first transmembrane and the first extracellular loop border) drastically altered the apparent γj. Specifically, G46D and G46E increased the Cx50 γj from 201 to 256 and 293 pS, respectively and the G46K channel showed an apparent γj of only 20 pS. G46K also drastically altered Vj gating properties in homotypic G46K and heterotypic Cx50/G46K channels, causing an apparent loss of fast Vj‐dependent gating transitions and leaving only loop gating transitions at the single channel current records. Both macroscopic and single channel currents of heterotypic Cx50/G46K channels showed a prominent rectification. Our homology structural models indicate that the pore surface electrostatic potentials are a dictating factor in determining the γj. Our data demonstrate, at the whole GJ channel level, a crucial role of the surface charge properties in the first transmembrane/first extracellular border domain in determining the efficiency of ion permeation and the Vj gating of Cx50 and possibly other GJ channels.

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 score0.002
Threshold uncertainty score0.005

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)0.0020.000

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 head0.019
GPT teacher head0.250
Teacher spread0.231 · 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

Citations29
Published2014
Admission routes1
Has abstractyes

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