The Liver Connexin32 Interactome Is a Novel Plasma Membrane-Mitochondrial Signaling Nexus
Bibliographic record
Abstract
Connexins are the structural subunits of gap junctions and act as protein platforms for signaling complexes. Little is known about tissue-specific connexin signaling nexuses, given significant challenges associated with affinity-purifying endogenous channel complexes to the level required for interaction analyses. Here, we used multiple subcellular fractionation techniques to isolate connexin32-enriched membrane microdomains from murine liver. We show, for the first time, that connexin32 localizes to both the plasma membrane and inner mitochondrial membrane of hepatocytes. Using a combination of immunoprecipitation-high throughput mass spectrometry, reciprocal co-IP, and subcellular fractionation methodologies, we report a novel interactome validated using null mutant controls. Eighteen connexin32 interacting proteins were identified. The majority represent resident mitochondrial proteins, a minority represent plasma membrane, endoplasmic reticulum, or cytoplasmic partners. In particular, connexin32 interacts with connexin26 and the mitochondrial protein, sideroflexin-1, at the plasma membrane. Connexin32 interaction enhances connexin26 stability. Converging bioinformatic, biochemical, and confocal analyses support a role for connexin32 in transiently tethering mitochondria to connexin32-enriched plasma membrane microdomains through interaction with proteins in the outer mitochondrial membrane, including sideroflexin-1. Complex formation increases the pool of sideroflexin-1 that is present at the plasma membrane. Together, these data identify a novel plasma membrane/mitochondrial signaling nexus in the connexin32 interactome.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".