Oxygen-independent disulfide bond formation in VEGF-A and CA9
Bibliographic record
Abstract
Low levels of oxygen (hypoxia) occurs in many (patho)physiological situations. Adaptation to hypoxia is in part mediated by proteins expressed in the extracellular space that mature in the endoplasmic reticulum (ER) prior to traversing the secretory pathway. The majority of such ER cargo proteins require disulfide bonds for structural stability. Disulfide bonds are formed co- and posttranslationally in a redox relay that requires a terminal electron acceptor such as oxygen. We have previously demonstrated that some ER cargo proteins such as low-density lipoprotein receptor (LDLR) and influenza hemagglutinin (Flu-HA) are unable to complete disulfide bond formation in the absence of oxygen, limiting their ability to pass ER quality control and their ultimate expression. Here, using radioactive pulse-chase immunoprecipitation analysis, we demonstrate that hypoxia-induced ER cargo proteins such as carbonic anhydrase 9 (CA9) and vascular endothelial growth factor A (VEGF-A) complete disulfide bond formation and mature with similar kinetics under hypoxia and normoxia. A global in silico analysis of ER cargo revealed that hypoxia-induced proteins on average contain fewer free cysteines and shorter-range disulfide bonds in comparison to other ER cargo proteins. These data demonstrate the existence of alternative electron acceptors to oxygen for disulfide bond formation in cellulo. However, the ability of different proteins to utilize an oxygen-independent pathway for disulfide bond formation varies widely, contributing to differential gene expression in hypoxia. The superior ability of hypoxia-induced proteins such as VEGF-A and CA9 to mature in hypoxia may be conferred by a simpler disulfide architecture.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".