A mitochondrial electron transport chain with atypical subunit composition confers oxygen sensitivity to a mammalian chemoreceptor
Bibliographic record
Abstract
Abstract The carotid body (CB) is the major chemoreceptor for blood oxygen in the control of ventilation in mammals, contributing to physiological adaptation to high altitude, pregnancy, and exercise, and its hyperactivity is linked to chronic conditions such as sleep-disorder breathing, hypertension, chronic heart failure, airway constriction, and metabolic syndrome ( 1–3 ). Upon acute hypoxia (PO 2 =100 mmHg to <80 mmHg), K + channels on CB glomus cells are inhibited, causing membrane depolarization to trigger Ca +2 influx and neurotransmitter release that stimulates afferent nerves ( 1–3 ). A longstanding model proposes that the CB senses hypoxia through atypical mitochondrial electron transport chain (ETC) metabolism that is more sensitive to decreases in oxygen than other tissues. This model is supported by observations that ETC inhibition by pharmacology and gene knockout activates CB sensory activity and that smaller decreases in oxygen concentration inhibit ETC activity in CB cells compared to other cells ( 1–5 ). Determining the composition of atypical ETC subunits in the CB and their specific activities is essential to delineate molecular mechanisms underlying the mitochondrial hypothesis of oxygen sensing. Here, we identify HIGD1C, a novel hypoxia inducible gene domain factor isoform, as an ETC Complex IV (CIV) protein highly and selectively expressed in glomus cells that mediates acute oxygen sensing by the CB. We demonstrate that HIGD1C negatively regulates oxygen consumption by CIV and acts with the hypoxia-induced CIV subunit COX4I2 to enhance the sensitivity of CIV to hypoxia, constituting an important component of mitochondrial oxygen sensing in the CB. Determining how HIGD1C and other atypical CIV proteins expressed in the CB work together to confer exquisite oxygen sensing to the ETC will help us better understand how tissue- and condition-specific CIV subunits contribute to physiological function and disease ( 6 ) and allow us to potentially target these proteins to treat chronic diseases characterized by CB dysfunction ( 7 ).
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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) | 0.001 | 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".