The dual‐coding gene <i>SLC35A4</i> protects against oxidative stress
Bibliographic record
Abstract
Alternative proteins (AltProts) represent a newly recognized class of biologically active proteins encoded from alternative open reading frames (AltORFs) within already annotated genes. This study focuses on the SLC35A4 gene, which encodes both the reference protein SLC35A4 and the alternative protein AltSLC35A4. Using a combination of microscopy and biochemical analyses, we confirmed the presence of AltSLC35A4 in the inner mitochondrial membrane, resolving previous conflicting reports. Previous studies employing ribosome profiling have revealed that during oxidative stress induced by sodium arsenite, the reference coding sequence of SLC35A4 exhibits the largest increase in translational efficiency among all cellular mRNAs. Our results confirmed this translational upregulation, with the emergence of SLC35A4 protein isoforms during oxidative stress in an upstream ORF-dependent manner. Notably, the expression of AltSLC35A4 remained unchanged during oxidative stress. Knock out of SLC35A4 or AltSLC35A4 enhanced sensitivity to oxidative stress in a rescuable manner, indicating a direct implication for these proteins in stress resistance. In conclusion, our research provides compelling evidence for the functional significance of the dual-coding nature of SLC35A4 for resistance to oxidative stress and highlights the importance of considering AltProts in the functional study of eukaryotic genes.
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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".