Molecular Evolution of the Nuclear Factor (Erythroid-Derived 2)-Like 2 Gene Nrf2 in Old World Fruit Bats (Chiroptera: Pteropodidae)
Bibliographic record
Abstract
Mammals developed antioxidant systems to defend against oxidative damage in their daily life. Enzymatic antioxidants and low molecular weight antioxidants (LMWAs) constitute major parts of the antioxidant systems. Nuclear factor (erythroid-derived 2)-like 2 (Nrf2, encoded by the Nrf2 gene) is a central transcriptional regulator, regulating transcription, of many antioxidant enzymes. Frugivorous bats eat large amounts of fruits that contain high levels of LMWAs such as vitamin C, thus, a reliance on LMWAs might greatly reduce the need for antioxidant enzymes in comparison to insectivorous bats. Therefore, it is possible that frugivorous bats have a reduced need for Nrf2 function due to their substantial intake of diet-antioxidants. To test whether the Nrf2 gene has undergone relaxed evolution in fruit-eating bats, we obtained Nrf2 sequences from 16 species of bats, including four Old World fruit bats (Pteropodidae) and one New World fruit bat (Phyllostomidae). Our molecular evolutionary analyses revealed changes in the selection pressure acting on Nrf2 gene and identified seven specific amino acid substitutions that occurred on the ancestral lineage leading to Old World fruit bats. Biochemical experiments were conducted to examine Nrf2 in Old World fruit bats and showed that the amount of catalase, which is regulated by Nrf2, was significantly lower in the brain, heart and liver of Old World fruit bats despite higher levels of Nrf2 protein in Old World fruit bats. Computational predictions suggest that three of these seven amino acid replacements might be deleterious to Nrf2 function. Therefore, the results suggest that Nrf2 gene might have experienced relaxed constraint in Old World fruit bats, however, we cannot rule out the possibility of positive selection. Our study provides the first data on the molecular adaptation of Nrf2 gene in frugivorous bats in compensation to the increased levels of LWMAs from their fruit-diet.
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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".