Thermal profiling of novel and known miRNAs during cold acclimation in Aedes aegypti
Bibliographic record
Abstract
The disease vector, Aedes aegypti, can better survive low temperature exposure following cold acclimation. This plasticity may be contributing to this species' recent range expansion. However, the molecular mechanisms behind this ability remain unexplored. MicroRNAs (miRNAs) can drive rapid changed in gene expression and are known to regulate thermal plasticity in other animals. We used a bioinformatic approach to identify three novel miRNAs in Ae. aegypti. After acclimating adult female Ae. aegypti to cold (15 °C) and warm (25 °C) conditions, we used RT-qPCR to perform differential expression analysis on these novel miRNAs and four other miRNAs downregulated during diapause in another mosquito species. Two novel miRNAs, aae-miR-novel2 and aae-miR-novel3, were upregulated in cold-acclimated individuals. Two described miRNAs associated with lipid metabolism and reproduction, aae-miR-8-3p and aae-miR-13b-3p, were downregulated in the cold-acclimated group, suggesting these processes are affected during cold acclimation. Temperature alone can alter miRNA target genes, and the thermodynamic parameters used to predict miRNA targets are typically established assuming body temperatures relevant to endotherms, rather than those applying to poikilothermic ectotherms. Here, we instead tested for cold-influenced targets of miRNAs of interest, predicted to only become thermodynamically stable at 15 °C. This approach provides insight into the putative roles that these novel miRNAs could play in cold acclimation. Many predicted targets were involved in processes associated with insect low temperature survival, like ion homeostasis and membrane stability, while others suggest roles for understudied processes. Our results suggest that miRNAs play a regulatory role in mosquito thermal plasticity that deserves further attention.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".