Genome‐wide Transcriptional Analysis of <i>Tetrahymena thermophila</i> Response to Exogenous Cholesterol
Bibliographic record
Abstract
The ciliate Tetrahymena thermophila does not require sterols for growth and synthesizes pentacyclic triterpenoid alcohols, mainly tetrahymanol, as sterol surrogates. However, when sterols are present in the environment, T. thermophila efficiently incorporates and modifies them. These modifications consist of desaturation reactions at positions C5(6), C7(8), and C22(23), and de-ethylation at C24 of 29-carbon sterols (i.e. phytosterols). Three out of four of the enzymes involved in the sterol modification pathway have been previously identified. However, identification of the sterol C22 desaturase remained elusive, as did other basic aspects of this metabolism. To get more insights into this peculiar metabolism, we here perform a whole transcriptome analysis of T. thermophila in response to exogenous cholesterol. We found 356 T. thermophila genes to be differentially expressed after supplementation with cholesterol for 2 h. Among those that were upregulated, we found two genes belonging to the long spacing family of desaturases that we tentatively identified by RNAi analysis as sterol C22 desaturases. Additionally, we determined that the inhibition of tetrahymanol synthesis after supplementation with cholesterol occurs by a transcriptional downregulation of genes involved in squalene synthesis and cyclization. Finally, we identified several uncharacterized genes that are likely involved in sterols transport and signaling.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".