Overexpression of the Transcription Factor AtLEC1 Significantly Improved the Lipid Content of Chlorella ellipsoidea
Bibliographic record
Abstract
Microalgae are considered to be a highly promising source for the production of biodiesel. However, the regulatory mechanism governing lipid biosynthesis has not been fully elucidated to date, and the improvement of lipid accumulation in microalgae is essential for the effective production of biodiesel. In this study, LEAFY COTYLEDON1 (LEC1) from Arabidopsis thaliana , a transcription factor (TF) that affects lipid content, was transferred into Chlorella ellipsoidea . Compared with wild-type (WT) strains, the total fatty acid content and total lipid content of AtLEC1 transgenic strains were significantly increased by 24.20–32.65 and 22.14–29.91%, respectively, under mixotrophic culture conditions and increased by 24.4–28.87 and 21.69–30.45%, respectively, under autotrophic conditions, while the protein content of the transgenic strains was significantly decreased by 18.23–21.44 and 12.28–18.66%, respectively, under mixotrophic and autotrophic conditions. Fortunately, the lipid and protein content variation did not affect the growth rate and biomass of transgenic strains under the two culture conditions. According to the transcriptomic data, the expression of 924 genes was significantly changed in the transgenic strain (LEC1-1). Of the 924 genes, 360 were upregulated, and 564 were downregulated. Based on qRT-PCR results, the expression profiles of key genes in the lipid synthesis pathway, such as ACCase , GPDH , PDAT1 , and DGAT1 , were significantly changed. By comparing the differentially expressed genes (DEGs) regulated by AtLEC1 in C. ellipsoidea and Arabidopsis , we observed that approximately 59% (95/160) of the genes related to lipid metabolism were upregulated in AtLEC1 transgenic Chlorella . Our research provides a means of increasing lipid content by introducing exogenous TF and presents a possible mechanism of AtLEC1 regulation of lipid accumulation in C. ellipsoidea .
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".