Impact of Different Light Characteristics on the Growth and Lipid Content of Diatom <i>Phaeodactylum tricornutum</i> Transconjugant Strains
Bibliographic record
Abstract
Light regulates important metabolic processes in microalgal cells, which can further impact the metabolism and the accumulation of biomolecules such as lipids, carbohydrates, and proteins. Different characteristics of light have been studied on various strains of the model diatom Phaeodactylum tricornutum, but not on transconjugant cells and information on wild-type strains is still limited. Therefore, we studied the impact of different light characteristics such as spectral quality, light intensity and light shift on the growth, and the composition in lipids and fatty acids of P. tricornutum cells to provide a comprehensive context for future applications. Initially, we tested the impact of spectral quality and light intensity on P. tricornutum transformed with an episomal vector (Ptev), harboring the resistance gene Sh ble. Results indicated that Ptev cells accumulated more biomass and overall lipids in spectral quality Red 1 (R1: 34% > 600 nm > 66%) more effectively as compared to Red 2 (R2: 8% > 600 nm > 92%). It was also detected that cell granularity was higher in R1 as compared to R2. Furthermore, by testing two light intensities 65 μmol·m-2·s-1 and 145 μmol·m-2·s-1 light, it was observed that 145 μmol·m-2·s-1 led to an increase in growth trend, total biomass and lipid content. Combining spectral qualities and light intensities, we show that the lipid accumulation raised by 2.8-fold. Studying the light intensity and spectral quality allowed us to optimize the light conditions to R1 spectral quality and light intensity 145 μmol·m-2·s-1. These initial results showed that red light R1 at 145 μmol·m-2·s-1 was the best condition for biomass and total lipids accumulation in Ptev cells. Next, we further combined these two-light optimizations with a third light characteristics, i.e. light shift, where the cultures were shifted during the early stationary phase to a different light environment. We studied Red light shift (Rs) to investigate how light condition variations impacted P. tricornutum transconjugants Ptev and with an episomal vector containing the reporter gene YFP (PtYFP). We observed that Rs induced growth and fatty acid eicosapentaenoic acid (EPA) in Ptev as compared to PtYFP. Altogether, the study shows that red light shift of R1 at 145 μmol·m-2·s-1 promoted biomass and total lipids accumulation in Ptev and PtYFP cells. The study provides a comprehensive approach to using different light characteristics with the aim to optimize growth and lipids, as well as to fatty acid production.
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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 | 0.001 |
| 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".