Rapid and Efficient Colony-PCR for High Throughput Screening of Genetically Transformed Chlamydomonas reinhardtii
Bibliographic record
Abstract
Microalgae biotechnologies are rapidly developing into new commercial settings. Several high value products already exist on the market, and biotechnological development is focused on genetic engineering of microalgae to open up future economic opportunities for food, fuel and pharmacological production. Colony-polymerase chain reaction (colony-PCR or cPCR) is a critical method for screening genetically transformed microalgae cells. However, the ability to rapidly screen thousands of transformants using the current colony-PCR method, becomes a very laborious and time-consuming process. Herein, the non-homologous transformation of Chlamydomonas reinhardtii using the electroporation and glass beads methods generated more than seven thousand transformants. In order to manage this impressive number of clones efficiently, we developed a high-throughput screening (HTS) cPCR method to rapidly maximize the detection and selection of positively transformed clones. For this, we optimized the Chlamydomonas transformed cell layout on the culture media to improve genomic DNA extraction and cPCR in 96-well plate. The application of this optimized HTS cPCR method offers a rapid, less expensive and reliable method for the detection and selection of microalgae transformants. Our method, which saves up to 80% of the experimental time, holds promise for evaluating genetically transformed cells and selection for microalgae-based biotechnological applications such as synthetic biology and metabolic engineering.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".