Fantastic yeasts and where to find them : a study of Saccharmyces cerevisiae strain diversity and proteome dynamics in application to recombinant production of laccase enzymes
Bibliographic record
Abstract
Saccharomyces cerevisiae is a widely utilized host cell for recombinant protein production owing to its extensive knowledge base, ability to secrete large and post-translationally modified proteins, fast growth and cost-effective culturing. However, recombinant protein yields from S. cerevisiae often fall behind other host systems. Despite the thousands of strains available, the natural diversity of S. cerevisiae has been under exploited for recombinant protein production. In this thesis, we utilize a high-throughput screen to identify strains with improved recombinant protein production capacity, then characterized them using gene-level analysis, comparative genomics and proteomics. First, we developed a high-throughput screen monitoring expression of recombinant Trametes trogii laccase from wild, industrial and laboratory strains, and used the screen to identify 9 non-laboratory strains with a higher capacity to produce active T. trogii laccase. We next examined whether higher protein yield may be a result of increased gene expression. We measured the laccase mRNA levels in the identified strains using RT-qPCR. Interestingly, lower levels of laccase mRNA were measured in most cases, indicating that the drivers of elevated protein production capacity lie beyond the regulation of mRNA levels. We then utilized comparative gene analysis to identify genes which may contribute to improved laccase expression. From this, we successfully identified several genes which improved laccase expression when deleted in a lab strain. To better understand how recombinant protein expression impacts the proteome, we utilized mass spectrometry to identify differences in the proteome composition of a lab strain and a subset of non-lab strains, when expressing laccase versus not. Several hundred proteins were differentially expressed, and bioinformatic analysis of those proteins revealed key pathways altered during laccase expression. Notably, we observed a decrease in sugar uptake but an increase in carbon metabolism related to use of fatty acids as a carbon source, indicating a shift in metabolism. Collectively, this thesis identified S. cerevisiae strains with improved laccase production capacity using a novel high-throughput screen and provides insight into how different yeast strains adapt to recombinant laccase expression. This work provides a platform to discover new strains for recombinant protein production and for engineering to improve existing strains.
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 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".