Metabolic engineering of the non-conventional yeast Kluyveromyces marxianus for enhancing the biosynthesis of succinic acid
Bibliographic record
Abstract
Succinic acid is a crucial four-carbon dicarboxylic acid with widespread applications in the detergent, food, and pharmaceutical industries. However, its microbial production on a large scale is limited by the utilization of neutralizing agents and high cooling costs. In this study, we conducted metabolic engineering of the thermotolerant and acid-tolerant yeast Kluyveromyces marxianus to facilitate the efficient biosynthesis of succinic acid at high temperature and low pH. A robust genetic manipulation platform for K. marxianus was established by developing gene editing tools, characterizing neutral integration sites, and identifying endogenous promoters. Leveraging this efficient platform, we systematically constructed and optimized the biosynthetic pathway of succinic acid through many metabolic engineering strategies, such as the knockout of byproduct pathways, the redistribution of carbon flux, and the enhancement of the succinic acid transport system. Finally, the engineered strain K. marxianus KmSA12 was able to produce 50.6 g/L succinic acid with a yield of 0.31 g/g and productivity of 0.42 g/L/h in a 5-L bioreactor. These results demonstrate the potential of K. marxianus as a promising platform for the large-scale production of various organic acids.
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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) | 0.001 | 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 | 0.001 |
| 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".