Regulating Expression of Pyruvate Kinase in <i>Bacillus subtilis</i> for Control of Growth Rate and Formation of Acidic Byproducts
Bibliographic record
Abstract
Our prior work has shown that a pyk mutant of Bacillus subtilis exhibited diminished acidic byproduct accumulation, dramatically elevated phosphoenolpyruvate (PEP) pool, and reduced growth rate. To determine if a low acetate-producing but fast-growing strain of B. subtilis could be developed, we placed the expression of the pyk gene under the control of an inducible promoter. Enzyme measurements proved that PYK activity of the inducible PYK mutant (iPYK) increases with the isopropyl-beta-d-thiogalactopyranoside concentration. Batch growth experiments showed that growth rate and acid formation are closely related to the induction level of pyk. Measurements of cell growth rate and acetate formation of the iPYK mutant at different induction levels revealed that a PYK activity of about 12% of wild-type allows for good growth rate (0.4 h(-)(1) versus 0.63 h(-)(1) of wild-type) and low acetate production (0.26 g/L versus 1.05 g/L of wild-type). This is the first report to our knowledge of a metabolically engineered B. subtilis strain that allows good growth rate and low acid production in batch cultures. Finally, it was found that, by varying the pyk induction level, intracellular PEP concentration can be controlled over a wide range. The intracellular PEP concentration is intimately connected to the regulation of the transport of phosphotransferase system (PTS) sugars in the presence of glucose. Because there is no other method for modulating intracellular PEP levels, this finding represents a major advance in one's ability to dissect the function of the PTS and sugar metabolism in bacteria.
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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 | 0.001 | 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".