Increased expression of β-glucosidase A in Clostridium thermocellum 27405 significantly increases cellulase activity
Bibliographic record
Abstract
β-glucosidase A (bglA) in Clostridium thermocellum 27405 was increased by expression from shuttle vector pIBglA in attempts to increase cellulase activity and ethanol titer by lowering the end product inhibition of cellulase. Through a modified electrotransformation protocol C. thermocellum transformant (+MCbglA) harbouring pIBglA was produced. The β-glucosidase activity of +MCbglA was 2.3- and 1.6-fold greater than wild-type (WT) during late log and stationary phases of growth. Similarly, total cellulase activity of +MCbglA was shown to be 1.7-, 2.3- and 1.6-fold greater than WT during, log, late log and stationary phases of growth. However, there was no significant correlation found between increased cellulase activity and increased ethanol titers for +MCbglA compared with the WT. C. thermocellum has industrial potential for consolidated bioprocessing (CBP) to make a more cost effective production of biofuels; however, the hydrolysis rate of the strain is still hindered by end product inhibition. We successfully increased total cellulase activity by increased expression of bglA and thereby increased the productivity of C. thermocellum during the hydrolysis stage in CBP. Our work also lends insights into the complex metabolism of C. thermocellum for future improvement of this strain.
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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 | 0.000 |
| 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".