The Metabolic Regulation of Sporulation and Parasporal Crystal Formation in Bacillus thuringiensis Revealed by Transcriptomics and Proteomics
Bibliographic record
Abstract
Bacillus thuringiensis is a well-known entomopathogenic bacterium used worldwide as an environmentally compatible biopesticide. During sporulation, B. thuringiensis accumulates a large number of parasporal crystals consisting of insecticidal crystal proteins (ICPs) that can account for nearly 20-30% of the cell's dry weight. However, the metabolic regulation mechanisms of ICP synthesis remain to be elucidated. In this study, the combined efforts in transcriptomics and proteomics mainly uncovered the following 6 metabolic regulation mechanisms: (1) proteases and the amino acid metabolism (particularly, the branched-chain amino acids) became more active during sporulation; (2) stored poly-β-hydroxybutyrate and acetoin, together with some low-quality substances provided considerable carbon and energy sources for sporulation and parasporal crystal formation; (3) the pentose phosphate shunt demonstrated an interesting regulation mechanism involving gluconate when CT-43 cells were grown in GYS medium; (4) the tricarboxylic acid cycle was significantly modified during sporulation; (5) an obvious increase in the quantitative levels of enzymes and cytochromes involved in energy production via the electron transport system was observed; (6) most F0F1-ATPase subunits were remarkably up-regulated during sporulation. This study, for the first time, systematically reveals the metabolic regulation mechanisms involved in the supply of amino acids, carbon substances, and energy for B. thuringiensis spore and parasporal crystal formation at both the transcriptional and translational levels.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".