Eukaryote-like Ser/Thr protein kinase PrkA modulates sporulation via regulating the transcriptional factor σK in Bacillus subtilis
Bibliographic record
Abstract
Protein kinase A (PrkA), also known as AMP-activated protein kinase, functions as a serine/threonine protein kinase (STPK), has been shown to be involved in a variety of important biologic processes, including pathogenesis of many important diseases in mammals. However, the biological functions of PrkA are less known in prokaryote cells. Here, we explored the function of PrkA as well as its underlying molecular mechanisms using the model bacterium Bacillus subtilis168. When PrkA is inhibited by 9-β-D-arabinofuranosyladenine (ara-A) in the wild type strain or deleted in the ΔprkA mutant strain, we observed sporulation defects in B. subtilis 168, suggesting that PrkA functions as a sporulation-related protein. Transcriptional analysis using the lacZ reporter gene demonstrated that deletion of prkA significantly reduced the expression of the transcriptional factor σ(K) and its downstream genes. Complementation of sigK gene in prkA knockout mutant partially rescued the phenotype of ΔprkA, further supporting the hypothesis that the decreased σ(K) expression should be one of the reasons for the sporulation defect resulting from prkA disruption. Finally, our data confirmed that Hpr (ScoC) negatively controlled the expression of transcriptional factor σ(K), and thus PrkA accelerated sporulation and the expression of σ(K) by suppression of Hpr (ScoC). Taken together, our study discovered a novel function of the eukaryotic-like STPK PrkA in spore development as well as its underlying molecular mechanism in B. subtilis.
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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 | 0.000 | 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".