The AppA and PpsR Proteins from <i>Rhodobacter sphaeroides</i> Can Establish a Redox-Dependent Signal Chain but Fail To Transmit Blue-Light Signals in Other Bacteria
Bibliographic record
Abstract
The AppA protein of Rhodobacter sphaeroides has the unique ability to sense and transmit redox and light signals. In response to decreasing oxygen tension, AppA antagonizes the transcriptional regulator PpsR, which represses the expression of photosynthesis genes, including the puc operon. This mechanism, which is based on direct protein-protein interaction, is prevented by blue-light absorption of the BLUF domain located in the N-terminal part of AppA. In order to test whether AppA and PpsR are sufficient to transmit redox and light signals, we expressed these proteins in three different bacterial species and monitored oxygen- and blue-light-dependent puc expression either directly or by using a luciferase-based reporter construct. The AppA/PpsR system could mediate redox-dependent gene expression in the alphaproteobacteria Rhodobacter capsulatus and Paracoccus denitrificans but not in the gammaproteobacterium Escherichia coli. Analysis of a prrA mutant strain of R. sphaeroides strongly suggests that light-dependent gene expression requires a balanced interplay of the AppA/PpsR system with the PrrA response regulator. Therefore, the AppA/PpsR system was unable to establish light signaling in other bacteria. Based on our data, we present a model for the interdependence of AppA/PpsR signaling and the PrrA transcriptional activator.
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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) | 0.000 | 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".