Enhanced Exoelectrogenic Activity of Cupriavidus metallidurans in Bioelectrochemical Systems through the Expression of a Constitutively Active Diguanylate Cyclase
Bibliographic record
Abstract
Electroactive bacteria have a wide range of applications, including electricity production, bioremediation, and the sensing of toxic compounds. Bacterial biofilm formation is often mediated by the second messenger cyclic guanosine monophosphate (c-di-GMP) synthesized by a diguanylate cyclase (DGC). The role of c-di-GMP in the expression of c-type cytochromes has been previously reported. The aim of this study was to determine the bioelectrogenic activity of Cupriavidus metallidurans strain CH34 pJBpleD*, which possesses a constitutively active DGC that increases c-di-GMP levels. Notably, the heterologous expression of the constitutively active DGC in C. metallidurans strain CH34 pJBpleD* showed a higher biofilm formation and increased the electrical current production up to 560%. In addition, C. metallidurans CH34 pJBpleD* showed increased levels of c-type cytochrome-associated transcripts compared with the wild-type strain CH34. Scanning electron microscopies revealed a denser extracellular matrix with an increased exopolymeric substance content in the CH34 pJBpleD* biofilm on the electrode surface. The results of this study suggest that higher levels of c-di-GMP synthesized by a constitutively active diguanylate cyclase in C. metallidurans strain CH34 pJBpleD* activated the formation of an electroactive biofilm on the electrode, enhancing its exoelectrogenic activity.
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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".