Effect of GFP-tagging on nitrogen fixation and plant growth promotion of an endophytic diazotrophic strain of <i>Paenibacillus polymyxa</i>
Bibliographic record
Abstract
Green fluorescent protein (GFP), a renowned marker protein, is typically believed to be inert with respect to affecting the physiology of the bacteria it occurs in. We analyzed the effects of GFP-tagging on the ability of an endophytic diazotroph, Paenibacillus polymyxa P2b-2R, to fix nitrogen and promote the overall growth of corn plants. The growth response and the amount of nitrogen fixed by P2b-2Rgfp-inoculated plants were compared with uninoculated controls and P2b-2R-inoculated plants at three harvests. P2b-2Rgfp inoculation significantly increased the biomass of corn plants as compared with non-inoculated controls and P2b-2R-treated plants. In-vitro tests revealed that strains P2b-2R and P2b-2Rgfp possess various plant-growth-promoting characteristics, namely phosphate solubilization, production of siderophores, indole acetic acid, ammonia, and enzymes such as cellulase, protease, and catalase. P2b-2Rgfp-inoculated plants fixed 18% atmospheric nitrogen, which was significantly higher than the P2b-2R-inoculated plants (15%). This difference led us to compare the expression of structural nif genes (nifH, nifD, nifK) of strains P2b-2R and P2b-2Rgfp. We observed that expression levels of structural nif genes of strain P2b-2Rgfp were 1.5-fold higher than those of strain P2b-2R. These results indicate that GFP-tagging positively affects the efficacy of strain P2b-2R with respect to promoting plant growth and fixing nitrogen, perhaps by increasing the expression levels of structural nif genes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".