Impact of glyphosate and glyphosate-based herbicides on phyllospheric Methylobacterium
Bibliographic record
Abstract
Symbiotic Methylobacterium comprise a significant portion of the phyllospheric microbiome, and are known to benefit host plant growth, development, and confer tolerance to stress factors. The near ubiquitous use of the broad-spectrum herbicide, glyphosate, in farming operations globally has necessitated a more expansive evaluation of the impacts of the agent itself and formulations containing glyphosate on important components of the plant phyllosphere, including Methylobacterium.This study provides an investigation of the sensitivity of 18 strains of Methylobacterium to glyphosate and two commercially available glyphosate-based herbicides (GBH). Nearly all strains of Methylobacterium showed signs of sensitivity to the popular GBH formulations WeatherMax® and Transorb® in a modified Kirby Bauer experiment. However, exposure to pure forms of glyphosate did not show a significant effect on growth for any strain in both the Kirby Bauer test and in liquid broth, until polysorbate-20 (Tween20) was added as a surfactant. Artificially increasing membrane permeability through the introduction of polysorbate-20 caused a 78-84% reduction in bacterial cell biomass relative to controls containing glyphosate or high levels of surfactant only (0-9% and 6-37% reduction respectively). Concentrations of glyphosate as low as 0.05% w/v (500 µg/L) from both commercial formulations tested, inhibited the culturability of Methylobacterium on fresh nutrient-rich medium.To better understand the compatibility of important phyllospheric bacteria with commercial glyphosate-based herbicides, this study endeavours to characterize sensitivity in multiple strains of Methylobacterium, and explore possible mechanisms by which toxicity may be induced.
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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) | 0.002 | 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".