Concurrent stimulation of diflufenican biodegradation and changes in the active microbiome in gravel revealed by Total RNA
Bibliographic record
Abstract
ABSTRACT The use of slowly degraded pesticides poses a particular problem when these are applied to urban areas such as gravel paths. The urban gravel provides an environment very different from agricultural soils; i.e., it is both lower in carbon and microbial activity. We, therefore, endeavored to stimulate the degradation of the pesticide diflufenican added to urban gravel microcosms amended with dry alfalfa to increase microbial activity. In the present study, alfalfa addition significantly increased the formation of diflufenican’s primary metabolite, 2-[3-(trifluoromethyl)phenoxy]nicotinic acid (AE-B), indicating stimulated biotransformation. The concurrent changes of the active microbial communities within the gravel were explored using shotgun metatranscriptomic sequencing of ribosomal RNA and messenger RNA. Although bacterial taxa remained dominant (87.0%–98.5% relative abundance), the alfalfa treatment led to a 4–5-fold increase in eukaryotic groups, including fungi and microbial grazers. Several microbial taxa potentially involved in the degradation of complex carbon compounds and aromatic pollutants—including Bacteroidetes , Verrucomicrobia , Sordariomycetes , Mortierellales , Tremellales, Sphingopyxis , and Phenylobacterium —increased in relative abundance following alfalfa amendment. Functional gene profiling revealed elevated expression of genes related to microbial activity and biomass production. Genes with potential roles in the breakdown of complex carbon structures (e.g., xylanases/chitin deacetylases) and in the transformation of aromatic compounds (e.g., ring-cleaving dioxygenases) were revealed. We conclude that complex carbon amendments can enhance the microbial activity, promoting the biotransformation of diflufenican in urban gravel environments. These findings provide new insights into the interactions between microbial community dynamics, gene expression profiles, and pesticide biotransformation in non-agricultural matrices. IMPORTANCE Pesticides used on urban areas, e.g., gravel paths, are likely to have different effects and fates than when these are used on agricultural soils. Hence, studies into the degradation of pesticides applied to urban matrices are needed. We have previously shown that metabolites of the persistent pesticide diflufenican are even more persistent in urban soils, and it has also previously been shown that these metabolites leach from gravel surfaces. The reasons behind this are that the urban gravel provides an environment very different from agricultural soils; i.e., it is both lower in carbon and microbial activity. In the present study, we, therefore, endeavored to stimulate the degradation of the pesticide diflufenican added to urban gravel microcosms amended with dry alfalfa to increase microbial activity, concurrently studying the changes in the active microbiome by Total RNA-metatranscriptomics.
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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".