The effect of crop species on DNase-producing bacteria in two soils
Bibliographic record
Abstract
Abstract Purpose Extracellular deoxyribonucleases (exDNases) from microbial origin contribute substantially to the restriction of extracellular DNA (exDNA) in the soil. Hence, it is imperative to understand the diversity of bacterial species capable of performing this important soil function and how crop species influence their dynamics in the soil. The present study investigates the occurrence of DNase-producing bacteria (DPB) in leachate samples obtained from soils in which the crop species of alfalfa (Medicago sativa L.), canola (Brassica napus L.), soybean (Glycine max [L.] Merr.) and wheat (Triticum aestivum L.) were raised in a growth room. Methods Selective media containing methyl green indicator was used to screen for DPB from leachate samples, whereas the 16S rRNA sequence analysis was employed to identify the isolates. Results The proportion of culturable DPB ranged between 5.72 and 40.01%; however, we did observe specific crop effects that shifted throughout the growing period. In general, higher proportions of exDNase producers were observed when the soils had lower nutrient levels. On using the 16S rRNA to classify the DPB isolates, most isolates were found to be members of the Bacillus genera, while other groups included Chryseobacterium, Fictibacillus, Flavobacterium, Microbacterium, Nubsella, Pseudomonas, Psychrobacillus, Rheinheimera, Serratia and Stenotrophomonas. Five candidate exDNase/nuclease-encoding proteins were also identified from Bacillus mycoides genomes using online databases. Conclusion Results from this study showed that crop species, growth stage and soil properties were important factors shaping the populations of DPB in leachate samples; however, soil properties seemed to have a greater influence on the trends observed on these bacterial populations. It may be possible to target soil indigenous bacteria that produce exDNases through management to decrease potential unintended effects of transgenes originating from genetically modified organisms (GMOs) or other introduced nucleic acid sequences in the environment.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".