Determining the environmental fate of a filamentous fungus,<i>Trichoderma reesei</i>, in laboratory-contained intact soil-core microcosms using competitive PCR and viability plating
Bibliographic record
Abstract
Trichoderma spp. are used extensively in industry and are routinely disposed of in landfill sites as spent biomass from fermentation plants. However, little is known regarding the environmental fate of this biomass. We tracked the survival of T. reesei strain QM6A#4 (a derivative of strain QM6A marked with a recombinant construct) over a 6-month period in laboratory-contained, intact soil-core microcosms incubated in a growth chamber. Survival was tested in 3 different soils and the effect of a plant rhizosphere (bush lima beans, Phaseolus limensis) was investigated. Levels and viability of the fungus were determined, respectively, by quantitative competitive polymerase chain reaction analysis of total soil DNA extracts and dilution-plating of soil on a semiselective growth medium. Whereas chemically killed QM6A#4 became undetectable within 3 d, QM6A#4 added as a live inoculum decreased approximately 4- to approximately 160-fold over the first 1-3 months and then reached a steady state. After 4 months, soil cores were subjected to a 1.5-month simulated winter period, which did not significantly affect QM6A#4 levels. Throughout the experiment, QM6A#4 remained viable. These results indicate that, following release into the environment, live T. reesei will persist in soil for at least 2 seasons.
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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 | 0.001 | 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".