Acid protease production in fungal root endophytes
Bibliographic record
Abstract
Fungal endophytes are ubiquitous in healthy root tissue, but little is known about their ecosystem functions, including their ability to utilize organic nutrient sources such as proteins. Root-associated fungi may secrete proteases to access the carbon and mineral nutrients within proteins in the soil or in the cells of their plant host. We compared the protein utilization patterns of multiple isolates of the root endophytes Phialocephala fortinii s.l., Meliniomyces variabilis and Umbelopsis isabellina with those of two ectomycorrhizal (ECM) fungi, Hebeloma incarnatulum and Laccaria bicolor, and the wood-decay fungus Irpex lacteus at pH values of 2-9 on liquid BSA media. We also assessed protease activity using a fluorescently labeled casein assay and gelatin zymography and characterized proteases using specific protease inhibitors. I. lacteus and U. isabellina utilized protein efficiently, while the ECM fungi exhibited poor protein utilization. ECM fungi secreted metallo-proteases and had pH optima above 4, while other fungi produced aspartic proteases with lower pH optima. The ascomycetous root endophytes M. variabilis and P. fortinii exhibited intermediate levels of protein utilization and M. variabilis exhibited a very low pH optimum. Comparing proteolytic profiles between fungal root endophytes and fungi with well defined ecological roles provides insight into the ecology of these cryptic root associates.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 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".