Relevance of in vitro agar based screens to characterize the anti-fungal activities of bacterial endophyte communities
Bibliographic record
Abstract
BACKGROUND: Endophytes are microbes that inhabit internal plant tissues without causing disease. Plant microbial communities consist of large numbers of endophyte species. Understanding the functions of these endophytes is a major challenge. An important function of some endophytes is to suppress fungal pathogens. Typically, plant associated microbes are screened for anti-fungal activities in vitro using the high-throughput dual culture screen, but it is not clear whether this method correlates with the activities of these microbes in planta. Furthermore, it is not clear whether in vitro screening captures all of the microbes that show this activity inside plants. The objective of this study was to evaluate the relevance of the in vitro dual culture method for screening endophytes with anti-fungal activity. RESULTS: In parallel, 190 bacterial endophytes from the corn grass family (Zea) were screened for suppression of two fungal pathogens (Sclerotinia homoeocarpa and Rhizoctonia solani) using the in vitro dual culture method, and in planta using the model plant, creeping bentgrass. All endophytes that showed anti-fungal activity in planta against Sclerotinia homoeocarpa and Rhizoctonia solani (3 or 4 strains, respectively, out of 190), were captured in vitro. The in vitro and in planta screening results strongly correlated (r = 0.81 and r = 0.94 for the two pathogens, respectively). CONCLUSIONS: Evidence was gained here that the in vitro dual culture method is a relevant method for high throughput screening of plant endophyte communities for anti-fungal activity. In our study, the method captured all of the microbes that suppressed the corresponding pathogens in planta.
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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".