Dissecting Community Structure in Wild Blueberry Root and Soil Microbiome
Bibliographic record
Abstract
A complex network of functions and symbiotic interactions between a eukaryotic host and its microbiome is a the foundation of the ecological unit holobiont. However, little is known about how the non-fungal eukaryotic microorganisms fit in this complex network of host-microbiome interactions. In this study, we employed a unique wild blueberry ecosystem to evaluate plant-associated microbiota, encompassing both eukaryotic and bacterial communities. We found that, while soil microbiome serves as a foundation for root microbiome, plant-influenced species sorting had stronger effect on eukaryotes than on bacteria. Our study identified several fungal and protist taxa, which are correlated with decreased fruit production in wild blueberry agricultural ecosystems. The specific effect of species sorting in root microbiome resulted in an increase in relative abundance of fungi adapted to plant-associated life-style, while the relative abundance of non-fungal eukaryotes was decreased along the soil-endosphere continuum in the root, probably because of low adaptation of these microorganisms to host-plant defense responses. Analysis of community correlation networks indicated that bacterial and eukaryotic interactions became more complex along the soil-endosphere continuum and, in addition to extensive mutualistic interactions, co-exclusion also played an important role in shaping wild blueberry associated microbiome. Our study identified several potential hub taxa with important roles in soil fertility and/or plant-microbe interaction, suggesting the key role of these taxa in the interconnection between soils and plant health and overall microbial community structure. This study also provides a comprehensive view of the role of non-fungal eukaryotes in soil ecosystem.
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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".