A Hydroponic Co-cultivation System for Simultaneous and Systematic Analysis of Plant/Microbe Molecular Interactions and Signaling
Bibliographic record
Abstract
An experimental design mimicking natural plant-microbe interactions is very important to delineate the complex plant-microbe signaling processes. Arabidopsis thaliana-Agrobacterium tumefaciens provides an excellent model system to study bacterial pathogenesis and plant interactions. Previous studies of plant-Agrobacterium interactions have largely relied on plant cell suspension cultures, the artificial wounding of plants, or the artificial induction of microbial virulence factors or plant defenses by synthetic chemicals. However, these methods are distinct from the natural signaling in planta, where plants and microbes recognize and respond in spatial and temporal manners. This work presents a hydroponic cocultivation system where intact plants are supported by metal mesh screens and cocultivated with Agrobacterium. In this cocultivation system, no synthetic phytohormone or chemical that induces microbial virulence or plant defense is supplemented. The hydroponic cocultivation system closely resembles natural plant-microbe interactions and signaling homeostasis in planta. Plant roots can be separated from the medium containing Agrobacterium, and the signaling and responses of both the plant hosts and the interacting microbes can be investigated simultaneously and systematically. At any given timepoint/interval, plant tissues or bacteria can be harvested separately for various "omics" analyses, demonstrating the power and efficacy of this system. The hydroponic cocultivation system can be easily adapted to study: 1) the reciprocal signaling of diverse plant-microbe systems, 2) signaling between a plant host and multiple microbial species (i.e. microbial consortia or microbiomes), 3) how nutrients and chemicals are implicated in plant-microbe signaling, and 4) how microbes interact with plant hosts and contribute to plant tolerance to biotic or abiotic stresses.
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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".