Plant microbiome analysis after Metarhizium amendment reveals increases in abundance of plant growth-promoting organisms and maintenance of disease-suppressive soil
Bibliographic record
Abstract
The microbial community in the plant rhizosphere is vital to plant productivity and disease resistance. Alterations in the composition and diversity of species within this community could be detrimental if microbes suppressing the activity of pathogens are removed. Species of the insect-pathogenic fungus, Metarhizium, commonly employed as biological control agents against crop pests, have recently been identified as plant root colonizers and provide a variety of benefits (e.g. growth promotion, drought resistance, nitrogen acquisition). However, the impact of Metarhizium amendment on the rhizosphere microbiome has yet to be elucidated. Using Illumina sequencing, we examined the community profiles (bacteria and fungi) of common bean (Phaseolus vulgaris) rhizosphere (loose soil and plant root) after amendment with M. robertsii conidia, in the presence and absence of an insect host. Although alpha diversity was not significantly affected overall, there were numerous examples of plant growth-promoting organisms that significantly increased with Metarhizium amendment (Bradyrhizobium, Flavobacterium, Chaetomium, Trichoderma). Specifically, the abundance of Bradyrhizobium, a group of nitrogen-fixing bacteria, was confirmed to be increased using a qPCR assay with genus-specific primers. In addition, the ability of the microbiome to suppress the activity of a known bean root pathogen was assessed. The development of disease symptoms after application with Fusarium solani f. sp. phaseoli was visible in the hypocotyl and upper root of plants grown in sterilized soil but was suppressed during growth in microbiome soil and soil treated with M. robertsii. Successful amendment of agricultural soils with biocontrol agents such as Metarhizium necessitates a comprehensive understanding of the effects on the diversity of the rhizosphere microbiome. Such research is fundamentally important towards sustainable agricultural practices to improve overall plant health and productivity.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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".