Soil and seed both influence bacterial diversity in the microbiome of the Cannabis sativa seedling endosphere
Bibliographic record
Abstract
Introduction Phytobiomes have a significant impact on plant health. The microbiome of Cannabis sativa is particularly interesting both because of renewed interest in this crop and because it is commercially propagated in two different ways (i.e. clonally and by seed). Angiosperms obtain a founding population of seed-borne endophytes from their seed-bearing parent. This study examines the influence of both seed and soil-derived bacteria on the endospheres of cannabis seedlings of both hemp- and drug-types. Methods A multi-factorial metagenomic study was conducted with three cannabis genotypes and two soil sources, which were tested both before and after autoclave sterilization. Seedlings were grown on soil, then rinsed and surface-sterilized, and 16S rDNA amplicons from seedling endophytes were sequenced, taxonomically classified, and used to estimate alpha- and beta-diversity in Qiime2. The statistical significance of differences in seedling microbiomes across treatments was tested, and PiCRUST2 was used to infer the functional relevance of these differences. Results Soil was found to have a profound effect on the alpha-diversity, beta-diversity, relative abundance, and functional genes of endophytic bacteria in germinating cannabis seedlings. Additionally, there was a significant effect of cannabis genotype on beta diversity, especially when genotypes were grown in sterilized soil. Gammaproteobacteria and Bacilli were the two most abundant taxa and were found in all genotypes and soil types, including sterilized soil. Discussion The results indicated that a component of cannabis seedling endosphere microbiomes is seed-derived and conserved across the environments tested. Functional prediction of seedling endophytes using piCRUST suggested a number of important functions of seed-borne endophytes in cannabis including nutrient and amino acid cycling, hormone regulation, and as precursors to antibiotics. This study suggested both seed and soil play a critical role in shaping the microbiome of germinating cannabis seedlings.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".