The Microbiome of Fertilization-Stage Maize Silks (Style) Encodes Genes and Expresses Traits That Potentially Promote Survival in Pollen/Style Niches and Host Reproduction
Bibliographic record
Abstract
Within flowers, the style channel receives pollen and transmits male gametes inside elongating pollen tubes to ovules. The styles of maize/corn are called silks. Fertilization-stage silks possess complex microbiomes, which may partially derive from pollen. These microbiomes lack functional analysis. We hypothesize that fertilization-stage silk microbiomes promote host fertilization to ensure their own vertical transmission. We further hypothesize that these microbes encode traits to survive stresses within the silk (water/nitrogen limitation) and pollen (dehydration/aluminum) habitats. Here, bacteria cultured from fertilization-stage silks of 14 North American maize genotypes underwent genome mining and functional testing, which revealed osmoprotection, nitrogen-fixation, and aluminum-tolerance traits. Bacteria contained auxin biosynthesis genes, and testing confirmed indole compound secretion, which is relevant, since pollen delivers auxin to silks to stimulate egg cell maturation. Some isolates encoded biosynthetic/transport compounds known to regulate pollen tube guidance/growth. The isolates encoded ACC deaminase, which degrades the precursor for ethylene that otherwise accelerates silk senescence. The findings suggest that members of the microbiome of fertilization-stage silks encode adaptations to survive the stress conditions of silk/pollen and have the potential to express signaling compounds known to impact reproduction. Overall, whereas these microbial traits have traditionally been assumed to primarily promote vegetative plant growth, this study proposes they may also play selfish roles during host reproduction.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".