Cotton Leaf Curl Disease Suppression by Interspecies Microbiome Transplantation
Bibliographic record
Abstract
Abstract Background Begomovirus, the causative agent of the Cotton Leaf Curl Disease (CLCuD), has been corrupting cotton yield, quality, and production throughout the world since its first outbreak in 1912. The cotton crop, the “white gold” of Pakistan, has been plucked by various biotic stresses including Cotton Leaf Curl Virus (CLCuV), amounting the production loss of the crop to almost half in the past ten years. Although several breeding attempts have been made to develop cotton lines tolerant to CLCuD, the mutation rate of CLCuV remains too high to allow permanent tolerance to any developed cultivar. In this study, the plant microbiome is proposed as a favorable environmental and economy friendly alternative to induce CLCuD suppression in the CLCuD-susceptible specie Gossypium hirsutum. The study employed the microbiome of the naturally immune diploid species of cotton, Gossypium arboreum, as a hub of diverse bacterial community. Both the rhizospheric and phyllospheric microbiotas of G. hirsutum (PFV1 and PFV2) and G. arboreum (FDH228) species with varying tolerance levels to CLCuD were isolated. The rhizospheric and phyllospheric microbiotas were termed as Microbial Fractions (MFs) and were transplanted to young G. hirsutum and G. arboreum seedlings, with null microbiota development, through soil drench method. Salicylic Acid (SA), a known plant phytohormone with defense-inducing properties, was also applied to a positive control group through foliar spray method. Results Most prominent CLCuD suppression was recorded through disease incidence assays in G. hirsutum varieties transplanted with rhizospheric MFs successively from FDH228 (RMF), PFV1 (pRMF) and PFV2 (SMF). The phyllospheric MFs also suppressed CLCuD but to a lesser extent as compared to rhizospheric MFs. The findings laid by disease incidence assays have been further supported with Illumina MiSeq 16S rRNA gene sequence analysis for microbial diversity of the MF samples and corresponding associated pathways. The results strongly demonstrate distinct bacteriomes of the cotton species governed by relative CLCuD tolerance levels. Conclusions A strong practical foundation is laid to present the role of plant microbiome in CLCuD suppression and remains the first attempt to elucidate this against a viral disease. Microbiome transplantation can contribute to the advancement of sustainable agriculture.
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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 | 0.000 | 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 | 0.001 |
| 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".