Potential Plant-to-Plant Transmission: Shared Endophytic Bacterial Community between Ziziphus lotus and its Parasite Cuscuta epithymum
Bibliographic record
Abstract
Abstract Microbiota associated with host–parasite relationships offer an opportunity to explore interactions among plants, parasites, and microbes, thereby contributing to the overall complexity of community structures. The dynamics of ecological interactions between parasitic plants and their hosts in arid environments remain largely understudied, especially in Africa. This study aimed to examine the bacterial communities of Cuscuta epithymum L. (clover dodder), an epiphytic parasitic plant, and its host, Ziziphus lotus L. (jujuba),in an arid environment. Our goal was to uncover the ecological complexities of microbial communities within the framework of plant–plant interactions. We conducted a comprehensive analysis of the bacterial composition and diversity within populations of the C. epithymum parasite, the infected- and non-infected jujuba host, and their interface at the shoots of the host. This involved amplicon sequencing, targeting the V5–V6 regions of the 16S rRNA gene. A total of 5680 amplicon sequence variants (ASVs) were identified, with Pseudomonadota, Bacillota, and Actinobacteriota being prevalent phyla. Among the bacterial communities, three genera were dominant: Cutibacterium, Staphylococcus, and Acinetobacter. Interestingly, analyses of alpha- and beta-diversities revealed no significant difference between jujuba and its parasite, suggesting a shared shoot endophytic bacteriome. This finding advances our comprehension of microbial communities linked to plant–parasite interactions in the arid environments of Africa. Further studies on functional diversity and elucidation of the mechanisms by which bacterial communities transfer between host and parasite are needed.
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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 | 0.000 |
| 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) | 0.001 | 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".