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Record W7151331016 · doi:10.5281/zenodo.19461740

Calcium availability influences the aggregation and adhesion of Xylella fastidiosa, the causal agent of Pierce's disease in grapes

2004· article· W7151331016 on OpenAlexaff
Breno Leite, María Ishida, Brent V. Brodbeck, Lyriam L. R. Marques, Merle E Olson, M. R. Braga, Peter C. Andersen

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2004
Typearticle
Language
FieldAgricultural and Biological Sciences
TopicPhytoplasmas and Hemiptera pathogens
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsXylemXylella fastidiosaCalciumCultivarDivalentPopulationUronic acid

Abstract

fetched live from OpenAlex

Description Xylem fluid collected from the same grapevine cultivars growing in California and Florida showed significant effects of both cultivar and location on the ratio of calcium/phosphate (Ca/P) as well as pH. It has been reported that calcium bridging is critical for the aggregation and adhesion of X. fastidiosa. Our results showed that under acidic pH (5.5), calcium remains in solution as free ions and X. fastidiosa aggregation is stimulated. In contrast, in basic pH (8.0), calcium phosphate precipitates. In California plants, the Ca/P ratio is close to 1 for Vitis rotundifolia cv. Noble (resistant) and 14.5 for V. vinifera cv. Chardonnay (susceptible). Additionally, the content of acidic pectins, which bind calcium, was higher in the xylem walls of the resistant cultivar Noble. These findings suggest that calcium availability may influence vessel clogging and symptom development in Pierce´s disease. Soil type (composition) may alter the pH of xylem fluid, which in turn may influence calcium availability, thereby impacting aggregation. Results The results identify divalent ions, particularly calcium, as essential factors in the pathogenicity of X. fastidiosa. Calcium binding and calcium bridging are critical during the initial stages of microcolony and colony formation. The availability of calcium and the population density of X. fastidiosa cells within the xylem vessel influence both the quantity and size of aggregates formed. Furthermore, the host plant may regulate this process by removing Ca2+ from the xylem lumen, as observed in the resistant cultivar Noble, which exhibits a higher uronic acid content in its xylem walls. Uronic acid, a form of pectin, is recognized for its capacity to sequester calcium. The mostly negatively charged surfaces of X. fastidiosa cells play a critical role in calcium binding and bridging. The abundance of these negative moieties may correlate with the strain's pathogenicity. Furthermore, Ca2+ mediated cell aggregation could initiate the activation of additional pathogenicity pathways. Xylem fluid composition has been shown to be significant for the development of Pierce’s disease. These findings suggest that management strategies for Pierce’s disease may require a fundamentally new approach. Conclusion Our primary aim is to reestablish homeostatic balance in the host and enhance its innate defense capacity to counter Xylella fastidiosa infection. We investigate plant responses and identify environmental factors that influence xylem sap composition. We seek natural strategies to prevent biofilm formation and subsequent plant infection. Additionally, we intend to collaborate with industry partners to develop eco-friendly solutions that mitigate stress and reduce vessel clogging in plants. Future Directions Ongoing research at the University of Campinas, led by PhD candidate Ayron Andrey da Silva Lima, focuses on developing novel chemically defined media for X. fastidiosa. This work investigates how variations in medium pH influence calcium availability. Acknowledgment: This work received support in its early stages from the American Vineyard Foundation and the California Department of Food and Agriculture, and is now supported by the Nano and Biosystems Laboratory - University of Campinas - Institute of Physics, Gleb Wataghin.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.868
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.041
GPT teacher head0.240
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2004
Admission routes1
Has abstractyes

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