Pangenome insights into the diversification and disease specificity of worldwide Xanthomonas outbreaks
Bibliographic record
Abstract
The bacterial genus Xanthomonas is responsible for disease outbreaks in several hundred plant species, many of them economically important crops. In the era of next-generation sequencing, thousands of strains from this genus have now been sequenced as part of isolated studies that focus on outbreak characterization, host range, diversity, and virulence factor identification. However, these data have not been synthesized and we lack a comprehensive phylogeny for the genus, with some species designations in public databases still relying on phenotypic similarities and representative sequence typing. The extent of genetic cohesiveness among Xanthomonas strains, the distribution of virulence factors across strains, and the impact of evolutionary history on host range across the genus are also poorly understood. In this study, we present a pangenome analysis of 1,910 diverse Xanthomonas genomes, highlighting their evolutionary relationships, the distribution of virulence-associated genes across strains, and rates of horizontal gene transfer. We find a number of broadly conserved classes of virulence factors and considerable diversity in the Type 3 Secretion Systems (T3SSs) and Type 3 Secreted Effector (T3SE) repertoires of different Xanthomonas species. We also use these data to re-assign incorrectly classified strains to phylogenetically informed species designations and find evidence of both monophyletic host specificity and convergent evolution of phylogenetically distant strains to the same host. Finally, we explore the role of recombination in maintaining genetic cohesion within the Xanthomonas genus as a result of both ancestral and recent recombination events. Understanding the evolutionary history of Xanthomonas species and the relationship of key virulence factors with host-specificity provides valuable insight into the mechanisms through which Xanthomonas species shift between hosts and will enable us to develop more robust resistance strategies against these highly virulent pathogens.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".