Comparative Genomics of Potato Common Scab-Causing Streptomyces spp. Displaying Varying Virulence
Bibliographic record
Abstract
Common scab of potato causes important economic losses worldwide following the development of necrotic lesions on tubers. In this study, the genomes of 14 prevalent scab-causing Streptomyces spp. isolated from Prince Edward Island, one of the most important Canadian potato production areas, were sequenced and annotated. Their phylogenomic affiliation was determined, their pan-genome was characterized, and pathogenic determinants involved in their virulence, ranging from weak to aggressive, were compared. 13 out of 14 strains clustered with Streptomyces scabiei, while the last strain clustered with Streptomyces acidiscabies. The toxicogenic and colonization genomic regions were compared, and while some atypical gene organizations were observed, no clear correlation with virulence was observed. The production of the phytotoxin thaxtomin A was also quantified and again, contrary to previous reports in the literature, no clear correlation was found between the amount of thaxtomin A secreted, and the virulence observed. Although no significant differences were observed when comparing the presence/absence of the main virulence factors among the strains of S. scabiei, a distinct profile was observed for S. acidiscabies. Several mutations predicted to affect the functionality of some virulence factors were identified, including one in the bldA gene that correlates with the absence of thaxtomin A production despite the presence of the corresponding biosynthetic gene cluster in S. scabiei LBUM 1485. These novel findings obtained using a large number of scab-causing Streptomyces strains are challenging some assumptions made so far on Streptomyces’ virulence and suggest that other factors, yet to be characterized, are also key contributors.
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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 | 0.000 | 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".