Characterizing the in vivo role of Scabin, a mono ADP- ribosyltransferase from the common scab pathogen Streptomyces scabiei
Bibliographic record
Abstract
Common scab is a widespread bacterial disease of potato and other root and tuber crops. The disease is characterized by the presence of superficial, raised or deep-pitted lesions on the surface of the potato tuber, and these lesions reduce the market value of the crop to cause major economic losses for farmers. To date, no fully resistant potato cultivar exists, and current management strategies are largely inadequate or inconsistent. Therefore, studying the virulence factors of the most prominent causative agent, Streptomyces scabiei, is of high importance. Recently, a new putative virulence factor called Scabin was identified in the genome of S. scabiei. Scabin is a mono ADP-ribosyltransferase that possesses in vitro activity towards DNA, RNA and small guanosine-containing molecules, a rare activity for this group of enzymes that typically target proteins. However, the in vivo target and role of Scabin remains unknown. The purpose of this study has been to investigate the function of Scabin and determine if it plays a role in S. scabiei pathogenesis. To achieve this, a scabin knockout mutant was created, and the mutant together with wild-type S. scabiei and a scabin overexpression strain were tested in several plant bioassays. The morphology of the mutant and overexpression strain was examined when the strains were cultured on several distinct agar media. The conditions under which scabin is expressed were investigated using RT-PCR, and subsequently, it was discovered that scabin is co-transcribed with a neighbouring gene, SCAB_27781, suggesting they are functionally linked. The distribution of Scabin and SCAB_27781 homologues in other Streptomyces species and the relative positions of the corresponding genes in each species were mapped out, and regions of interest in both proteins were predicted using various bioinformatic tools. This study is the first to investigate possible in vivo roles for Scabin.
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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) | 0.000 | 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 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".