Evaluation of a SUMO E2 Conjugating Enzyme Involved in Resistance to Clavibacter michiganensis Subsp. michiganensis in Solanum peruvianum, Through a Tomato Mottle Virus VIGS Assay
Bibliographic record
Abstract
Clavibacter michiganensis subsp. michiganensis (Cmm) causes bacterial wilt and canker of tomato. Currently, no Solanum lycopersicum resistant varieties are commercially available, but some degree of Cmm resistance has been identified in Solanum peruvianum. Previous research showed up-regulation of a SUMO E2 conjugating enzyme (SCEI) transcript in S. peruvianum compared to S. lycopersicum following infection with Cmm. In order to test the role of SCEI in resistance to Cmm, a fragment of SCEI from S. peruvianum was cloned into a novel virus-induced gene-silencing (VIGS) vector based on the geminivirus, Tomato Mottle Virus (ToMoV). Using biolistic inoculation, the ToMoV-based VIGS vector was shown to be effective in S. peruvianum by silencing the magnesium chelatase gene, resulting in leaf bleaching. VIGS with the ToMoV_SCEI construct resulted in ~61% silencing of SCEI in leaves of S. peruvianum as determined by quantitative RT-PCR. The SCEI-silenced plants showed unilateral wilting (15 dpi) and subsequent death (20 dpi) of the entire plant after Cmm inoculation, whereas the empty vector-treated plants only showed wilting in the Cmm-inoculated leaf. The SCEI-silenced plants showed higher Cmm colonization and an average of 4.5 times more damaged tissue compared to the empty vector control plants. SCEI appears to play an important role in the innate immunity of S. peruvianum against Cmm, perhaps through the regulation of transcription factors, leading to expression of proteins involved in salicylic acid-dependent defense responses.
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 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 | 0.001 | 0.001 |
| 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".