Selection and characterization of<i>Spiroplasma citri</i>mutants by random transposome mutagenesis
Bibliographic record
Abstract
Phytopathogenic spiroplasmas can multiply in vascular plants and insects. A deeper understanding of this dual-host life could be furthered through the identification by random mutagenesis of spiroplasma genes required. The ability of the EZ::TN™ Tnp transposome™ system to create random insertional mutations in the genome of Spiroplasma citri was evaluated. The efficiency of electroporation-mediated transformation of S. citri BR3-3X averaged 28.8 CFUs/ng transposome for 10(9) spiroplasma cells. Many transformants appearing on the selection plates were growth impaired when transferred to broth. Altering broth composition in various ways did not improve their growth. However, placing colonies into a small broth volume resulted in robust growth and successful subsequent passages of a subset of transformants. PCR using primers for the dihydrofolate reductase gene confirmed the transposon's presence in the genomes of selected transformants. Southern blot hybridization and nucleotide sequencing suggested that insertion was random within the chromosome and usually at single sites. The insertions were stable. Growth rates of all transformants were lower than that of the wild-type S. citri, but none lost the ability to adhere to a Circulifer tenellus (CT-1) cell line. The EZ::TN™ Tnp transposome™ system represents an additional tool for genetic manipulation of the fastidious spiroplasmas.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".