Construction of a mariner-based transposon vector for use in insertion sequence mutagenesis in selected members of the Rhizobiaceae
Bibliographic record
Abstract
BACKGROUND: The Rhizobiaceae family of Gram-negative bacteria often engage in symbiosis with plants of economic importance. Historically, genetic studies to identify the function of individual genes, and characterize the biology of these bacteria have relied on the use of classical transposon mutagenesis. To increase the rate of scientific discovery in the Rhizobiaceae there is a need to adapt high-throughput genetic screens like insertion sequencing for use in this family of bacteria. Here we describe a Rhizobiaceae compatible MmeI-adapted mariner transposon that can be used with insertion sequencing for high-throughput genetic screening. RESULTS: The newly constructed mariner transposon pSAM_Rl mutagenized R. leguminosarum, S. meliloti, and A. tumefaciens at a high frequency. In R. leguminosarum, mutant pools were generated that saturated 88% of potential mariner insertions sites in the genome. Analysis of the R. leguminosarum transposon insertion sequencing data with a previously described hidden Markov model-based method resulted in assignment of the contribution of all annotated genes in the R. leguminosarum 3841 genome for growth on a complex medium. Good concordance was observed between genes observed to be required for growth on the complex medium, and previous studies. CONCLUSIONS: The newly described Rhizobiaceaee compatible mariner transposon insertion sequencing vector pSAM_Rl has been shown to mutagenize at a high frequency and to be an effective tool for use in high-throughput genetic screening. The construction and validation of this transposon insertion sequencing tool for use in the Rhizobiziaceae will provide an opportunity for researchers in the Rhizobiaceae community to use high-throughput genetic screening, allowing for significant increase in the rate of genetic discovery, particularly given the recent release of genome sequences from many Rhizobiaceae strains.
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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 | 0.001 |
| 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) | 0.000 | 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".