Novel DNA Sequences from Natural Strains of the Nitrogen-Fixing Symbiotic Bacterium <i>Sinorhizobium meliloti</i>
Bibliographic record
Abstract
Variation in genome size and content is common among bacterial strains. Identifying these naturally occurring differences can accelerate our understanding of bacterial attributes, such as ecological specialization and genome evolution. In this study, we used representational difference analysis to identify potentially novel sequences not present in the sequenced laboratory strain Rm1021 of the nitrogen-fixing bacterium Sinorhizobium meliloti. Using strain Rm1021 as the driver and the type strain of S. meliloti ATCC 9930, which has a genome size approximately 370 kilobases bigger than that of strain Rm1021, as the tester, we identified several groups of sequences in the ATCC 9930 genome not present in strain Rm1021. Among the 85 novel DNA fragments examined, 55 showed no obvious homologs anywhere in the public databases. Of the remaining 30 sequences, 24 contained homologs to the Rm1021 genome as well as unique segments not found in Rm1021, 3 contained sequences homologous to those published for another S. meliloti strain but absent in Rm1021, 2 contained sequences homologous to other symbiotic nitrogen-fixing bacteria (Rhizobium etli and Bradyrhizobium japonicum), and 1 contained a sequence homologous to a gene in a non-nitrogen-fixing species, Pseudomonas sp. NK87. Using PCR, we assayed the distribution of 12 of the above 85 novel sequences in a collection of 59 natural S. meliloti strains. The distribution varied widely among the 12 novel DNA fragments, from 1.7% to 72.9%. No apparent correlation was found between the distribution of these novel DNA sequences and their genotypes obtained using multilocus enzyme electrophoresis. Our results suggest potentially high rates of gene gain and loss in S. meliloti genomes.
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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 | 0.001 |
| 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".