A minimized symbiotic gene set from the 1.68 Mb pSymB chromid of Sinorhizobium meliloti reveals auxiliary symbiotic loci
Bibliographic record
Abstract
Abstract Background Symbiotic nitrogen-fixation between bacteria called rhizobia and leguminous plants is a critical aspect of sustainable agriculture. Complex, two-way communication governs the invasion of plant roots and the formation of nodules in which the rhizobia reduce N2 to bioavailable ammonia. Research has uncovered many of the genes required for the symbiosis; however, engineering the symbiosis to function with alternative hosts such as cereal crops necessitates the establishment of a core set of symbiotic players. Results We examined the symbiotic relevance of the genes on the 1.68 Mb pSymB chromid of the model rhizobium Sinorhizobium meliloti. By employing a strain in which pSymB was removed, we used a gain-of-function approach to assess a select group of known symbiotic regions totalling 261 kb (15.5%) of pSymB. This gene set enabled symbiotic N2-fixation with alfalfa with a high degree of plant genotype-dependent variation in which nodules often senesced prematurely. We demonstrate that additional regions lacking canonical symbiosis genes are important for the efficient formation of symbiosis with the plant host. These regions appear to contain auxiliary symbiotic loci whose genes encode products with quasi-essential functions for the symbiosis and that are redundant in nature. We further established a 673-kb pSymB genome that engages consistently in N2-fixation with alfalfa with 45% efficiency. Conclusions The reduction of the pSymB genome showcases the complexity and nuance of its involvement in the N2-fixing symbiosis.
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) | 0.001 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".