New perspectives on an old grouping: The genomic and phenotypic variability of Oxalobacter formigenes and the implications for calcium oxalate stone prevention
Bibliographic record
Abstract
Oxalobacter formigenes is a unique bacterium with the ability to metabolize oxalate as a primary carbon source. Most kidney stones in humans are composed of calcium and oxalate. Therefore, supplementation with an oxalate-degrading bacterium may reduce stone burden in patients suffering from recurrent calcium oxalate-based urolithiasis. Strains of O. formigenes are divided into two groups: group I and group II. However, the differences between strains from each group remain unclear and elucidating these distinctions will provide a better understanding of their physiology and potential clinical applications. Here, genomes from multiple O. formigenes strains underwent whole genome sequencing followed by phylogenetic and functional analyses. Genetic differences suggest that the O. formigenes taxon should be divided into an additional three species: Oxalobacter aliiformigenes sp. nov, Oxalobacter paeniformigenes sp. nov, and Oxalobacter paraformigenes sp. nov. Despite the similarities in the oxalyl-CoA gene (oxc), which is essential for oxalate degradation, these strains have multiple unique genetic features that may be potential exploited for clinical use. Further investigation into the growth of these strains in a simulated fecal environment revealed that O. aliiformigenes strains are capable of thriving within the human gut microbiota. O. aliiformigenes may be a better therapeutic candidate than current group I strains (retaining the name O. formigenes), which have been previously tested and shown to be ineffective as an oral supplement to mitigate stone disease. By performing genomic analyses and identifying these novel characteristics, Oxalobacter strains better suited to mitigation of calcium oxalate-based urolithiasis may be identified in the future.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.006 | 0.016 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".