Non-symbiotic <i>Bradyrhizobium</i> ecotypes dominate North American forest soils
Bibliographic record
Abstract
The genus Bradyrhizobium has served as a model system for studying host-microbe symbiotic interactions and nitrogen fixation due to its importance in agricultural productivity and global nitrogen cycling. In this study, we identify a bacterial group affiliated with this genus that dominates the microbial communities of coniferous forest soils from six distinct ecozones across North America. Representative isolates from this group were obtained and characterized. Using quantitative population genomics, we show that forest soil populations of Bradyrhizobium represent ecotypes incapable of nodulating legume root hairs or fixing atmospheric nitrogen. Instead, these populations appear to be free living and have a greater potential for metabolizing aromatic carbon sources than their close symbiotic relatives. In addition, we identify fine-scaled differentiation between populations inhabiting neighboring soil layers that illustrate how diversity within Bradyrhizobium is structured by habitat similarity. These findings reconcile incongruent observations about this widely studied and important group of bacteria and highlight the value of ecological context to interpretations of microbial diversity and taxonomy. These results further suggest that the influence of this genus likely extends well beyond facilitating agriculture, especially as forest ecosystems are large and integral components of the biosphere. In addition, this study demonstrates how focusing research on economically important microorganisms can bias our understanding of the natural world.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".