Mechanism of acid tolerance in a rhizobium strain isolated from <i>Pueraria lobata</i> (Willd.) Ohwi
Bibliographic record
Abstract
The Rhizobium sp. strain PR389 was isolated from the root nodules of Pueraria lobata (Willd.) Ohwi, which grows in acidic (pH 4.6) yellow soil of the Jinyun Mountains of Beibei, Chongqing, China. While rhizobia generally have a pH range of 6.5-7.5 for optimum growth, strain PR389 grew in a liquid yeast extract - mannitol agar medium at pH 4.6, as well as in a pH 4.1 soil suspension, suggesting acid tolerance in this specific strain of rhizobium . However, at pH 4.6, the lag phase before vigorous growth was 40 h compared with 4 h under neutral conditions (pH 7.0). For PR389, the generation time after the lag phase remained the same at different pH levels despite the different durations of the lag phase. Except in the pH 4.4 treatment, the pH of the culturing media increased from 4.6, 4.8, 5.0, and 5.5 to neutral and slightly alkaline after 70 h of culture. Chloramphenicol was added to determine if protein production was involved in the increasing pH process. Chloramphenicol significantly inhibited PR389 growth under acid stress but had little effect under neutral conditions. Proton flux measured during a short acid shock (pH 3.8) revealed that this strain has an intrinsic ability to prevent H(+) from entering cells when compared with acid-sensitive rhizobia. We propose that the mechanism for acid tolerance in PR389 involves both intracellular and extracellular processes. When the extracellular pH is lower than pH 4.4, the cell membrane blocks hydrogen from entering the cell. When the pH exceeds 4.4, the rhizobium strain has the ability to raise the extracellular pH, thereby, potentially decreasing the toxicity of aluminum in acid soil.
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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 | 0.000 | 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 | 0.000 |
| 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".