Adaptive responses of <i>Bacillus cereus </i><scp>ATCC</scp>14579 cells upon exposure to acid conditions involve <scp>ATP</scp>ase activity to maintain their internal <scp>pH</scp>
Bibliographic record
Abstract
Abstract This study examined the involvement of ATPase activity in the acid tolerance response (ATR) of Bacillus cereus ATCC14579 strain. In the current work, B. cereus cells were grown in anaerobic chemostat culture at external pH (pHe) 7.0 or 5.5 and at a growth rate of 0.2 h−1. Population reduction and internal pH (pHi) after acid shock at pH 4.0 was examined either with or without ATPase inhibitor N,N’‐dicyclohexylcarbodiimide (DCCD) and ionophores valinomycin and nigericin. Population reduction after acid shock at pH 4.0 was strongly limited in cells grown at pH 5.5 (acid‐adapted cells) compared with cells grown at pH 7.0 (unadapted cells), indicating that B. cereus cells grown at low pHe were able to induce a significant ATR and Exercise‐induced increase in ATPase activity. However, DCCD and ionophores had a negative effect on the ability of B. cereus cells to survive and maintain their pHi during acid shock. When acid shock was achieved after DCCD treatment, pHi was markedly dropped in unadapted and acid‐adapted cells. The ATPase activity was also significantly inhibited by DCCD and ionophores in acid‐adapted cells. Furthermore, transcriptional analysis revealed that atpB (ATP beta chain) transcripts was increased in acid‐adapted cells compared to unadapted cells before and after acid shock. Our data demonstrate that B. cereus is able to induce an ATR during growth at low pH. These adaptations depend on the ATPase activity induction and pHi homeostasis. Our data demonstrate that the ATPase enzyme can be implicated in the cytoplasmic pH regulation and in acid tolerance of B. cereus acid‐adapted cells.
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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".