Effect of NaCl stress on exoproteome profiles of Bacillus amyloliquefaciens EB2003A and Lactobacillus helveticus EL2006H
Bibliographic record
Abstract
Salt stress can affect survival, multiplication and ability of plant growth promoting microorganisms to enhance plant growth. Changes in a microbe’s proteome profile is one of the mechanisms employed by PGPM to enhance tolerance of salt stress. This study was focused on understanding changes in the exoproteome profile of Bacillus amyloliquefaciens EB2003A and Lactobacillus helveticus EL2006H when exposed to salt stress. The strains were cultured in 100 mL M13 (B. amyloliquefaciens) and 100 mL De man, Rogosa and Sharpe (MRS) (L. helveticus) media, supplemented with 200 and 0 mM NaCl (control), at pH 7.0. The strains were then incubated for 48 h (late exponential growth phase), at 120 rpm and 30 (B. amyloliquefaciens) and 37 (L. helveticus) °C. The microbial cultures were then centrifuged and filtered sterilized, to obtain cell free supernatants whose proteome profiles were studied using LC–MS/MS analysis and quantified using scaffold. Results of the study revealed that treatment with 200 mM NaCl negatively affected the quantity of identified proteins in comparison to the control, for both strains. There was upregulation and downregulation of some proteins, even up to 100%, which resulted in identification of proteins significantly unique between the control or 200 mM NaCl (p ≤ 0.05), for both microbial species. Proteins unique to 200 mM NaCl were mostly those involved in cell wall metabolism, substrate transport, oxidative stress tolerance, gene expression and DNA replication and repair. Some of the identified unique proteins have also been reported to enhance plant growth. In conclusion, based on the results of the work described here, PGPM alter their exoproteome profile when exposed to salt stress, potentially upregulating proteins that enhance their tolerance to this stress.
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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".