Solute Transport Proteins and the Outer Membrane Protein NmpC Contribute to Heat Resistance of Escherichia coli AW1.7
Bibliographic record
Abstract
This study aimed to elucidate determinants of heat resistance in Escherichia coli by comparing the composition of membrane lipids, as well as gene expression, in heat-resistant E. coli AW1.7 and heat-sensitive E. coli GGG10 with or without heat shock. The survival of E. coli AW1.7 at late exponential phase was 100-fold higher than that of E. coli GGG10 after incubation at 60°C for 15 min. The cytoplasmic membrane of E. coli AW1.7 contained a higher proportion of saturated and cyclopropane fatty acids than that of E. coli GGG10. Microarray hybridization of cDNA libraries obtained from exponentially growing or heat-shocked cultures was performed to compare gene expression in these two strains. Expression of selected genes from different functional groups was quantified by quantitative PCR. DnaK and 30S and 50S ribosomal subunits were overexpressed in E. coli GGG10 relative to E. coli AW1.7 upon heat shock at 50°C, indicating improved ribosome stability. The outer membrane porin NmpC and several transport proteins were overexpressed in exponentially growing E. coli AW1.7. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis analysis of membrane properties confirmed that NmpC is present in the outer membrane of E. coli AW1.7 but not in that of E. coli GGG10. Expression of NmpC in E. coli GGG10 increased survival at 60°C 50- to 1,000-fold. In conclusion, the outer membrane porin NmpC contributes to heat resistance in E. coli AW1.7, but the heat resistance of this strain is dependent on additional factors, which likely include the composition of membrane lipids, as well as solute transport proteins.
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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".