Global responses of<i>Escherichia coli</i>to adverse conditions determined by microarrays and FT-IR spectroscopy
Bibliographic record
Abstract
The global gene expression and biomolecular composition in an Escherichia coli model strain exposed to 10 adverse conditions (sodium chloride, ethanol, glycerol, hydrochloric and acetic acid, sodium hydroxide, heat (46 degrees C), and cold (15 degrees C), as well as ethidium bromide and the disinfectant benzalkonium chloride) were determined using DNA microarrays and Fourier transform infrared (FT-IR) spectroscopy. In total, approximately 40% of all investigated genes (1682/4279 genes) significantly changed expression, compared with a nonstressed control. There were, however, only 3 genes (ygaW (unknown function), rmf (encoding a ribosomal modification factor), and ghrA (encoding a glyoxylate/hydroxypyruvate reductase)) that significantly changed expression under all conditions (not including benzalkonium chloride). The FT-IR analysis showed an increase in unsaturated fatty acids during ethanol and cold exposure, and a decrease during acid and heat exposure. Cold conditions induced changes in the carbohydrate composition of the cell, possibly related to the upregulation of outer membrane genes (glgAP and rcsA). Although some covariance was observed between the 2 data sets, principle component analysis and regression analyses revealed that the gene expression and the biomolecular responses are not well correlated in stressed populations of E. coli, underlining the importance of multiple strategies to begin to understand the effect on the whole cell.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".