Temperature-Sensitive Growth and Decreased Thermotolerance Associated with <i>relA</i> Mutations in <i>Escherichia coli</i>
Bibliographic record
Abstract
The relA gene of Escherichia coli encodes guanosine 3',5'-bispyrophosphate (ppGpp) synthetase I, a ribosome-associated enzyme that is activated during amino acid starvation. The stringent response is thought to be mediated by ppGpp. Mutations in relA are known to result in pleiotropic phenotypes. We now report that three different relA mutant alleles, relA1, relA2, and relA251::kan, conferred temperature-sensitive phenotypes, as demonstrated by reduced plating efficiencies on nutrient agar (Difco) or on Davis minimal agar (Difco) at temperatures above 41 degrees C. The relA-mediated temperature sensitivity was osmoremedial and could be completely suppressed, for example, by the addition of NaCl to the medium at a concentration of 0.3 M. The temperature sensitivities of the relA mutants were associated with decreased thermotolerance; e.g., relA mutants lost viability at 42 degrees C, a temperature that is normally nonlethal. The spoT gene encodes a bifunctional enzyme possessing ppGpp synthetase and ppGpp pyrophosphohydrolase activities. The introduction of the spoT207::cat allele into a strain bearing the relA251::kan mutation completely abolished ppGpp synthesis. This ppGpp null mutant was even more temperature sensitive than the strain carrying the relA251::kan mutation alone. The relA-mediated thermosensitivity was suppressed by certain mutant alleles of rpoB (encoding the beta subunit of RNA polymerase) and spoT that have been previously reported to suppress other phenotypic characteristics conferred by relA mutations. Collectively, these results suggest that ppGpp may be required in some way for the expression of genes involved in thermotolerance.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".