Microbial lag phase can be indicative of, or independent from, cellular stress
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Measures of microbial growth, used as indicators of cellular stress, are sometimes quantified at a single time-point. In reality, these measurements are compound representations of length of lag, exponential growth-rate, and other factors. Here, we investigate whether length of lag phase can act as a proxy for stress, using a number of model systems ( Aspergillus penicillioides ; Bacillus subtilis ; Escherichia coli ; Eurotium amstelodami , E. echinulatum , E. halophilicum , and E. repens; Mrakia frigida ; Saccharomyces cerevisiae ; Xerochrysium xerophilum ; Xeromyces bisporus ) exposed to mechanistically distinct types of cellular stress including low water activity, other solute-induced stresses, and dehydration-rehydration cycles. Lag phase was neither proportional to germination rate for X. bisporus (FRR3443) in glycerol-supplemented media (r 2 = 0.012), nor to exponential growth-rates for other microbes. In some cases, growth-rates varied greatly with stressor concentration even when lag remained constant. By contrast, there were strong correlations for B. subtilis in media supplemented with polyethylene-glycol 6000 or 600 (r 2 = 0.925 and 0.961), and for other microbial species. We also analysed data from independent studies of food-spoilage fungi under glycerol stress ( Aspergillus aculeatinus and A. sclerotiicarbonariu s); mesophilic/psychrotolerant bacteria under diverse, solute-induced stresses ( Brochothrix thermosphacta , Enterococcus faecalis , Pseudomonas fluorescens , Salmonella typhimurium , Staphylococcus aureus ); and fungal enzymes under acid-stress ( Terfezia claveryi lipoxygenase and Agaricus bisporus tyrosinase). These datasets also exhibited diversity, with some strong- and moderate correlations between length of lag and exponential growth-rates; and sometimes none. In conclusion, lag phase is not a reliable measure of stress because length of lag and growth-rate inhibition are sometimes highly correlated, and sometimes not at all.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.003 | 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 it