Impact of bacterial inactivation methods on Caenorhabditis elegans feeding and healthspan
Bibliographic record
Abstract
Accurate bacterial inactivation methods are essential for nutritional and microbiota studies in Caenorhabditis elegans , to determine whether the observed effects arise from nutrients provided by ingested bacteria or from active symbiotic interactions. However, some inactivation methods alter bacterial palatability, complicating conclusions about their direct impact. We aimed to identify an effective method for inactivating the bacterial strain Escherichia coli OP50, the standard food source for most C. elegans experiments, that preserves normal behavior and physiology in C. elegans . We compared heat inactivation (65 °C for 35 min) with 0.5% paraformaldehyde (PFA) inactivation. Worms fed PFA-inactivated bacteria showed no food aversion, and maintained wild-type pharyngeal pumping levels, fertility rates, and lipid accumulation, closely resembling the behavior and physiology of worms fed alive E. coli OP50. In contrast, heat‑inactivated bacteria elicited strong food avoidance, reduced pumping activity, activation of the mitochondrial unfolded protein response (UPR mt ), decreased lipid stores and fertility, and increased survival relative to the other groups. These findings demonstrate that 0.5% PFA inactivation more accurately preserves C. elegans physiological and behavioral traits than heat inactivation, making it a more suitable method for microbiota and nutritional studies.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
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".