Effects of feces storage conditions for host-microbiota screenings in C. elegans
Bibliographic record
Abstract
Background and aims Current research on host-gut microbiota interactions is hindered by almost infinite bacterial combinations depending on intrinsic characteristics, environment, and health status, which prevents large-scale screenings in mammals. For these reasons, the bacterivore model organism C. elegans has been developed to test the effects of gut microbiota extracts from mammals. This study tested whether storage conditions of mouse feces and fecal extracts modify normal C. elegans healthspan. Methods Feces from mice were processed for microbiota extraction after collection or after one or twelve months at -80 °C and compared to microbiota extracted six months before and left at room temperature. Extracts were probed for bacterial composition, viability, and nutritional content and tested in synchronized wild-type (strain N2) worms for food preferences and intake, development, fat accumulation, brood size, and maximal lifespan. Results Long-term freezing of feces before microbiota extraction modified composition but did not negatively impact subsequent worm development, fat accumulation, reproduction, and maximal lifespan, whereas using samples extracted and left at room temperature after a long period of time resulted in robust avoidance and was detrimental for normal growth. Conclusions Using frozen feces to test for impacts of microbiota in C. elegans appears an appropriate method since it did not affect normal biology and healthspan, which supports protocols with already existing feces stored in biobanks for high-throughput phenotype screenings.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".