Age polyethism drives community structure of the bacterial gut microbiota in the fungus‐cultivating termite <scp> <i>O</i> </scp> <i>dontotermes formosanus</i>
Bibliographic record
Abstract
Fungus-cultivating termites (Macrotermitinae) possess an elaborate strategy of lignocellulose digestion. It involves a lignocellulose-degrading fungal symbiont (genus Termitomyces), a diverse gut microbiota and a characteristic labour division in food processing. In this study, using pyrotag sequencing and electron microscopy, we analysed the bacterial microbiota in the hindgut of Odontotermes formosanus and its fungus comb to investigate the spatial organization, establishment and temporal succession of the bacterial communities colonizing specific microhabitats. Our results document strong differences between the communities at the hindgut epithelium and the luminal fluid of newly moulted, young and old worker termites. The differences in community structure were consistent with the density, morphology and spatial distribution of bacterial cells and the pools of microbial metabolites in the hindgut compartment, underlining that both gut development and the age-specific changes in diet affect the composition and functional role of their gut microbiota. These findings provide strong support for the concept that changes in diet and gut environment are important determinants of community structure because they create new niches for microbial symbionts.
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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) | 0.000 | 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 | 0.000 |
| 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".