Spatial compartmentalisation of bacteria in phoronid microbiomes
Bibliographic record
Abstract
The phylum Phoronida comprises filter-feeding invertebrates that live in a protective tube sometimes reinforced with particulate material from the surrounding environments. Animals with these characteristics make promising candidate hosts for symbiotic bacteria, given the constant interactions with various bacterial colonizers, yet phoronids are one of the very few animal phyla with no available microbiome data whatsoever. Here, by sequencing the V4 region of the 16S rRNA gene, we compare bacterial microbiomes in whole phoronids, including both tube and living tissues, with those associated exclusively to the isolated tube and/or the naked animal inside. We also compare these communities with those from the surrounding water. Phoronid microbiomes from specimens belonging to the same colony but collected a month apart were significantly different, and bacterial taxa previously reported in association with invertebrates and sediment were found to drive this difference. The microbiomes associated with the tubes are very similar in composition to those isolated from whole animals. However, just over half of bacteria found in whole specimens are also found both in tubes and naked specimens. In conclusion, phoronids harbour bacterial microbiomes that differ from those in the surrounding water, but the composition of those microbiomes is not stable and appears to change in the same colony over a relatively short time frame. Considering individual spatial/anatomical compartments, the phoronid tube contributes most to the whole-animal microbiome.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".