Metabolic differences between symbiont subpopulations in the deep-sea tubeworm <i>Riftia pachyptila</i>
Bibliographic record
Abstract
Abstract The hydrothermal vent tube worm Riftia pachyptila lives in intimate symbiosis with intracellular sulfur-oxidizing gammaproteobacteria. Although the symbiont population consists of a single 16S rRNA phylotype, bacteria in the same host animal exhibit a remarkable degree of metabolic diversity: They simultaneously utilize two carbon fixation pathways and various energy sources and electron acceptors. Whether these multiple metabolic routes are employed in the same symbiont cells, or rather in distinct symbiont subpopulations, was unclear. As Riftia symbionts vary considerably in cell size and shape, we enriched individual symbiont cell sizes by density gradient centrifugation in order to test whether symbiont cells of different sizes show different metabolic profiles. Metaproteomic analysis and statistical evaluation using clustering and random forests, supported by microscopy and flow cytometry, strongly suggest that Riftia symbiont cells of different sizes represent metabolically dissimilar stages of a physiological differentiation process: Small symbionts actively divide and may establish cellular symbiont-host interaction, as indicated by highest abundance of the cell division key protein FtsZ and highly abundant chaperones and porins in this initial phase. Large symbionts, on the other hand, apparently do not divide, but still replicate DNA, leading to DNA endoreduplication. Highest abundance of enzymes for CO 2 fixation, carbon storage and biosynthesis in large symbionts indicates that in this late differentiation stage the symbiont’s metabolism is efficiently geared towards the production of organic material. We propose that this division of labor between smaller and larger symbionts benefits the productivity of the symbiosis as a whole.
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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 | 0.000 |
| 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".