Chemosynthetic symbiont with a drastically reduced genome serves as primary energy storage in the marine flatworm <i>Paracatenula</i>
Bibliographic record
Abstract
Hosts of chemoautotrophic bacteria typically have much higher biomass than their symbionts and consume symbiont cells for nutrition. In contrast to this, chemoautotrophic Candidatus Riegeria symbionts in mouthless Paracatenula flatworms comprise up to half of the biomass of the consortium. Each species of Paracatenula harbors a specific Ca . Riegeria, and the endosymbionts have been vertically transmitted for at least 500 million years. Such prolonged strict vertical transmission leads to streamlining of symbiont genomes, and the retained physiological capacities reveal the functions the symbionts provide to their hosts. Here, we studied a species of Paracatenula from Sant’Andrea, Elba, Italy, using genomics, gene expression, imaging analyses, as well as targeted and untargeted MS. We show that its symbiont, Ca . R. santandreae has a drastically smaller genome (1.34 Mb) than the symbiont´s free-living relatives (4.29–4.97 Mb) but retains a versatile and energy-efficient metabolism. It encodes and expresses a complete intermediary carbon metabolism and enhanced carbon fixation through anaplerosis and accumulates massive intracellular inclusions such as sulfur, polyhydroxyalkanoates, and carbohydrates. Compared with symbiotic and free-living chemoautotrophs, Ca . R. santandreae’s versatility in energy storage is unparalleled in chemoautotrophs with such compact genomes. Transmission EM as well as host and symbiont expression data suggest that Ca . R. santandreae largely provisions its host via outer-membrane vesicle secretion. With its high share of biomass in the symbiosis and large standing stocks of carbon and energy reserves, it has a unique role for bacterial symbionts—serving as the primary energy storage for its animal host.
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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) | 0.000 | 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".