Differentially expressed genes reveal adaptations between free-living and symbiotic niches of <i>Vibrio fischeri</i> in a fully established mutualism
Bibliographic record
Abstract
A major force driving in the innovation of mutualistic symbioses is the number of adaptations that both organisms must acquire to provide overall increased fitness for a successful partnership. Many of these symbioses are relatively dependent on the ability of the symbiont to locate a host (specificity), as well as provide some novel capability upon colonization. The mutualism between sepiolid squids and members of the Vibrionaceae is a unique system in which development of the symbiotic partnership has been studied in detail, but much remains unknown about the genetics of symbiont colonization and persistence within the host. Using a method that captures exclusively expressed transcripts in either free-living or host-associated strains of Vibrio fischeri, we identified and verified expression of genes differentially expressed in both states from two symbiotic strains of V. fischeri. These genes provide a glimpse into the microhabitat V. fischeri encounters in both free-living seawater and symbiotic host light organ-associated habitats, providing insight into the elements necessary for local adaptation and the evolution of host specificity in this unique mutualism.
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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".