Perturbation of gut bacteria induces a coordinated cellular immune response in the purple sea urchin larva
Bibliographic record
Abstract
The purple sea urchin (Strongylocentrotus purpuratus) genome sequence contains a complex repertoire of genes encoding innate immune recognition proteins and homologs of important vertebrate immune regulatory factors. To characterize how this immune system is deployed within an experimentally tractable, intact animal, we investigate the immune capability of the larval stage. Sea urchin embryos and larvae are morphologically simple and transparent, providing an organism-wide model to view immune response at cellular resolution. Here we present evidence for immune function in five mesenchymal cell types based on morphology, behavior and gene expression. Two cell types are phagocytic; the others interact at sites of microbial detection or injury. We characterize immune-associated gene markers for three cell types, including a perforin-like molecule, a scavenger receptor, a complement-like thioester-containing protein and the echinoderm-specific immune response factor 185/333. We elicit larval immune responses by (1) bacterial injection into the blastocoel and (2) seawater exposure to the marine bacterium Vibrio diazotrophicus to perturb immune state in the gut. Exposure at the epithelium induces a strong response in which pigment cells (one type of immune cell) migrate from the ectoderm to interact with the gut epithelium. Bacteria that accumulate in the gut later invade the blastocoel, where they are cleared by phagocytic and granular immune cells. The complexity of this coordinated, dynamic inflammatory program within the simple larval morphology provides a system in which to characterize processes that direct both aspects of the echinoderm-specific immune response as well as those that are shared with other deuterostomes, including vertebrates.
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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".