Single-cell and Spatial Transcriptomics Illuminate Bat Immunity and Barrier Tissue Evolution
Bibliographic record
Abstract
Bats have adapted to pathogens through diverse mechanisms, including increased resistance-rapid pathogen elimination, and tolerance-limiting tissue damage following infection. In the Egyptian fruit bat (an important model in comparative immunology), several mechanisms conferring disease tolerance were discovered, but mechanisms underpinning resistance remain poorly understood. Previous studies on other species suggested that the elevated basal expression of innate immune genes may lead to increased resistance to infection. Here, we test whether such transcriptional patterns occur in Egyptian fruit bat tissues through single-cell and spatial transcriptomics of gut, lung, and blood cells, comparing gene expression between bat, mouse, and human. Despite numerous recent loss and expansion events of interferons in the bat genome, interferon expression and induction are remarkably similar to that of mouse. In contrast, central complement system genes are highly and uniquely expressed in key regions in bat lung and gut epithelium, unlike in human and mouse. Interestingly, the unique expression of these genes in the bat gut is strongest in the crypt, where developmental expression programs are highly conserved. The complement system genes also evolve rapidly in their coding sequences across the bat lineage. Finally, the bat complement system displays strong hemolytic activity. Together, these results indicate a distinctive transcriptional divergence of the complement system, which may be linked to bat resistance, and highlight the intricate evolutionary landscape of bat immunity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".