Diverse hosts, diverse immune systems: Evolutionary variation in bat immunology
Bibliographic record
Abstract
The ability of multiple bat species to host zoonotic pathogens without often showing disease has fostered a growing interest in bat immunology to discover the ways immune systems may differ between bats and other vertebrates. However, interspecific variation in immunological diversity among bats has only begun to be recognized. The order Chiroptera accounts for over 20% of all mammalian species and shows extreme diversity in a suite of correlated ecological traits, such that bats should not be expected to be immunologically homogenous. We review the ecological and evolutionary diversity of chiropteran hosts and highlight case studies emphasizing the range of immune strategies thus far observed across bat species, including responses to SARS-CoV-2. Next, we synthesize and propose hypotheses to explain this immunological diversity, focusing on pathogen exposure, biogeography, host energetics, and environmental stability. We then analyze immunology-related citations across bat species to motivate discussions of key research priorities. Broad sampling is needed to remedy current biases, as only a fraction of bat species has been immunologically studied. Such work should integrate methodological advancements, in vitro and in vivo studies, and phylogenetic comparative methods to robustly test evolutionary hypotheses and understand the drivers and consequences of immunological diversity among bats.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".