Lymphatic constraint of germinal centers optimizes protective antibody responses
Bibliographic record
Abstract
Immunization strategies are central to pathogen control, where efficacy relies on antigen uptake, distribution, persistence, and inflammatory context. We recently demonstrated that dermal lymphatic capillaries regulate antigen presentation in lymph nodes (LN) by restraining fluid and virion transport following vaccinia virus (VACV) infection by skin scarification. Concurrently, a perifollicular, LN lymphangiogenic response encapsulates expanding B cell follicles. Given the important role of antigen transport and uptake on humoral immunity, we tested the hypothesis that lymphatic remodeling in the skin and LNs regulates germinal center (GC)-dependent antibody responses during infection. Using a model of lymphatic-specific VEGFR2 inhibition, we found that inhibiting viral-induced lymphatic remodeling in skin and LNs prompted significant GC expansion but paradoxically decreases protective VACV-specific class-switched antibodies. While the larger GC responses appeared structurally normal, they failed to support a proliferative burst consistent with clonal selection. Mathematical modeling revealed that this disconnect between GC size and function arises from impaired productive T follicular cell interactions in larger GC volumes and consistent with this finding, the optimal GC size was evolutionarily conserved across diverse mammals. Finally, we found that the presence of virus in the LN initiates these changes in GC function, inhibits LN lymphangiogenesis, increases B cell follicle size, and reduces selection efficiency. Therefore, protecting LN lymphatic vessels from virus-induced interferons rescues perifollicular lymphatic growth and follicle size, indicating that LN lymphangiogenesis directly constrains the follicular response. In summary, this study underscores the central role of lymphatic remodeling in compartmentalizing antigen and inflammatory signals to optimize GC fitness and protective antibody responses.
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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) | 0.002 | 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".