Topological measures on phylogenetic trees of the antibody repertoire reveal the underlying kinetics of B cell fate decisions 4844
Year: 2025
Type: article
Abstract: Description The immune response to vaccination generates an antibody repertoire by Darwinian evolution via selection, mutation, and proliferative expansion of B cells. Alternations in B cell fate decisions due to prior exposures, chronic inflammation, or SNPs can impair the response. We asked whether B cell fate decision kinetics in vivo are encoded in phylogenetic trees constructed from antibody repertoire sequencing. We developed a mathematical model parameterizing survival, mutation, and proliferation probabilities of B cells under sequence-based selection. We performed Monte Carlo simulations of phylogenetic trees in the repertoire and analyzed distributions of graph-theoretic topological measures. We found that purely shape-based measures like root-to-tip depth are sensitive to mutation and death rates, while measures weighted by sequence abundance better reflect positive selection. To determine how well these kinetics can be mutually distinguished with perfect data, we trained a regression model to infer generative parameters given any phylogenetic tree, and achieved accuracy >70% for 3 parameters. However, our results also showed that accuracy in inferring cell fate decision parameters is drastically diminished by cell sub-sampling loss. This novel approach yields quantitative insights across biological scales, inferring control of B cell fate decisions from the resulting antibody repertoire. As a potential diagnostic measure it may inform strategies for personalizing vaccination. Funding Sources We acknowledge support from NIH grants R01AI132731 and R01AI127867 (to AH), Damon Runyon Quantitative Biology award DRQ11-21 (to HVN), and UCLA Undergraduate Research Scholarship (to CL). Topic Categories Computational and Systems Immunology (COMP)
Source: The Journal of Immunology
Institutions: University of California, Los Angeles, Zhejiang University
Language: English
Topic: T-cell and B-cell Immunology
Subfield: Immunology
Field: Immunology and Microbiology
Domain: Life Sciences
Open Access status: bronze
OpenAlex ID: W4416448472
FWCI:
Cites:
Cited by:
Related to:
