Phylogenetic analysis of migration, differentiation, and class switching in B cells

Kenneth B Hoehn, Oliver G Pybus and Steven H Kleinstein

PLOS Computational Biology, 2022, vol. 18, issue 4, 1-24

Abstract: B cells undergo rapid mutation and selection for antibody binding affinity when producing antibodies capable of neutralizing pathogens. This evolutionary process can be intermixed with migration between tissues, differentiation between cellular subsets, and switching between functional isotypes. B cell receptor (BCR) sequence data has the potential to elucidate important information about these processes. However, there is currently no robust, generalizable framework for making such inferences from BCR sequence data. To address this, we develop three parsimony-based summary statistics to characterize migration, differentiation, and isotype switching along B cell phylogenetic trees. We use simulations to demonstrate the effectiveness of this approach. We then use this framework to infer patterns of cellular differentiation and isotype switching from high throughput BCR sequence datasets obtained from patients in a study of HIV infection and a study of food allergy. These methods are implemented in the R package dowser, available at https://dowser.readthedocs.io.Author summary: B cells produce high affinity antibodies through an evolutionary process of mutation and selection during adaptive immune responses. Migration between tissues, differentiation to cellular subtypes, and switching between different antibody isotypes can be important factors in shaping the role B cells play in response to infection, autoimmune disease, and allergies. B cell receptor (BCR) sequence data has the potential to elucidate important information about these processes. However, there is currently no robust, generalizable framework for making such inferences from BCR sequence data. Here, we develop three parsimony-based summary statistics to characterize migration, differentiation, and isotype switching along B cell phylogenetic trees. We confirm the effectiveness of our approach using simulations and further apply our method to data from patients with HIV and allergy. Our methods are released in the R package dowser: https://dowser.readthedocs.io.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1009885

DOI: 10.1371/journal.pcbi.1009885

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