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

Journal article

Understanding the diversity of antibody (IG) molecules at the DNA and RNA level is imperative for understanding immunological processes and disease. Much of the work to uncover IG diversity has been focused on diversity in the variable region of the IG molecule which is crucial for antigen binding. However, the diversity of the constant region responsible for the functions of IG has largely been ignored in the field of immunogenetics. The work presented in this thesis challenges the dogma that the constant region is invariant in terms of genetic diversity. In this thesis we present the development of a long-read sequencing method and computational framework for near-full-length Adaptive Immune Receptor Repertoire sequencing (FLAIRR-seq). Upon the successful development of FLAIRR-seq we utilized the technology alongside DNA IG-capture to demonstrate the diversity of IG heavy chain constant region (IGHC) in 10 healthy donors (HDs). Here we showed the discovery of 28 novel alleles in IgG and IgM not documented in the international ImMunoGeneTics information system (IMGT). FLAIRR-seq provides the highest resolution at the subisotype allele level of IG heavy chains (IGH) to date. We also present preliminary analysis of IG at the DNA and RNA level using FLAIRR-seq and IG-capture from anti-acetylcholine receptor antibody-positive myasthenia gravis (AChR MG) donors compared to HDs. From this analysis we show repertoire trends such as clonal expansion and evidence of biased IGH gene usage in repertoire of AChR-MG individuals. From preliminary genotypes we also uncovered novel IGHC alleles in both AChR-MG (70 alleles) and HDs (44 alleles) demonstrating diversity in IGHC. From this cohort we resolved the presence of increased hinge length variants in IgG3 that could drive increased complement fixation in some AChR-MG individuals. Collectively this combined work lays the foundation for future studies in IGHC diversity

Authors: Hoehn, KB; Pybus, OG; Kleinstein, SH

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Public Library of Science
• Journal: PLoS Computational Biology
• Volume: 18
• Issue: 4
• Pages: e1009885-e1009885
• Publication date: 2022-04-25
• DOI: 10.1371/journal.pcbi.1009885
• EISSN: 1553-7358
• ISSN: 1553-734X
• Language: English
• Keywords: Computer science; Phylogenetics; Class (philosophy); Gene; Computational biology; Biology; Genetics; Phylogenetic tree; Artificial intelligence; Evolutionary biology