Computational mapping of human B cell migration and differentiation pathways

Human B cells play a fundamental role in the adaptive immune response to infection, development of protective immunity from vaccination, and pathology of many autoimmune diseases. Central to all of these processes are migration of B cells among different tissues and differentiation of B cells into functional subtypes. Currently, understanding B cell migration and differentiation is limited because these processes are dynamic and difficult to directly observe, particularly in humans. Our previous work has demonstrated that it is possible to detect migration and differentiation events along evolutionary trees inferred from B cell receptor (BCR) sequences, which are subject to rapid somatic hypermutation and antigen-driven selection during adaptive immune responses. This is analogous to viral phylogeography, the use of evolutionary trees to track the spread of viruses during epidemics. However, there are key differences in the biology of B cells and viruses that require modifying and extending existing approaches to make them appropriate for B cells. The goal of this proposal is to enable B cell phylogeography. We will develop novel computational methods that leverage recent advances in single B cell sequencing technology to infer how B cells migrate between tissues and differentiate into cellular subtypes based on their activation states during immune responses. The aims of this proposal focus on solving the roadblocks to the development of phylogeographic methods for B cells. These methods will be validated by simulations and experimental analysis. We will work with established experimental collaborators to translate these novel methods into meaningful outcomes in the research of influenza vaccine response and the treatment of autoimmune diseases, including lupus and myasthenia gravis. We will implement these methods in widely available free software, which will greatly increase their potential to inform vaccination strategies against other pathogens like HIV and SARS-CoV-2, as well as treatment of other B cell-mediated conditions such as multiple sclerosis and asthma. The K99 phase of this proposal will be guided by Prof. Steven Kleinstein at Yale School of Medicine, a world leader in computational methods development for BCR sequence analysis, and Prof. Kevin O'Connor, a leading experimental biologist in the B cell pathology of neurologic autoimmune diseases. The candidate, Dr. Kenneth Hoehn, has a strong background in genetics and evolutionary biology, and has an established record of developing evolutionary models to study B cell populations from BCR sequence data. The work detailed in this proposal will fill gaps in the candidate's training in B cell biology, single cell analysis, and software development. The R00 phase will build off of this work to develop a highly generalizable framework for characterizing the complex migration and differentiation patterns that underlie B cells' role in vaccination and autoimmunity. This will support new, medically-relevant discoveries about B cell biology, and serve as a foundation for the candidate's future as an independent computational immunologist.