Single-cell profiling of antibody repertoires and transcriptomes from B cells to determine the relationship with antigen-specificity and aging
Description: The humoral immune response is mediated by B-cells and their vast collection of molecularly diverse antibodies. This antibody repertoire represents both the past and current immunological status of an individual. Recent progress in deep sequencing and bioinformatics has catalyzed a systems level view of antibody repertoires and B-cell responses. However, most studies have relied on deep sequencing in bulk (pooled B-cells), which does not preserve the native variable heavy (VH) and variable light (VL) chain pairing, and thus is unable to recover specificity (antigen-binding) in antibody repertoires. Additionally, to date there has been little research related to how B-cell transcriptional profiles influence antibody repertoires and their cognate specificities. Finally, aging in the immune system, commonly referred to as immune senescence has been shown to dampen adaptive immune responses; while systems level work on T-cells has been performed, there is little information on how aging impacts B-cells and antibody repertoires as well as their direct contribution to age-related homeostasis in certain tissues like the brain. The overall goal of this proposal is to answer fundamental and systems level questions related to basic B-cell biology (clonal selection, expansion and evolution) (Project 1) and the role of infiltrating B-cells in the brain (Project 2) within the context of aging in the immune system. This will be accomplished by using single-cell sequencing of antibody repertoires and transcriptomes. Furthermore, our previous expertise in deep sequencing, bioinformatics, genome editing and machine learning will enable us to perform an in-depth and multifaceted set of studies. First, we will perform single-cell sequencing to simultaneously obtain the paired VH and VL chain repertoire and transcriptomes from B-cells of immunized (Project 1) and unimmunized (Project 2) mice (Aim 1). An important aspect of our study will be the use of both young and old mice which will address how B-cells and antibody repertoires are impacted by aging. Next, we will take advantage of the fact that single-cell sequencing will provide us with both the VL and VH chain sequences from B-cells, thus providing the information needed to reconstruct full antibodies with their native binding properties. We will then use our established mammalian cell antibody expression system to screen for antigen-specificity among the highly clonally expanded B-cells (Aim 2). At the conclusion of this aim we will be able to answer several fundamental questions on how clonal expansion and evolution are related to antigen-specificity. Finally, we will use the information on antibody repertoires and antigen specificity and combine it with single-cell transcriptome data to gain a multi-dimensional profile of B-cells (Aim 3). Furthermore, by performing analysis on both young (2.5 months) and old mice (12 and 18 months), we will gain insight into how aging impacts the clonal selection, expansion, evolution and transcriptome profile of B-cells (Project 1) and we will be able to directly gain mechanistic insights into the specificity and potential role of clonally expanded B cells in the brain (Project 2). In addition to single-cell sequencing and antibody screening assays, we will also take advantage of machine learning to determine if antigen-specificity can be predicted from transcriptome clustering. In addition to answering long-standing questions in humoral immunity, this proposal may finally lead to novel approaches for antibody drug discovery and humoral immune profiling after vaccination or infection as well as new biomarkers for B-cell mediated pathologies in the brain.
Amount: CHF 712,800
Funding type: research
Funder scheme: Project funding
Start date: 2020-11-01
End date: 2024-10-31
Investigator: Reddy, Sai
Institution: ETH Zurich – ETHZ
Funded outputs count: 7
Funder award ID: 197941
OpenAlex ID: G6992482453