An Integrated Multi-omic Single-Cell Atlas of Human B Cell Identity.
David R Glass1, Albert G Tsai2, John Paul Oliveria3
1Immunology Graduate Program, Stanford University, Stanford, CA, 94305, USA; Department of Pathology, Stanford University, Stanford, CA, 94305, USA.
Immunity
|July 16, 2020
Summary
Researchers developed a new method to classify human B cells based on surface molecules. This classification identifies twelve unique B cell subsets, aiding in understanding their diverse functions for clinical applications.
Area of Science:
- Immunology
- Cell Biology
- Translational Medicine
Background:
- Human B cells exhibit diverse effector functions crucial for immunity.
- A standardized classification of B cells is needed for clinical applications.
- Understanding B cell heterogeneity is key to harnessing their potential.
Purpose of the Study:
- To develop a comprehensive classification system for human B cells.
- To identify unique B cell subsets based on surface molecule expression.
- To link B cell subsets to their functional characteristics.
Main Methods:
- Utilized a highly multiplexed screening approach to analyze 351 surface molecules.
- Quantified co-expression patterns on millions of human B cells from four lymphoid tissues.
- Integrated surface molecule data with isotype usage, VDJ sequence, metabolic profiles, and signaling responses.
Main Results:
- Identified differentially expressed surface molecules across human B cell populations.
- Proposed a novel classification scheme defining twelve distinct B cell subsets.
- Characterized subsets including CD45RB+CD27- early memory and CD39+ tonsil-resident B cells.
- Identified a CD19hiCD11c+ memory population with potent immune activation response.
Conclusions:
- The proposed classification framework provides a valuable resource for B cell research.
- This classification aids in understanding human B cell identity and functional diversity.
- The findings facilitate further investigation and potential clinical translation of B cell functions.
