Autoreactive B cells are associated with the development of several autoimmune
diseases, including systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA). The
low frequency of these cells represents a major barrier to their analysis.
Antigen-tetramers prepared from linear epitopes represent a promising strategy for the
identification of small subsets of antigen-reactive immune cells. This is challenging
given the requirement for identification and validation of linear epitopes and the
complexity of autoantibody responses, including the broad spectrum of autoantibody
specificities and the contribution of isotype to pathogenicity. We therefore tested a
two-tiered peptide microarray approach, coupled with epitope mapping of known
autoantigens, to identify and characterize autoepitopes using the BXD2 autoimmune mouse
model. Microarray results were verified through comparison with established age-associated
profiles of autoantigen specificities and autoantibody class switching in BXD2 and control
(B6) mice and high-throughput ELISA and ELISPOT analyses of synthetic peptides. Tetramers
were prepared from two linear peptides derived from two ribonucleic acid binding proteins
(RBP): lupus La and 70 kDa U1 small nuclear ribonucleoprotein (snRNP). Flow cyotmetric
analysis of tetramer-reactive B-cell subsets revealed a significantly higher frequency and
greater numbers of RBP-reactive marginal zone precursor (MZ-P), transitional T3 and
PDL-2+CD80+ memory B cells, with significantly elevated CD69 and
CD86 observed in RBP+ MZ-P B cells in the spleens of BXD2 compared to B6 mice,
suggesting a regulatory defect. This study establishes a feasible strategy for the
characterization of autoantigen-specific B-cell subsets in different models of
autoimmunity and, potentially, humans.