학술논문

Validation of a murine proteome-wide phage display library for identification of autoantibody specificities
Document Type
article
Source
JCI Insight. 8(23)
Subject
Biomedical and Clinical Sciences
Immunology
Autoimmune Disease
Diabetes
Lupus
Biotechnology
Genetics
2.1 Biological and endogenous factors
Aetiology
Inflammatory and immune system
Animals
Mice
Inbred NOD
Humans
Mice
Bacteriophages
Peptides
Proteome
Autoantibodies
Autoimmunity
Adaptive immunity
Antigen
Autoimmune diseases
Biomedical and clinical sciences
Health sciences
Language
Abstract
Autoimmunity is characterized by loss of tolerance to tissue-specific as well as systemic antigens, resulting in complex autoantibody landscapes. Here, we introduce and extensively validate the performance characteristics of a murine proteome-wide library for phage display immunoprecipitation and sequencing (PhIP-seq) in profiling mouse autoantibodies. This library was validated using 7 genetically distinct mouse lines across a spectrum of autoreactivity. Mice deficient in antibody production (Rag2-/- and μMT) were used to model nonspecific peptide enrichments, while cross-reactivity was evaluated using anti-ovalbumin B cell receptor-restricted OB1 mice as a proof of principle. The PhIP-seq approach was then utilized to interrogate 3 distinct autoimmune disease models. First, serum from Lyn-/- IgD+/- mice with lupus-like disease was used to identify nuclear and apoptotic bleb reactivities. Second, serum from nonobese diabetic (NOD) mice, a polygenic model of pancreas-specific autoimmunity, was enriched in peptides derived from both insulin and predicted pancreatic proteins. Lastly, Aire-/- mouse sera were used to identify numerous autoantigens, many of which were also observed in previous studies of humans with autoimmune polyendocrinopathy syndrome type 1 carrying recessive mutations in AIRE. These experiments support the use of murine proteome-wide PhIP-seq for antigenic profiling and autoantibody discovery, which may be employed to study a range of immune perturbations in mouse models of autoimmunity profiling.