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Whole-Proteome Peptide Microarrays for Profiling Autoantibody Repertoires within Multiple Sclerosis and Narcolepsy.

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Path 3
  • Scientific Publication
  • January 25, 2017

Zandian A, et al. (2017) “Whole-Proteome Peptide Microarrays for Profiling Autoantibody Repertoires within Multiple Sclerosis and Narcolepsy.” J Proteome Res. 16(3): 1300-13. doi: 10.1021/acs.jproteome.6b00916

Abstract

The underlying molecular mechanisms of autoimmune diseases are poorly understood. To unravel the autoimmune processes across diseases, comprehensive and unbiased analyses of proteins targets recognized by the adaptive immune system are needed. Here we present an approach starting from high-density peptide arrays to characterize autoantibody repertoires and to identify new autoantigens. A set of ten plasma and serum samples from subjects with multiple sclerosis, narcolepsy, and without any disease diagnosis were profiled on a peptide array representing the whole proteome, hosting 2.2 million 12-mer peptides with a six amino acid lateral shift. On the basis of the IgG reactivities found on these whole-proteome peptide microarrays, a set of 23 samples was then studied on a targeted array with 174 000 12-mer peptides of single amino acid lateral shift. Finally, verification of IgG reactivities was conducted with a larger sample set (n = 448) using the bead-based peptide microarrays. The presented workflow employed three different peptide microarray formats to discover and resolve the epitopes of human autoantibodies and revealed two potentially new autoantigens: MAP3K7 in multiple sclerosis and NRXN1 in narcolepsy. The presented strategy provides insights into antibody repertoire reactivity at a peptide level and may accelerate the discovery and validation of autoantigens in human diseases.

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PreviousHigh-throughput immuno-profiling of mamba (Dendroaspis) venom toxin epitopes using high-density peptide microarrays.
NextEpitopes of anti-RIFIN antibodies and characterization of rif-expressing Plasmodium falciparum parasites by RNA sequencing.
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