Deconvoluting virome-wide antibody epitope reactivity profiles

作者：Daniel R. Monaco, Sanjay Kottapalli, Florian P. Breitwieser, Danielle E. Anderson, Limin Wijaya, Kevin Tan, Wan Ni Chia, Kai Kammers, Patrizio Caturegli, Kathleen Waugh, Mario Roederer, Michelle Petri, Daniel Goldman, Marian Rewers, Lin‐Fa Wang, H. Benjamin Larman · 发表于：EBioMedicine · 年份：2021 · DOI：10.1016/j.ebiom.2021.103747 · 被引用次数：40 · 研究领域：vaccines and immunoinformatics approaches、Diabetes and associated disorders、Systemic Lupus Erythematosus Research

BACKGROUND: Comprehensive characterization of exposures and immune responses to viral infections is critical to a basic understanding of human health and disease. We previously developed the VirScan system, a programmable phage-display technology for profiling antibody binding to a library of peptides designed to span the human virome. Previous VirScan analytical approaches did not carefully account for antibody cross-reactivity among sequences shared by related viruses or for the disproportionate representation of individual viruses in the library. METHODS: Here we present the AntiViral Antibody Response Deconvolution Algorithm (AVARDA), a multi-module software package for analyzing VirScan datasets. AVARDA provides a probabilistic assessment of infection with species-level resolution by considering sequence alignment of all library peptides to each other and to all human viruses. We employed AVARDA to analyze VirScan data from a cohort of encephalitis patients with either known viral infections or undiagnosed etiologies. We further assessed AVARDA's utility in associating viral infection with type 1 diabetes and lupus. FINDINGS: By comparing acute and convalescent sera, AVARDA successfully confirmed or detected encephalitis-associated responses to human herpesviruses 1, 3, 4, 5, and 6, improving the rate of diagnosing viral encephalitis in this cohort by 44%. AVARDA analyses of VirScan data from the type 1 diabetes and lupus cohorts implicated enterovirus and herpesvirus in...