A Bioinformatics Approach to Identify Natural Autoantibodies from Healthy Blood Donors' Sera Reactive with the HCV NS5A-Derived Peptide by Immunoassay

Abstract

Natural autoantibodies (NAbs) are continually produced throughout life and have an ability to recognize self and altered self, as well as foreign antigens, by recognizing cellular pattern recognition receptors. Sometimes NAb specificity demonstrates overlap between human and pathologic proteomes. This information can be useful in selecting target sequences for screening purposes. In this study we undertook a multi-step bioinformatics search to predict a virus-derived peptide that can be recognized by NAbs in sera of uninfected individuals. We selected protein hepatitis C virus (HCV) NS5A as a target sequence, motivated by the fact that the HCV proteome is characterized by extensive sequence similarities to the human proteome, and because screening for anti-HCV antibodies, including anti-NS5A, is important clinically, particularly in screening of potential blood donors. The virus-specific peptide P1, and the homologous human peptide derived from enzyme-inducible nitric oxide synthase (iNOS), P2, exhibiting not only simple homology, but also complementarities of physicochemical patterns, were synthesized and 80 HCV-negative and 50 HCV-positive blood donor sera were tested by ELISA. These peptides reacted similarly (p<0.001) with HCV-negative sera, and in several cases the measured reactivity was significantly above the cut-off value of commercial anti-HCV screening assays. In HCV-positive sera, the titers of antibodies reactive with analyzed HCV NS5A peptide were not significantly increased (p<0.001) compared to host peptide, the implications of which are unclear, but may be consistent with these antibodies being "naturally produced." Finally, we extended our bioinformatics analyses to the dataset of human self-binding sequences, and propose a general approach for the selection of specific diagnostic and screening antigens for use in immunoassays.