Review Computational analysis of high-density peptide microarray data with application from systemic sclerosis to multiple sclerosis Michael Hecker a, b, ⁎, Peter Lorenz a , Felix Steinbeck a, c , Li Hong a, d , Gabriela Riemekasten e , Yixue Li d , Uwe K. Zettl b , Hans-Jürgen Thiesen a, c a Department of Immunology, University of Rostock, Rostock, Germany b Department of Neurology, University of Rostock, Rostock, Germany c Gesellschaft für Individualisierte Medizin mbH (IndyMED), Rostock, Germany d Chinese Academy of Sciences, Shanghai Institutes for Biological Sciences, Key Lab of Systems Biology, Shanghai, PR China e Department of Rheumatology and Clinical Immunology, Charité Universitätsmedizin Berlin, Germany abstract article info Available online 18 May 2011 Keywords: Peptide microarrays Antibody epitope mapping Bioinformatics Multiple sclerosis Systemic sclerosis Auto-antibodies are implicated in the pathophysiology of various autoimmune diseases. High-density peptide microarrays incubated with human serum can detect antibody reactivities against thousands of peptides. This enables the identification of new auto-antigens and the determination of the parts of protein antigens (epitopes) that are recognized by antibody paratopes. We discuss the utility of peptide microarrays to investigate epitope-antibody-recognitions (EAR) from systemic sclerosis to multiple sclerosis. The technology can help to establish reliable diagnostic and prognostic biomarkers employing a combination of antigenic peptides. We describe the specifics of peptide microarray data and present bioinformatic methods for their analysis. Quality control, data pre-processing and the filtering of specific peptides are demonstrated on an example data set. Peptide microarrays representing 24 selected proteins by 3235 overlapping 15mer peptides were used to measure antibodies in serum of 10 patients with limited cutaneous systemic sclerosis (SSC) and 10 healthy blood donors. The data showed a sparse and skewed distribution, and we observed strong individual differences since many peptide sequences were bound by antibodies of only one serum sample. In the sera of the SSc patients, but not of the healthy controls, we found antibodies to three peptides MGPRRRSRKPEAPRR, TPTPGPSRRGPSLGA and GPSRRGPSLGASSHQ that share a similar sequence motif (GP-R/ S-RR). These peptides map to two known linear epitopes at the N-terminus of centromere protein A (CENPA), demonstrating the utility of peptide microarrays. Presented experimental and bioinformatic approach can be applied in the same manner for multiple sclerosis research. © 2011 Elsevier B.V. All rights reserved. Contents 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181 2. Experimental and bioinformatic methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182 2.1. Study population . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182 2.2. Preparation and staining of peptide microarrays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182 2.3. Data pre-processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 2.3.1. Image analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 2.3.2. Background correction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 2.3.3. Data truncation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 2.3.4. Outlier correction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 Autoimmunity Reviews 11 (2012) 180–190 Abbreviations: AA, amino acid; Ab, antibody; ACA, anti-centromere Ab; BSA, bovine serum albumin; CENPA, centromere protein A; CNS, central nervous system; CSF, cerebrospinal fluid; Ctr, healthy control; CV, coefficient of variation; dcSSc, diffuse cutaneous systemic sclerosis; ELISA, enzyme-linked immuno sorbent assay; HEp-2, human epithelioma type 2; ID, identifier; IgG, immunoglobulin G; lcSSc, limited cutaneous systemic sclerosis; MAID, MA plot-based signal intensity-dependent fold-change criterion; MS, multiple sclerosis; NMO, neuromyelitis optica; OCB, oligoclonal bands; PDB, Protein Data Bank; SSc, systemic sclerosis; SAM, significance analysis of microarrays; SD, standard deviation. ⁎ Corresponding author at: Department of Immunology, University of Rostock, Schillingallee 68, 18057 Rostock, Germany. Tel.: + 49 381 494 5891; fax: + 49 381 494 5882. E-mail address: michael.hecker@rocketmail.com (M. Hecker). 1568-9972/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.autrev.2011.05.010 Contents lists available at ScienceDirect Autoimmunity Reviews journal homepage: www.elsevier.com/locate/autrev