Hansen Christian Skjødt, Østerbye Thomas, Marcatili Paolo, Lund Ole, Buus Søren, Nielsen Morten
Center for Biological Sequence Analysis, Department of Bio and Health Informatics, Technical University of Denmark, Kgs. Lyngby, Denmark.
Laboratory of Experimental Immunology, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark.
PLoS One. 2017 Jan 17;12(1):e0168453. doi: 10.1371/journal.pone.0168453. eCollection 2017.
Identification of epitopes targeted by antibodies (B cell epitopes) is of critical importance for the development of many diagnostic and therapeutic tools. For clinical usage, such epitopes must be extensively characterized in order to validate specificity and to document potential cross-reactivity. B cell epitopes are typically classified as either linear epitopes, i.e. short consecutive segments from the protein sequence or conformational epitopes adapted through native protein folding. Recent advances in high-density peptide microarrays enable high-throughput, high-resolution identification and characterization of linear B cell epitopes. Using exhaustive amino acid substitution analysis of peptides originating from target antigens, these microarrays can be used to address the specificity of polyclonal antibodies raised against such antigens containing hundreds of epitopes. However, the interpretation of the data provided in such large-scale screenings is far from trivial and in most cases it requires advanced computational and statistical skills. Here, we present an online application for automated identification of linear B cell epitopes, allowing the non-expert user to analyse peptide microarray data. The application takes as input quantitative peptide data of fully or partially substituted overlapping peptides from a given antigen sequence and identifies epitope residues (residues that are significantly affected by substitutions) and visualize the selectivity towards each residue by sequence logo plots. Demonstrating utility, the application was used to identify and address the antibody specificity of 18 linear epitope regions in Human Serum Albumin (HSA), using peptide microarray data consisting of fully substituted peptides spanning the entire sequence of HSA and incubated with polyclonal rabbit anti-HSA (and mouse anti-rabbit-Cy3). The application is made available at: www.cbs.dtu.dk/services/ArrayPitope.
鉴定抗体靶向的表位（B细胞表位）对于许多诊断和治疗工具的开发至关重要。对于临床应用，此类表位必须进行广泛表征，以验证特异性并记录潜在的交叉反应性。B细胞表位通常分为线性表位，即蛋白质序列中的短连续片段，或通过天然蛋白质折叠形成的构象表位。高密度肽微阵列的最新进展使得能够高通量、高分辨率地鉴定和表征线性B细胞表位。通过对源自靶抗原的肽进行详尽的氨基酸取代分析，这些微阵列可用于研究针对含有数百个表位的此类抗原产生的多克隆抗体的特异性。然而，对此类大规模筛选中提供的数据进行解释绝非易事，在大多数情况下需要先进的计算和统计技能。在此，我们展示了一个用于自动鉴定线性B细胞表位的在线应用程序，使非专业用户能够分析肽微阵列数据。该应用程序将来自给定抗原序列的完全或部分取代的重叠肽的定量肽数据作为输入，识别表位残基（受取代显著影响的残基），并通过序列标志图可视化对每个残基的选择性。为展示其效用，该应用程序利用由跨越人血清白蛋白（HSA）整个序列的完全取代肽组成的肽微阵列数据，并与多克隆兔抗HSA（和小鼠抗兔-Cy3）孵育，用于鉴定和研究HSA中18个线性表位区域的抗体特异性。该应用程序可在以下网址获取：www.cbs.dtu.dk/services/ArrayPitope。
