New Bioanalytical Methods Based on Next Generation Sequencing

描述(由申请人提供)：生物分子的检测和定量在生物医学研究和临床检测中具有重要意义。我们的目标是开发和应用新的生物分析方法，利用下一代测序(NGS)通常用于分析核酸、发现靶标特异性多肽配体以及高度并行分析它们之间相互作用的能力。我们的假设是，在核糖体展示(RD)条件下，通过体外翻译在多肽序列和它们的编码RNA之间建立直接联系，定量分析数百万 单次实验中的多肽将由NGS实现。下一代测序(NGS)使核酸分析发生了革命性的变化。单个实验中的NGS分析可以提供有关样本中数百万特定核酸序列的身份和相对丰度的信息。我们认为，通过结合核糖体展示(RD)和NGS分析，可以利用NGS分析的非凡能力来分析多肽相互作用。在RD中，编码肽序列的RNA在体外翻译，条件是肽产品及其对应的RNA与核糖体保持关联，有效地用唯一的RNA序列标签标记每个肽，从而能够应用NGS分析。我们为这种NGS增强型RD(NGSERD)方法设想了两个主要应用。第一个是将其用作配体发现工具(目标1)。NGSERD应用程序的一个特殊优势和独特功能将是将计算工具应用于NGS数据，从而能够发现复杂目标的配体，其中识别所需目标的真实配体必须从多余的虚假或非特定配体中挑选出来。NGSERD(AIM 2)的第二个应用将是将其用作一种新的高度平行的结合分析，其中NGS分析将提供唯一的读数，其中RNA序列标签将识别配基，该序列的读取计数将提供超灵敏的定量信号报告配基结合，使得能够在一次实验中分析大量(多达数百万)多肽试剂。一旦在AIMS 1和2中开发了NGSERD方法，我们将把它应用于人类血清中与疾病相关的抗体的分析。识别、检测、分析 而封闭抗体在自身免疫和传染病、癌症和疫苗开发方面具有巨大的研究、临床和治疗价值。为了建立基于NGSERD的抗体分析的实际应用范例，我们将把它应用于系统性红斑狼疮(SLE)，这是一种自身免疫性疾病，产生的针对自身抗原的抗体是疾病的病理机制。该项目的影响在于NGSERD方法在研究、疾病诊断和预后、疾病早期检测、治疗剂设计和疫苗开发中的许多令人兴奋的应用。

DESCRIPTION (provided by applicant): Detection and quantitation of biomolecules is of central importance in biomedical research and in clinical assays. Our goal is to develop and apply novel bioanalytical methodology that will utilize the power of Next Generation Sequencing (NGS) that is normally reserved for analysis of nucleic acids, for discovery of target-specific polypeptide ligands and for highly parallel analysis of their interactions. Our hypothesis is that y establishing a direct link between peptide sequences and their coding RNA through in vitro translation under ribosome display (RD) conditions, quantitative analysis of binding of millions of peptides in a single experiment will be enabled by NGS. Next Generation Sequencing (NGS) has revolutionized analysis of nucleic acids. NGS analysis in a single experiment can provide information on identity and relative abundance of millions of specific nucleic acid sequences in a sample. We propose that the extraordinary power of NGS analysis can be harnessed for analysis of polypeptide interactions by combining ribosome display (RD) with NGS analysis. In RD, RNA encoding peptide sequences is translated in vitro under conditions where peptide products and its corresponding RNA's remain associated with the ribosomes effectively labeling each peptide with a unique RNA sequence tag enabling application of NGS analysis. We envision two major applications for this NGS-enhanced RD (NGSERD) approach. The first will be to use it as a ligand discovery tool (aim 1). A particular strength and unique feature of this NGSERD application will be the possibility of applying computational tools to NGS data to enable discovery of ligands for complex targets where authentic ligands recognizing desired target have to be sorted out from excess of spurious or nonspecific ligands. The second application for NGSERD (aim 2) will be to use it as a novel highly parallel binding assay in which NGS analysis will provide a unique readout where the RNA sequence tag will identify the ligand and the read count for the sequence will provide supersensitive quantitative signal reporting ligand binding enabling analysis of a large number (up to millions) of peptide reagents in a single experiment. Once the NGSERD methodology is developed in aims 1&2, we will apply it for the analysis of disease-related antibodies in human serum. Identification, detection, profiling and blocking antibodies has tremendous research, clinical and therapeutic values in autoimmune and infectious diseases, in cancer and in vaccine development. To establish a paradigm for practical applications of NGSERD-based antibody analysis, we will apply it to systemic lupus erythematosus (SLE), an autoimmune disease in which the antibodies produced to self-antigens are responsible for the pathology of the disease. The impact of this project lies in multitudes of exciting applications of NGSERD approach in research, in disease diagnosis and prognosis, in early detection of the disease, in design of therapeutic agents, and in vaccine development.