Next-Generation Proteomics: Massively Parallel Single-Molecule Protein Identifica

下一代蛋白质组学：大规模并行单分子蛋白质鉴定

• 批准号: 8710285
• 负责人: EDWARD M MARCOTTE
• 金额: $ 77.25万
• 依托单位: UNIVERSITY OF TEXAS AT AUSTIN
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-30 至 2017-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8710285
• 关键词: Amino Acid Sequence; Antibodies; Biochemical; Biological Assay; Biological Markers; Biology; Biopsy; Blood; Communicable Diseases; Complex Mixtures; DNA; DNA Sequence; Development; Diagnosis; Diagnostic; Disease; Fluorescence Microscopy; Gene Expression; Genome; Goals; Growth; Individual; Malignant Neoplasms; Massive Parallel Sequencing; Medicine; Methods; Molecular; Monitor; Mutation; Nucleic Acids; Nucleotides; Pattern; Peptide Sequence Determination; Peptides; Post-Translational Protein Processing; Procedures; Proteins; Proteomics; Reading; Research; Running; Saliva; Sampling; Serum; Technology; Urine; abstracting; base; cancer diagnosis; interest; next generation; protein aminoacid sequence; protein expression; protein profiling; single molecule; success

DESCRIPTION Abstract: The development of next-generation DNA sequencing methods for quickly acquiring genome and gene expression information has transformed biology. The basis of “next-gen” DNA sequencing is the acquisition of large numbers of short reads (typically 35–500 nucleotides) in parallel. Currently available single-molecule next-gen sequencing platforms monitor the sequencing of single DNA molecules using fluorescence microscopy, allowing for approx. a billion sequencing reads per run. Unfortunately, no method of similar scale and throughput exists to identify and quantify specific proteins in complex mixtures, representing a critical bottleneck in many biochemical, molecular diagnostic, and biomarker discovery assays. What is urgently needed is a massively parallel method, akin to next-gen DNA sequencing, for identifying and quantifying individual peptides or proteins in a sample. I propose a single-molecule peptide sequencing strategy that will achieve exactly this goal. This will in principle allow billions of distinct peptides to be sequenced in parallel (or at least sequenced sufficiently to provide informative sequence patterns), thereby identifying proteins composing the sample and digitally quantifying them by direct counting of peptides. This transformative approach should enable the quantitative, massively parallel sequencing of proteins. Success of the proposed research will create a technology sufficiently ready for real-world protein sequencing problems. Such an approach would have broad applications across biology and medicine, and could be as fundamental for proteins as, for example, PCR is for nucleic acid research. Potential applications include, for example, profiling of protein expression in normal body niches or in disease, metaproteomics, profiling the circulating serum antibodies, the search for and quantification of protein post-translational modifications, and, of particular interest, identifying biomarkers relevant to cancer and infectious diseases. In short, single-molecule sequencing could potentially solve many of the problems currently limiting the field of proteomics and biomarker discovery, promising improvements of more than 5 orders of magnitude in sensitivity and throughput and offering a path forward that can reasonably be expected to mirror the phenomenal growth and impact of next-gen DNA sequencing.

描述 抽象的： 下一代DNA测序方法的开发，用于快速研究基因组和基因 表达信息已改变了生物学。 “下一代” DNA测序的基础是获取 并联大量的简短读数（通常为35-500个核苷酸）。目前可用的单分子 下一代测序平台使用荧光监测单个DNA分子的测序 显微镜，允许大约。每次运行的十亿个测序读数。不幸的是，没有类似规模的方法 存在吞吐量，以识别和量化复杂混合物中的特定蛋白质，代表关键 许多生化，分子诊断和生物标志物发现分析中的瓶颈。什么是迫切的 所需的是一种类似于下一代DNA测序的大规模平行方法，用于识别和量化 样品中的个体宠物或蛋白质。我提出了一种单分子胡椒测序策略 实现这一目标。原则上，这将允许并行排序数十亿个不同的辣椒（或 至少正确测序以提供信息序列模式），从而识别蛋白质 组成样品并通过直接计数肽来量化它们。这种变革性 方法应实现蛋白质的定量，大规模平行的测序。提议的成功 研究将为现实世界中的蛋白质测序问题提供足够的准备。 方法将在生物学和医学范围内广泛应用，并且可能对 例如，蛋白质为PCR用于核酸研究。潜在应用包括，例如分析 正常体壁细分市场或疾病，元蛋白质组学中的蛋白质表达，分析循环系统 抗体，对蛋白质后翻译后修饰的搜索和定量，特别是 兴趣，确定与癌症和传染病有关的生物标志物。简而言之，单分子 测序可能会解决当前限制蛋白质组学领域和的许多问题 生物标志物发现，有望改善敏感性和吞吐量超过5个数量级 并提供一条前进的道路，可以合理地期望反映现象的增长和影响 下一代DNA测序。