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

描述 摘要： 用于快速获取基因组和基因表达信息的下一代DNA测序方法的发展已经改变了生物学。“下一代”DNA测序的基础是并行获取大量的短读段（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显微镜监测单个DNA分子的测序，允许大约100个DNA分子。每次运行十亿次测序读取。不幸的是，不存在类似规模和通量的方法来鉴定和定量复杂混合物中的特定蛋白质，这代表了许多生物化学、分子诊断和生物标志物发现测定中的关键瓶颈。迫切需要的是一种类似于下一代DNA测序的大规模并行方法，用于识别和定量样品中的单个肽或蛋白质。我提出了一个单分子肽测序策略，将实现这一目标。原则上，这将允许对数十亿个不同的肽进行平行测序（或至少充分测序 以提供信息序列模式），从而鉴定组成样品的蛋白质并通过肽的直接计数对其进行数字定量。这种变革性的方法应该能够实现蛋白质的定量，大规模并行测序。这项研究的成功将为现实世界的蛋白质测序问题创造一种足够的技术。这种方法将在生物学和医学领域具有广泛的应用，并且可能像PCR用于核酸研究一样对蛋白质具有基础性作用。潜在的应用包括，例如，正常身体小生境或疾病中蛋白质表达的谱分析、元蛋白质组学、循环血清抗体的谱分析、蛋白质翻译后修饰的搜索和定量，以及特别感兴趣的，鉴定与癌症和传染病相关的生物标志物。

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 wil create a technology suficiently 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, identifyin biomarkers relevant to cancer and infectious diseas