An Efficient Phage Display Based Protease Activity Profiling Platform

项目概要/摘要 蛋白质裂解是一个严格调控的生物学过程，在癌症中通常功能失调。的 缺乏可扩展的、无偏倚的测定方法严重限制了我们表征蛋白酶谱的能力 底物，或测量肿瘤样本、血液或尿液样品内的蛋白水解活性。这里 我们建议开发一种有效的基于噬菌体展示的蛋白酶活性分析平台， 对与人类癌症相关的蛋白酶活性进行敏感和无偏的分析。 在初步研究中，我们展示了一种新的噬菌体展示载体，加上一个完整的 人“肽组”噬菌体文库可用于有效地分析蛋白酶。我们将其命名为 方法通过标签表位的去除或“分离”来感测内肽酶活性。初始 实验表明，当蛋白酶在以下条件下被分析时， 生理浓度，并且可以从这种分析中产生新的生物学见解。 在这里，我们建议开发工作流程和分析管道，以实现无偏见的SEPARATE分析 （i）重组蛋白酶，（ii）复杂的生物样品，和（iii）遗传编码的蛋白酶。 我们预计，过程自动化和样品多路复用将实现高度可重复性， 便宜（每个样品约40美元），蛋白酶活性的蛋白质组范围分析。 目的1：建立单酶与生物样品的固相分离技术。 将开发一个灵活、优化的工作流程来分析重组蛋白酶和复合物 生物标本使用来自不同催化类别的蛋白酶，我们将优化SEPARATE 测定条件并确定测定性能指标。该平台的效用将由 验证与癌症生物学/免疫学相关的新型蛋白酶底物。 目标2：建立基因编码蛋白酶的“共表达”分离。 大多数蛋白酶不能作为活性酶商购获得。基因侧写的能力 以高通量编码的蛋白酶将能够产生大的蛋白酶-底物数据库， 最终促进复杂的SEPARATE数据的反褶积。将建立一个系统， 在E.大肠杆菌宿主细胞仅在人类的活跃复制期间 肽组文库。将展示切割的肽与展示切割的肽分离的方法 将开发未裂解的肽。复杂生物样品的分析数据将 通过大的蛋白酶-肽查找表解卷积。 影响：该项目将为癌症研究人员提供全面分析的能力 单个蛋白酶以及复杂的癌症相关生物样品的高通量检测。

PROJECT SUMMARY/ABSTRACT Protein cleavage is a tightly regulated biological process, which is often dysfunctional in cancer. The lack of scalable, unbiased assays has severely limited our ability to characterize the spectrum of protease substrates, or to measure proteolytic activities within tumor specimens, blood or urine samples. Here we propose to develop an efficient phage display based protease activity profiling platform to enable the sensitive and unbiased analysis of protease activities associated with human cancers. In preliminary studies, we demonstrate how a novel phage display vector, coupled with a complete human ‘peptidome’ phage library, can be used to efficiently profile proteases. We have named this approach Sensing EndoPeptidase Activities via RemovAl of Tag Epitopes, or ‘SEPARATE’. Initial experiments indicate that substrate cleavage can be robustly detected when proteases are profiled at physiological concentrations, and that novel biological insight can arise from such analyses. Here we propose to develop workflows and analytical pipelines for unbiased SEPARATE profiling of (i) recombinant proteases, (ii) complex biological samples, and (iii) genetically encoded proteases. We expect that process automation and sample multiplexing will enable highly reproducible, inexpensive (~$40 per sample), proteome-wide profiling of protease activities. Aim 1: Establish ‘solid phase’ SEPARATE for single enzymes and biological samples. A flexible, optimized workflow will be developed to analyze recombinant proteases and complex biological specimens. Using proteases from different catalytic classes, we will optimize the SEPARATE assay conditions and determine assay performance metrics. The utility of the platform will be tested by validating novel protease substrates of relevance to cancer biology/immunology. Aim 2: Establish ‘co-expression’ SEPARATE for genetically-encoded proteases. Most proteases are not commercially available as active enzymes. The ability to profile genetically encoded proteases in high throughput would enable generation of a large protease-substrate database, ultimately facilitating the deconvolution of complex SEPARATE data. A system will be established to express recombinant proteases inside E. coli host cells only during active replication of the human peptidome library. Methods of separating phages displaying cleaved peptides from phages displaying uncleaved peptides will be developed. Data from the analysis of complex biological samples will be deconvoluted by means of a large protease-peptide lookup table. Impact: This project will provide cancer researchers with the ability to comprehensively profile individual proteases, as well as complex cancer-relevant biological samples in high throughput.