An Efficient Phage Display Based Protease Activity Profiling Platform

项目摘要/摘要 蛋白质裂解是一个严格控制的生物过程，在癌症中通常是功能失调的。这个 缺乏可伸缩的、无偏倚的分析严重限制了我们表征蛋白酶谱的能力。 或测量肿瘤标本、血液或尿样中的蛋白分解活性。这里 我们建议开发一个高效的基于噬菌体展示的蛋白酶活性分析平台，以使 对与人类癌症有关的蛋白水解酶活性的敏感和公正的分析。 在初步研究中，我们展示了一种新的噬菌体展示载体，与完整的 人的‘多肽’噬菌体文库，可以用来有效地分析蛋白酶。我们已将其命名为 通过去除标签表位或“分离”来检测内肽酶活性。首字母 实验表明，当蛋白水解酶被分析到 生理集中，这种新的生物学洞察力可以从这种分析中产生。 在这里，我们建议开发工作流和分析管道，以实现无偏见的单独分析 (I)重组蛋白水解酶、(Ii)复杂生物样本和(Iii)基因编码的水解酶。 我们预计，过程自动化和样品多路传输将实现高度可重复性， 价格低廉(每个样本约40美元)，对整个蛋白质组的蛋白酶活性进行分析。 目的1：建立单酶和生物样品的“固相”分离。 将开发一个灵活的、优化的工作流程来分析重组蛋白酶和复合体 生物标本。使用不同催化类别的蛋白酶，我们将优化分离 分析条件并确定分析性能指标。平台的效用将通过以下方式进行测试 验证与癌症生物学/免疫学相关的新的蛋白酶底物。 目的2：建立基因编码的蛋白水解酶的“共表达”分离。 大多数蛋白水解酶在商业上都不是活性酶。从基因上分析的能力 高通量编码的蛋白水解酶将能够产生大的蛋白水解酶底物数据库， 最终促进了复杂的分离数据的去卷积。将建立一个制度，以 只有在人的活性复制过程中才能在大肠杆菌宿主细胞中表达重组蛋白酶 多肽文库。展示裂解肽的噬菌体与展示噬菌体的分离方法 未切割的多肽将被开发出来。来自复杂生物样本分析的数据将是 通过一个大的蛋白酶-多肽查询表进行去卷积。 影响：该项目将为癌症研究人员提供全面描述 单独的蛋白酶，以及与癌症相关的复杂生物样本的高通量。

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.