PPiSeq: High-Throughput Protein-Protein Interaction Sequencing

PPiSeq：高通量蛋白质-蛋白质相互作用测序

• 批准号: 9145264
• 负责人: SASHA F LEVY
• 金额: $ 33.36万
• 依托单位: STATE UNIVERSITY NEW YORK STONY BROOK
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-16 至 2019-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9145264
• 关键词: Antifungal Agents; Biological Assay; Buffers; Cataloging; Catalogs; Cells; Cellular biology; Chromosomes; Chromosomes, Human, Pair 3; Communities; DNA; Diploidy; Drug Targeting; Drug resistance; Environment; Fungal Drug Resistance; Future; Genes; Genotype; Growth; Haploidy; Health; Heating; Left; Libraries; Measurement; Measures; Mutation; Partner in relationship; Pharmaceutical Preparations; Phenotype; Play; Process; Protein Engineering; Protein Fragment; Proteins; Resistance; Resources; Role; Saccharomyces cerevisiae; Staging; Stress; Structure; System; Technology; Temperature; Testing; Time; Translating; Variant; Work; Yeasts; assault; cell growth; cost; drug discovery; fitness; genome-wide; high throughput screening; in vivo; innovation; insight; macromolecule; next generation sequencing; novel therapeutics; protein complex; protein protein interaction; research study; response; sequencing platform; tool; yeast protein

 DESCRIPTION (provided by applicant): Large-scale protein-protein interaction assays are widely useful in studies of protein interaction networks, drug activity, and protein engineering. The protein-fragment complementation (PCA) assay screens for in vivo protein-protein interactions (PPIs) in Saccharomyces cerevisiae by converting the strength of an interaction to a relative fitness. For each PPI, protein-fragment-containing haploid yeast pairs are mated and the resulting diploids are tested one-at-a-time. We have developed three technologies that will make PCA more repeatable and higher throughput: 1) a random DNA barcode system that allows us to construct millions of uniquely barcoded yeast strains, 2) a double barcode system that translocates two barcodes on homologous chromosomes to close proximity on the same chromosome, and 3) a pooled fitness assay that allows for accurate measurements of the relative fitness of millions of barcoded genotypes simultaneously via next- generation sequencing. We propose to combine PCA with the above three innovations to generate a massively parallel protein-protein interaction sequencing platform (PPiSeq). Random barcodes are inserted into yeast and are mated to existing PCA strains. Mating of barcoded haploid PCA pools and translocation of barcodes in vivo and en masse yields diploid PCA strains, each with a double barcode representing a specific PPI. Growth of cell pools and sequencing of double barcodes yields an accurate fitness measurement of each double barcode in the pool, which can be translated to an interaction score for each pairwise protein combination. PPiSeq will have have several significant advantages over traditional PCA: it is fast, cheap, highly scalable, and has a low barrier to entry. Notably, PPiSeq throughput scales quadratically with the number of PCA strains, while its costs decline at the rate of next generation sequencing costs. Here, we will construct a large diploid PPiSeq library consisting of ~655,000 unique PPIs and ~6 million double barcodes and use this library to measure the interaction score of each PPI simultaneously via pooled growth (AIM 1). One additional major advantage of PPiSeq over traditional PCA is repeatability across perturbations. That is, once constructed, all pairwise interactions can be re-assayed in new environments easily. Here, we will assay how the yeast protein interactome changes in a heat gradient (AIM 2) and in the presence of three antifungal drugs (AIM 3). This work will provide the first genome-scale view of how the protein interactome changes across perturbations. The constructed PPiSeq library will be provided as a resource to the scientific community for future perturbation studies. Additionally, this work will set the stag for future large-scale PPI screens, such as those involved in drug discovery and protein engineering.

 描述（由申请人提供）：大规模蛋白质-蛋白质相互作用测定广泛用于蛋白质相互作用网络、药物活性和蛋白质工程的研究。蛋白质片段互补（PCA）测定通过将相互作用的强度转换为相对适合度来筛选酿酒酵母中的体内蛋白质-蛋白质相互作用（PPI）。对于每个PPI，将含有蛋白质片段的单倍体酵母配对，并一次一个地测试所得的二倍体。我们开发了三种技术，使PCA更具可重复性和更高的吞吐量：1）随机DNA条形码系统，其允许我们构建数百万个独特条形码化的酵母菌株，2）双条形码系统，其将同源染色体上的两个条形码易位到同一染色体上的紧密接近，和3）允许通过下一代测序同时精确测量数百万个条形码化基因型的相对适合度的汇集适合度测定。我们提出将联合收割机PCA与上述三个创新相结合，以生成大规模并行蛋白质-蛋白质相互作用测序平台（PPiSeq）。将随机条形码插入酵母中并与现有PCA菌株交配。条形码化的单倍体PCA池的交配和条形码的体内易位和传代产生二倍体PCA菌株，每个菌株具有代表特定PPI的双条形码。细胞池的生长和双条形码的测序产生池中每个双条形码的准确适合度测量，其可以转化为每个成对蛋白质组合的相互作用评分。PPiSeq与传统PCA相比有几个显著的优势：快速，廉价，高度可扩展，进入门槛低。值得注意的是，PPiSeq的通量与PCA菌株的数量成二次方，而其成本以下一代测序成本的速度下降。在这里，我们将构建一个由约655，000个独特PPI和约600万个双条形码组成的大型二倍体PPiSeq文库，并使用该文库通过合并生长（AIM 1）同时测量每个PPI的相互作用评分。PPiSeq相对于传统PCA的另一个主要优势是扰动的可重复性。也就是说，一旦构建，所有成对相互作用可以在新环境中容易地重新测定。在这里，我们将分析酵母蛋白相互作用组如何在热梯度（AIM 2）和三种抗真菌药物（AIM 3）的存在下发生变化。这项工作将提供第一个基因组规模的蛋白质相互作用组如何在扰动中变化的观点。构建的PPiSeq库将作为科学界未来微扰研究的资源。此外，这项工作将为未来的大规模PPI筛选奠定基础，例如涉及药物发现和蛋白质工程的筛选。