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（由适用提供）：大规模蛋白质 - 蛋白质相互作用测定在蛋白质相互作用网络，药物活性和蛋白质工程方面广泛有用。通过将相互作用的强度转换为相对适应性的强度，在酿酒酵母中用于体内蛋白质 - 蛋白质相互作用（PPI）的蛋白质碎片完成（PCA）测定筛选。对于每个PPI，含有蛋白质的单倍体酵母对配对，并对产生的二倍体进行一次测试。我们已经开发了三种技术，可以使PCA更具重复性和更高的吞吐量：1）随机DNA条形码系统，使我们能够构建数百万个独特的条形码酵母菌菌株，2）一个双条形码系统，可以使同种染色体上的同源染色体上的两个条形码易于易于衡量，并在同一镀层上均具有相对量的相对性，并均可衡量3），并具有3）的准确性。仅通过下一代测序即可进行条形码基因型。我们建议将PCA与上述三个创新相结合，以生成大量平行的蛋白质 - 蛋白质相互作用测序平台（PPISEQ）。随机条形码插入酵母中，并与现有的PCA菌株配对。条形码单倍体PCA池的交配以及体内和ensse的条形码的易位可产生二倍体PCA菌株，每个PCA菌株均具有代表特定PPI的双条形码。细胞池的生长和双条形码的测序可对池中每个双条形码进行准确的适应性测量，这可以将每个成对蛋白组合的相互作用得分转化为相互作用得分。 Ppiseq将比传统的PCA具有几个重要的优势：它是快速，便宜，可扩展的，并且进入进入障碍较低。值得注意的是，ppiseq吞吐量量表与PCA菌株的数量二次相关，而其成本则以下一代测序成本的速度下降。在这里，我们将构建一个大型二倍体PPISEQ库，该库由约655,000个独特的PPI和约600万个双条形码组成，并使用此库简单地通过合并的增长来衡量每个PPI的相互作用得分（AIM 1）。 PPISEQ比传统PCA的另一个主要优势是跨扰动的可重复性。也就是说，一旦构建，所有成对交互都可以轻松地在新环境中重新构建。在这里，我们将断言酵母蛋白相互作用如何在热梯度（AIM 2）和存在三种抗真菌药物的情况下变化（AIM 3）。这项工作将为蛋白质相互作用如何在扰动中变化提供第一个基因组规模的观点。构建的Ppiseq库将作为科学界的资源提供，以供未来的扰动研究。此外，这项工作将为未来的大规模PPI屏幕（例如参与药物发现和蛋白质工程的屏幕）树立雄鹿。