High-throughput single-molecule protein identification via super-resolution imaging

通过超分辨率成像进行高通量单分子蛋白质鉴定

• 批准号: 9980953
• 负责人: Peng Yin
• 金额: $ 131.95万
• 依托单位: HARVARD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9980953
• 关键词: Address; Bar Codes; Biological; Biological Assay; COVID-19 pandemic; Cells; Communities; Complex Mixtures; DNA; Data; Development; Devices; Diagnostic; Early Diagnosis; Image; Infection; Malignant Neoplasms; Mass Spectrum Analysis; Methods; Nanotechnology; Nature; Nerve Degeneration; Optics; Proteins; Proteome; Proteomics; Resolution; Sampling; Stretching; Technology; Testing; Work; base; biomarker panel; brain research; imaging modality; improved; next generation sequencing; novel marker; prevent; public health relevance; single molecule; tool; tumor immunology; ultra high resolution

Modified Project Summary/Abstract Section A technology capable of generating robust protein data across various biological states, with the sensitivity and coverage available to next-generation sequencing, would drastically change our understanding of cellular proteomes and ability to detect rare proteins in limited samples. Mass spectrometry is a powerful tool for proteomics. However, it suffers from limited sensitivity (>10{6} molecules required) preventing the identification of low-abundance proteins and single-cell proteomics. A high-throughput single-molecule protein identification method remains a key technical challenge for the proteomic community. Addressing this challenge will dramatically improve the ability to discover and assay novel biomarkers, with transformative impact in our understanding of cancer, immunology and brain research. We propose a robust high-throughput strategy for single-molecule protein identification. This approach will be based on our recent technological breakthrough on developing the highly multiplexed (10-plex; Nature Methods 2014), precisely quantitative (>90% precision and accuracy; Nature Methods 2016), and ultra-high resolution (sub-5 nm; Nature Nanotechnology 2016) DNA-PAINT super-resolution imaging method. Using DNA-PAINT to image a DNA-barcoded and stretched protein will provide a unique optical signature for accurate identification of any proteins in a complex mixture. This method will enable parallel identification of proteins with single-molecule sensitivity, resulting in broadly transformative impacts on fundamental and translational biomedical studies. To address the unmet testing need for the current COVID-19 pandemic, we will also work to develop a rapid diagnostics device.

修改项目摘要/摘要部分 一种能够在各种生物状态下生成强大的蛋白质数据的技术，具有下一代测序的灵敏度和覆盖范围，将极大地改变我们对细胞蛋白质组的理解以及在有限样本中检测稀有蛋白质的能力。质谱分析是蛋白质组学研究的有力工具。然而，它的灵敏度有限（需要>10{6}个分子），妨碍了低丰度蛋白和单细胞 蛋白质组学高通量单分子蛋白质鉴定方法仍然是蛋白质组学领域的关键技术挑战。解决这一挑战将大大提高发现和检测新生物标志物的能力，对我们理解癌症、免疫学和大脑研究产生变革性影响。我们提出了一个强大的高通量单分子蛋白质鉴定策略。这种方法将基于我们最近在开发高度多重（10重; Nature Methods 2014），精确定量 （>90%的精确度和准确度; Nature Methods 2016）和超高分辨率（亚5 nm; Nature Nanotechnology 2016）DNA-PAINT超分辨率成像方法。使用DNA-PAINT对DNA条形码和拉伸蛋白质进行成像将提供独特的光学特征，用于准确识别复杂混合物中的任何蛋白质。这种方法将能够并行识别具有单分子灵敏度的蛋白质，从而对基础和转化生物医学研究产生广泛的变革性影响。为应对当前COVID-19疫情未满足的检测需求，我们还将致力于开发快速诊断设备。