CAREER: Programming digital bits with DNA for barcoded nanoscale imaging applications

非技术解释：生物分子是构成所有生物的微小分子积木。了解生物分子的结构和功能对于促进我们对生命如何工作的理解以及寻求将生物分子重新定位于技术发展的新兴工程学科至关重要。电子冷冻显微镜(Cryo-EM)使研究人员能够可视化生物分子的结构。这项技术的一个技术限制是，生物分子必须一次成像一个，因为它们太小了，当混合在一起时无法区分开来。如果有可能将“条形码”附加到生物分子上，以便在数据分析过程中能够同时唯一地识别它们，那将是一个重大的进步。该项目的目标是使用DNA作为纳米级可编程建筑材料来创建和优化这种条形码。如果成功，建议的方法将极大地提高冷冻-EM技术的速度和影响。技术描述：为了克服电子冷冻显微镜(Cryo-EM)的吞吐量限制，Pi建议创建基于DNA的纳米结构，该结构利用模块化的、定义明确的不对称特征(BITS)，可以在不同状态之间切换，从而实现样本多路复用。即使切换一个比特的结构差异也足够显著，以至于EM可以很容易地区分不同的条形码，并通过标准图像处理算法将其划分为不同的类别。PI建议通过首先对已经成像和描述的蛋白质结合的纳米结构进行结构研究来验证这一方法，然后将这项研究扩展到成像和描述尚未用其他方法可视化的大分子。

Nontechnical explanation:Biomolecules are the tiny molecular building blocks out of which all living organisms are made. Understanding the structure and function of biomolecules is critical for advancement of our understanding of how life works, as well as emerging engineering disciplines that seek to repurpose biomolecules for technology development. Electron cryo-microscopy (cryo-EM) enables researchers to visualize the structure of biomolecules. One technical limitation of the technique is that biomolecules must be imaged one at a time because they are too small to tell apart when mixed together. It would be a significant advance if it were possible to attach "barcodes" to biomolecules so they could be imaged simultaneously and uniquely identified during data analysis. The goal of this project is to create and optimize such barcodes using DNA as a nano-scale programmable building material. If successful, the proposed approach should greatly increase the speed and impact of the cryo-EM technique.Technical description:Toward overcoming the throughput limitation of electron cryo-microscopy (cryo-EM), PI proposes to create DNA-based nanostructures that make use of modular, well-defined asymmetric features ("bits") that can be toggled between different states that enable sample multiplexing. The structural difference of toggling even a single bit is dramatic enough that different barcodes can be easily distinguished by EM, and sorted into distinct classes by standard image processing algorithms. PI proposes to validate this methodology by first performing structural studies of nanostructures bound to a protein that has already been imaged and described, and then extend this research to image and describe macromolecules that have not yet been visualized by other methods.