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用于 DNA 测序显微镜的计算框架。

A computational framework for DNA sequencing microscopy.

机构信息

Department of Medical Biochemistry and Biophysics, Karolinska Institutet, S-17177 Stockholm, Sweden.

Department of Computer Science, Aalto University, FI-00076 Aalto, Finland.

出版信息

Proc Natl Acad Sci U S A. 2019 Sep 24;116(39):19282-19287. doi: 10.1073/pnas.1821178116. Epub 2019 Sep 4.

Abstract

We describe a method whereby microscale spatial information such as the relative positions of biomolecules on a surface can be transferred to a sequence-based format and reconstructed into images without conventional optics. Barcoded DNA "polymerase colony" (polony) amplification techniques enable one to distinguish specific locations of a surface by their sequence. Image formation is based on pairwise fusion of uniquely tagged and spatially adjacent polonies. The network of polonies connected by shared borders forms a graph whose topology can be reconstructed from pairs of barcodes fused during a polony cross-linking phase, the sequences of which are determined by recovery from the surface and next-generation (next-gen) sequencing. We developed a mathematical and computational framework for this principle called polony adjacency reconstruction for spatial inference and topology and show that Euclidean spatial data may be stored and transmitted in the form of graph topology. Images are formed by transferring molecular information from a surface of interest, which we demonstrated in silico by reconstructing images formed from stochastic transfer of hypothetical molecular markers. The theory developed here could serve as a basis for an automated, multiplexable, and potentially superresolution imaging method based purely on molecular information.

摘要

我们描述了一种方法,通过该方法可以将微观空间信息(例如表面上生物分子的相对位置)转换为基于序列的格式,并在无需传统光学的情况下重建为图像。带条码的 DNA“聚合酶菌落”(polony)扩增技术可通过序列来区分表面的特定位置。图像形成基于独特标记和空间相邻 polony 的成对融合。通过共享边界连接的 polony 网络形成一个图,该图的拓扑结构可以通过在 polony 交联阶段融合的一对条形码重建来重建,其序列通过从表面和下一代(next-gen)测序中恢复来确定。我们为此原理开发了一个数学和计算框架,称为用于空间推理和拓扑结构的 polony 邻接重建,并表明欧几里得空间数据可以以图拓扑的形式存储和传输。图像是通过从感兴趣的表面转移分子信息形成的,我们通过从假设的分子标记的随机转移中重建图像在计算机上进行了演示。这里开发的理论可以为一种基于纯分子信息的自动化、可多路复用和潜在的超分辨率成像方法提供基础。

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