A computational framework for DNA sequencing microscopy.

Proc Natl Acad Sci U S A

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

Published: September 2019

AI Article Synopsis

  • This method allows for the transfer of spatial information about biomolecule positions on a surface into a sequence-based format that can be reconstructed into images without using traditional optics.
  • Barcoded DNA amplification techniques help distinguish specific surface locations based on their unique sequences and create a network of connections that forms a graph.
  • The authors introduced a framework called polony adjacency reconstruction which enables the storage and transmission of spatial data as graph topology, paving the way for advanced imaging techniques based solely on molecular information.

Article 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6765314PMC
http://dx.doi.org/10.1073/pnas.1821178116DOI Listing

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