Temporal DNA barcodes: A time-based approach for single-molecule imaging


Conference Paper

© Springer Nature Switzerland AG 2018. In the past decade, single-molecule imaging has opened new opportunities to understand reaction kinetics of molecular systems. DNA-PAINT uses transient binding of DNA strands to perform super-resolution fluorescence imaging. An interesting challenge in DNA nanoscience and related fields is the unique identification of single-molecules. While wavelength multiplexing (using fluorescent dyes of different colors) can be used to increase the number of distinguishable targets, the resultant total number of targets is still limited by the number of dyes with non-overlapping spectra. In this work, we introduce the use of time-domain to develop a DNA-based reporting framework for unique identification of single-molecules. These fluorescent DNA devices undergo a series of conformational transformations that result in (unique) time-changing intensity signals. We define this stochastic temporal intensity trace as the device’s temporal barcode since it can uniquely identify the corresponding DNA device if the collection time is long enough. Our barcodes work with as few as one dye making them easy to design, extremely low-cost, and greatly simplifying the hardware setup. In addition, by adding multiple dyes, we can create a much larger family of uniquely identifiable reporter molecules. Finally, our devices are designed to follow the principle of transient binding and can be imaged using total internal reflection fluorescence (TIRF) microscopes so they are not susceptible to photo-bleaching, allowing us to monitor their activity for extended time periods. We model our devices using continuous-time Markov chains (CTMCs) and simulate their behavior using a stochastic simulation algorithm (SSA). These temporal barcodes are later analyzed and classified in their parameter space. The results obtained from our simulation experiments can provide crucial insights for collecting experimental data.

Full Text

Duke Authors

Cited Authors

  • Shah, S; Reif, J

Published Date

  • January 1, 2018

Published In

Volume / Issue

  • 11145 LNCS /

Start / End Page

  • 71 - 86

Electronic International Standard Serial Number (EISSN)

  • 1611-3349

International Standard Serial Number (ISSN)

  • 0302-9743

International Standard Book Number 13 (ISBN-13)

  • 9783030000295

Digital Object Identifier (DOI)

  • 10.1007/978-3-030-00030-1_5

Citation Source

  • Scopus