Diverse and robust molecular algorithms using reprogrammable DNA self-assembly

Woods, Damien; Doty, David; Myhrvold, Cameron; Hui, Joy; Zhou, Felix; Yin, Peng; Winfree, Erik

doi:10.1038/s41586-019-1014-9

Cited by 230 publications

(209 citation statements)

References 73 publications

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“…Undoubtedly, DNA‐based computers and also protein‐based computing systems are leading the developments there. For instance, recently a 6‐bit Boolean algorithm‐processing DNA computer with proof‐reading and a self‐assembling readout was proposed, and earlier systems for reaching consensus decisions, bistability (memories) and programmable oscillators were discussed . Unfortunately, the connection of such advances in systems chemistry toward materials are still limited, which calls for a closer collaboration at the interface of systems chemistry and advanced materials.…”

Section: Computation and Communicationmentioning

confidence: 99%

Viewpoint: From Responsive to Adaptive and Interactive Materials and Materials Systems: A Roadmap

2019

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toward higher levels of complexity and takes increasing inspiration from the concepts of living species, it feels imminent and of high importance to foster the discussion on this topic and provide a roadmap to evolve synthetic systems from responsive to adaptive and interactive systems and materials. This is not only important in the context of highlighting landmark advances of future systems over present ones, but also relevant for the education of the next generation of researchers going to operate in the field. Furthermore, we are often faced with an inadequate inflation of terminology, which may also not help to develop new conceptual research directions in a clear manner.It is the objective of this Viewpoint to discuss relevant conceptual differences between these material classes (responsive vs adaptive vs interactive) in a generally accessible way-albeit certainly from a personal perspective-and fertilize and contribute to this discussion, and hopefully provide some definitions and a roadmap for future materials system design. Given the brevity of this viewpoint, it will only relate at selected places shortly to some existing literature, but has the main objective on communicating concepts underlying advanced adaptivity and interactivity. Responsive SystemsLet us first look back at the class of stimuli-responsive materials, which have been an outstanding success story for the design of advanced switchable soft materials that continue to widely Soft matter systems and materials are moving toward adaptive and interactive behavior, which holds outstanding promise to make the next generation of intelligent soft materials systems inspired from the dynamics and behavior of living systems. But what is an adaptive material? What is an interactive material? How should classical responsiveness or smart materials be delineated? At present, the literature lacks a comprehensive discussion on these topics, which is however of profound importance in order to identify landmark advances, keep a correct and noninflating terminology, and most importantly educate young scientists going into this direction. By comparing different levels of complex behavior in biological systems, this Viewpoint strives to give some definition of the various different materials systems characteristics. In particular, the importance of thinking in the direction of training and learning materials, and metabolic or behavioral materials is highlighted, as well as communication and information-processing systems. This Viewpoint aims to also serve as a switchboard to further connect the important fields of systems chemistry, synthetic biology, supramolecular chemistry and nano-and microfabrication/3D printing with advanced soft materials research. A convergence of these disciplines will be at the heart of empowering future adaptive and interactive materials systems with increasingly complex and emergent life-like behavior.

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Section: Computation and Communicationmentioning

confidence: 99%

Viewpoint: From Responsive to Adaptive and Interactive Materials and Materials Systems: A Roadmap

2019

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“…Furthermore, the free energy for assembling equivalent-size critical nuclei can be up to twice the magnitude for crisscross compared to square tiles. Indeed, Woods et al found they were unable to achieve seeded growth with satisfactory suppression of spontaneous nucleation for square tiles at 1 µM each (see Supplementary Information A, Section S5.1.1 and Figure S27A from Woods et al 31 ).…”

Section: How Crisscross Polymerization Enables Robust Control Over Numentioning

confidence: 99%

“…high concentrations of monomers and well below the reversible temperature), such that a subpopulation of smaller or incomplete assemblies will arise. In the case of algorithmic assembly, where each seed kinetically triggers a particular pattern of tile accretion, contamination from unseeded growths can be especially problematic [24][25][26][27][28][29][30][31][32] . Tile assembly faces a particularly stringent test for application in single-molecule amplification schemes for point-of-care diagnostics, where the speed of growth is at a premium while, conversely, the limit of detection is bounded by the rate of spontaneous nucleation.…”

Section: Introductionmentioning

confidence: 99%

Robust nucleation control via crisscross polymerization of DNA slats

Minev

Ershova

et al. 2019

Preprint

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Natural biomolecular assemblies such as actin filaments or microtubules polymerize in a nucleation-limited fashion 1,2 . The barrier to nucleation arises in part from chelate cooperativity, where stable capture of incoming monomers requires straddling multiple subunits on a filament end 3 . For programmable self-assembly from building blocks such as synthetic DNA 4-23 , it is likewise desirable to be able to suppress spontaneous nucleation 24-31 . However, existing approaches that exploit just a low level of cooperativity can limit spontaneous nucleation only for slow growth, near-equilibrium conditions 32 . Here we introduce ultracooperative assembly of ribbons densely woven from single-stranded DNA slats. An inbound "crisscross" slat snakes over and under six or more previously captured slats on a growing ribbon end, forming weak but specific half-duplex interactions with each. We demonstrate growth of crisscross ribbons with distinct widths and twists to lengths representing many thousands of slat additions. Strictly seedinitiated extension is attainable over a broad range of temperatures, divalent-cation concentrations, and free-slat concentrations, without unseeded ribbons arising even after a hundred hours to the limit of agarose-gel detection. We envision that crisscross assembly will be broadly enabling for all-or-nothing formation of microstructures with nanoscale features, algorithmic self-assembly, and signal amplification in diagnostic applications requiring extreme sensitivity.

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“…A specific solution path connecting a given pair of start and end vertices can be easily extracted from the set of all paths taken by the navigators collectively. Recently, a complex DNA computing system was developed by Winfree and co‐workers (Figure h), where they designed a set of 355 single‐stranded tiles that can be reprogrammed to implement a wide variety of 6‐bit algorithms. Using this set of tiles, they constructed a number of 21 circuits that can execute algorithms, including copying, sorting, random walking, electing a leader, simulating cellular automata, generating deterministic and randomized patterns, counting to 63, and so on, with an overall per‐tile error rate of less than 1 in 3000, suggesting that molecular self‐assembly may be a reliable algorithmic component within programmable chemical systems.…”

Section: Dna‐guided Assembly Of Molecules Materials and Cellsmentioning

confidence: 99%

DNA‐Guided Assembly of Molecules, Materials, and Cells

Yang

Zhou

Gao

et al. 2019

Advanced Intelligent Systems

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DNA is the genetic blueprint for most known living organisms on Earth, but it is not merely the secret of life. Because of its programmability derived from Watson-Crick base-pairing, DNA exhibits unparalleled versatility in constructing designer molecular structures by self-assembly-a field called DNA nanotechnology. After decades of active pursuit, DNA has demonstrated unprecedented capability in designing highly prescribed and sophisticated artificial nanostructures, which could be either static, with well-controlled physicochemical properties, or dynamic, with the ability to change in response to external stimuli. Researchers have devoted considerable efforts to exploring the utility of DNA nanotechnology in a variety of fields, with the majority related to harvesting their assembling power, since they are highly capable of guiding the assembly of other entities-molecules, materials, living cells, and so on-to fabricate artificial assemblies with emergent properties and functions. Herein, a brief introduction is given to self-assembly methods in DNA nanotechnology, including DNA tiles, modular DNA bricks, and DNA origami. Four sections are then dedicated to covering the utilization of DNA nanotechnology for guided assembly of organic materials, inorganic materials, biological materials, and living cells. Lastly, DNA-enabled molecular intelligent systems that are able to compute and execute algorithms are discussed.

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Diverse and robust molecular algorithms using reprogrammable DNA self-assembly

Cited by 230 publications

References 73 publications

Viewpoint: From Responsive to Adaptive and Interactive Materials and Materials Systems: A Roadmap

Viewpoint: From Responsive to Adaptive and Interactive Materials and Materials Systems: A Roadmap

Robust nucleation control via crisscross polymerization of DNA slats

DNA‐Guided Assembly of Molecules, Materials, and Cells

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