Programmable chemical controllers made from DNA

By Yuan-Jyue Chen, Neil Dalchau, Niranjan Srinivas, Andrew Phillips, Luca Cardelli, David Soloveichik, Georg Seelig. Nature Nanotechnology, 2013

488 citations recorded by the source corpus.

Biological organisms use complex molecular networks to navigate their environment and regulate their internal state. The development of synthetic systems with similar capabilities could lead to applications such as smart therapeutics or fabrication methods based on self-organization. To achieve this, molecular control circuits need to be engineered to perform integrated sensing, computation and actuation. Here we report a DNA-based technology for implementing the computational core of such controllers. We use the formalism of chemical reaction networks as a 'programming language', and our DNA architecture can, in principle, implement any behaviour that can be mathematically expressed as such. Unlike logic circuits, our formulation naturally allows complex signal processing of intrinsically analogue biological and chemical inputs. Controller components can be derived from biologically synthesized (plasmid) DNA, which reduces errors associated with chemically synthesized DNA. We implement several building-block reaction types and then combine them into a network that realizes, at the molecular level, an algorithm used in distributed control systems for achieving consensus between multiple agents.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/bcc74eca5a41434b1344016b44ed210b2837b40b

How researchers see this paper

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In Molecular Biology

1. Karin Strauss
2. Luis Ceze
3. Dan Alistarh
4. Georg Seelig

Citations in the corpus

• PopSGD: Decentralized Stochastic Gradient Descent in the Population Model (2019, background): “Population protocols have a rich history in distributed computing (e.g. [8, 11, 10, 9, 12, 4, 5]), and are standard in modelling distributed systems with millions or billions of nodes, such as Chemical Reaction Networks (CRNs) [16, 18] and synthetic DNA strand displacement cascades [20].”
• A DNA-Based Archival Storage System (2016, background): “Researchers have proposed the use of DNA for Boolean circuits [26], neural networks [21], and chemical reaction networks [5].”