Using Strand Displacing Polymerase To Program Chemical Reaction Networks.


Journal

Journal of the American Chemical Society
ISSN: 1520-5126
Titre abrégé: J Am Chem Soc
Pays: United States
ID NLM: 7503056

Informations de publication

Date de publication:
27 05 2020
Historique:
pubmed: 5 5 2020
medline: 14 4 2021
entrez: 5 5 2020
Statut: ppublish

Résumé

Chemical reaction networks (CRNs) provide a powerful abstraction to formally represent complex biochemical processes. DNA provides a promising substrate to implement the abstract representation (or programming language) of CRNs due to its programmable nature. Prior works that used DNA to implement CRNs either used DNA-only systems or multienzyme DNA circuits. Architectures with DNA-only components had the rationale of being biologically simple systems. Multienzyme systems, on the other hand, aimed at using natural enzymes to improve circuit performance, although, at the cost of increased complexity. In this work, we explore an alternative architecture that lies along the spectrum in between DNA-only systems and multienzyme DNA systems. Our architecture relies on only a strand displacing polymerase enzyme and DNA hybridization reactions for implementing CRNs. First, we briefly introduce the theory and DNA design of simple CRNs and then explore the fundamental properties of polymerase-based strand displacement systems. Finally, we engineer a catalytic amplifier

Identifiants

pubmed: 32364723
doi: 10.1021/jacs.0c02240
doi:

Substances chimiques

DNA 9007-49-2
DNA-Directed DNA Polymerase EC 2.7.7.7

Types de publication

Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

9587-9593

Auteurs

Shalin Shah (S)

Department of Electrical & Computer Engineering, Duke University, Durham, North Carolina 27701, United States.
Department of Computer Science, Duke University, Durham, North Carolina 27701, United States.
Microsoft Research, Redmond, Washington 98052, United States.

Jasmine Wee (J)

Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, Washington 98195, United States.

Tianqi Song (T)

Department of Computer Science, Duke University, Durham, North Carolina 27701, United States.

Luis Ceze (L)

Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, Washington 98195, United States.

Karin Strauss (K)

Microsoft Research, Redmond, Washington 98052, United States.

Yuan-Jyue Chen (YJ)

Microsoft Research, Redmond, Washington 98052, United States.

John Reif (J)

Department of Electrical & Computer Engineering, Duke University, Durham, North Carolina 27701, United States.
Department of Computer Science, Duke University, Durham, North Carolina 27701, United States.

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Classifications MeSH