Ultrasensitivity by Molecular Titration in Spatially Propagating Enzymatic Reactions

Semenov, Sergey N.; Markvoort, Albert J.; Gevers, Wouter; Piruska, Aigars; Greef, Tom F. A. de; Huck, Wilhelm T. S.

doi:10.1016/j.bpj.2013.07.002

Cited by 25 publications

(25 citation statements)

References 67 publications

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“…Synthetic reaction-diffusion systems can also produce spatiotemporal chemical patterns from the bottom up, using inorganic systems such as the Belousov-Zhabotinsky reaction, 22,23 or enzymatic networks [24][25][26][27][28][29] both with transcriptional circuits 30 and with the Polymerase, Exonuclease, Nickase (PEN) toolbox, 31,32 including gradients, traveling waves and spatial patterns of spots or stripes. 33,34 However, the kinetics of many enzyme-based RD systems are sensitive to temperature variations of a few C and to buffer conditions, limiting when they can be applied.…”

Section: -14mentioning

confidence: 99%

Stable DNA-based reaction–diffusion patterns

et al. 2017

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We demonstrate reaction-diffusion systems that generate stable patterns of DNA oligonucleotide concentrations within agarose gels, including linear and "hill" (i.e. increasing then decreasing) shapes in one and two dimensions. The reaction networks that produce these patterns are driven by enzyme-free DNA strand-displacement reactions, in which reactant DNA complexes continuously release and recapture target strands of DNA in the gel; a balance of these reactions produces stable patterns. The reactant complexes are maintained at high concentrations by liquid reservoirs along the gel boundary. We monitor our patterns using time-lapse fluorescence microscopy and show that the shape of our patterns can be easily tuned by manipulating the boundary reservoirs. Finally, we show that two overlapping, stable gradients can be generated by designing two sets of non-interacting release and recapture reactions with DNA strand-displacement systems. This paper represents a step toward the generation of scalable, complex reaction-diffusion patterns for programming the spatiotemporal behavior of synthetic materials.

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Section: -14mentioning

confidence: 99%

Stable DNA-based reaction–diffusion patterns

et al. 2017

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“…Cr does not cleave C 1 (Figure S21 of the SI), but rapidly cleaves thioester 3 , activating the formation of C 2 . Finally, the enzymatic network is deactivated by the presence of soybean trypsin inhibitor (STI) protein, a strong, reversible inhibitor of Tr ( K D 1 n m ) that sets a threshold for the Tr input that will activate the network. We found that STI also reversibly inhibits Cr ( K D =634 n m , Figure S14), but with a dissociation constant at least two orders of magnitude larger than for Tr.…”

Section: Figurementioning

confidence: 99%

Preprogramming Complex Hydrogel Responses using Enzymatic Reaction Networks

Postma¹,

Vialshin²,

Gerritsen³

et al. 2017

Angewandte Chemie

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The creation of adaptive matter is heavily inspired by biological systems. However, it remains challenging to design complex material responses that are governed by reaction networks, which lie at the heart of cellular complexity. The main reason for this slow progress is the lack of a general strategy to integrate reaction networks with materials. Herein we use a systematic approach to preprogram the response of a hydrogel to a trigger, in this case the enzyme trypsin, which activates a reaction network embedded within the hydrogel. A full characterization of all the kinetic rate constants in the system enabled the construction of a computational model, which predicted different hydrogel responses depending on the input concentration of the trigger. The results of the simulation are in good agreement with experimental findings. Our methodology can be used to design new, adaptive materials of which the properties are governed by reaction networks of arbitrary complexity.

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“…Extending the work by de Greef & Huck et al (vide supra), 40 positive feedback was added to the trypsin-inhibitor system by employing trypsinogen, a zymogen that is autocatalytically cleaved into trypsin. Similarly, Huck and colleagues 42 combined enzymatic autocatalysis and molecular titration to develop a system which is able to sense the spatial distribution of enzymes.…”

Section: View Article Onlinementioning

confidence: 99%

Programmable chemical reaction networks: emulating regulatory functions in living cells using a bottom-up approach

et al. 2015

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Living cells are able to produce a wide variety of biological responses when subjected to biochemical stimuli. It has become apparent that these biological responses are regulated by complex chemical reaction networks (CRNs). Unravelling the function of these circuits is a key topic of both systems biology and synthetic biology. Recent progress at the interface of chemistry and biology together with the realisation that current experimental tools are insufficient to quantitatively understand the molecular logic of pathways inside living cells has triggered renewed interest in the bottom-up development of CRNs. This builds upon earlier work of physical chemists who extensively studied inorganic CRNs and showed how a system of chemical reactions can give rise to complex spatiotemporal responses such as oscillations and pattern formation. Using purified biochemical components, in vitro synthetic biologists have started to engineer simplified model systems with the goal of mimicking biological responses of intracellular circuits. Emulation and reconstruction of system-level properties of intracellular networks using simplified circuits are able to reveal key design principles and molecular programs that underlie the biological function of interest. In this Tutorial Review, we present an accessible overview of this emerging field starting with key studies on inorganic CRNs followed by a discussion of recent work involving purified biochemical components. Finally, we review recent work showing the versatility of programmable biochemical reaction networks (BRNs) in analytical and diagnostic applications.

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Ultrasensitivity by Molecular Titration in Spatially Propagating Enzymatic Reactions

Cited by 25 publications

References 67 publications

Stable DNA-based reaction–diffusion patterns

Stable DNA-based reaction–diffusion patterns

Preprogramming Complex Hydrogel Responses using Enzymatic Reaction Networks

Programmable chemical reaction networks: emulating regulatory functions in living cells using a bottom-up approach

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