Rational Design of Robust Biomolecular Circuits: from Specification to Parameters

Hafner, Marc; Petrov, Tatjana; Lu, James; Koeppl, Heinz

doi:10.1007/978-1-4419-6766-4_12

Cited by 4 publications

(4 citation statements)

References 61 publications

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“…In silico design of synthetic biochemical circuits consists of a performance and a robustness classification phase. 52 In the previous sections, we have classified the performance of two DNA-based CRNs resulting in parameter ranges where the desired response can be observed. However, this procedure does not yield insight in the robustness of the response, that is, the effect of small perturbations on the performance of the circuit.…”

Section: ■ Results and Discussionmentioning

confidence: 99%

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Automated Design of Programmable Enzyme-Driven DNA Circuits

Roekel¹,

Meijer²,

Masroor³

et al. 2014

ACS Synth. Biol.

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Molecular programming allows for the bottom-up engineering of biochemical reaction networks in a controlled in vitro setting. These engineered biochemical reaction networks yield important insight in the design principles of biological systems and can potentially enrich molecular diagnostic systems. The DNA polymerase-nickase-exonuclease (PEN) toolbox has recently been used to program oscillatory and bistable biochemical networks using a minimal number of components. Previous work has reported the automatic construction of in silico descriptions of biochemical networks derived from the PEN toolbox, paving the way for generating networks of arbitrary size and complexity in vitro. Here, we report an automated approach that further bridges the gap between an in silico description and in vitro realization. A biochemical network of arbitrary complexity can be globally screened for parameter values that display the desired function and combining this approach with robustness analysis further increases the chance of successful in vitro implementation. Moreover, we present an automated design procedure for generating optimal DNA sequences, exhibiting key characteristics deduced from the in silico analysis. Our in silico method has been tested on a previously reported network, the Oligator, and has also been applied to the design of a reaction network capable of displaying adaptation in one of its components. Finally, we experimentally characterize unproductive sequestration of the exonuclease to phosphorothioate protected ssDNA strands. The strong nonlinearities in the degradation of active components caused by this unintended cross-coupling are shown computationally to have a positive effect on adaptation quality.

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Section: ■ Results and Discussionmentioning

confidence: 99%

“…In silico design of synthetic biochemical circuits consists of a performance and a robustness classification phase . In the previous sections, we have classified the performance of two DNA-based CRNs resulting in parameter ranges where the desired response can be observed.…”

Section: Resultsmentioning

confidence: 99%

Automated Design of Programmable Enzyme-Driven DNA Circuits

Roekel¹,

Meijer²,

Masroor³

et al. 2014

ACS Synth. Biol.

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“…The robustness of models of biochemical systems with respect to temporal properties has been studied [6,18,22]. These approaches differ from ours in that in our work we focus on quantifying robustness with respect to a concrete source of perturbation of the parameters (such as point mutations).…”

Section: Introductionmentioning

confidence: 97%

“…These approaches differ from ours in that in our work we focus on quantifying robustness with respect to a concrete source of perturbation of the parameters (such as point mutations). In [18] and [22], the authors present methods to evaluate the satisfaction degree of a trace with respect to a temporal formula, but no assumption is made on the distribution of parameters, while in [6], the authors use a symbolic technique to synthesise the parameter space for which the property is satisfied, but robustness is defined in terms of the relative size of the error intervals around some reference parameter values.…”

Section: Introductionmentioning

confidence: 99%

Model checking the evolution of gene regulatory networks

et al. 2016

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The behaviour of gene regulatory networks (GRNs) is typically analysed using simulation-based statistical testing-like methods. In this paper, we demonstrate that we can replace this approach by a formal verification-like method that gives higher assurance and scalability. We focus on Wagner's weighted GRN model with varying weights, which is used in evolutionary biology. In the model, weight parameters represent the gene interaction strength that may change due to genetic mutations. For a property of interest, we synthesise the constraints over the parameter space that represent the set of GRNs satisfying the property. We experimentally show that our parameter synthesis procedure computes the mutational robustness of GRNs-an important problem of interest in evolutionary biology-more efficiently than the classical simulation method. We specify the property in linear temporal logic. We employ symbolic bounded model checking and SMT solving to compute the space of GRNs that satisfy the property, which amounts to synthesizing a set of linear constraints on the weights.

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Inverse problems from biomedicine

August

Koeppl

2012

J. Math. Biol.

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Many complex diseases that are difficult to treat cannot be mapped onto a single cause, but arise from the interplay of multiple contributing factors. In the study of such diseases, it is becoming apparent that therapeutic strategies targeting a single protein or metabolite are often not efficacious. Rather, a systems perspective describing the interaction of physiological components is needed. In this paper, we demonstrate via examples of disease models the kind of inverse problems that arise from the need to infer disease mechanisms and/or therapeutic strategies. We identify the challenges that arise, in particular the need to devise strategies that are robust against variable physiological states and parametric uncertainties.

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Rational Design of Robust Biomolecular Circuits: from Specification to Parameters

Cited by 4 publications

References 61 publications

Automated Design of Programmable Enzyme-Driven DNA Circuits

Automated Design of Programmable Enzyme-Driven DNA Circuits

Model checking the evolution of gene regulatory networks

Inverse problems from biomedicine

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