Biologically inspired design of feedback control systems implemented using DNA strand displacement reactions.

The use of abstract chemical reaction networks (CRNs) as a modelling and design framework for the implementation of computing and control circuits using enzyme-free, entropy driven DNA strand displacement (DSD) reactions is starting to garner widespread attention in the area of synthetic biology. Previous work in this area has demonstrated the theoretical plausibility of using this approach to design biomolecular feedback control systems based on classical proportional-integral (PI) controllers, which may be constructed from CRNs implementing gain, summation and integrator operators. Here, we propose an alternative design approach that utilises the abstract chemical reactions involved in cellular signalling cycles to implement a biomolecular controller - termed a signalling-cycle (SC) controller.

Implementing Nonlinear Feedback Controllers Using DNA Strand Displacement Reactions.

We show how an important class of nonlinear feedback controllers can be designed using idealized abstract chemical reactions and implemented via DNA strand displacement (DSD) reactions. Exploiting chemical reaction networks (CRNs) as a programming language for the design of complex circuits and networks, we show how a set of unimolecular and bimolecular reactions can be used to realize input-output dynamics that produce a nonlinear quasi sliding mode (QSM) feedback controller. The kinetics of the required chemical reactions can then be implemented as enzyme-free, enthalpy/entropy driven DNA reactions using a toehold mediated strand displacement mechanism via Watson-Crick base pairing and branch migration.

Computational design of nucleic acid feedback control circuits.

The design of synthetic circuits for controlling molecular-scale processes is an important goal of synthetic biology, with potential applications in future in vitro and in vivo biotechnology. In this paper, we present a computational approach for designing feedback control circuits constructed from nucleic acids. Our approach relies on an existing methodology for expressing signal processing and control circuits as biomolecular reactions.

Gene regulatory network modeling using literature curated and high throughput data.

Building on the linear matrix inequality (LMI) formulation developed recently by Zavlanos et al. (Automatica: Special Issue Syst Biol 47(6):1113-1122, 2011), we present a theoretical framework and algorithms to derive a class of ordinary differential equation (ODE) models of gene regulatory networks using literature curated data and microarray data. The solution proposed by Zavlanos et al.

Characterizing the memory of the GAL regulatory network in Saccharomyces cerevisiae.

Genetic regulatory networks respond dynamically to perturbations in the intracellular and extracellular environments of an organism. The GAL system in the yeast Saccharomyces cerevisiae has evolved to utilize galactose as an alternative carbon and energy source, in the absence of glucose in the environment. We present a dynamic model for GAL system in Saccharomyces cerevisiae, which includes a novel mechanism for Gal3p activation upon induction with galactose.

Synthesis of robust tunable oscillators using mitogen activated protein kinase cascades.

Mitogen activated protein kinase (MAPK) cascade is evolutionally preserved in all eukaryotic cells, and regulates various cellular activities such as gene expression, mitosis, differentiation, and apoptosis. Recently, Bashor et al. have shown that Ste5 scaffold protein can be used to reshape the MAPK cascade through engineered feedback loops, and have used heuristic tuning mechanisms to synthesize the feedback.

Stability analysis of the GAL regulatory network in Saccharomyces cerevisiae and Kluyveromyces lactis.

Background: In the yeast Saccharomyces cerevisiae, interactions between galactose, Gal3p, Gal80p, and Gal4p determine the transcriptional status of the genes required for the galactose utilization. Increase in the cellular galactose concentration causes the galactose molecules to bind onto Gal3p which, via Gal80p, activates Gal4p, which induces the GAL3 and GAL80 gene transcription. Recently, a linear time-invariant multi-input multi-output (MIMO) model of this GAL regulatory network has been proposed; the inputs being galactose and Gal4p, and the outputs being the active Gal4p and galactose utilization.