Implementing Nonlinear Feedback Controllers Using DNA Strand Displacement Reactions

Sawlekar, Rucha; Montefusco, Francesco; Kulkarni, Vishwesh V.; Bates, Declan G.

doi:10.1109/tnb.2016.2560764

Cited by 66 publications

(36 citation statements)

References 32 publications

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“…Going even beyond the biological area, the advent of “soft robots" [ 59 ] which could conceivably be endowed with chemical sensing capabilities, and incorporating adaptation at the sensory level could be relevant here as well. Our insights are also relevant to the engineering of information processing and homeostatic controllers through non-enzymatic mechanisms such as DNA strand displacement reactions [ 60 – 64 ]. We have shown how it is possible to construct compact adaptive circuits which combine features of exact adaptation in static stimuli, ramps, temporal periodic stimuli and static spatial stimuli (or any subset of these capabilities).…”

Section: Discussionmentioning

confidence: 99%

Adaptive information processing of network modules to dynamic and spatial stimuli

Krishnan

Floros

2019

BMC Syst Biol

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BackgroundAdaptation and homeostasis are basic features of information processing in cells and seen in a broad range of contexts. Much of the current understanding of adaptation in network modules/motifs is based on their response to simple stimuli. Recently, there have also been studies of adaptation in dynamic stimuli. However a broader synthesis of how different circuits of adaptation function, and which circuits enable a broader adaptive behaviour in classes of more complex and spatial stimuli is largely missing.ResultsWe study the response of a variety of adaptive circuits to time-varying stimuli such as ramps, periodic stimuli and static and dynamic spatial stimuli. We find that a variety of responses can be seen in ramp stimuli, making this a basis for discriminating between even similar circuits. We also find that a number of circuits adapt exactly to ramp stimuli, and dissect these circuits to pinpoint what characteristics (architecture, feedback, biochemical aspects, information processing ingredients) allow for this. These circuits include incoherent feedforward motifs, inflow-outflow motifs and transcritical circuits. We find that changes in location in such circuits where a signal acts can result in non-adaptive behaviour in ramps, even though the location was associated with exact adaptation in step stimuli. We also demonstrate that certain augmentations of basic inflow-outflow motifs can alter the behaviour of the circuit from exact adaptation to non-adaptive behaviour. When subject to periodic stimuli, some circuits (inflow-outflow motifs and transcritical circuits) are able to maintain an average output independent of the characteristics of the input. We build on this to examine the response of adaptive circuits to static and dynamic spatial stimuli. We demonstrate how certain circuits can exhibit a graded response in spatial static stimuli with an exact maintenance of the spatial mean-value. Distinct features which emerge from the consideration of dynamic spatial stimuli are also discussed. Finally, we also build on these results to show how different circuits which show any combination of presence or absence of exact adaptation in ramps, exact mainenance of time average output in periodic stimuli and exact maintenance of spatial average of output in static spatial stimuli may be realized.ConclusionsBy studying a range of network circuits/motifs on one hand and a range of stimuli on the other, we isolate characteristics of these circuits (structural) which enable different degrees of exact adaptive and homeostatic behaviour in such stimuli, how they may be combined, and also identify cases associated with non-homeostatic behaviour. We also reveal constraints associated with locations where signals may act to enable homeostatic behaviour and constraints associated with augmentations of circuits. This consideration of multiple experimentally/naturally relevant stimuli along with circuits of adaptation of relevance in natural and engineered biology, provides a platform for deepening our understandin...

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Section: Discussionmentioning

confidence: 99%

Adaptive information processing of network modules to dynamic and spatial stimuli

Krishnan

Floros

2019

BMC Syst Biol

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“…Though challenges surrounding the modularity and unpredictability of biological systems persist, thanks to fundamental biological research there is an ever-increasing assortment of biological elements that can be used for synthetic designs. Constructs can be built using systems operating on a range of molecular biological levels (for example, using DNA [36], RNA [37] or Protein [14]), as well as at varying time-scales [38], [39], [40] and species concentrations [31]. However, working with this disparate assortment of components requires extensive inter-disciplinary expertise, and can substantially increase the necessity for experimental troubleshooting and system fine-tuning.…”

Section: The Bacterial Chemotaxis System Is a Model Example Of A Natumentioning

confidence: 99%

Design Constraints for Biological Systems That Achieve Adaptation and Disturbance Rejection

Steel

Papachristodoulou

2018

IEEE Trans. Control Netw. Syst.

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Many processes in natural biological systems, such as chemotaxis in bacteria and osmoregulation in yeast, rely on control architectures fundamentally equivalent to commonly used motifs from electrical and control engineering. However, difficulties arise when designing and implementing these architectures in a biological context due to uncertainties inherent in the behaviour of biological systems, and physical limitations of the available parts. In this paper we discuss recent developments in the study of biological control systems, which are increasingly necessary for realisation of complex synthetic biological constructs, focusing on methods for their design and implementation. We establish a range of desirable properties that ease implementation of biological constructs, and apply classical control theory to derive a set of constraints to aid the design of systems that achieve adaptation or disturbance rejection. We demonstrate how these constraints can be used in practice, first deriving the necessary structure for a linear system that achieves adaptation, and then embedding this in a non-linear model of biological relevance that could be built in the laboratory.

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“…Such naturally-occurring feedbacks have been shown to be key motifs in gene regulatory networks [36]. Furthermore, design of in-vitro/insilico feedback system for controlling gene expression are an intense area of current research [37]- [44].…”

Section: Introductionmentioning

confidence: 99%

Stochastic delays suppress noise in a genetic circuit with negative feedback

Smith

Singh

2019

Preprint

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We consider a mechanistic stochastic model of an autoregulatory genetic circuit with time delays. More specifically, a protein is expressed in random bursts from its corresponding gene. The synthesized protein is initially inactive and becomes active after a time delay. Rather than considering a deterministic delay, a key aspect of this work is to incorporate stochastic time delays, where delay is an independent and identically distributed random variable. The active protein inhibits its own production creating a negative feedback loop. Our analysis reveals that for an exponentially-distributed time delay, the noise in the protein levels decreases to the Poisson limit with increasing mean time delay. Interesting, for a gammadistributed time delay contrasting noise behaviors emerge based on the negative feedback strength. At low feedback strengths the protein noise levels monotonically decreases to the Poisson limit with increasing average delay. At intermediate feedback strengths, the noise levels first increase to reach a maximum, and then decease back to the Poisson limit with increasing average delay. Finally, for strong feedbacks the protein noise levels monotonically increase with the average delay. For each of these scenarios we provide approximate analytical formulas for the protein mean and noises levels, and validate these results by performing exact Monte Carlo simulations. In conclusion, our results uncover a counter intuitive feature where inclusion of stochastic delays in a negative feedback circuit can play a beneficial role in buffering deleterious fluctuations in the level of a protein.

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Implementing Nonlinear Feedback Controllers Using DNA Strand Displacement Reactions

Cited by 66 publications

References 32 publications

Adaptive information processing of network modules to dynamic and spatial stimuli

Adaptive information processing of network modules to dynamic and spatial stimuli

Design Constraints for Biological Systems That Achieve Adaptation and Disturbance Rejection

Stochastic delays suppress noise in a genetic circuit with negative feedback

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