Hard Limits and Performance Tradeoffs in a Class of Sequestration Feedback Systems

Olsman, Noah; Baetica, Ania-Ariadna; Xiao, Fangzhou; Leong, Yoke Peng; Murray, Richard M.; Doyle, John C.

doi:10.1101/222042

Cited by 16 publications

(63 citation statements)

References 51 publications

(56 reference statements)

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“…The field of synthetic biology has focused on the development of novel organisms, devices and systems for the purposes of improving industrial processes [Savage et al, 2008, Clomburg and Gonzalez, 2010, Dunlop et al, 2010, Hemme et al, 2010, Narcross et al, 2016, discovering the principles of natural biological systems [Gardner et al, 2000, Elowitz and Leibler, 2000, Guo et al, 2014, and 20 performing biomolecular computation [Qian et al, 2011, Thubagere Jagadeesh, 2017. Current applications of synthetic biology include industrial fermentation [Georgianna and Mayfield, 2012], toxin detection [McBride et al, 2003, Wang et al, 2009, biosensor development [Hsiao et al, 2016], diagnostics detection [Pardee et al, 2014], materials production [Cherny and Gazit, 2008, Moon et al, 2010, DeLoache et al, 2015, novel protein design [Dahiyat and Mayo, 1996, Arnold, 1998, Kuhlman et al, 2003, and biological computation [Moon et al, 2012, Daniel et al, 2013. The applications and capabilities of synthetic biology are still expanding because it is a relatively novel field.…”

Section: Introductionmentioning

confidence: 99%

“…However, tools and concepts have been developed to ameliorate them [Levine, 2010, Friedland, with no controller species degradation and demonstrated that they can achieve perfect adaptation under certain conditions of stability. Nevertheless, we and others have found the assumption of zero controller species degradation to be too restrictive for the practical implementation of sequestration feedback [Ang et al, 2010, Ren et al, 2017, Qian and Del Vecchio, 2018, Olsman et al, 2018.…”

Section: Introductionmentioning

confidence: 99%

“…Previous research on sequestration feedback networks has determined conditions for their stability, along with their performance and robustness properties [Briat et al, 2016,Qian and Del Vecchio, 2018, Olsman et al, 2018. The current paper uses these properties of stability, performance, and robustness to find optimal designs for sequestration feedback networks.…”

Section: Introductionmentioning

confidence: 99%

“…In turn, these performance specifications inform the biological implementation of sequestration feedback networks. Throughout this paper, we use the stability and performance properties of sequestration feedback networks determined in , Olsman et al, 2018, Briat et al, 2016 to inform their design.…”

Section: Introductionmentioning

confidence: 99%

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Design Guidelines For Sequestration Feedback Networks

Baetica

Leong

Olsman

et al. 2018

Preprint

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Integral control is commonly used in mechanical and electrical systems to ensure perfect adaptation. A proposed design of integral control for synthetic biological systems employs the sequestration of two biochemical controller species. The unbound amount of controller species captures the integral of the error between the current and the desired state of the system. However, implementing integral control inside bacterial cells using sequestration feedback has been challenging due to the controller molecules being degraded and diluted. Furthermore, integral control can only 10 be achieved under stability conditions that not all sequestration feedback networks fulfill. In this work, we give guidelines for ensuring stability and good performance (small steady-state error) in sequestration feedback networks. Our guidelines provide simple tuning options to obtain a flexible and practical biological implementation of sequestration feedback control. Using tools and metrics from control theory, we pave the path for the systematic design of synthetic biological circuits.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Design Guidelines For Sequestration Feedback Networks

Baetica

Leong

Olsman

et al. 2018

Preprint

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“…The reference is set by the external IPTG level that induce AHL synthesis rate so that teh two cell populations achieve a controlled fraction in consortia. The circuit has good tracking accuracy of the reference and robust adaptation because it includes a sequestration-based controller that can be approximated as an integral feedback [25]- [27].…”

Section: Introductionmentioning

confidence: 99%

Role of communication network topology in controlling microbial population in consortia

Ren

Murray

2018

Preprint

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Engineering microbial consortia is an important new frontier for synthetic biology given its efficiency in performing complex tasks and endurance to environmental uncertainty. Most synthetic circuits regulate populational behaviors via cell-to-cell communications, which are affected by spatially heterogenous environments. Therefore, it is important to understand the limits on controlling system dynamics that are determined by interconnections among cell agents and provide a control strategy for engineering consortia. Here, we build a network model for a fractional population control circuit in twostrain consortia, and characterize the cell-to-cell communication network by topological properties, such as symmetry, locality and connectivity. Using linear network control theory, we relate the network topology to system output's tracking performance. We analytically and numerically demonstrate that the minimum network control energy for accurate tracking depends on locality difference between two cell population's spatial distributions and how strongly the controller node contributes to communication strength. To realize a robust consortia, we can manipulate the communication network topology and construct strongly connected consortia by altering chemicals in environments. Our results ground the expected cell population dynamics in its spatially organized communication network, and inspire directions in cooperative control in microbial consortia. . Bacteria have evolved communications by producing, exporting and sensing autoinducers that are mostly small and diffusible signaling molecules. This phenomenon is called quorum sensing, where the accumulation of autoinducers in environment provides a good measure of cell population density and can quantitatively affect a cell's gene expression or trigger a differentiation process [9]. Engineered communication with dedicated signal molecules are used to coordinate population level behaviors, such as cell suicide [10], pattern formation [11], and biofilm formation [12].Existing work in ecology demonstrate that the cooperative behaviors in consortia rely on the spatial distribution of multiple cell agents and the structure of their communication [13]. Efforts in network science provide a good approach to define this spatial cell-to-cell communication as a network graph, to describe the consortia as an integrated system and to analyze population level performance and robustness by graph metrics [14]. Many forms of network characteristics can determine system behaviors of complex networks such as human brain [15], gene regulatory networks [16] and social networks [17], and specific features of network topology usually play a big role [18], [19]. As multiple cell populations are usually spatially organized and form heterogeneous consorta, understanding the relationship between cell-to-cell communication network topology and cooperative dynamics in consortia is particular useful for system-level controller design in synthetic biology. By linking the communication network topology...

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Architectural Principles for Characterizing the Performance of Antithetic Integral Feedback Networks

2019

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Summary As we begin to design increasingly complex synthetic biomolecular systems, it is essential to develop rational design methodologies that yield predictable circuit performance. Here we apply mathematical tools from the theory of control and dynamical systems to yield practical insights into the architecture and function of a particular class of biological feedback circuit. Specifically, we show that it is possible to analytically characterize both the operating regime and performance tradeoffs of an antithetic integral feedback circuit architecture. Furthermore, we demonstrate how these principles can be applied to inform the design process of a particular synthetic feedback circuit.

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Hard Limits and Performance Tradeoffs in a Class of Sequestration Feedback Systems

Cited by 16 publications

References 51 publications

Design Guidelines For Sequestration Feedback Networks

Design Guidelines For Sequestration Feedback Networks

Role of communication network topology in controlling microbial population in consortia

Architectural Principles for Characterizing the Performance of Antithetic Integral Feedback Networks

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