Effective interaction graphs arising from resource limitations in gene networks

Qian, Yili; Vecchio, Domitilla Del

doi:10.1109/acc.2015.7172024

Cited by 16 publications

(24 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…While, for small circuits, the added load by synthetic circuits on these resources may be sufficiently small and thus negligible, as the circuit size increases, these loads cannot be neglected any longer. These can cause harmful effects to cell physiology (toxicity) and may result in counterintuitive couplings among otherwise independent circuits [42][43][44][45]. Suitable engineering solutions to make a circuit's behaviour more robust to fluctuations in available resources and more generally to changes in the cellular context are highly desirable and the subject of intense research.…”

Section: From Modules To Systemsmentioning

confidence: 99%

Control theory meets synthetic biology

Vecchio

Qian

2016

J. R. Soc. Interface.

Self Cite

241

191

View full text Add to dashboard Cite

The past several years have witnessed an increased presence of control theoretic concepts in synthetic biology. This review presents an organized summary of how these control design concepts have been applied to tackle a variety of problems faced when building synthetic biomolecular circuits in living cells. In particular, we describe success stories that demonstrate how simple or more elaborate control design methods can be used to make the behaviour of synthetic genetic circuits within a single cell or across a cell population more reliable, predictable and robust to perturbations. The description especially highlights technical challenges that uniquely arise from the need to implement control designs within a new hardware setting, along with implemented or proposed solutions. Some engineering solutions employing complex feedback control schemes are also described, which, however, still require a deeper theoretical analysis of stability, performance and robustness properties. Overall, this paper should help synthetic biologists become familiar with feedback control concepts as they can be used in their application area. At the same time, it should provide some domain knowledge to control theorists who wish to enter the rising and exciting field of synthetic biology.

show abstract

Section: From Modules To Systemsmentioning

confidence: 99%

Control theory meets synthetic biology

Vecchio

Qian

2016

J. R. Soc. Interface.

Self Cite

241

191

View full text Add to dashboard Cite

show abstract

“…This concept is illustrated in Fig 2A by the fact that the intergene coupling is reduced when 50 ng of total plasmid DNA is transfected rather than 500 ng. To determine the scales under which burden can be neglected and the circuit components should function as expected, a framework for modelling gene expression with resource limitations, as described in this and other publications 13,16,40,47 , could be applied. We believe that our simple framework for introducing resource-limited steps into pre-existing models of synthetic circuits provides a simple way of avoiding such downfalls, supporting the design of circuits that are apt to dealing with burden.…”

Section: Discussionmentioning

confidence: 99%

Characterization, modelling and mitigation of gene expression burden in mammalian cells

Frei

Cella

Tedeschi

et al. 2019

Preprint

View full text Add to dashboard Cite

The ability to engineer synthetic circuits and devices in mammalian cells has enabled a multitude of exciting applications in industrial biotechnology and medical therapy. In spite of the recent availability of powerful genome engineering tools such as CRISPR-Cas9, the process of designing and implementing functioning genetic circuits remains painstakingly slow and fraught with inexplicable failures. The unexpected divergence between intended and actual function of synthetic circuits can be attributed to several factors, most notably the contextual background in which these circuits operate. In particular, t he dependence of synthetic circuits on cellular resources which are limited leads to unintended dynamic couplings between the various exogenous components of the circuit, as well as with endogenous components of the host cell. The consumption of these resources by synthetic circuits thus exerts a burden on the host cell that reduces its capacity to support additional circuits, potentially resulting in counter-intuitive functional behaviors and detrimental effects on host physiology. In spite of its critical importance, gene expression burden in mammalian cells remains largely unstudied. Here, we comprehensively investigate the impact of host resource limitations on synthetic constructs in mammalian cells. We show that effects of both transcriptional and translational resource limitations can be observed and that each can lead to the coupling of independent, co-expressed synthetic genes, which in turn imposes trade-offs in their expression and diminishes performance. We next explore the role of post-transcriptional regulators, such as microRNAs (miRNAs) and RNA binding proteins (RBPs) and show that they can redistribute resources in a way that limits burden-induced coupling effects. To quantify and predict the influence of burden on gene expression in engineered cells, we describe a modelling framework that allows to incorporate the effect of limited resources into classical models of gene expression. Based on this framework, we identify network topologies that mitigate burden and then implement these topologies using endogenous and synthetic miRNA-based circuits that buffer the expression of genes of interest from fluctuations in cellular resources. Among other regulators, microRNAs can conveniently tailor synthetic device regulation in different cell lines and tissues, as well as during dynamic changes of cellular states and downstream information processing, or in pathological conditions. This study thus establishes a foundation for context-aware predictions of in vivo synthetic circuit performance and paves the way towards a more rational synthetic construct design in mammalian cells.

show abstract

“…As many translational processes simultaneously take place inside the cell, significant variations in the concentration of available ribosomes R arise [25], [24], [27], [26], [30], making the process of translating the mRNA to the protein subject to disturbances. Here, we propose a design where the rate of transcription can be amplified by the introduction of high concentrations of the RNA polymerase T7RNAP [31], resulting in a transcription rate g, where g is large.…”

Section: Examplementioning

confidence: 99%

“…For our purposes, we are interested in designing a genetic sensor, the protein output concentration of which tracks the concentration of an input transcription factor. Often, such sensors are subject to perturbations arising from changes in the availability of cellular resources [24], [25], [26], [27]. We propose to use high gain negative feedback to regulate the sensor against such perturbations.…”

Section: Introductionmentioning

confidence: 99%

A contraction approach to input tracking via high gain feedback

Hamadeh

Sontag

Vecchio

2015

2015 54th IEEE Conference on Decision and Control (CDC)

Self Cite

View full text Add to dashboard Cite

This paper adopts a contraction approach to study exogenous input tracking in dynamical systems under high gain proportional output feedback. We give conditions under which contraction of a nonlinear system's tracking error implies input to output stability from the input signal's time derivatives to the tracking error. This result is then used to demonstrate that the negative feedback connection of plants composed of two strictly positive real subsystems in cascade can follow external inputs with tracking errors that can be made arbitrarily small by applying a sufficiently large feedback gain. We utilize this result to design a biomolecular feedback regulation scheme for a synthetic genetic sensor model, making it robust to variations in the availability of a cellular resource required for protein production.

show abstract

Effective interaction graphs arising from resource limitations in gene networks

Cited by 16 publications

References 23 publications

Control theory meets synthetic biology

Control theory meets synthetic biology

Characterization, modelling and mitigation of gene expression burden in mammalian cells

A contraction approach to input tracking via high gain feedback

Contact Info

Product

Resources

About