Self-adaptive Biosystems Through Tunable Genetic Parts and Circuits (original) (raw)

Engineering Gene Circuits: Foundations and Applications

Nanotechnology in Biology and Medicine, 2007

Synthetic biology has emerged as a useful approach to decoding fundamental laws underlying biological control. Recent efforts have produced many exciting systems and generated substantial insights. These progresses highlight the potential of synthetic biology to impact diverse areas including biology, computation, engineering, and medicine. 20.1 Introduction Biological systems often function reliably in diverse environments despite internal or external perturbations. This behavior is often characterized as ''robustness.'' Based on extensive studies over the last several decades, much of this robustness can be attributed to the control of gene expression through complex cellular networks [1-4]. These networks are known to consist of various regulatory modules, including feedback [5] and feed-forward [6] regulation and cell-cell communication [7]. With these basic regulatory modules and motifs, researchers are now constructing artificial networks that mimic nature to gain fundamental biological insight and understanding [8]. In addition, other artificial networks that are engineered with novel functions will serve as building blocks for future practical applications. These efforts form the foundation of the recent emergence of synthetic biology [3,9,10]. These artificial networks are interchangeably called ''synthetic gene circuits'' or ''engineered gene circuits.'' Recent accomplishments in synthetic biology include engineered switches [11-14], oscillators [15,16], logic gates [17-19], metabolic control [20], reengineered translational machinery [21], population control [22] and pattern formation [23] using natural or synthetic [24] cell-cell communication, reengineered viral genome [25], and hierarchically complex circuits built upon smaller, well-characterized

Tunable genetic devices through simultaneous control of transcription and translation

2019

Synthetic genetic circuits allow us to modify the behavior of living cells. However, changes in environmental conditions and unforeseen interactions between a circuit and the host cell can cause deviations from a desired function, resulting in the need for time-consuming physical re-assembly to fix these issues. Here, we use a regulatory motif controlling transcription and translation to create genetic devices whose response functions can be dynamically tuned. This approach allows us, after assembly, to shift the on and off states of a sensor by 4.5- and 28-fold, respectively, and modify a genetic NOT gate to allow its transition from an on to off state to be varied over a 7-fold range. In both cases, "tuning" leads to trade-offs in the fold-change and separation between the distributions of cells in on and off states. By using mathematical modelling, we derive design principles that are used to further optimize these devices. This work lays the foundation for adaptive gen...

Tuneable Synthetic Genetic Devices

2020

Synthetic genetic circuits are gene regulatory networks used to engineer biological systems to carry out useful functions. Moving circuits between environments or host cells alters their function in ways we can't predict, leading to circuit failures that can only be fixed by laboriously rebuilding them. Here, we propose a novel regulatory motif that controls transcription and translation of a gene. We implemented the motif to design a device-a tuneable expression system (TES) that used a riboregulator to activate translation of a gene in response to cognate small RNAs (sRNA). Transcription of the gene and sRNA were independently regulated by two sensors that were activated in response to different inducers, allowing us to dynamically tune the device's response function. The TES's outputs at high and low inputs could be shifted 4.5 and 28-fold, respectively. We tested the TES in a range of glucose concentrations to emulate how these conditions would affect device performance in industry and found that it produced protein >2-times faster in higher glucose concentrations. We showed that the TES can be regulated so protein production rate remains constant in different glucose concentrations. We then used the TES to build a tuneable repressor protein based NOT gate, whose transition between on and off states can be tuned over a >6-fold range. However, in all devices, tuning the device reduced its fold-change and separation between populations of cells with high and low inputs. Using deterministic and thermodynamic models we found we could improve the device's performance by increasing the rate of sRNA transcription and removing a self-cleaving ribozyme insulator that interfered with riboregulator function. Circuits built using the TES could be tuned and fixed dynamically, removing the need to reassemble them from new parts and accelerating genetic circuit development. Furthermore, TESs provide the basis for novel adaptive circuits, systems that self-regulate their behaviour to be optimal in all condition. i I declare that the work in this dissertation was carried out in accordance with the requirements of the University's Regulations and Code of Practice for Research Degree Programmes and that it has not been submitted for any other academic award. Except where indicated by specific reference in the text, the work is the candidate's own work. Work done in collaboration with, or with the assistance of, others, is indicated as such. Any views expressed in the dissertation are those of the author.

Context-aware synthetic biology by controller design: Engineering the mammalian cell

Cell Systems, 2021

The rise of the field of systems biology has ushered a new paradigm: the view of the cell as a system that processes environmental inputs to drive phenotypic outputs. Synthetic biology provides a complementary approach, allowing us to program cell behavior through the addition of synthetic genetic devices into the cellular processor. These devices, and the complex genetic circuits they compose, are engineered using a design-prototype-test cycle, allowing for predictable device performance to be achieved in a context-dependent manner. Within mammalian cells, context effects impact synthetic genetic device performance at multiple scales, including the genetic, cellular and extracellular levels. In order for synthetic genetic devices to achieve predictable behaviors, approaches to overcome context-dependence are necessary. Here, we describe control systems approaches for achieving context-aware devices that are robust to context effects. We then consider the application of cell fate programming as a case study to explore the potential impact of context-aware devices for regenerative medicine applications. The cell as a processor Cells are dynamic units of life that rely on microenvironmental cues to drive their decision-making. A cell's behavior-to divide, die, move, or otherwise-is driven by social interactions with neighboring cells, binding to the extracellular matrix (ECM), and by messages in the form of soluble signals. Whether a member of the multicellular societies that compose our tissues or solo explorers in the unicellular world, each cell is a processor that must map these dynamical chemical and mechanical inputs to phenotypic outputs (Figure 1A). Rooted in the field of systems

Engineering in the biological substrate: information processing in genetic circuits

Proceedings of the IEEE, 2000

We review the rapidly evolving efforts to analyze, model, simulate, and engineer genetic and biochemical information processing systems within living cells. We begin by showing that the fundamental elements of information processing in electronic and genetic systems are strikingly similar, and follow this theme through a review of efforts to create synthetic genetic circuits. In particular, we describe and review the "silicon mimetic" approach, where genetic circuits are engineered to mimic the functionality of semiconductor devices such as logic gates, latched circuits, and oscillators. This is followed with a review of the analysis, modeling, and simulation of natural and synthetic genetic circuits, which often proceed in a manner similar to that used for electronic systems. We conclude by presenting examples of naturally occurring genetic and biochemical systems that recently have been conceptualized in terms familiar to systems engineers. Our review of these newly forming fields of research demonstrates that the expertise and skills contained within electrical and computer engineering disciplines apply not only to design within biological systems, but also to the development of a deeper understanding of biological functionality. This review of these efforts points to the emergence of both engineering and basic science disciplines following parallel paths.

Synthetic biology by controller design

2022

Natural biological systems display complex regulation and synthetic biomolecular systems have been used to understand their natural counterparts and to parse sophisticated regulations into core design principles. At the same time, the engineering of biomolecular systems has unarguable potential to transform current and to enable new, yet, to be imagined, biotechnology applications. In this review, we discuss the progression of control systems design in synthetic biology, from the purpose of understanding the function of naturally occurring regulatory motifs to that of creating genetic circuits whose function is sufficiently robust for biotechnology applications.

Synthetic multicellular oscillatory systems: controlling protein dynamics with genetic circuits

Physica Scripta, 2011

Synthetic biology is a relatively new research discipline that combines standard biology approaches with the constructive nature of engineering. Thus, recent efforts in the field of synthetic biology have given a perspective to consider cells as 'programmable matter'. Here, we address the possibility of using synthetic circuits to control protein dynamics. In particular, we show how intercellular communication and stochasticity can be used to manipulate the dynamical behavior of a population of coupled synthetic units and, in this manner, finely tune the expression of specific proteins of interest, e.g. in large bioreactors.

The Design and Construction of a Set of Modular Synthetic BioLogic Devices for Programming Cells

IFMBE Proceedings, 2009

Modularity is an essential property for rationally engineered standard parts and devices. This principle is now being extended to biological based parts and devices for programming cells. However, the design principles and building blocks which are currently in Synthetic Biology are somewhat limited. In addition, it is important to explore the underlying mechanisms of existing, natural biological systems in order to utilise them in designing novel genetic circuit modules. In this paper, we will describe a set of modular synthetic biological parts and devices that are based in rational design. Particularly, a modular tight-controlled and hypersensitive genetic circuit with digital logic AND function is rationally designed and engineered. They use a sigma factor 54 dependent heteroregulation module in the hrp (hypersensitive response and pathogenicity) gene regulatory system for Type III secretion in Pseudomonas syringae. Their inputs and outputs are both promoters and thus do not rely on specific inducible promoters and could drive various cellular responses. It shows that the hrp system has significant potential for building a range of biological parts and devices with good performance and flexibility.

A synthetic biology challenge: making cells compute

Molecular BioSystems, 2007

Advances in biology and engineering have enabled the reprogramming of cells with well-defined functions, leading to the emergence of synthetic biology. Early successes in this nascent field suggest its potential to impact diverse areas. Here, we examine the feasibility of engineering circuits for cell-based computation. We illustrate the basic concepts by describing the mapping of several computational problems to engineered gene circuits. Revolving around these examples and past studies, we discuss technologies and computational methods available to design, test, and optimize gene circuits. We conclude with discussion of challenges involved in a typical design cycle, as well as those specific to cellular computation.

Genetic circuit building blocks for cellular computation, communications, and signal processing

2003

In this paper, we review an emerging engineering discipline to program cell behaviors by embedding synthetic gene networks that perform computation, communications, and signal processing. To accomplish this goal, we begin with a genetic component library and a biocircuit design methodology for assembling these components into compound circuits. The main challenge in biocircuit design lies in selecting well-matched genetic components that when coupled, reliably produce the desired behavior. We use simulation tools to guide circuit design, a process that consists of selecting the appropriate components and genetically modifying existing components until the desired behavior is achieved. In addition to such rational design, we also employ directed evolution to optimize genetic circuit behavior. Building on Nature's fundamental principle of evolution, this unique process directs cells to mutate their own DNA until they find gene network configurations that exhibit the desired system characteristics. The integration of all the above capabilities in future synthetic gene networks will enable cells to perform sophisticated digital and analog computation, both as individual entities and as part of larger cell communities. This engineering discipline and its associated tools will advance the capabilities of genetic engineering, and allow us to harness cells for a myriad of applications not previously achievable.