Systematic Design and Implementation of a Novel Synthetic Fold-Change Detector Biocircuit In Vivo

Biological signaling systems not only detect the absolute levels of the signals, but are also able to sense the fold-changes of the signals. The ability to detect fold-changes provides a powerful tool for biological organisms to adapt to the changes in environment. Here we present the first novel synthetic fold-change detector (FCD) circuit built from ground up in vivo. We systematically designed the FCD circuit in silico, prototyped it in cell-free transcription-translation platform (TX-TL), and eventually implemented it in E. coli cells. We were able to show that the FCD circuit can not only generate pulse-like behavior in response to input, but also produce the same pulse response with inputs of the same fold-change, despite of different absolute signal levels

Prototyping And Implementation Of A Novel Feedforward Loop In A Cell-Free Transcription-Translation System And Cells

Building novel synthetic biological devices is a time-consuming task because of the lengthy cell-based testing and optimization processes. Recent progress made in the cell-free field suggests that the utilization of mathematical models and cell-free transcription-translation testing platforms to systematically design and test novel synthetic biocircuits may help streamline some of the processes. Here we present a study of building a novel functional biological network motif from scratch with the aid of the mathematical modeling and the cell-free prototyping. In this work, we demonstrated that we were able to make a 3-promoter feedforward circuit from a concept to a working biocircuit in cells within a month. We started with performing simulations with a cell-free transcription–translation simulation toolbox. After verifying the feasibility of the circuit design, we used a fast assembling method to build the constructs and used the linear DNAs directly in the cell-free system for prototyping. After additional tests and assemblies, we implemented the circuit in plasmid forms in cells and showed that the in vivo results were consistent with the simulations and the outcomes in the cell-free platform. This study showed the usefulness of modeling and prototyping in building synthetic biocircuits and that we can use these tools to help streamline the process of circuit optimizations in future studies

Systematic Design and Implementation of a Novel Synthetic Fold-Change Detector Biocircuit In Vivo

Biological signaling systems not only detect the absolute levels of the signals, but are also able to sense the fold-changes of the signals. The ability to detect fold-changes provides a powerful tool for biological organisms to adapt to the changes in environment. Here we present the first novel synthetic fold-change detector (FCD) circuit built from ground up in vivo. We systematically designed the FCD circuit in silico, prototyped it in cell-free transcription-translation platform (TX-TL), and eventually implemented it in E. coli cells. We were able to show that the FCD circuit can not only generate pulse-like behavior in response to input, but also produce the same pulse response with inputs of the same fold-change, despite of different absolute signal levels

Prototyping Diverse Synthetic Biological Circuits in a Cell-Free Transcription-Translation System

Synthetic biological circuits are the foundation for the ultimate goals of controlling cells and building artificial cells from the ground up. To get closer to these goals in a more efficient way, we utilize a cell-free transcription-translation system to help perfect biological circuits for the simplicity, freedom, and convenience that the system offers. In this thesis, we demonstrate three distinct aspects of biological circuits in a cell-free transcription-translation system: circuit dynamics, phosphorylation, and membrane proteins. We start with a simple feedforward circuit, which shows dynamic responses to the input. We first prototype the feedforward circuit in the cell-free system with the aid of mathematical modeling. Then, based on the knowledge learned from prototyping, we successfully implement the circuit in cells. Not only do we show that a circuit with dynamics can be prototyped in the cell- free system, but we also test a more complicated circuit involving a phosphorylation cycle. The phosphorylation-based insulator circuit is prototyped and then a model created for the circuit is shown to be identifiable in the cell-free system. To further expand the capability of the cell-free system, we demonstrate that biologically active membrane proteins can be generated in the cell-free system with engineering, suggesting that even biological circuits requiring membrane proteins can be prototyped in the system. These results help advance our knowledge of both biological circuits and the cell-free transcription-translation system, and bring us one step closer to our ultimate goals of implementing control theory in synthetic biology

Implementation and System Identification of a Phosphorylation-Based Insulator in a Cell-Free Transcription-Translation System

An outstanding challenge in the design of synthetic biocircuits is the development of a robust and efficient strategy for interconnecting functional modules. Recent work demonstrated that a phosphorylation-based insulator (PBI) implementing a dual strategy of high gain and strong negative feedback can be used as a device to attenuate retroactivity. This paper describes the implementation of such a biological circuit in a cell-free transcription-translation system and the structural identifiability of the PBI in the system. We first show that the retroactivity also exists in the cell-free system by testing a simple negative regulation circuit. Then we demonstrate that the PBI circuit helps attenuate the retroactivity significantly compared to the control. We consider a complex model that provides an intricate description of all chemical reactions and leveraging specific physiologically plausible assumptions. We derive a rigorous simplified model that captures the output dynamics of the PBI. We performed standard system identification analysis and determined that the model is globally identifiable with respect to three critical parameters. These three parameters are identifiable under specific experimental conditions and we performed these experiments to estimate the parameters. Our experimental results suggest that the functional form of our simplified model is sufficient to describe the reporter dynamics and enable parameter estimation. In general, this research illustrates the utility of the cell-free expression system as an alternate platform for biocircuit implementation and system identification and it can provide interesting insights into future biological circuit designs

System-level studies of a cell-free transcription-translation platform for metabolic engineering

Current methods for assembling biosynthetic pathways in microorganisms require a process of repeated trial and error and have long design-build-test cycles. We describe the use of a cell-free transcription-translation (TX-TL) system as a biomolecular breadboard for the rapid engineering of the 1,4-butanediol (BDO) pathway. We demonstrate the reliability of TX-TL as a platform for engineering biological systems by undertaking a careful characterization of its transcription and translation capabilities and provide a detailed analysis of its metabolic output. Using TX-TL to survey the design space of the BDO pathway enables rapid tuning of pathway enzyme expression levels for improved product yield. Leveraging TX-TL to screen enzyme variants for improved catalytic activity accelerates design iterations that can be directly applied to in vivo strain development

BioCRNpyler: Compiling Chemical Reaction Networks from Biomolecular Parts in Diverse Contexts

Biochemical interactions in systems and synthetic biology are often modeled with Chemical Reaction Networks (CRNs). CRNs provide a principled modeling environment capable of expressing a huge range of biochemical processes. In this paper, we present a software toolbox, written in python, that complies high-level design specifications to CRN representations. This compilation process offers three advantages. First, the building of the actual CRN representation is automatic and outputs Systems Biology Markup Language (SBML) models compatible with numerous simulators. Second, a library of modular biochemical components allows for different architectures and implementations of biochemical circuits to represented succinctly with design choices propogated throughout the underlying CRN automatically. This prevents the often occurring mismatch between high-level designs and model dynamics. Third, high-level design specification can be embedded into diverse biomolecular environments, such as cell-free extracts and in vivo milieus. With these advantages offered by BioCRNpyler, users can quickly build and test multitude of models in different environments. Finally, our software toolbox has a parameter database, which allows users to rapidly prototype large models using very few parameters which can be customized later

BioCRNpyler: Compiling Chemical Reaction Networks from Biomolecular Parts in Diverse Contexts

Biochemical interactions in systems and synthetic biology are often modeled with Chemical Reaction Networks (CRNs). CRNs provide a principled modeling environment capable of expressing a huge range of biochemical processes. In this paper, we present a software toolbox, written in python, that complies high-level design specifications to CRN representations. This compilation process offers three advantages. First, the building of the actual CRN representation is automatic and outputs Systems Biology Markup Language (SBML) models compatible with numerous simulators. Second, a library of modular biochemical components allows for different architectures and implementations of biochemical circuits to represented succinctly with design choices propogated throughout the underlying CRN automatically. This prevents the often occurring mismatch between high-level designs and model dynamics. Third, high-level design specification can be embedded into diverse biomolecular environments, such as cell-free extracts and in vivo milieus. With these advantages offered by BioCRNpyler, users can quickly build and test multitude of models in different environments. Finally, our software toolbox has a parameter database, which allows users to rapidly prototype large models using very few parameters which can be customized later

Quantifying resource competition and its effects in the TX-TL system

Without accounting for the limited availability of shared cellular resources, the standard model of gene expression fails to reliably predict experimental data obtained in vitro. To overcome this limitation, we develop a dynamical model of gene expression explicitly modeling competition for scarce resources. In addition to accurately describing the experimental data, this model only depends on a handful of easily identifiable parameters with clear physical interpretation. Based on this model, we then characterize the combinations of protein concentrations that are simultaneously realizable with shared resources. As application examples, we demonstrate how the results can be used to explain similarities/differences among different in vitro extracts, furthermore, we illustrate that accounting for resource usage is essential in circuit design considering the toggle switch