Robustness of a Reconstituted Escherichia coli Protein Translation System Analyzed by Computational Modeling

Cell-free expression system: a promising platform for bacteriophage production and engineering

Cell-free expression is a technique used to synthesize proteins without utilising living cells. This technique relies mainly on the cellular machinery -ribosomes, enzymes, and other components - extracted from cells to produce proteins in vitro. Thus far, cell-free expression systems have been used for an array of biologically important purposes, such as studying protein functions and interactions, designing synthetic pathways, and producing novel proteins and enzymes. In this review article, we aim to provide bacteriophage (phage) researchers with an understanding of the cell-free expression process and the potential it holds to accelerate phage production and engineering for phage therapy and other applications. Throughout the review, we summarize the system's main steps and components, both generally and particularly for the self-assembly and engineering of phages and discuss their potential optimization for better protein and phage production. Cell-free expression systems have the potential to serve as a platform for the biosynthetic production of personalized phage therapeutics. This is an area of in vitro biosynthesis that is becoming increasingly attractive, given the current high interest in phages and their promising potential role in the fight against antimicrobial resistant infections.

Impact of Chemical Dynamics of Commercial PURE Systems on Malachite Green Aptamer Fluorescence

The malachite green aptamer (MGapt) is known for its utility in RNA measurement in vivo and in lysate-based cell-free protein systems. However, MGapt fluorescence dynamics do not accurately reflect RNA concentration. Our study finds that MGapt fluorescence is unstable in commercial PURE systems. We discovered that the chemical composition of the cell-free reaction strongly influences MGapt fluorescence, which leads to inaccurate RNA calculations. Specific to the commercial system, we posit that MGapt fluorescence is significantly affected by the system's chemical properties, governed notably by the presence of dithiothreitol (DTT). We propose a model that, on average, accurately predicts MGapt measurement within a 10% margin, leveraging DTT concentration as a critical factor. This model sheds light on the complex dynamics of MGapt in cell-free systems and underscores the importance of considering environmental factors in RNA measurements using aptamers.

Chemical Reaction Models in Synthetic Promoter Design in Bacteria

We discuss the formalism of chemical reaction networks (CRNs) as a computer-aided design interface for using formal methods in engineering living technologies. We set out by reviewing formal methods within a broader view of synthetic biology. Based on published results, we illustrate, step by step, how mathematical and computational techniques on CRNs can be used to study the structural and dynamic properties of the designed systems. As a case study, we use an E. coli two-component system that relays the external inorganic phosphate concentration signal to genetic components. We show how CRN models can scan and explore phenotypic regimes of synthetic promoters with varying detection thresholds, thereby providing a means for fine-tuning the promoter strength to match the specification.

ePURE_JSBML: A Tool for Constructing a Deterministic Model of a Reconstituted Escherichia coli Protein Translation System with a User-Specified Nucleic Acid Sequence

A protein synthesis system is one of the most important and complex biological networks, which translates DNA-encoded information into specific functions. Here, ePURE_JSBML, a tool for constructing biologically relevant large-scale and detailed computational models based on a reconstituted cell-free protein synthesis system, is presented; the user can specify the mRNA sequence, initial component concentration, and decoding rule. Model construction is based on Systems Biology Markup Language (SBML) using JSBML, a pure Java programming library. The tool generates simulation files, executable with Matlab, that enable a variety of simulation experiments including the synthesis of proteins of a few hundred residues.

Cell-Free PURE System: Evolution and Achievements

The cell-free protein synthesis (CFPS) system, as a technical core of synthetic biology, can simulate the transcription and translation process in an in vitro open environment without a complete living cell. It has been widely used in basic and applied research fields because of its advanced engineering features in flexibility and controllability. Compared to a typical crude extract-based CFPS system, due to defined and customizable components and lacking protein-degrading enzymes, the protein synthesis using recombinant elements (PURE) system draws great attention. This review first discusses the elemental composition of the PURE system. Then, the design and preparation of functional proteins for the PURE system, especially the critical ribosome, were examined. Furthermore, we trace the evolving development of the PURE system in versatile areas, including prototyping, synthesis of unnatural proteins, peptides and complex proteins, and biosensors. Finally, as a state-of-the-art engineering strategy, this review analyzes the opportunities and challenges faced by the PURE system in future scientific research and diverse applications.

Stochastic Simulations as a Tool for Assessing Signal Fidelity in Gene Expression in Synthetic Promoter Design

Simple Summary

Synthetic biology is an emerging discipline, offering new perspectives in many industrial fields, from pharma and row-material production to renewable energy. Developing synthetic biology applications is often a lengthy and expensive process with extensive and tedious trial-and-error runs. Computational models can direct the engineering of biological circuits in a computer-aided design setting. By providing a virtual lab environment, in silico models of synthetic circuits can contribute to a quantitative understanding of the underlying molecular pathways before a wet-lab implementation. Here, we illustrate this notion from the point of view of signal fidelity and noise relationship. Noise in gene expression can undermine signal fidelity with implications on the well-functioning of the engineered organisms. For our analysis, we use a specific biological circuit that regulates the gene expression in bacterial inorganic phosphate economy. Applications that use this circuit include those in pollutant detection and wastewater treatment. We provide computational models with different levels of molecular detail as virtual labs. We show that inherent fluctuations in the gene expression machinery can be predicted via stochastic simulations to introduce control in the synthetic promoter design process. Our analysis suggests that noise in the system can be alleviated by strong synthetic promoters with slow unbinding rates. Overall, we provide a recipe for the computer-aided design of synthetic promoter libraries with specific signal to noise characteristics.

Abstract

The design and development of synthetic biology applications in a workflow often involve connecting modular components. Whereas computer-aided design tools are picking up in synthetic biology as in other areas of engineering, the methods for verifying the correct functioning of living technologies are still in their infancy. Especially, fine-tuning for the right promoter strength to match the design specifications is often a lengthy and expensive experimental process. In particular, the relationship between signal fidelity and noise in synthetic promoter design can be a key parameter that can affect the healthy functioning of the engineered organism. To this end, based on our previous work on synthetic promoters for the E. coli PhoBR two-component system, we make a case for using chemical reaction network models for computational verification of various promoter designs before a lab implementation. We provide an analysis of this system with extensive stochastic simulations at a single-cell level to assess the signal fidelity and noise relationship. We then show how quasi-steady-state analysis via ordinary differential equations can be used to navigate between models with different levels of detail. We compare stochastic simulations with our full and reduced models by using various metrics for assessing noise. Our analysis suggests that strong promoters with low unbinding rates can act as control tools for filtering out intrinsic noise in the PhoBR context. Our results confirm that even simpler models can be used to determine promoters with specific signal to noise characteristics.

Computer-Aided Whole-Cell Design: Taking a Holistic Approach by Integrating Synthetic With Systems Biology

Computer-aided design (CAD) for synthetic biology promises to accelerate the rational and robust engineering of biological systems. It requires both detailed and quantitative mathematical and experimental models of the processes to (re)design biology, and software and tools for genetic engineering and DNA assembly. Ultimately, the increased precision in the design phase will have a dramatic impact on the production of designer cells and organisms with bespoke functions and increased modularity. CAD strategies require quantitative models of cells that can capture multiscale processes and link genotypes to phenotypes. Here, we present a perspective on how whole-cell, multiscale models could transform design-build-test-learn cycles in synthetic biology. We show how these models could significantly aid in the design and learn phases while reducing experimental testing by presenting case studies spanning from genome minimization to cell-free systems. We also discuss several challenges for the realization of our vision. The possibility to describe and build whole-cells in silico offers an opportunity to develop increasingly automatized, precise and accessible CAD tools and strategies.

Cell-Free Systems: A Proving Ground for Rational Biodesign

Cell-free gene expression systems present an alternative approach to synthetic biology, where biological gene expression is harnessed inside non-living, in vitro biochemical reactions. Taking advantage of a plethora of recent experimental innovations, they easily overcome certain challenges for computer-aided biological design. For instance, their open nature renders all their components directly accessible, greatly facilitating model construction and validation. At the same time, these systems present their own unique difficulties, such as limited reaction lifetimes and lack of homeostasis. In this Perspective, I propose that cell-free systems are an ideal proving ground to test rational biodesign strategies, as demonstrated by a small but growing number of examples of model-guided, forward engineered cell-free biosystems. It is likely that advances gained from this approach will contribute to our efforts to more reliably and systematically engineer both cell-free as well as living cellular systems for useful applications.

Bottom-Up Construction of Complex Biomolecular Systems With Cell-Free Synthetic Biology

Cell-free systems offer a promising approach to engineer biology since their open nature allows for well-controlled and characterized reaction conditions. In this review, we discuss the history and recent developments in engineering recombinant and crude extract systems, as well as breakthroughs in enabling technologies, that have facilitated increased throughput, compartmentalization, and spatial control of cell-free protein synthesis reactions. Combined with a deeper understanding of the cell-free systems themselves, these advances improve our ability to address a range of scientific questions. By mastering control of the cell-free platform, we will be in a position to construct increasingly complex biomolecular systems, and approach natural biological complexity in a bottom-up manner.

Quantitative modeling of transcription and translation of an all-E. coli cell-free system

Cell-free transcription-translation (TXTL) is expanding as a polyvalent experimental platform to engineer biological systems outside living organisms. As the number of TXTL applications and users is rapidly growing, some aspects of this technology could be better characterized to provide a broader description of its basic working mechanisms. In particular, developing simple quantitative biophysical models that grasp the different regimes of in vitro gene expression, using relevant kinetic constants and concentrations of molecular components, remains insufficiently examined. In this work, we present an ODE (Ordinary Differential Equation)-based model of the expression of a reporter gene in an all E. coli TXTL that we apply to a set of regulatory elements spanning several orders of magnitude in strengths, far beyond the T7 standard system used in most of the TXTL platforms. Several key biochemical constants are experimentally determined through fluorescence assays. The robustness of the model is tested against the experimental parameters, and limitations of TXTL resources are described. We establish quantitative references between the performance of E. coli and synthetic promoters and ribosome binding sites. The model and the data should be useful for the TXTL community interested either in gene network engineering or in biomanufacturing beyond the conventional platforms relying on phage transcription.

Construction of an Efficient and Robust Aspergillus terreus Cell Factory for Monacolin J Production

Monacolin J is a key precursor for the synthesis of the cholesterol-lowering drug simvastatin. Industrially, monacolin J is manufactured through the alkaline hydrolysis of the fungal polyketide lovastatin, which is relatively complex and environmentally unfriendly. A cell factory for monacolin J production was created by heterologously introducing lovastatin hydrolase into Aspergillus terreus in our previous study. However, residual lovastatin remained a problem for the downstream product purification. In this study, we used combined metabolic engineering strategies to create a more efficient and robust monacolin J-producing cell factory that completely lacks lovastatin residue. The complete deletion of the key gene lovF blocked the biosynthesis of lovastatin and led to a large accumulation of monacolin J without any lovastatin residue. Additionally, the overexpression of the specific transcription factor lovE under the P gpdAt promoter further increased the titer of monacolin J by 52.5% to 5.5 g L^-1. Interestingly, the fermentation robustness was also significantly improved by the expression of lovE. This improvement not only avoids the process of alkaline hydrolysis but also simplifies the downstream separation process.

A Simple, Robust, and Low-Cost Method To Produce the PURE Cell-Free System

We demonstrate a simple, robust, and low-cost method for producing the PURE cell-free transcription-translation system. Our OnePot PURE system achieved a protein synthesis yield of 156 μg/mL at a cost of 0.09 USD/μL, leading to a 14-fold improvement in cost normalized protein synthesis yield over existing PURE systems. The one-pot method makes the PURE system easy to generate and allows it to be readily optimized and modified.

Is Research on "Synthetic Cells" Moving to the Next Level?

"Synthetic cells" research focuses on the construction of cell-like models by using solute-filled artificial microcompartments with a biomimetic structure. In recent years this bottom-up synthetic biology area has considerably progressed, and the field is currently experiencing a rapid expansion. Here we summarize some technical and theoretical aspects of synthetic cells based on gene expression and other enzymatic reactions inside liposomes, and comment on the most recent trends. Such a tour will be an occasion for asking whether times are ripe for a sort of qualitative jump toward novel SC prototypes: is research on "synthetic cells" moving to a next level?

Models for Cell-Free Synthetic Biology: Make Prototyping Easier, Better, and Faster

Cell-free TX-TL is an increasingly mature and useful platform for prototyping, testing, and engineering biological parts and systems. However, to fully accomplish the promises of synthetic biology, mathematical models are required to facilitate the design and predict the behavior of biological components in cell-free extracts. We review here the latest models accounting for transcription, translation, competition, and depletion of resources as well as genome scale models for lysate-based cell-free TX-TL systems, including their current limitations. These models will have to find ways to account for batch-to-batch variability before being quantitatively predictive in cell-free lysate-based platforms.