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

Leveraging Active Learning to Establish Efficient In Vitro Transcription and Translation from Bacterial Chromosomal DNA

Gene expression is a fundamental aspect in the construction of a minimal synthetic cell, and the use of chromosomes will be crucial for the integration and regulation of complex modules. Expression from chromosomes in vitro transcription and translation (IVTT) systems presents limitations, as their large size and low concentration make them far less suitable for standard IVTT reactions. Here, we addressed these challenges by optimizing lysate-based IVTT systems at low template concentrations. We then applied an active learning tool to adapt IVTT to chromosomes as template DNA. Further insights into the dynamic data set led us to adjust the previous protocol for chromosome isolation and revealed unforeseen trends pointing at limiting transcription kinetics in our system. The resulting IVTT conditions allowed a high template DNA efficiency for the chromosomes. In conclusion, our system shows a protein-to-chromosome ratio that moves closer to in vivo biology and represents an advancement toward chromosome-based synthetic cells.

Experimental and biophysical modeling of transcription and translation dynamics in bacterial- and mammalian-based cell-free expression systems

Cell-free expression (CFE) systems have been used extensively in systems and synthetic biology as a promising platform for manufacturing proteins and chemicals. Currently, the most widely used CFE system is in vitro protein transcription and translation platform. As the rapidly increased applications and uses, it is crucial to have a standard biophysical model for quantitative studies of gene circuits, which will provide a fundamental understanding of basic working mechanisms of CFE systems. Current modeling approaches mainly focus on the characterization of E. coli-based CFE systems, a computational model that can be utilized for both bacterial- and mammalian-based CFE has not been investigated. Here, we developed a simple ODE (ordinary differential equation)-based biophysical model to simulate transcription and translation dynamics for both bacterial- and mammalian- based CFE systems. The key parameters were estimated and adjusted based on experimental results. We next tested four gene circuits to characterize kinetic dynamics of transcription and translation in E. coli- and HeLa-based CFE systems. The real-time transcription and translation were monitored using Broccoli aptamer, double stranded locked nucleic acid (dsLNA) probe and fluorescent protein. We demonstrated the difference of kinetic dynamics for transcription and translation in both systems, which will provide valuable information for quantitative genomic and proteomic studies. This simple biophysical model and the experimental data for both E. coli- and HeLa-based CFE will be useful for researchers that are interested in genetic engineering and CFE bio-manufacturing.

A genetic circuit on a single DNA molecule as an autonomous dissipative nanodevice

Realizing genetic circuits on single DNA molecules as self-encoded dissipative nanodevices is a major step toward miniaturization of autonomous biological systems. A circuit operating on a single DNA implies that genetically encoded proteins localize during coupled transcription-translation to DNA, but a single-molecule measurement demonstrating this has remained a challenge. Here, we use a genetically encoded fluorescent reporter system with improved temporal resolution and observe the synthesis of individual proteins tethered to a DNA molecule by transient complexes of RNA polymerase, messenger RNA, and ribosome. Against expectations in dilute cell-free conditions where equilibrium considerations favor dispersion, these nascent proteins linger long enough to regulate cascaded reactions on the same DNA. We rationally design a pulsatile genetic circuit by encoding an activator and repressor in feedback on the same DNA molecule. Driven by the local synthesis of only several proteins per hour and gene, the circuit dynamics exhibit enhanced variability between individual DNA molecules, and fluctuations with a broad power spectrum. Our results demonstrate that co-expressional localization, as a nonequilibrium process, facilitates single-DNA genetic circuits as dissipative nanodevices, with implications for nanobiotechnology applications and artificial cell design.

Detection of viral RNAs at ambient temperature via reporter proteins produced through the target-splinted ligation of DNA probes

Nucleic acid assays are not typically deployable in point-of-care settings because they require costly and sophisticated equipment for the control of the reaction temperature and for the detection of the signal. Here we report an instrument-free assay for the accurate and multiplexed detection of nucleic acids at ambient temperature. The assay, which we named INSPECTR (for internal splint-pairing expression-cassette translation reaction), leverages the target-specific splinted ligation of DNA probes to generate expression cassettes that can be flexibly designed for the cell-free synthesis of reporter proteins, with enzymatic reporters allowing for a linear detection range spanning four orders of magnitude and peptide reporters (which can be mapped to unique targets) enabling highly multiplexed visual detection. We used INSPECTR to detect a panel of five respiratory viral targets in a single reaction via a lateral-flow readout and ~4,000 copies of viral RNA via additional ambient-temperature rolling circle amplification of the expression cassette. Leveraging synthetic biology to simplify workflows for nucleic acid diagnostics may facilitate their broader applicability at the point of care.

Engineering activatable promoters for scalable and multi-input CRISPRa/i circuits

Dynamic, multi-input gene regulatory networks (GRNs) are ubiquitous in nature. Multilayer CRISPR-based genetic circuits hold great promise for building GRNs akin to those found in naturally occurring biological systems. We develop an approach for creating high-performing activatable promoters that can be assembled into deep, wide, and multi-input CRISPR-activation and -interference (CRISPRa/i) GRNs. By integrating sequence-based design and in vivo screening, we engineer activatable promoters that achieve up to 1,000-fold dynamic range in an Escherichia coli-based cell-free system. These components enable CRISPRa GRNs that are six layers deep and four branches wide. We show the generalizability of the promoter engineering workflow by improving the dynamic range of the light-dependent EL222 optogenetic system from 6-fold to 34-fold. Additionally, high dynamic range promoters enable CRISPRa systems mediated by small molecules and protein-protein interactions. We apply these tools to build input-responsive CRISPRa/i GRNs, including feedback loops, logic gates, multilayer cascades, and dynamic pulse modulators. Our work provides a generalizable approach for the design of high dynamic range activatable promoters and enables classes of gene regulatory functions in cell-free systems.

Bacteriophage-based techniques for elucidating the function of zebrafish gut microbiota

Bacteriophages (or phages) are unique viruses that can specifically infect bacteria. Since their discovery by Twort and d'Herelle, phages with bacterial specificity have played important roles in microbial regulation. The intestinal microbiota and host health are intimately linked with nutrient, metabolism, development, and immunity aspects. However, the mechanism of interactions between the composition of the microbiota and their functions in maintaining host health still needs to be further explored. To address the lack of methodology and functions of intestinal microbiota in the host, we first proposed that, with the regulations of special intestinal microbiota and applications of germ-free (GF) zebrafish model, phages would be used to infect and reduce/eliminate the defined gut bacteria in the conventionally raised (CR) zebrafish and compared with the GF zebrafish colonized with defined bacterial strains. Thus, this review highlighted the background and roles of phages and their functional characteristics, and we also summarized the phage-specific infection of target microorganisms, methods to improve the phage specificity, and their regulation within the zebrafish model and gut microbial functional study. Moreover, the primary protocol of phage therapy to control the intestinal microbiota in zebrafish models from larvae to adults was recommended including phage screening from natural sources, identification of host ranges, and experimental design in the animal. A well understanding of the interaction and mechanism between phages and gut bacteria in the host can potentially provide powerful strategies or techniques for preventing bacteria-related human diseases by precisely regulating in vitro and in vivo, which will provide novel insights for phages' application and combined research in the future. KEY POINTS: • Zebrafish models for clarifying the microbial and phages' functions were discussed • Phages infect host bacteria with exquisite specificity and efficacy • Phages can reduce/eliminate the defined gut bacteria to clarify their function.

The Long Road to a Synthetic Self-Replicating Central Dogma

The construction of a biochemical system capable of self-replication is a key objective in bottom-up synthetic biology. Throughout the past two decades, a rapid progression in the design of in vitro cell-free systems has provided valuable insight into the requirements for the development of a minimal system capable of self-replication. The main limitations of current systems can be attributed to their macromolecular composition and how the individual macromolecules use the small molecules necessary to drive RNA and protein synthesis. In this Perspective, we discuss the recent steps that have been taken to generate a minimal cell-free system capable of regenerating its own macromolecular components and maintaining the homeostatic balance between macromolecular biogenesis and consumption of primary building blocks. By following the flow of biological information through the central dogma, we compare the current versions of these systems to date and propose potential alterations aimed at designing a model system for self-replicative synthetic cells.

Parasites, Infections, and Inoculation in Synthetic Minimal Cells

Synthetic minimal cells provide a controllable and engineerable model for biological processes. While much simpler than any live natural cell, synthetic cells offer a chassis for investigating the chemical foundations of key biological processes. Herein, we show a synthetic cell system with host cells, interacting with parasites and undergoing infections of varying severity. We demonstrate how the host can be engineered to resist infection, we investigate the metabolic cost of carrying resistance, and we show an inoculation that immunizes the host against pathogens. Our work expands the synthetic cell engineering toolbox by demonstrating host-pathogen interactions and mechanisms for acquiring immunity. This brings synthetic cell systems one step closer to providing a comprehensive model of complex, natural life.

Mechanistic Insights into Cell-Free Gene Expression through an Integrated -Omics Analysis of Extract Processing Methods

Cell-free systems derived from crude cell extracts have developed into tools for gene expression, with applications in prototyping, biosensing, and protein production. Key to the development of these systems is optimization of cell extract preparation methods. However, the applied nature of these optimizations often limits investigation into the complex nature of the extracts themselves, which contain thousands of proteins and reaction networks with hundreds of metabolites. Here, we sought to uncover the black box of proteins and metabolites in Escherichia coli cell-free reactions based on different extract preparation methods. We assess changes in transcription and translation activity from σ⁷⁰ promoters in extracts prepared with acetate or glutamate buffer and the common post-lysis processing steps of a runoff incubation and dialysis. We then utilize proteomic and metabolomic analyses to uncover potential mechanisms behind these changes in gene expression, highlighting the impact of cold shock-like proteins and the role of buffer composition.

Rapid Single-Pot Assembly of Modular Chromatin Proteins for Epigenetic Engineering

Chromatin is the nucleoprotein complex that organizes genomic DNA in the nuclei of eukaryotic cells. Chromatin-modifying enzymes and chromatin-binding regulators generate chromatin states that affect DNA compaction, repair, gene expression, and ultimately cell phenotype. Many natural chromatin mediators contain subdomains that can be isolated and recombined to build synthetic regulators and probes. Engineered chromatin proteins make up a growing collection of new tools for cell engineering and can help deepen our understanding of the mechanism by which chromatin features, such as modifications of histones and DNA, contribute to the epigenetic states that govern DNA-templated processes. To support efficient exploration of the large combinatorial design space of synthetic chromatin proteins, we have developed a Golden Gate assembly method for one-step construction of protein-encoding recombinant DNA. A set of standard 2-amino acid linkers allows facile assembly of any combination of up to four protein modules, obviating the need to design different compatible overhangs to ligate different modules. Beginning with the identification of protein modules of interest, a synthetic chromatin protein can be built and expressed in vitro or in cells in under 2 weeks.

Programmable Synthesis of Biobased Materials Using Cell-Free Systems

Motivated by the intricate mechanisms underlying biomolecule syntheses in cells that chemistry is currently unable to mimic, researchers have harnessed biological systems for manufacturing novel materials. Cell-free systems (CFSs) utilizing the bioactivity of transcriptional and translational machineries in vitro are excellent tools that allow supplementation of exogenous materials for production of innovative materials beyond the capability of natural biological systems. Herein, recent studies that have advanced the ability to expand the scope of biobased materials using CFS are summarized and approaches enabling the production of high-value materials, prototyping of genetic parts and modules, and biofunctionalization are discussed. By extending the reach of chemical and enzymatic reactions complementary to cellular materials, CFSs provide new opportunities at the interface of materials science and synthetic biology.

Multiple Gene Expression in Cell-Free Protein Synthesis Systems for Reconstructing Bacteriophages and Metabolic Pathways

As a fast and reliable technology with applications in diverse biological studies, cell-free protein synthesis has become popular in recent decades. The cell-free protein synthesis system can be considered a complex chemical reaction system that is also open to exogenous manipulation, including that which could otherwise potentially harm the cell's viability. On the other hand, since the technology depends on the cell lysates by which genetic information is transformed into active proteins, the whole system resembles the cell to some extent. These features make cell-free protein synthesis a valuable addition to synthetic biology technologies, expediting the design-build-test-learn cycle of synthetic biology routines. While the system has traditionally been used to synthesize one protein product from one gene addition, recent studies have employed multiple gene products in order to, for example, develop novel bacteriophages, viral particles, or synthetic metabolisms. Thus, we would like to review recent advancements in applying cell-free protein synthesis technology to synthetic biology, with an emphasis on multiple gene expressions.

Rapid modeling of experimental molecular kinetics with simple electronic circuits instead of with complex differential equations

Kinetic modeling has relied on using a tedious number of mathematical equations to describe molecular kinetics in interacting reactions. The long list of differential equations with associated abstract variables and parameters inevitably hinders readers’ easy understanding of the models. However, the mathematical equations describing the kinetics of biochemical reactions can be exactly mapped to the dynamics of voltages and currents in simple electronic circuits wherein voltages represent molecular concentrations and currents represent molecular fluxes. For example, we theoretically derive and experimentally verify accurate circuit models for Michaelis-Menten kinetics. Then, we show that such circuit models can be scaled via simple wiring among circuit motifs to represent more and arbitrarily complex reactions. Hence, we can directly map reaction networks to equivalent circuit schematics in a rapid, quantitatively accurate, and intuitive fashion without needing mathematical equations. We verify experimentally that these circuit models are quantitatively accurate. Examples include 1) different mechanisms of competitive, noncompetitive, uncompetitive, and mixed enzyme inhibition, important for understanding pharmacokinetics; 2) product-feedback inhibition, common in biochemistry; 3) reversible reactions; 4) multi-substrate enzymatic reactions, both important in many metabolic pathways; and 5) translation and transcription dynamics in a cell-free system, which brings insight into the functioning of all gene-protein networks. We envision that circuit modeling and simulation could become a powerful scientific communication language and tool for quantitative studies of kinetics in biology and related fields.

Negative autoregulation controls size scaling in confined gene expression reactions

Gene expression via transcription-translation is the most fundamental reaction to sustain biological systems, and complex reactions occur in a small compartment of living cells. There is increasing evidence that physical effects, such as molecular crowding or excluded volume effects of transcriptional-translational machinery, affect the yield of reaction products. On the other hand, transcriptional feedback that controls gene expression during mRNA synthesis is also a vital mechanism that regulates protein synthesis in cells. However, the excluded volume effect of spatial constraints on feedback regulation is not well understood. Here, we study the confinement effect on transcriptional autoregulatory feedbacks of gene expression reactions using a theoretical model. The excluded volume effects between molecules and the membrane interface suppress the gene expression in a small cell-sized compartment. We find that negative feedback regulation at the transcription step mitigates this size-induced gene repression and alters the scaling relation of gene expression level on compartment volume, approaching the regular scaling relation without the steric effect. This recovery of regular size-scaling of gene expression does not appear in positive feedback regulation, suggesting that negative autoregulatory feedback is crucial for maintaining reaction products constant regardless of compartment size in heterogeneous cell populations.

Cell-Free Gene Expression Dynamics in Synthetic Cell Populations

The ability to build synthetic cellular populations from the bottom-up provides the groundwork to realize minimal living tissues comprising single cells which can communicate and bridge scales into multicellular systems. Engineered systems made of synthetic micron-sized compartments and integrated reaction networks coupled with mathematical modeling can facilitate the design and construction of complex and multiscale chemical systems from the bottom-up. Toward this goal, we generated populations of monodisperse liposomes encapsulating cell-free expression systems (CFESs) using double-emulsion microfluidics and quantified transcription and translation dynamics within individual synthetic cells of the population using a fluorescent Broccoli RNA aptamer and mCherry protein reporter. CFE dynamics in bulk reactions were used to test different coarse-grained resource-limited gene expression models using model selection to obtain transcription and translation rate parameters by likelihood-based parameter estimation. The selected model was then applied to quantify cell-free gene expression dynamics in populations of synthetic cells. In combination, our experimental and theoretical approaches provide a statistically robust analysis of CFE dynamics in bulk and monodisperse synthetic cell populations. We demonstrate that compartmentalization of CFESs leads to different transcription and translation rates compared to bulk CFE and show that this is due to the semipermeable lipid membrane that allows the exchange of materials between the synthetic cells and the external environment.

Accelerating Whole-Cell Simulations of mRNA Translation Using a Dedicated Hardware

In recent years, intracellular biophysical simulations have been used with increasing frequency not only for answering basic scientific questions but also in the field of synthetic biology. However, since these models include networks of interaction between millions of components, they are extremely time-consuming and cannot run easily on parallel computers. In this study, we demonstrate for the first time a novel approach addressing this challenge by using a dedicated hardware designed specifically to simulate such processes. As a proof of concept, we specifically focus on mRNA translation, which is the process consuming most of the energy in the cell. We design a hardware that simulates translation in Escherichia coli and Saccharomyces cerevisiae for thousands of mRNAs and ribosomes, which is in orders of magnitude faster than a similar software solution. With the sharp increase in the amount of genomic data available today and the complexity of the corresponding models inferred from them, we believe that the strategy suggested here will become common and can be used among others for simulating entire cells with all gene expression steps.

Functionalizing Cell-Free Systems with CRISPR-Associated Proteins: Application to RNA-Based Circuit Engineering

Cell-free systems have become a compelling choice for the prototyping of synthetic circuits. Many robust protocols for preparing cell-free systems are now available along with toolboxes designed for a variety of applications. Thus far, the production of cell-free extracts has often been decoupled from the production of functionalized proteins. Here, we leveraged a recent protocol for producing an E. coli-based cell-free expression system with two CRISPR-associated proteins, Csy4 and dCas9, expressed prior to harvest. We found that pre-expression did not affect the resulting extract performance, and the final concentrations of the endonucleases matched the level required for synthetic circuit prototyping. We demonstrated the benefits and versatility of dCas9 and Csy4 through the use of RNA circuitry based on a combination of single guide RNAs, small transcriptional activator RNAs, and toehold switches. For instance, we show that Csy4 processing increased 4-fold the dynamic range of a previously published AND-logic gate. Additionally, blending the CRISPR-enhanced extracts enabled us to reduce leakage in a multiple inputs gate, and to extend the type of Boolean functions available for RNA-based circuits, such as NAND-logic. Finally, we reported the use of simultaneous transcriptional and translational reporters in our RNA-based circuits. In particular, the AND-gate mRNA and protein levels were able to be independently monitored in response to transcriptional and translational activators. We hope this work will facilitate the adoption of advanced processing tools for RNA-based circuit prototyping in a cell-free environment.

Biofoundry-assisted expression and characterization of plant proteins

Many goals in synthetic biology, including the elucidation and refactoring of biosynthetic pathways and the engineering of regulatory circuits and networks, require knowledge of protein function. In plants, the prevalence of large gene families means it can be particularly challenging to link specific functions to individual proteins. However, protein characterization has remained a technical bottleneck, often requiring significant effort to optimize expression and purification protocols. To leverage the ability of biofoundries to accelerate design-built-test-learn cycles, we present a workflow for automated DNA assembly and cell-free expression of plant proteins that accelerates optimization and enables rapid screening of enzyme activity. First, we developed a phytobrick-compatible Golden Gate DNA assembly toolbox containing plasmid acceptors for cell-free expression using Escherichia coli or wheat germ lysates as well as a set of N- and C-terminal tag parts for detection, purification and improved expression/folding. We next optimized automated assembly of miniaturized cell-free reactions using an acoustic liquid handling platform and then compared tag configurations to identify those that increase expression. We additionally developed a luciferase-based system for rapid quantification that requires a minimal 11-amino acid tag and demonstrate facile removal of tags following synthesis. Finally, we show that several functional assays can be performed with cell-free protein synthesis reactions without the need for protein purification. Together, the combination of automated assembly of DNA parts and cell-free expression reactions should significantly increase the throughput of experiments to test and understand plant protein function and enable the direct reuse of DNA parts in downstream plant engineering workflows.

Phase Separation and Protein Partitioning in Compartmentalized Cell-Free Expression Reactions

Liquid-liquid phase separation (LLPS) is important to control a wide range of reactions from gene expression to protein degradation in a cell-sized space. To bring a better understanding of the compatibility of such phase-separated structures with protein synthesis, we study emergent LLPS in a cell-free transcription-translation (TXTL) reaction. When the TXTL reaction composed of many proteins is concentrated, the uniformly mixed state becomes unstable, and membrane-less phases form spontaneously. This LLPS droplet formation is induced when the TXTL reaction is enclosed in water-in-oil emulsion droplets, in which water evaporates from the surface. As the emulsion droplets shrink, smaller LLPS droplets appear inside the emulsion droplets and coalesce into large phase-separated domains that partition the localization of synthesized reporter proteins. The presence of PEG in the TXTL reaction is important not only for versatile cell-free protein synthesis but also for the formation of two large domains capable of protein partitioning. Our results may shed light on the dynamic interplay of LLPS formation and cell-free protein synthesis toward the construction of synthetic organelles.

Complex dependence of CRISPR-Cas9 binding strength on guide RNA spacer lengths

It is established that for CRISPR-Cas9 applications guide RNAs with 17-20 bp long spacer sequences are optimal for accurate target binding and cleavage. In this work we perform cell-free CRISPRa (CRISPR activation) and CRISPRi (CRISPR inhibition) experiments to demonstrate the existence of a complex dependence of CRISPR-Cas9 binding as a function of the spacer length and complementarity. Our results show that significantly truncated or mismatched spacer sequences can form stronger guide-target bonds than the conventional 17-20 bp long spacers. To explain this phenomenon, we take into consideration previous structural and single-molecule CRISPR-Cas9 experiments and develop a novel thermodynamic model of CRISPR-Cas9 target recognition.

Longer DNA exhibits greater potential for cell-free gene expression

Cell-free gene expression systems have been valuable tools for understanding how transcription/translation can be regulated in living cells. Many studies have investigated the determining factors that affect gene expression. Here we report the effect of the length of linearized reporter DNAs encoding the firefly luciferase gene so as to exclude the influence of supercoiling. It is found that longer DNA molecules exhibit significantly greater potency in gene expression; for example, the expression level for DNA with 25.7 kbp is 1000-times higher than that for DNA of 1.7 kbp. AFM observation of the DNA conformation indicates that longer DNA takes shrunken conformation with a higher segment density in the reaction mixture for gene expression, in contrast to the stiff conformation of shorter DNA. We propose an underlying mechanism for the favorable effect of longer DNA on gene expression in terms of the enhancement of access of RNA polymerase to the shrunken conformation. It is expected that the enhancement of gene expression efficiency with a shrunken DNA conformation would also be a rather general mechanism in living cellular environments.

A Streptomyces venezuelae Cell-Free Toolkit for Synthetic Biology

Prokaryotic cell-free coupled transcription–translation (TX-TL) systems are emerging as a powerful tool to examine natural product biosynthetic pathways in a test tube. The key advantages of this approach are the reduced experimental time scales and controlled reaction conditions. To realize this potential, it is essential to develop specialized cell-free systems in organisms enriched for biosynthetic gene clusters. This requires strong protein production and well-characterized synthetic biology tools. The Streptomyces genus is a major source of natural products. To study enzymes and pathways from Streptomyces, we originally developed a homologous Streptomyces cell-free system to provide a native protein folding environment, a high G+C (%) tRNA pool, and an active background metabolism. However, our initial yields were low (36 μg/mL) and showed a high level of batch-to-batch variation. Here, we present an updated high-yield and robust Streptomyces TX-TL protocol, reaching up to yields of 266 μg/mL of expressed recombinant protein. To complement this, we rapidly characterize a range of DNA parts with different reporters, express high G+C (%) biosynthetic genes, and demonstrate an initial proof of concept for combined transcription, translation, and biosynthesis of Streptomyces metabolic pathways in a single “one-pot” reaction.

Characterization of synthetic riboswitch in cell-free protein expression systems

Riboswitches are RNA-based regulatory elements that utilize ligand-induced structural changes in the 5'-untranslated region of mRNA to regulate the expression of associated genes. The majority of synthetic riboswitches have been selected and tested in cell-based systems. Cell-free protein expression systems (CFPS) have several advantages for the development and testing of synthetic riboswitches, including eliminating interactions with complex cellular networks, and the decoupling of transcription and translation processes. To gain a better understanding of the riboswitch regulatory mechanism, to allow for more efficient riboswitch optimization and use for biosensing applications, we studied the performance of a theophylline-responsive synthetic riboswitch coupled with the superfolder green fluorescent protein (sfGFP) reporter gene in E. coli cellular extract and PURE cell-free systems. To monitor the mRNA dynamics, a malachite green aptamer sequence was added to the 3'-untranslated region of sfGFP mRNA. Performance of the theophylline riboswitch was compared with a constitutively expressed sfGFP (control). Transcription dynamics of the riboswitch mRNA was very similar to the transcription of the control mRNA for all theophylline concentrations tested in both E. coli extract and PURE CFPS. However, sfGFP expression in the riboswitch construct was one order of magnitude lower, even at the highest concentration of theophylline. A mathematical model of riboswitch activation governed by the kinetic trapping mechanism was developed. Two factors - a reduced fraction of mRNA in the 'ON' state and a considerably lower translation initiation rate in the riboswitch - contribute to the much lower level of protein expression in the theophylline riboswitch compared to the control construct.

Effective Biophysical Modeling of Cell Free Transcription and Translation Processes

Transcription and translation are at the heart of metabolism and signal transduction. In this study, we developed an effective biophysical modeling approach to simulate transcription and translation processes. The model, composed of coupled ordinary differential equations, was tested by comparing simulations of two cell free synthetic circuits with experimental measurements generated in this study. First, we considered a simple circuit in which sigma factor 70 induced the expression of green fluorescent protein. This relatively simple case was then followed by a more complex negative feedback circuit in which two control genes were coupled to the expression of a third reporter gene, green fluorescent protein. Many of the model parameters were estimated from previous biophysical studies in the literature, while the remaining unknown model parameters for each circuit were estimated by minimizing the difference between model simulations and messenger RNA (mRNA) and protein measurements generated in this study. In particular, either parameter estimates from published studies were used directly, or characteristic values found in the literature were used to establish feasible ranges for the parameter estimation problem. In order to perform a detailed analysis of the influence of individual model parameters on the expression dynamics of each circuit, global sensitivity analysis was used. Taken together, the effective biophysical modeling approach captured the expression dynamics, including the transcription dynamics, for the two synthetic cell free circuits. While, we considered only two circuits here, this approach could potentially be extended to simulate other genetic circuits in both cell free and whole cell biomolecular applications as the equations governing the regulatory control functions are modular and easily modifiable. The model code, parameters, and analysis scripts are available for download under an MIT software license from the Varnerlab GitHub repository.

Compartmentalizing Cell-Free Systems: Toward Creating Life-Like Artificial Cells and Beyond

Building an artificial cell is a research area that is rigorously studied in the field of synthetic biology. It has brought about much attention with the aim of ultimately constructing a natural cell-like structure. In particular, with the more mature cell-free platforms and various compartmentalization methods becoming available, achieving this aim seems not far away. In this review, we discuss the various types of artificial cells capable of hosting several cellular functions. Different compartmental boundaries and the mature and evolving technologies that are used for compartmentalization are examined, and exciting recent advances that overcome or have the potential to address current challenges are discussed. Ultimately, we show how compartmentalization and cell-free systems have, and will, come together to fulfill the goal to assemble a fully synthetic cell that displays functionality and complexity as advanced as that in nature. The development of such artificial cell systems will offer insight into the fundamental study of evolutionary biology and the sea of applications as a result. Although several challenges remain, emerging technologies such as artificial intelligence also appear to help pave the way to address them and achieve the ultimate goal.

From deterministic to fuzzy decision-making in artificial cells

Building autonomous artificial cells capable of homeostasis requires regulatory networks to gather information and make decisions that take time and cost energy. Decisions based on few molecules may be inaccurate but are cheap and fast. Realizing decision-making with a few molecules in artificial cells has remained a challenge. Here, we show decision-making by a bistable gene network in artificial cells with constant protein turnover. Reducing the number of gene copies from 10⁵ to about 10 per cell revealed a transition from deterministic and slow decision-making to a fuzzy and rapid regime dominated by small-number fluctuations. Gene regulation was observed at lower DNA and protein concentrations than necessary in equilibrium, suggesting rate enhancement by co-expressional localization. The high-copy regime was characterized by a sharp transition and hysteresis, whereas the low-copy limit showed strong fluctuations, state switching, and cellular individuality across the decision-making point. Our results demonstrate information processing with low-power consumption inside artificial cells.

Modeling Cell-Free Protein Synthesis Systems-Approaches and Applications

In vitro systems are ideal setups to investigate the basic principles of biochemical reactions and subsequently the bricks of life. Cell-free protein synthesis (CFPS) systems mimic the transcription and translation processes of whole cells in a controlled environment and allow the detailed study of single components and reaction networks. In silico studies of CFPS systems help us to understand interactions and to identify limitations and bottlenecks in those systems. Black-box models laid the foundation for understanding the production and degradation dynamics of macromolecule components such as mRNA, ribosomes, and proteins. Subsequently, more sophisticated models revealed shortages in steps such as translation initiation and tRNA supply and helped to partially overcome these limitations. Currently, the scope of CFPS modeling has broadened to various applications, ranging from the screening of kinetic parameters to the stochastic analysis of liposome-encapsulated CFPS systems and the assessment of energy supply properties in combination with flux balance analysis (FBA).

Programming multi-protein assembly by gene-brush patterns and two-dimensional compartment geometry

The assembly of protein machines in cells is precise, rapid, and coupled to protein synthesis with regulation in space and time. The assembly of natural and synthetic nanomachines could be similarly controlled by genetic programming outside the cell. Here, we present quasi-two-dimensional (2D) silicon compartments that enable programming of protein assembly lines by local synthesis from surface-immobilized DNA brushes. Using this platform, we studied the autonomous synthesis and assembly of a structural complex from a bacteriophage and a bacterial RNA-synthesizing machine. Local synthesis and surface capture of complexes provided high assembly yield and sensitive detection of spatially resolved assembly intermediates, with the 3D geometry of the compartment and the 2D pattern of brushes dictating the yield and mode of assembly steps. Localized synthesis of proteins in a single gene brush enhances their interactions, and displacement of their genes in separated brushes leads to step-by-step surface assembly. This methodology enables spatial regulation of protein synthesis, and deciphering, reconstruction and design of biological machine assembly lines.

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.