Reaction dynamics analysis of a reconstituted Escherichia coli protein translation system by computational modeling

Metabolic Tug-of-War between Glycolysis and Translation Revealed by Biochemical Reconstitution

Inside cells, various biological systems work cooperatively for homeostasis and self-replication. These systems do not work independently as they compete for shared elements like ATP and NADH. However, it has been believed that such competition is not a problem in codependent biological systems such as the energy-supplying glycolysis and the energy-consuming translation system. In this study, we biochemically reconstituted the coupling system of glycolysis and translation using purified elements and found that the competition for ATP between glycolysis and protein synthesis interferes with their coupling. Both experiments and simulations revealed that this interference is derived from a metabolic tug-of-war between glycolysis and translation based on their reaction rates, which changes the threshold of the initial substrate concentration for the success coupling. By the metabolic tug-of-war, translation energized by strong glycolysis is facilitated by an exogenous ATPase, which normally inhibits translation. These findings provide chemical insights into the mechanism of competition among biological systems in living cells and provide a framework for the construction of synthetic metabolism in vitro.

Improving Cell-Free Expression of Model Membrane Proteins by Tuning Ribosome Cotranslational Membrane Association and Nascent Chain Aggregation

Cell-free gene expression (CFE) systems are powerful tools for transcribing and translating genes outside of a living cell. Synthesis of membrane proteins is of particular interest, but their yield in CFE is substantially lower than that for soluble proteins. In this paper, we study the CFE of membrane proteins and develop a quantitative kinetic model. We identify that ribosome stalling during the translation of membrane proteins is a strong predictor of membrane protein synthesis due to aggregation between the ribosome nascent chains. Synthesis can be improved by the addition of lipid membranes, which incorporate protein nascent chains and, therefore, kinetically compete with aggregation. We show that the balance between peptide-membrane association and peptide aggregation rates determines the yield of the synthesized membrane protein. We define a membrane protein expression score that can be used to rationalize the engineering of lipid composition and the N-terminal domain of a native and computationally designed membrane proteins produced through CFE.

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.

Rapid and Finely-Tuned Expression for Deployable Sensing Applications

Organisms from across the tree of life have evolved highly efficient mechanisms for sensing molecules of interest using biomolecular machinery that can in turn be quite valuable for the development of biosensors. However, purification of such machinery for use in in vitro biosensors is costly, while the use of whole cells as in vivo biosensors often leads to long sensor response times and unacceptable sensitivity to the chemical makeup of the sample. Cell-free expression systems overcome these weaknesses by removing the requirements associated with maintaining living sensor cells, allowing for increased function in toxic environments and rapid sensor readout at a production cost that is often more reasonable than purification. Here, we focus on the challenge of implementing cell-free protein expression systems that meet the stringent criteria required for them to serve as the basis for field-deployable biosensors. Fine-tuning expression to meet these requirements can be achieved through careful selection of the sensing and output elements, as well as through optimization of reaction conditions via tuning of DNA/RNA concentrations, lysate preparation methods, and buffer conditions. Through careful sensor engineering, cell-free systems can continue to be successfully used for the production of tightly regulated, rapidly expressing genetic circuits for biosensors.

Recent Advances in Polymer Additive Engineering for Diagnostic and Therapeutic Hydrogels

Hydrogels are hydrophilic polymer materials that provide a wide range of physicochemical properties as well as are highly biocompatible. Biomedical researchers are adapting these materials for the ever-increasing range of design options and potential applications in diagnostics and therapeutics. Along with innovative hydrogel polymer backbone developments, designing polymer additives for these backbones has been a major contributor to the field, especially for expanding the functionality spectrum of hydrogels. For the past decade, researchers invented numerous hydrogel functionalities that emerge from the rational incorporation of additives such as nucleic acids, proteins, cells, and inorganic nanomaterials. Cases of successful commercialization of such functional hydrogels are being reported, thus driving more translational research with hydrogels. Among the many hydrogels, here we reviewed recently reported functional hydrogels incorporated with polymer additives. We focused on those that have potential in translational medicine applications which range from diagnostic sensors as well as assay and drug screening to therapeutic actuators as well as drug delivery and implant. We discussed the growing trend of facile point-of-care diagnostics and integrated smart platforms. Additionally, special emphasis was given to emerging bioinformatics functionalities stemming from the information technology field, such as DNA data storage and anti-counterfeiting strategies. We anticipate that these translational purpose-driven polymer additive research studies will continue to advance the field of functional hydrogel engineering.

System concentration shift as a regulator of transcription-translation system within liposomes

Biochemical systems in living cells have their optimum concentration ratio among each constituent element to maintain their functionality. However, in the case of the biochemical system with complex interactions and feedbacks among elements, their activity as a system greatly changes by the concentration shift of the entire system irrespective of the concentration ratio among elements. In this study, by using a transcription-translation (TX-TL) system as the subject, we illustrate the principle of the nonlinear relationship between the system concentration and the activity of the system. Our experiment and simulation showed that shifts of the system concentration of TX-TL by dilution and concentration works as a switch of activity and demonstrated its ability to induce a biochemical system to confer the permeability of small molecules to liposomes. These results contribute to the creation of artificial cells with the switch and provide an insight into the emergence of protocells.

A Relationship between NTP and Cell Extract Concentration for Cell-Free Protein Expression

The cell-free protein synthesis (CFPS) that synthesizes mRNA and protein from a template DNA has been featured as an important tool to emulate living systems in vitro. However, an obstacle to emulate living cells by CFPS is the loss of activity in the case of usage of high concentration cell extracts. In this study, we found that a high concentration of NTP which inhibits in the case of lower concentration cell extract restored the loss of CFPS activity using high concentration cell extracts. The NTP restoration was independent of the energy regeneration system used, and NTP derivatives also restored the levels of CFPS using a high concentration cell extract. Experiments using dialysis mode of CFPS showed that continuous exchange of small molecule reduced levels of NTP requirement and improved reaction speed of CFPS using the high concentration of cell extract. These findings contribute to the development of a method to understand the condition of living cells by in vitro emulation, and are expected to lead to the achievement of the reconstitution of living cells from biomolecule mixtures.

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.

A partially self-regenerating synthetic cell

Self-regeneration is a fundamental function of all living systems. Here we demonstrate partial molecular self-regeneration in a synthetic cell. By implementing a minimal transcription-translation system within microfluidic reactors, the system is able to regenerate essential protein components from DNA templates and sustain synthesis activity for over a day. By quantitating genotype-phenotype relationships combined with computational modeling we find that minimizing resource competition and optimizing resource allocation are both critically important for achieving robust system function. With this understanding, we achieve simultaneous regeneration of multiple proteins by determining the required DNA ratios necessary for sustained self-regeneration. This work introduces a conceptual and experimental framework for the development of a self-replicating synthetic cell.

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.

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).

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.

A stochastic model for simulating ribosome kinetics in vivo

Computational modelling of in vivo protein synthesis is highly complicated, as it requires the simulation of ribosomal movement over the entire transcriptome, as well as consideration of the concentration effects from 40+ different types of tRNAs and numerous other protein factors. Here I report on the development of a stochastic model for protein translation that is capable of simulating the dynamical process of in vivo protein synthesis in a prokaryotic cell containing several thousand unique mRNA sequences, with explicit nucleotide information for each, and report on a number of biological predictions which are beyond the scope of existing models. In particular, I show that, when the complex network of concentration dependent interactions between elongation factors, tRNAs, ribosomes, and other factors required for protein synthesis are included in full detail, several biological phenomena, such as the increasing peptide elongation rate with bacterial growth rate, are predicted as emergent properties of the model. The stochastic model presented here demonstrates the importance of considering the translational process at this level of detail, and provides a platform to interrogate various aspects of translation that are difficult to study in more coarse-grained models.

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.

Efficiency of protein synthesis inhibition depends on tRNA and codon compositions

Regulation and maintenance of protein synthesis are vital to all organisms and are thus key targets of attack and defense at the cellular level. Here, we mathematically analyze protein synthesis for its sensitivity to the inhibition of elongation factor EF-Tu and/or ribosomes in dependence of the system’s tRNA and codon compositions. We find that protein synthesis reacts ultrasensitively to a decrease in the elongation factor’s concentration for systems with an imbalance between codon usages and tRNA concentrations. For well-balanced tRNA/codon compositions, protein synthesis is impeded more effectively by the inhibition of ribosomes instead of EF-Tu. Our predictions are supported by re-evaluated experimental data as well as by independent computer simulations. Not only does the described ultrasensitivity render EF-Tu a distinguished target of protein synthesis inhibiting antibiotics. It may also enable persister cell formation mediated by toxin-antitoxin systems. The strong impact of the tRNA/codon composition provides a basis for tissue-specificities of disorders caused by mutations of human mitochondrial EF-Tu as well as for the potential use of EF-Tu targeting drugs for tissue-specific treatments.

We predict and analyze the response of differently composed protein synthesis systems to the inhibition of elongation factor EF-Tu and/or ribosomes. The study reveals a strong interdependency of a protein synthesis system’s composition and its susceptibility to inhibition. This interdependency defines a generic mechanism that provides a common basis for a variety of seemingly unrelated phenomena including, for example, persister cell formation and tissue-specificity of certain mitochondrial diseases. The described mechanism applies to simple artificial translation systems as well as to complex protein synthesis in vivo.

Microfluidics for Artificial Life: Techniques for Bottom-Up Synthetic Biology

Synthetic biology is a rapidly growing multidisciplinary branch of science that exploits the advancement of molecular and cellular biology. Conventional modification of pre-existing cells is referred to as the top-down approach. Bottom-up synthetic biology is an emerging complementary branch that seeks to construct artificial cells from natural or synthetic components. One of the aims in bottom-up synthetic biology is to construct or mimic the complex pathways present in living cells. The recent, and rapidly growing, application of microfluidics in the field is driven by the central tenet of the bottom-up approach-the pursuit of controllably generating artificial cells with precisely defined parameters, in terms of molecular and geometrical composition. In this review we survey conventional methods of artificial cell synthesis and their limitations. We proceed to show how microfluidic approaches have been pivotal in overcoming these limitations and ushering in a new generation of complexity that may be imbued in artificial cells and the milieu of applications that result.

Cell-Free Protein Synthesis: Chassis toward the Minimal Cell

The quest for a minimal cell not only sheds light on the fundamental principles of life but also brings great advances in related applied fields such as general biotechnology. Minimal cell projects came from the study of a plausible route to the origin of life. Later on, research extended and also referred to the construction of artificial cells, or even more broadly, as in vitro synthetic biology. The cell-free protein synthesis (CFPS) techniques harness the central cellular activity of transcription/translation in an open environment, providing the framework for multiple cellular processes assembling. Therefore, CFPS systems have become the first choice in the construction of the minimal cell. In this review, we focus on the recent advances in the quantitative analysis of CFPS and on its advantage for addressing the bottom-up assembly of a minimal cell and illustrate the importance of systemic chassis behavior, such as stochasticity under a compartmentalized micro-environment.

Cell-Free Protein Synthesis and Its Perspectives for Assembling Cells from the Bottom-Up

The underlying idea of synthetic biology is that biological reactions/modules/systems can be precisely engineered and controlled toward desired products. Numerous efforts in the past decades in deciphering the complexity of biological systems in vivo have led to a variety of tools for synthetic biology, especially based on recombinant DNA. However, one generic limitation of all living systems is that the vast majority of energy input is dedicated to maintain the system as a whole, rather than the small part of interest. Cell-free synthetic biology is aiming at exactly this fundamental limitation, providing the next level of flexibility for engineering and designing biological systems in vitro. New technology has continuously inspired cell-free biology and extended its applications, including gene circuits, spatiotemporally controlled pathways, coactivated catalysts systems, and rationally designed multienzyme pathways, in particular, minimal cell construction. In the context of this special issue, discussing work being carried out in the "MaxSynBio" consortium, the advances in characterizing stochasticity and dynamics of cell-free protein synthesis within cell-sized compartments, as well as the molecular crowding effect, are discussed. The organization of spatial heterogeneity is the key prerequisite for achieving hierarchy and stepwise assembly of minimal cells from the bottom-up.

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?

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

Robustness against environmental changes is one of the major features of biological systems, but its origin is not well understood. We recently constructed a large-scale computational model of an Escherichia coli-based reconstituted in vitro translation system that enumerates all protein synthesis processes in detail. Our model synthesizes a formyl-Met-Gly-Gly tripeptide (MGG peptide) from 27 initial molecular components through 968 biochemical reactions. Among the 968 kinetic parameters, 483 are nonzero parameters, and the simulator was used to determine how perturbations of 483 individual reactions affect the complex reaction network. We found that even when the kinetic parameter was changed from 100- to 0.01-fold, 94% of the changes hardly affected the two indicators of reaction dynamics in MGG peptide synthesis, which represent the yield of the MGG peptide and the initial lag-time of the peptide synthesis. Moreover, none of the indicators increased proportionally to these changes: e.g., a 100-fold increase in the kinetic parameter increased the yield by only 2.2-fold at most, indicating the insensitivity of the reaction network to perturbation. Robustness and insensitivity are likely to be a common feature of large-scale biological reaction networks.

Extrinsic stochastic factors (solute partition) in gene expression inside lipid vesicles and lipid-stabilized water-in-oil droplets: a review

The encapsulation of transcription-translation (TX-TL) machinery inside lipid vesicles and water-in-oil droplets leads to the construction of cytomimetic systems (often called 'synthetic cells') for synthetic biology and origins-of-life research. A number of recent reports have shown that protein synthesis inside these microcompartments is highly diverse in terms of rate and amount of synthesized protein. Here, we discuss the role of extrinsic stochastic effects (i.e. solute partition phenomena) as relevant factors contributing to this pattern. We evidence and discuss cases where between-compartment diversity seems to exceed the expected theoretical values. The need of accurate determination of solute content inside individual vesicles or droplets is emphasized, aiming at validating or rejecting the predictions calculated from the standard fluctuations theory. At the same time, we promote the integration of experiments and stochastic modeling to reveal the details of solute encapsulation and intra-compartment reactions.

Anomalous Scaling of Gene Expression in Confined Cell-Free Reactions

Cellular surface breaks the symmetry of molecular diffusion across membrane. Here, we study how steric interactions between the surface and the bulk of cell-sized emulsion droplets alters gene expression emulated by a cell-free transcription/translation (TXTL) system. The concentration of synthesized reporter proteins in droplets of radius R shows an anomalous geometric scaling of R⁴ different from the expected size-dependence of R³. Given that TXTL becomes less efficient at thin surface layer, a mathematical model explains the anomalous size-dependence found in experiment. The surface of cell-sized compartment can thus play a regulatory role for cell-free gene expression.

Cell-Free Approaches in Synthetic Biology Utilizing Microfluidics

Synthetic biology is a rapidly growing multidisciplinary branch of science which aims to mimic complex biological systems by creating similar forms. Constructing an artificial system requires optimization at the gene and protein levels to allow the formation of entire biological pathways. Advances in cell-free synthetic biology have helped in discovering new genes, proteins, and pathways bypassing the complexity of the complex pathway interactions in living cells. Furthermore, this method is cost- and time-effective with access to the cellular protein factory without the membrane boundaries. The freedom of design, full automation, and mimicking of in vivo systems reveal advantages of synthetic biology that can improve the molecular understanding of processes, relevant for life science applications. In parallel, in vitro approaches have enhanced our understanding of the living system. This review highlights the recent evolution of cell-free gene design, proteins, and cells integrated with microfluidic platforms as a promising technology, which has allowed for the transformation of the concept of bioprocesses. Although several challenges remain, the manipulation of biological synthetic machinery in microfluidic devices as suitable 'homes' for in vitro protein synthesis has been proposed as a pioneering approach for the development of new platforms, relevant in biomedical and diagnostic contexts towards even the sensing and monitoring of environmental issues.

Cell-free synthesis of stable isotope-labeled internal standards for targeted quantitative proteomics

High-sensitivity mass spectrometry approaches using selected reaction monitoring (SRM) or multiple reaction monitoring (MRM) methods are powerful tools for targeted quantitative proteomics-based investigation of dynamics in specific biological systems. Both high-sensitivity detection of low-abundance proteins and their quantification using this technique employ stable isotope-labeled peptide internal standards. Currently, there are various ways for preparing standards, including chemical peptide synthesis, cellular protein expression, and cell-free protein or peptide synthesis. Cell-free protein synthesis (CFPS) or in vitro translation (IVT) systems in particular provide high-throughput and low-cost preparation methods, and various cell types and reconstituted forms are now commercially available. Herein, we review the use of such systems for precise and reliable protein quantification.

Translation inhibition and resource balance in the TX-TL cell-free gene expression system

Quantifying the effect of vital resources on transcription (TX) and translation (TL) helps to understand the degree to which the concentration of each resource must be regulated for achieving homeostasis. Utilizing the synthetic TX-TL system, we study the impact of nucleotide triphosphates (NTPs) and magnesium (Mg²⁺) on gene expression. Recent observations of the counter-intuitive phenomenon of suppression of gene expression at high NTP concentrations have led to the speculation that such suppression is due to the consumption of resources by TX, hence leaving fewer resources for TL. In this work, we investigate an alternative hypothesis: direct suppression of the TL rate via stoichiometric mismatch in necessary reagents. We observe NTP-dependent suppression even in the early phase of gene expression, contradicting the resource-limitation argument. To further decouple the contributions of TX and TL, we performed gene expression experiments with purified messenger RNA (mRNA). Simultaneously monitoring mRNA and protein abundances allowed us to extract a time-dependent translation rate. Measuring TL rates for different Mg²⁺ and NTP concentrations, we observe a complex resource dependence. We demonstrate that TL is the rate-limiting process that is directly inhibited by high NTP concentrations. Additional Mg²⁺ can partially reverse this inhibition. In several experiments, we observe two maxima of the TL rate viewed as a function of both Mg²⁺ and NTP concentration, which can be explained in terms of an NTP-independent effect on the ribosome complex and an NTP-Mg²⁺ titration effect. The non-trivial compensatory effects of abundance of different vital resources signal the presence of complex regulatory mechanisms to achieve optimal gene expression.

Artificial cell mimics as simplified models for the study of cell biology

Living cells are hugely complex chemical systems composed of a milieu of distinct chemical species (including DNA, proteins, lipids, and metabolites) interconnected with one another through a vast web of interactions: this complexity renders the study of cell biology in a quantitative and systematic manner a difficult task. There has been an increasing drive towards the utilization of artificial cells as cell mimics to alleviate this, a development that has been aided by recent advances in artificial cell construction. Cell mimics are simplified cell-like structures, composed from the bottom-up with precisely defined and tunable compositions. They allow specific facets of cell biology to be studied in isolation, in a simplified environment where control of variables can be achieved without interference from a living and responsive cell. This mini-review outlines the core principles of this approach and surveys recent key investigations that use cell mimics to address a wide range of biological questions. It will also place the field in the context of emerging trends, discuss the associated limitations, and outline future directions of the field. Impact statement Recent years have seen an increasing drive to construct cell mimics and use them as simplified experimental models to replicate and understand biological phenomena in a well-defined and controlled system. By summarizing the advances in this burgeoning field, and using case studies as a basis for discussion on the limitations and future directions of this approach, it is hoped that this minireview will spur others in the experimental biology community to use artificial cells as simplified models with which to probe biological systems.