Engineering a Functional Small RNA Negative Autoregulation Network with Model-Guided Design

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.

Enzyme-Free Nucleic Acid Circuits for Fold-Change Detection

Fold-change detection is widespread in sensory systems of various organisms. Dynamic DNA nanotechnology provides an important toolbox for reproducing structures and responses of cellular circuits. In this work, we construct an enzyme-free nucleic acid circuit based on the incoherent feed-forward loop using toehold-mediated DNA strand displacement reactions and explore its dynamic behaviors. The mathematical model based on ordinary differential equations is used to evaluate the parameter regime required for fold-change detection. After selecting appropriate parameters, the constructed synthetic circuit exhibits approximate fold-change detection for multiple rounds of inputs with different initial concentrations. This work is anticipated to shed new light on the design of DNA dynamic circuits in the enzyme-free environment.

Enabling technology and core theory of synthetic biology

Synthetic biology provides a new paradigm for life science research ("build to learn") and opens the future journey of biotechnology ("build to use"). Here, we discuss advances of various principles and technologies in the mainstream of the enabling technology of synthetic biology, including synthesis and assembly of a genome, DNA storage, gene editing, molecular evolution and de novo design of function proteins, cell and gene circuit engineering, cell-free synthetic biology, artificial intelligence (AI)-aided synthetic biology, as well as biofoundries. We also introduce the concept of quantitative synthetic biology, which is guiding synthetic biology towards increased accuracy and predictability or the real rational design. We conclude that synthetic biology will establish its disciplinary system with the iterative development of enabling technologies and the maturity of the core theory.

Layered feedback control overcomes performance trade-off in synthetic biomolecular networks

Layered feedback is an optimization strategy in feedback control designs widely used in engineering. Control theory suggests that layering multiple feedbacks could overcome the robustness-speed performance trade-off limit. In natural biological networks, genes are often regulated in layers to adapt to environmental perturbations. It is hypothesized layering architecture could also overcome the robustness-speed performance trade-off in genetic networks. In this work, we validate this hypothesis with a synthetic biomolecular network in living E. coli cells. We start with system dynamics analysis using models of various complexities to guide the design of a layered control architecture in living cells. Experimentally, we interrogate system dynamics under three groups of perturbations. We consistently observe that the layered control improves system performance in the robustness-speed domain. This work confirms that layered control could be adopted in synthetic biomolecular networks for performance optimization. It also provides insights into understanding genetic feedback control architectures in nature.

Characterizing a New Fluorescent Protein for a Low Limit of Detection Sensing in the Cell-Free System

Cell-free protein synthesis-based biosensors have been developed as highly accurate, low-cost biosensors. However, since most biomarkers exist at low concentrations in various types of biopsies, the biosensor's dynamic range must be increased in the system to achieve low limits of detection necessary while deciphering from higher background signals. Many attempts to increase the dynamic range have relied on amplifying the input signal from the analyte, which can lead to complications of false positives. In this study, we aimed to increase the protein synthesis capability of the cell-free protein synthesis system and the output signal of the reporter protein to achieve a lower limit of detection. We utilized a new fluorescent protein, mNeonGreen, which produces a higher output than those commonly used in cell-free biosensors. Optimizations of DNA sequence and the subsequent cell-free protein synthesis reaction conditions allowed characterizing protein expression variability by given DNA template types, reaction environment, and storage additives that cause the greatest time constraint on designing the cell-free biosensor. Finally, we characterized the fluorescence kinetics of mNeonGreen compared to the commonly used reporter protein, superfolder green fluorescent protein. We expect that this finely tuned cell-free protein synthesis platform with the new reporter protein can be used with sophisticated synthetic gene circuitry networks to increase the dynamic range of a cell-free biosensor to reach lower detection limits and reduce the false-positive proportion.

RNA Compensation: A Positive Feedback Insulation Strategy for RNA-Based Transcription Networks

The lack of signaling modularity of biomolecular systems poses major challenges toward engineering complex networks. Directional signaling between an upstream and a downstream circuit requires the presence of binding events, which result in the consumption of regulatory molecules and can compromise the operation of the upstream circuit. This issue has been previously addressed by introducing insulation strategies that include high-gain negative feedback and activation-deactivation reaction cycles. In this paper, we focus on RNA-based circuits and propose a new positive-feedback strategy to mitigate signal consumption that we propose occurs for each regulatory event due to irreversible binding of the RNA input to the RNA target. To mitigate this, an extra RNA input is added in tandem with transcription output to compensate the RNA consumption, leading to concentration robustness of the input RNA molecule regardless of the amount of downstream modules. We term this strategy RNA compensation, and it can be applied to systems that have a stringent input-output gain, such as Small Transcription Activating RNAs (STARs). Our theoretical analysis shows that RNA compensation not only eliminates the signaling consumption in individual STAR-based regulators, but also improves the composability of STAR cascades and the modularity of RNA bistable systems.

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.

Design and Evaluation of Synthetic RNA-Based Incoherent Feed-Forward Loop Circuits

RNA-based regulators are promising tools for building synthetic biological systems that provide a powerful platform for achieving a complex regulation of transcription and translation. Recently, de novo-designed synthetic RNA regulators, such as the small transcriptional activating RNA (STAR), toehold switch (THS), and three-way junction (3WJ) repressor, have been utilized to construct RNA-based synthetic gene circuits in living cells. In this work, we utilized these regulators to construct type 1 incoherent feed-forward loop (IFFL) circuits in vivo and explored their dynamic behaviors. A combination of a STAR and 3WJ repressor was used to construct an RNA-only IFFL circuit. However, due to the fast kinetics of RNA–RNA interactions, there was no significant timescale difference between the direct activation and the indirect inhibition, that no pulse was observed in the experiments. These findings were confirmed with mechanistic modeling and simulation results for a wider range of conditions. To increase delay in the inhibition pathway, we introduced a protein synthesis process to the circuit and designed an RNA–protein hybrid IFFL circuit using THS and TetR protein. Simulation results indicated that pulse generation could be achieved with this RNA–protein hybrid model, and this was further verified with experimental realization in E. coli. Our findings demonstrate that while RNA-based regulators excel in speed as compared to protein-based regulators, the fast reaction kinetics of RNA-based regulators could also undermine the functionality of a circuit (e.g., lack of significant timescale difference). The agreement between experiments and simulations suggests that the mechanistic modeling can help debug issues and validate the hypothesis in designing a new circuit. Moreover, the applicability of the kinetic parameters extracted from the RNA-only circuit to the RNA–protein hybrid circuit also indicates the modularity of RNA-based regulators when used in a different context. We anticipate the findings of this work to guide the future design of gene circuits that rely heavily on the dynamics of RNA-based regulators, in terms of both modeling and experimental realization.

A dynamic and multilocus metabolic regulation strategy using quorum-sensing-controlled bacterial small RNA

Metabolic regulation strategies have been developed to redirect metabolic fluxes to production pathways. However, it is difficult to screen out target genes that, when repressed, improve yield without affecting cell growth. Here, we report a strategy using a quorum-sensing system to control small RNA transcription, allowing cell-density-dependent repression of target genes. This strategy is shown with convenient operation, dynamic repression, and availability for simultaneous regulation of multiple genes. The parameters A_i, A_m, and R_A (3-oxohexanoyl-homoserine lactone [AHL] concentrations at which half of the maximum repression and the maximum repression were reached and value of the maximum repression when AHL was added manually, respectively) are defined and introduced to characterize repression curves, and the variant LuxR_I58N is identified as the most suitable tuning factor for shake flask culture. Moreover, it is shown that dynamic overexpression of the Hfq chaperone is the key to combinatorial repression without disruptions on cell growth. To show a broad applicability, the production titers of pinene, pentalenene, and psilocybin are improved by 365.3%, 79.5%, and 302.9%, respectively, by applying combinatorial dynamic repression.

Multidimensional Characterization of Parts Enhances Modeling Accuracy in Genetic Circuits

Mathematical models can aid the design of genetic circuits, but may yield inaccurate results if individual parts are not modeled at the appropriate resolution. To illustrate the importance of this concept, we study transcriptional cascades consisting of two inducible synthetic transcription factors connected in series. Despite the simplicity of this design, we find that accurate prediction of circuit behavior requires mapping the dose responses of each circuit component along the dimensions of both its expression level and its inducer concentration. Using this multidimensional characterization, we were able to computationally explore the behavior of 16 different circuit designs. We experimentally verified a subset of these predictions and found substantial agreement. This method of biological part characterization enables the use of models to identify (un)desired circuit behaviors prior to experimental implementation, thus shortening the design-build-test cycle for more complex circuits.

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.

Domain-Specific Programming Languages for Computational Nucleic Acid Systems

The construction of models of system behavior is of great importance throughout science and engineering. In bioengineering and bionanotechnology, these often take the form of dynamic models that specify the evolution of different species over time. To ensure that scientific observations and conclusions are consistent and that systems can be reliably engineered on the basis of model predictions, it is important that models of biomolecular systems can be constructed in a reliable, principled, and efficient manner. This review focuses on efforts to address this need by using domain-specific programming languages as the basis for custom design tools for researchers working on computational nucleic acid devices, where a domain-specific language is simply a programming language tailored to a particular application domain. The underlying thesis of our review is that there is a continuum of practical implementation strategies for computational nucleic acid systems, which can all benefit from appropriate domain-specific languages and software design tools. We emphasize the need for specialized yet flexible tools that can be realized using domain-specific languages that compile to more general-purpose representations.

Cell-Free Protein Synthesis as a Prototyping Platform for Mammalian Synthetic Biology

The field of mammalian synthetic biology is expanding quickly, and technologies for engineering large synthetic gene circuits are increasingly accessible. However, for mammalian cell engineering, traditional tissue culture methods are slow and cumbersome, and are not suited for high-throughput characterization measurements. Here we have utilized mammalian cell-free protein synthesis (CFPS) assays using HeLa cell extracts and liquid handling automation as an alternative to tissue culture and flow cytometry-based measurements. Our CFPS assays take a few hours, and we have established optimized protocols for small-volume reactions using automated acoustic liquid handling technology. As a proof-of-concept, we characterized diverse types of genetic regulation in CFPS, including T7 constitutive promoter variants, internal ribosomal entry sites (IRES) constitutive translation-initiation sequence variants, CRISPR/dCas9-mediated transcription repression, and L7Ae-mediated translation repression. Our data shows simple regulatory elements for use in mammalian cells can be quickly prototyped in a CFPS model system.

Cell-Free Prototyping of AND-Logic Gates Based on Heterogeneous RNA Activators

RNA-based devices controlling gene expression bear great promise for synthetic biology, as they offer many advantages such as short response times and light metabolic burden compared to protein-circuits. However, little work has been done regarding their integration to multilevel regulated circuits. In this work, we combined a variety of small transcriptional activator RNAs (STARs) and toehold switches to build highly effective AND-gates. To characterize the components and their dynamic range, we used an Escherichia coli (E. coli) cell-free transcription-translation (TX-TL) system dispensed via nanoliter droplets. We analyzed a prototype gate in vitro as well as in silico, employing parametrized ordinary differential equations (ODEs), for which parameters were inferred via parallel tempering, a Markov chain Monte Carlo (MCMC) method. On the basis of this analysis, we created nine additional AND-gates and tested them in vitro. The functionality of the gates was found to be highly dependent on the concentration of the activating RNA for either the STAR or the toehold switch. All gates were successfully implemented in vivo, offering a dynamic range comparable to the level of protein circuits. This study shows the potential of a rapid prototyping approach for RNA circuit design, using cell-free systems in combination with a model prediction.

Point-of-care biomarker quantification enabled by sample-specific calibration

Easy-to-perform, relatively inexpensive blood diagnostics have transformed at-home healthcare for some patients, but they require analytical equipment and are not easily adapted to measuring other biomarkers. The requirement for reliable quantification in complex sample types (such as blood) has been a critical roadblock in developing and deploying inexpensive, minimal-equipment diagnostics. Here, we developed a platform for inexpensive, easy-to-use diagnostics that uses cell-free expression to generate colored readouts that are visible to the naked eye, yet quantitative and robust to the interference effects seen in complex samples. We achieved this via a parallelized calibration scheme that uses the patient sample to generate custom reference curves. We used this approach to quantify a clinically relevant micronutrient and to quantify nucleic acids, demonstrating a generalizable platform for low-cost quantitative diagnostics.

Cell-Free Synthetic Biology Platform for Engineering Synthetic Biological Circuits and Systems

Synthetic biology brings engineering disciplines to create novel biological systems for biomedical and technological applications. The substantial growth of the synthetic biology field in the past decade is poised to transform biotechnology and medicine. To streamline design processes and facilitate debugging of complex synthetic circuits, cell-free synthetic biology approaches has reached broad research communities both in academia and industry. By recapitulating gene expression systems in vitro, cell-free expression systems offer flexibility to explore beyond the confines of living cells and allow networking of synthetic and natural systems. Here, we review the capabilities of the current cell-free platforms, focusing on nucleic acid-based molecular programs and circuit construction. We survey the recent developments including cell-free transcription-translation platforms, DNA nanostructures and circuits, and novel classes of riboregulators. The links to mathematical models and the prospects of cell-free synthetic biology platforms will also be discussed.

Evolving methods for rational de novo design of functional RNA molecules

Artificial RNA molecules with novel functionality have many applications in synthetic biology, pharmacy and white biotechnology. The de novo design of such devices using computational methods and prediction tools is a resource-efficient alternative to experimental screening and selection pipelines. In this review, we describe methods common to many such computational approaches, thoroughly dissect these methods and highlight open questions for the individual steps. Initially, it is essential to investigate the biological target system, the regulatory mechanism that will be exploited, as well as the desired components in order to define design objectives. Subsequent computational design is needed to combine the selected components and to obtain novel functionality. This process can usually be split into constrained sequence sampling, the formulation of an optimization problem and an in silico analysis to narrow down the number of candidates with respect to secondary goals. Finally, experimental analysis is important to check whether the defined design objectives are indeed met in the target environment and detailed characterization experiments should be performed to improve the mechanistic models and detect missing design requirements.

Cell-free microcompartmentalised transcription-translation for the prototyping of synthetic communication networks

Recent efforts in synthetic biology have shown the possibility of engineering distributed functions in populations of living cells, which requires the development of highly orthogonal, genetically encoded communication pathways. Cell-free transcription-translation (TXTL) reactions encapsulated in microcompartments enable prototyping of molecular communication channels and their integration into engineered genetic circuits by mimicking critical cell features, such as gene expression, cell size, and cell individuality within a community. In this review, we discuss the uses of cell-free transcription-translation reactions for the development of synthetic genetic circuits, with a special focus on the use of microcompartments supporting this reaction. We highlight several studies where molecular communication between non-living microcompartments and living cells have been successfully engineered.