Characterization and mitigation of gene expression burden in mammalian cells

Engineering Plant Cell Fates and Functions for Agriculture and Industry

Many plant species are grown to enable access to specific organs or tissues, such as seeds, fruits, or stems. In some cases, a value is associated with a molecule that accumulates in a single type of cell. Domestication and subsequent breeding have often increased the yields of these target products by increasing the size, number, and quality of harvested organs and tissues but also via changes to overall plant growth architecture to suit large-scale cultivation. Many of the mutations that underlie these changes have been identified in key regulators of cellular identity and function. As key determinants of yield, these regulators are key targets for synthetic biology approaches to engineer new forms and functions. However, our understanding of many plant developmental programs and cell-type specific functions is still incomplete. In this Perspective, we discuss how advances in cellular genomics together with synthetic biology tools such as biosensors and DNA-recording devices are advancing our understanding of cell-specific programs and cell fates. We then discuss advances and emerging opportunities for cell-type-specific engineering to optimize plant morphology, responses to the environment, and the production of valuable compounds.

Harnessing Catalytic RNA Circuits for Construction of Artificial Signaling Pathways in Mammalian Cells

Engineering of genetic networks with artificial signaling pathways (ASPs) can reprogram cellular responses and phenotypes under different circumstances for a variety of diagnostic and therapeutic purposes. However, construction of ASPs between originally independent endogenous genes in mammalian cells is highly challenging. Here we report an amplifiable RNA circuit that can theoretically build regulatory connections between any endogenous genes in mammalian cells. We harness the system of catalytic hairpin assembly with combination of controllable CRISPR-Cas9 function to transduce the signals from distinct messenger RNA expression of trigger genes into manipulation of target genes. Through introduction of these RNA-based genetic circuits, mammalian cells are endowed with autonomous capabilities to sense the changes of RNA expression either induced by ligand stimuli or from various cell types and control the cellular responses and fates via apoptosis-related ASPs. Our design provides a generalized platform for construction of ASPs inside the genetic networks of mammalian cells based on differentiated RNA expression.

Kinetics of RNA-LNP delivery and protein expression

Lipid nanoparticles (LNPs) employing ionizable lipids are the most advanced technology for delivery of RNA, most notably mRNA, to cells. LNPs represent well-defined core-shell particles with efficient nucleic acid encapsulation, low immunogenicity and enhanced efficacy. While much is known about the structure and activity of LNPs, less attention is given to the timing of LNP uptake, cytosolic transfer and protein expression. However, LNP kinetics is a key factor determining delivery efficiency. Hence quantitative insight into the multi-cascaded pathway of LNPs is of interest to elucidate the mechanism of delivery. Here, we review experiments as well as theoretical modeling of the timing of LNP uptake, mRNA-release and protein expression. We describe LNP delivery as a sequence of stochastic transfer processes and review a mathematical model of subsequent protein translation from mRNA. We compile probabilities and numbers obtained from time resolved microscopy. Specifically, live-cell imaging on single cell arrays (LISCA) allows for high-throughput acquisition of thousands of individual GFP reporter expression time courses. The traces yield the distribution of mRNA life-times, expression rates and expression onset. Correlation analysis reveals an inverse dependence of gene expression efficiency and transfection onset-times. Finally, we discuss why timing of mRNA release is critical in the context of codelivery of multiple nucleic acid species as in the case of mRNA co-expression or CRISPR/Cas gene editing.

Engineering pluripotent stem cells with synthetic biology for regenerative medicine

Pluripotent stem cells (PSCs), characterized by self-renewal and capacity of differentiating into three germ layers, are the programmable building blocks of life. PSC-derived cells and multicellular systems, particularly organoids, exhibit great potential for regenerative medicine. However, this field is still in its infancy, partly due to limited strategies to robustly and precisely control stem cell behaviors, which are tightly regulated by inner gene regulatory networks in response to stimuli from the extracellular environment. Synthetic receptors and genetic circuits are powerful tools to customize the cellular sense-and-response process, suggesting their underlying roles in precise control of cell fate decision and function reconstruction. Herein, we review the progress and challenges needed to be overcome in the fields of PSC-based cell therapy and multicellular system generation, respectively. Furthermore, we summarize several well-established synthetic biology tools and their applications in PSC engineering. Finally, we highlight the challenges and perspectives of harnessing synthetic biology to PSC engineering for regenerative medicine.

Synthetic dosage-compensating miRNA circuits allow precision gene therapy for Rett syndrome

A longstanding challenge in gene therapy is expressing a dosage-sensitive gene within a tight therapeutic window. For example, loss of MECP2 function causes Rett syndrome, while its duplication causes MECP2 duplication syndrome. Viral gene delivery methods generate variable numbers of gene copies in individual cells, creating a need for gene dosage-invariant expression systems. Here, we introduce a compact miRNA-based, incoherent feed-forward loop circuit that achieves precise control of Mecp2 expression in cells and brains, and improves outcomes in an AAV-based mouse model of Rett syndrome gene therapy. Single molecule analysis of endogenous and ectopic Mecp2 mRNA revealed precise, sustained expression across a broad range of gene dosages. Delivered systemically in a brain-targeting AAV capsid, the circuit strongly suppressed Rett behavioral symptoms for over 24 weeks, outperforming an unregulated gene therapy. These results demonstrate that synthetic miRNA-based regulatory circuits can enable precise in vivo expression to improve the safety and efficacy of gene therapy.

A coarse-grained bacterial cell model for resource-aware analysis and design of synthetic gene circuits

Within a cell, synthetic and native genes compete for expression machinery, influencing cellular process dynamics through resource couplings. Models that simplify competitive resource binding kinetics can guide the design of strategies for countering these couplings. However, in bacteria resource availability and cell growth rate are interlinked, which complicates resource-aware biocircuit design. Capturing this interdependence requires coarse-grained bacterial cell models that balance accurate representation of metabolic regulation against simplicity and interpretability. We propose a coarse-grained E. coli cell model that combines the ease of simplified resource coupling analysis with appreciation of bacterial growth regulation mechanisms and the processes relevant for biocircuit design. Reliably capturing known growth phenomena, it provides a unifying explanation to disparate empirical relations between growth and synthetic gene expression. Considering a biomolecular controller that makes cell-wide ribosome availability robust to perturbations, we showcase our model's usefulness in numerically prototyping biocircuits and deriving analytical relations for design guidance.

Resource allocation in mammalian systems

Cells execute biological functions to support phenotypes such as growth, migration, and secretion. Complementarily, each function of a cell has resource costs that constrain phenotype. Resource allocation by a cell allows it to manage these costs and optimize their phenotypes. In fact, the management of resource constraints (e.g., nutrient availability, bioenergetic capacity, and macromolecular machinery production) shape activity and ultimately impact phenotype. In mammalian systems, quantification of resource allocation provides important insights into higher-order multicellular functions; it shapes intercellular interactions and relays environmental cues for tissues to coordinate individual cells to overcome resource constraints and achieve population-level behavior. Furthermore, these constraints, objectives, and phenotypes are context-dependent, with cells adapting their behavior according to their microenvironment, resulting in distinct steady-states. This review will highlight the biological insights gained from probing resource allocation in mammalian cells and tissues.

Context-dependent redesign of robust synthetic gene circuits

Cells provide dynamic platforms for executing exogenous genetic programs in synthetic biology, resulting in highly context-dependent circuit performance. Recent years have seen an increasing interest in understanding the intricacies of circuit-host relationships, their influence on the synthetic bioengineering workflow, and in devising strategies to alleviate undesired effects. We provide an overview of how emerging circuit-host interactions, such as growth feedback and resource competition, impact both deterministic and stochastic circuit behaviors. We also emphasize control strategies for mitigating these unwanted effects. This review summarizes the latest advances and the current state of host-aware and resource-aware design of synthetic gene circuits.

Tobacco Plant: A Novel and Promising Heterologous Bioreactor for the Production of Recombinant Bovine Chymosin

The natural source of chymosin, a key enzyme in the dairy industry, is insufficient for rapidly growing cheese industries. Large-scale production of recombinant proteins in heterologous hosts provides an efficient alternative solution. Here, the codon-optimized synthetic prochymosin gene, which has a CAI index of 0.926, was subcloned from a cloning vector (pUC57-bCYM) into the pBI121 vector, resulting in the construct named pBI121-bCYM. CAI ranges from 0 to 1 and higher CAI improves gene expression in heterologous hosts. The overexpression of the prochymosin gene was under the control of constitutive CaMV 35S promoter and NOS terminator and was transferred into the tobacco via A. tumefaciens strain LBA4404. Explant type, regeneration method, inoculation temperature, cell density (OD600) of Agrobacterium for inoculation, and acetosyringone concentration were leaf explants, direct somatic embryogenesis, 19 °C, 0.1, and 100 µM, respectively. The successful integration and expression of the prochymosin gene, along with the bioactivity of recombinant chymosin, were confirmed by PCR, RT-PCR, and milk coagulation assay, respectively. Overall, this study reports the first successful overexpression of the codon-optimized prochymosin form of the bovine chymosin enzyme in the tobacco via indirect transformation. Production of recombinant bovine chymosin in plants can be an easy-to-scale-up, safe, and inexpensive platform.

Engineered Protease-Responsive RNA-Binding Proteins (RBPs) to Expand the Toolbox of Synthetic Circuits in Mammalian Cells

Genetically encoded sensor-actuator circuits aim at reprogramming cellular functions and are inspired by intracellular networks: from the input signal (sensor) to the desired output response (actuator). In the last years, circuits with posttranscriptional regulation of gene expression have aroused great interest for their potential in the biomedical space. Posttranscriptional modulation can be achieved with ribozymes, riboswitches (simple regulatory elements based on RNA secondary structures), noncoding RNAs, and RNA-binding proteins (RBPs). RBPs are proteins that recognize specific motifs on the mRNA target inducing mRNA decay or translation inhibition. The use of RBPs deriving from different species in mammalian cells has allowed to create sophisticated and multilayered regulatory networks, addressing the previous limitation of regulatory orthogonal parts that can be assembled in synthetic devices. In this chapter, we describe the engineering and tests of protease-responsive RNA-binding proteins (L7Ae and MS2-cNOT7) to expand the toolbox of synthetic circuits in mammalian cells.

Mechanistic Model-Driven Biodesign in Mammalian Synthetic Biology

Mathematical modeling plays a vital role in mammalian synthetic biology by providing a framework to design and optimize design circuits and engineered bioprocesses, predict their behavior, and guide experimental design. Here, we review recent models used in the literature, considering mathematical frameworks at the molecular, cellular, and system levels. We report key challenges in the field and discuss opportunities for genome-scale models, machine learning, and cybergenetics to expand the capabilities of model-driven mammalian cell biodesign.

Customizing cellular signal processing by synthetic multi-level regulatory circuits

As synthetic biology permeates society, the signal processing circuits in engineered living systems must be customized to meet practical demands. Towards this mission, novel regulatory mechanisms and genetic circuits with unprecedented complexity have been implemented over the past decade. These regulatory mechanisms, such as transcription and translation control, could be integrated into hybrid circuits termed "multi-level circuits". The multi-level circuit design will tremendously benefit the current genetic circuit design paradigm, from modifying basic circuit dynamics to facilitating real-world applications, unleashing our capabilities to customize cellular signal processing and address global challenges through synthetic biology.

Competition and evolutionary selection among core regulatory motifs in gene expression control

Gene products that are beneficial in one environment may become burdensome in another, prompting the emergence of diverse regulatory schemes that carry their own bioenergetic cost. By ensuring that regulators are only expressed when needed, we demonstrate that autoregulation generally offers an advantage in an environment combining mutation and time-varying selection. Whether positive or negative feedback emerges as dominant depends primarily on the demand for the target gene product, typically to ensure that the detrimental impact of inevitable mutations is minimized. While self-repression of the regulator curbs the spread of these loss-of-function mutations, self-activation instead facilitates their propagation. By analyzing the transcription network of multiple model organisms, we reveal that reduced bioenergetic cost may contribute to the preferential selection of autoregulation among transcription factors. Our results not only uncover how seemingly equivalent regulatory motifs have fundamentally different impact on population structure, growth dynamics, and evolutionary outcomes, but they can also be leveraged to promote the design of evolutionarily robust synthetic gene circuits.

Engineering a scalable and orthogonal platform for synthetic communication in mammalian cells

The rational design and implementation of synthetic mammalian communication systems can unravel fundamental design principles of cell communication circuits and offer a framework for engineering of designer cell consortia with potential applications in cell therapeutics. Here, we develop the foundations of an orthogonal, and scalable mammalian synthetic communication platform that exploits the programmability of synthetic receptors and selective affinity and tunability of diffusing coiled-coil peptides. Leveraging the ability of coiled-coils to exclusively bind to a cognate receptor, we demonstrate orthogonal receptor activation and Boolean logic operations at the receptor level. We show intercellular communication based on synthetic receptors and secreted multidomain coiled-coils and demonstrate a three-cell population system that can perform AND gate logic. Finally, we show CC-GEMS receptor-dependent therapeutic protein expression. Our work provides a modular and scalable framework for the engineering of complex cell consortia, with the potential to expand the aptitude of cell therapeutics and diagnostics.

Transient inhibition of lysosomal functions potentiates nucleic acid vaccines

Nucleic acid vaccines have shown promising results in the clinic against infectious diseases and cancers. To robustly improve the vaccine efficacy and safety, we developed an approach to increase the intracellular stability of nucleic acids by transiently inhibiting lysosomal function in targeted tissues using sucrose. To achieve efficient and localized delivery of sucrose in animals, we designed a biomimetic lipid nanoparticle (LNP) to target the delivery of sucrose into mouse muscle cells. Using this approach, viral antigen expression in mouse muscle after DNA vaccination was substantially increased and prolonged without inducing local or systemic inflammation or toxicity. The same change in antigen expression would be achieved if the vaccine dose could be increased by 3,000 folds, which is experimentally and clinically impractical due to material restrictions and severe toxicity that will be induced by such a high dose of nucleic acids. The increase in antigen expression augmented the infiltration and activation of antigen-presenting cells, significantly improved vaccine-elicited humoral and T cell responses, and fully protected mice against the viral challenge at a low dose of vaccine. Based on these observations, we conclude that transient inhibition of lysosome function in target tissue by sucrose LNPs is a safe and potent approach to substantially improve nucleic acid-based vaccines.

Advancing reproducibility can ease the 'hard truths' of synthetic biology

Reproducibility has been identified as an outstanding challenge in science, and the field of synthetic biology is no exception. Meeting this challenge is critical to allow the transformative technological capabilities emerging from this field to reach their full potential to benefit the society. We discuss the current state of reproducibility in synthetic biology and how improvements can address some of the central shortcomings in the field. We argue that the successful adoption of reproducibility as a routine aspect of research and development requires commitment spanning researchers and relevant institutions via education, incentivization and investment in related infrastructure. The urgency of this topic pervades synthetic biology as it strives to advance fundamental insights and unlock new capabilities for safe, secure and scalable applications of biotechnology. Graphical Abstract.

PI3K signaling through a biochemical systems lens

Following 3 decades of extensive research into PI3K signaling, it is now evidently clear that the underlying network does not equate to a simple ON/OFF switch. This is best illustrated by the multifaceted nature of the many diseases associated with aberrant PI3K signaling, including common cancers, metabolic disease, and rare developmental disorders. However, we are still far from a complete understanding of the fundamental control principles that govern the numerous phenotypic outputs that are elicited by activation of this well-characterized biochemical signaling network, downstream of an equally diverse set of extrinsic inputs. At its core, this is a question on the role of PI3K signaling in cellular information processing and decision making. Here, we review the determinants of accurate encoding and decoding of growth factor signals and discuss outstanding questions in the PI3K signal relay network. We emphasize the importance of quantitative biochemistry, in close integration with advances in single-cell time-resolved signaling measurements and mathematical modeling.

Expression of GFP and DsRed fluorescent proteins after gene electrotransfer of tumour cells in vitro

Fluorescent reporter genes are widely used to study the transfection of various types of primary cells and cell lines. The aim of our research was to investigate the expression dynamics of GFP and DsRed reporter genes individually and combined after gene electrotransfer of plasmids with two different electroporation protocols in B16F10 and CT26 cells in vitro. The cytotoxicity after gene electrotransfer of both plasmids was first determined. Second, the intensity of fluorescence and the percentage of cells transfected with both plasmids individually and in combination were monitored in real time. The results show that the percentage of viability after gene electrotransfer of plasmids using the EP2 pulses was significantly higher compared to the EP1 pulses. In contrast, the percentage of transfected cells and fluorescence intensity were higher after gene electrotransfer with the EP1 pulse protocol. Moreover, the percentage of transfected cells was higher and started earlier in the B16F10 cell line than in the CT26 cell line. However, fluorescence intensity was higher in CT26 cells. Co-expression of fluorescent proteins was achieved only in a small number of cells. In conclusion, this study elucidated some of the dynamics of reporter gene expression in cancer cell lines after gene electrotransfer.

Synthetic biology for plant genetic engineering and molecular farming

Many efforts have been put into engineering plants to improve crop yields and stress tolerance and boost the bioproduction of valuable molecules. Yet, our capabilities are still limited due to the lack of well-characterized genetic building blocks and resources for precise manipulation and given the inherently challenging properties of plant tissues. Advancements in plant synthetic biology can overcome these bottlenecks and release the full potential of engineered plants. In this review, we first discuss the recently developed plant synthetic elements from single parts to advanced circuits, software, and hardware tools expediting the engineering cycle. Next, we survey the advancements in plant biotechnology enabled by these recent resources. We conclude the review with outstanding challenges and future directions of plant synthetic biology.

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.

Genetic effects on molecular network states explain complex traits

The complexity of many cellular and organismal traits results from the integration of genetic and environmental factors via molecular networks. Network structure and effect propagation are best understood at the level of functional modules, but so far, no concept has been established to include the global network state. Here, we show when and how genetic perturbations lead to molecular changes that are confined to small parts of a network versus when they lead to modulation of network states. Integrating multi-omics profiling of genetically heterogeneous budding and fission yeast strains with an array of cellular traits identified a central state transition of the yeast molecular network that is related to PKA and TOR (PT) signaling. Genetic variants affecting this PT state globally shifted the molecular network along a single-dimensional axis, thereby modulating processes including energy and amino acid metabolism, transcription, translation, cell cycle control, and cellular stress response. We propose that genetic effects can propagate through large parts of molecular networks because of the functional requirement to centrally coordinate the activity of fundamental cellular processes.

Growth Feedback Confers Cooperativity in Resource-Competing Synthetic Gene Circuits

Modularity is a key concept in designing synthetic gene circuits, as it allows for constructing complex molecular systems using well-characterized building blocks. One of the major challenges in this field is that these modular components often do not function as expected when assembled into larger circuits. One of the major issues is caused by resource competition, where multiple genes in the circuit compete for the same limited cellular resources, such as transcription factors and ribosomes. In addition, the mutual inhibition between synthetic gene circuits and cell growth results in growth feedback that significantly impacts its host-circuit dynamics. However, the complexity of the gene circuit dynamics under intertwined resource competition and growth feedback is not fully understood. This study developed a theoretical framework to examine the dynamics of synthetic gene circuits by considering both growth feedback and resource competition. Our results suggest a cooperative behavior between resource-competing gene circuits under growth feedback. Cooperation or competition is non-monotonically determined by the metabolic burden threshold. These two diverse effects could lead to the activation or deactivation of one circuit by the other. Lastly, the cooperativity mediated by growth feedback can attenuate the winner-takes-all resource competition. These findings show that coupling growth feedback and resource competition plays a crucial role in the dynamics of the host-circuit system, and understanding its effects helps control unexpected gene expression behaviors.

Multi-input Drug-Controlled Switches of Mammalian Gene Expression Based on Engineered Nuclear Hormone Receptors

Protein-based switches that respond to different inputs to regulate cellular outputs, such as gene expression, are central to synthetic biology. For increased controllability, multi-input switches that integrate several cooperating and competing signals for the regulation of a shared output are of particular interest. The nuclear hormone receptor (NHR) superfamily offers promising starting points for engineering multi-input-controlled responses to clinically approved drugs. Starting from the VgEcR/RXR pair, we demonstrate that novel (multi)drug regulation can be achieved by exchange of the ecdysone receptor (EcR) ligand binding domain (LBD) for other human NHR-derived LBDs. For responses activated to saturation by an agonist for the first LBD, we show that outputs can be boosted by an agonist targeting the second LBD. In combination with an antagonist, output levels are tunable by up to three simultaneously present small-molecule drugs. Such high-level control validates NHRs as a versatile, engineerable platform for programming multidrug-controlled responses.

Resource-aware construct design in mammalian cells

Resource competition can be the cause of unintended coupling between co-expressed genetic constructs. Here we report the quantification of the resource load imposed by different mammalian genetic components and identify construct designs with increased performance and reduced resource footprint. We use these to generate improved synthetic circuits and optimise the co-expression of transfected cassettes, shedding light on how this can be useful for bioproduction and biotherapeutic applications. This work provides the scientific community with a framework to consider resource demand when designing mammalian constructs to achieve robust and optimised gene expression.

Maximizing protein production by keeping cells at optimal secretory stress levels using real-time control approaches

Optimizing the production of recombinant proteins is a problem of major industrial and pharmaceutical importance. Secretion of the protein by the host cell considerably simplifies downstream purification processes. However, for many proteins, this is also the limiting production step. Current solutions involve extensive engineering of the chassis cell to facilitate protein trafficking and limit protein degradation triggered by excessive secretion-associated stress. Here, we propose instead a regulation-based strategy in which induction is dynamically adjusted to an optimal strength based on the current stress level of the cells. Using a small collection of hard-to-secrete proteins, a bioreactor-based platform with automated cytometry measurements, and a systematic assay to quantify secreted protein levels, we demonstrate that the secretion sweet spot is indicated by the appearance of a subpopulation of cells that accumulate high amounts of proteins, decrease growth, and face significant stress, that is, experience a secretion burnout. In these cells, adaptations capabilities are overwhelmed by a too strong production. Using these notions, we show for a single-chain antibody variable fragment that secretion levels can be improved by 70% by dynamically keeping the cell population at optimal stress levels using real-time closed-loop control.

A blueprint for a synthetic genetic feedback optimizer

Biomolecular control enables leveraging cells as biomanufacturing factories. Despite recent advancements, we currently lack genetically encoded modules that can be deployed to dynamically fine-tune and optimize cellular performance. Here, we address this shortcoming by presenting the blueprint of a genetic feedback module to optimize a broadly defined performance metric by adjusting the production and decay rate of a (set of) regulator species. We demonstrate that the optimizer can be implemented by combining available synthetic biology parts and components, and that it can be readily integrated with existing pathways and genetically encoded biosensors to ensure its successful deployment in a variety of settings. We further illustrate that the optimizer successfully locates and tracks the optimum in diverse contexts when relying on mass action kinetics-based dynamics and parameter values typical in Escherichia coli.

Deciphering mechanisms of production of natural compounds using inducer-producer microbial consortia

Living organisms produce a wide range of metabolites. Because of their potential antibacterial, antifungal, antiviral, or cytostatic properties, such natural molecules are of high interest to the pharmaceutical industry. In nature, these metabolites are often synthesized via secondary metabolic biosynthetic gene clusters that are silent under the typical culturing conditions. Among different techniques used to activate these silent gene clusters, co-culturing of "producer" species with specific "inducer" microbes is a particularly appealing approach due to its simplicity. Although several "inducer-producer" microbial consortia have been reported in the literature and hundreds of different secondary metabolites with attractive biopharmaceutical properties have been described as a result of co-cultivating inducer-producer consortia, less attention has been devoted to the understanding of the mechanisms and possible means of induction for production of secondary metabolites in co-cultures. This lack of understanding of fundamental biological functions and inter-species interactions significantly limits the diversity and yield of valuable compounds using biological engineering tools. In this review, we summarize and categorize the known physiological mechanisms of production of secondary metabolites in inducer-producer consortia, and then discuss approaches that could be exploited to optimize the discovery and production of secondary metabolites.

Programmable mammalian translational modulators by CRISPR-associated proteins

Translational modulation based on RNA-binding proteins can be used to construct artificial gene circuits, but RNA-binding proteins capable of regulating translation efficiently and orthogonally remain scarce. Here we report CARTRIDGE (Cas-Responsive Translational Regulation Integratable into Diverse Gene control) to repurpose Cas proteins as translational modulators in mammalian cells. We demonstrate that a set of Cas proteins efficiently and orthogonally repress or activate the translation of designed mRNAs that contain a Cas-binding RNA motif in the 5'-UTR. By linking multiple Cas-mediated translational modulators, we designed and built artificial circuits like logic gates, cascades, and half-subtractor circuits. Moreover, we show that various CRISPR-related technologies like anti-CRISPR and split-Cas9 platforms could be similarly repurposed to control translation. Coupling Cas-mediated translational and transcriptional regulation enhanced the complexity of synthetic circuits built by only introducing a few additional elements. Collectively, CARTRIDGE has enormous potential as a versatile molecular toolkit for mammalian synthetic biology.

Recent advances, opportunities and challenges in cybergenetic identification and control of biomolecular networks

Cybergenetics is a new area of research aimed at developing digital and biological controllers for living systems. Synthetic biologists have begun exploiting cybergenetic tools and platforms to both accelerate the development of mathematical models and develop control strategies for complex biological phenomena. Here, we review the state of the art in cybergenetic identification and control. Our aim is to lower the entry barrier to this field and foster the adoption of methods and technologies that will accelerate the pace at which Synthetic Biology progresses toward applications.

Precise programming of multigene expression stoichiometry in mammalian cells by a modular and programmable transcriptional system

Context-dependency of mammalian transcriptional elements has hindered the quantitative investigation of multigene expression stoichiometry and its biological functions. Here, we describe a host- and local DNA context-independent transcription system to gradually fine-tune single and multiple gene expression with predictable stoichiometries. The mammalian transcription system is composed of a library of modular and programmable promoters from bacteriophage and its cognate RNA polymerase (RNAP) fused to a capping enzyme. The relative expression of single genes is quantitatively determined by the relative binding affinity of the RNAP to the promoters, while multigene expression stoichiometry is predicted by a simple biochemical model with resource competition. We use these programmable and modular promoters to predictably tune the expression of three components of an influenza A virus-like particle (VLP). Optimized stoichiometry leads to a 2-fold yield of intact VLP complexes. The host-independent orthogonal transcription system provides a platform for dose-dependent control of multiple protein expression which may be applied for advanced vaccine engineering, cell-fate programming and other therapeutic applications.

A cybergenetic framework for engineering intein-mediated integral feedback control systems

The ability of biological systems to tightly regulate targeted variables, despite external and internal disturbances, is known as Robust Perfect Adaptation (RPA). Achieved frequently through biomolecular integral feedback controllers at the cellular level, RPA has important implications for biotechnology and its various applications. In this study, we identify inteins as a versatile class of genetic components suitable for implementing these controllers and present a systematic approach for their design. We develop a theoretical foundation for screening intein-based RPA-achieving controllers and a simplified approach for modeling them. We then genetically engineer and test intein-based controllers using commonly used transcription factors in mammalian cells and demonstrate their exceptional adaptation properties over a wide dynamic range. The small size, flexibility, and applicability of inteins across life forms allow us to create a diversity of genetic RPA-achieving integral feedback control systems that can be used in various applications, including metabolic engineering and cell-based therapy.

Stability, robustness, and containment: preparing synthetic biology for real-world deployment

As engineered microbes are used in increasingly diverse applications across human health and bioproduction, the field of synthetic biology will need to focus on strategies that stabilize and contain the function of these populations within target environments. To this end, recent advancements have created layered sensing circuits that can compute cell survival, genetic contexts that are less susceptible to mutation, burden, and resource control circuits, and methods for population variability reduction. These tools expand the potential for real-world deployment of complex microbial systems by enhancing their environmental robustness and functional stability in the face of unpredictable host response and evolutionary pressure.

Negatively Competitive Incoherent Feedforward Loops Mitigate Winner-Take-All Resource Competition

The effects of host resource limitations on the function of synthetic gene circuits have gained significant attention over the past years. Hosts, having evolved resource capacities optimal for their own genome, have been repeatedly demonstrated to suffer from the added burden of synthetic genetic programs, which may in return pose deleterious effects on the circuit's function. Three resource controller archetypes have been proposed previously to mitigate resource distribution problems in dynamic circuits: the local controller, the global controller, and a "negatively competitive" regulatory (NCR) controller that utilizes synthetic competition to combat resource competition. The dynamics of negative feedback forms of these controllers have been previously investigated, and here we extend the analysis of these resource allocation strategies to the incoherent feedforward loop (iFFL) topology. We demonstrate that the three iFFL controllers can attenuate Winner-Take-All resource competition between two bistable switches. We uncover that the parameters associated with the synthetic competition in the NCR iFFL controller are paramount to its increased efficacy over the local controller type, while the global controllers demonstrate to be relatively ineffectual. Interestingly, unlike the negative feedback counterpart topologies, iFFL controllers exhibit a unique coupling of switch activation thresholds which we term the "coactivation threshold shift" effect. Finally, we demonstrate that a nearly fully orthogonal set of bistable switches could be achieved by pairing an NCR controller with an appropriate level of controller resource consumption.

Synthetic biology by controller design

Natural biological systems display complex regulation and synthetic biomolecular systems have been used to understand their natural counterparts and to parse sophisticated regulations into core design principles. At the same time, the engineering of biomolecular systems has unarguable potential to transform current and to enable new, yet-to-be-imagined, biotechnology applications. In this review, we discuss the progression of control systems design in synthetic biology, from the purpose of understanding the function of naturally occurring regulatory motifs to that of creating genetic circuits whose function is sufficiently robust for biotechnology applications.

Emerging technologies for genetic control systems in cellular therapies

Progress in synthetic biology has enabled the construction of designer cells that sense biological inputs, and, in response, activate user-defined biomolecular programs. Such engineered cells provide unique opportunities for treating a wide variety of diseases. Current strategies mostly rely on cell-surface receptor systems engineered to convert binding interactions into activation of a transcriptional program. Genetic control systems are emerging as an appealing alternative to receptor-based sensors as they overcome the need for receptor engineering and result in cellular behaviors that operate over therapeutically relevant timescales. Genetic control systems include synthetic gene networks, RNA-based sensors, and post-translational tools. These technologies present fundamental challenges, including the requirement for precise integration with innate pathways, the need for parts orthogonal to existing circuitries, and the metabolic burden induced by such complex cell engineering endeavors. This review discusses the challenges in the design of genetic control systems for cellular therapies and their translational applications.

Cryopreservation does not change the performance and characteristics of allogenic mesenchymal stem cells highly over-expressing a cytoplasmic therapeutic transgene for cancer treatment

Background

Mesenchymal stem cells (MSCs) driven gene directed enzyme prodrug therapy is a promising approach to deliver therapeutic agents to target heterogenous solid tumours. To democratize such a therapy, cryopreservation along with cold chain transportation is an essential part of the logistical process and supply chain. Previously, we have successfully engineered MSCs by a non-viral DNA transfection approach for prolonged and exceptionally high expression of the fused transgene cytosine deaminase, uracil phosphoribosyl transferase and green fluorescent protein (CD::UPRT::GFP). The aim of this study was to determine the effects of cryopreservation of MSCs engineered to highly overexpress this cytoplasmic therapeutic transgene.

Methods

Modified MSCs were preserved in a commercially available, GMP-grade cryopreservative—CryoStor10 (CS10) for up to 11 months. Performance of frozen-modified MSCs was compared to freshly modified equivalents in vitro. Cancer killing potency was evaluated using four different cancer cell lines. Migratory potential was assessed using matrigel invasion assay and flow cytometric analysis for CXCR4 expression. Frozen-modified MSC was used to treat canine patients via intra-tumoral injections, or by intravenous infusion followed by a daily dose of 5-flucytosine (5FC).

Results

We found that cryopreservation did not affect the transgene expression, cell viability, adhesion, phenotypic profile, and migration of gene modified canine adipose tissue derived MSCs. In the presence of 5FC, the thawed and freshly modified MSCs showed comparable cytotoxicity towards one canine and three human cancer cell lines in vitro. These cryopreserved cells were stored for about a year and then used to treat no-option-left canine patients with two different types of cancers and notably, the patients showed progression-free interval of more than 20 months, evidence of the effectiveness in treating spontaneously occurring cancers.

Conclusion

This study supports the use of cryopreserved, off-the-shelf transiently transfected MSCs for cancer treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13287-022-03198-z.

Synthetic gene circuits for cell state detection and protein tuning in human pluripotent stem cells

During development, cell state transitions are coordinated through changes in the identity of molecular regulators in a cell type‐ and dose‐specific manner. The ability to rationally engineer such transitions in human pluripotent stem cells (hPSC) will enable numerous applications in regenerative medicine. Herein, we report the generation of synthetic gene circuits that can detect a desired cell state using AND‐like logic integration of endogenous miRNAs (classifiers) and, upon detection, produce fine‐tuned levels of output proteins using an miRNA‐mediated output fine‐tuning technology (miSFITs). Specifically, we created an “hPSC ON” circuit using a model‐guided miRNA selection and circuit optimization approach. The circuit demonstrates robust PSC‐specific detection and graded output protein production. Next, we used an empirical approach to create an “hPSC‐Off” circuit. This circuit was applied to regulate the secretion of endogenous BMP4 in a state‐specific and fine‐tuned manner to control the composition of differentiating hPSCs. Our work provides a platform for customized cell state‐specific control of desired physiological factors in hPSC, laying the foundation for programming cell compositions in hPSC‐derived tissues and beyond.

Supercoiling-mediated feedback rapidly couples and tunes transcription

Transcription induces a wave of DNA supercoiling, altering the binding affinity of RNA polymerases and reshaping the biochemical landscape of gene regulation. As supercoiling rapidly diffuses, transcription dynamically reshapes the regulation of proximal genes, forming a complex feedback loop. However, a theoretical framework is needed to integrate biophysical regulation with biochemical transcriptional regulation. To investigate the role of supercoiling-mediated feedback within multi-gene systems, we model transcriptional regulation under the influence of supercoiling-mediated polymerase dynamics, allowing us to identify patterns of expression that result from physical inter-gene coupling. We find that gene syntax—the relative ordering and orientation of genes—defines the expression profiles, variance, burst dynamics, and inter-gene correlation of two-gene systems. Furthermore, supercoiling can enhance or weaken biochemical regulation. Our results suggest that supercoiling couples behavior between neighboring genes, providing a regulatory mechanism that tunes transcriptional variance in engineered gene networks and explains the behavior of co-localized native circuits.

Supercoiling-mediated feedback couples the transcription of proximal genes. Here, Johnstone and Galloway provide a framework for integrating biochemical gene regulation with the biophysical effects of DNA supercoiling. This unified model provides design principles for improving the performance of gene networks, developing novel regulatory functions, and accessing previously inaccessible regulatory dynamics.

Eukaryotic gene regulation at equilibrium, or non?

Models of transcriptional regulation that assume equilibrium binding of transcription factors have been less successful at predicting gene expression from sequence in eukaryotes than in bacteria. This could be due to the non-equilibrium nature of eukaryotic regulation. Unfortunately, the space of possible non-equilibrium mechanisms is vast and predominantly uninteresting. The key question is therefore how this space can be navigated efficiently, to focus on mechanisms and models that are biologically relevant. In this review, we advocate for the normative role of theory-theory that prescribes rather than just describes-in providing such a focus. Theory should expand its remit beyond inferring mechanistic models from data, towards identifying non-equilibrium gene regulatory schemes that may have been evolutionarily selected, despite their energy consumption, because they are precise, reliable, fast, or otherwise outperform regulation at equilibrium. We illustrate our reasoning by toy examples for which we provide simulation code.

Implementation of a Novel Optogenetic Tool in Mammalian Cells Based on a Split T7 RNA Polymerase

Optogenetic tools are widely used to control gene expression dynamics both in prokaryotic and eukaryotic cells. These tools are used in a variety of biological applications from stem cell differentiation to metabolic engineering. Despite some tools already available in bacteria, no light-inducible system currently exists to control gene expression independently from mammalian transcriptional and/or translational machineries thus working orthogonally to endogenous regulatory mechanisms. Such a tool would be particularly important in synthetic biology, where orthogonality is advantageous to achieve robust activation of synthetic networks. Here we implement, characterize, and optimize a new optogenetic tool in mammalian cells based on a previously published system in bacteria called Opto-T7RNAPs. The tool is orthogonal to the cellular machinery for transcription and consists of a split T7 RNA polymerase coupled with the blue light-inducible magnets system (mammalian OptoT7–mOptoT7). In our study we exploited the T7 polymerase’s viral origins to tune our system’s expression level, reaching up to an almost 20-fold change activation over the dark control. mOptoT7 is used here to generate mRNA for protein expression, shRNA for protein inhibition, and Pepper aptamer for RNA visualization. Moreover, we show that mOptoT7 can mitigate the gene expression burden when compared to another optogenetic construct. These properties make mOptoT7 a powerful new tool to use when orthogonality and viral RNA species (that lack endogenous RNA modifications) are desired.

Scalable biological signal recording in mammalian cells using Cas12a base editors

Biological signal recording enables the study of molecular inputs experienced throughout cellular history. However, current methods are limited in their ability to scale up beyond a single signal in mammalian contexts. Here, we develop an approach using a hyper-efficient dCas12a base editor for multi-signal parallel recording in human cells. We link signals of interest to expression of guide RNAs to catalyze specific nucleotide conversions as a permanent record, enabled by Cas12's guide-processing abilities. We show this approach is plug-and-play with diverse biologically relevant inputs and extend it for more sophisticated applications, including recording of time-delimited events and history of chimeric antigen receptor T cells' antigen exposure. We also demonstrate efficient recording of up to four signals in parallel on an endogenous safe-harbor locus. This work provides a versatile platform for scalable recording of signals of interest for a variety of biological applications.

Mitigating Host Burden of Genetic Circuits by Engineering Autonegatively Regulated Parts and Improving Functional Prediction

Mitigating unintended interferences between circuits and host cells is key to realize applications of synthetic regulatory systems both for bacteria and mammalian cells. Here, we demonstrated that growth burden and circuit dysregulation occurred in a concentration-dependent manner for specific transcription factors (CymR*/CymR) in E.coli, and direct negative feedback modules were able to control the concentration of CymR*/CymR, mitigate growth burden, and restore circuit functions. A quantitative design scheme was developed for circuits embedded with autorepression modules. Four key parameters were theoretically identified to determine the performance of autoregulated switches and were experimentally modified by fine-tuning promoter architectures and cooperativity. Using this strategy, we synthesized a number of switches and demonstrated its improvement of product titers and host growth controlling the complex deoxyviolacein biosynthesis pathway. Furthermore, we restored functions of a dysregulated multilayer NOR gate by integrating autorepression modules. Our work provides a blueprint for engineering host-adaptable synthetic systems.

A genetic mammalian proportional-integral feedback control circuit for robust and precise gene regulation

To survive in the harsh environments they inhabit, cells have evolved sophisticated regulatory mechanisms that can maintain a steady internal milieu or homeostasis. This robustness, however, does not generally translate to engineered genetic circuits, such as the ones studied by synthetic biology. Here, we introduce an implementation of a minimal and universal gene regulatory motif that produces robust perfect adaptation for mammalian cells, and we improve on it by enhancing the precision of its regulation.

The processes that keep a cell alive are constantly challenged by unpredictable changes in its environment. Cells manage to counteract these changes by employing sophisticated regulatory strategies that maintain a steady internal milieu. Recently, the antithetic integral feedback motif has been demonstrated to be a minimal and universal biological regulatory strategy that can guarantee robust perfect adaptation for noisy gene regulatory networks in Escherichia coli. Here, we present a realization of the antithetic integral feedback motif in a synthetic gene circuit in mammalian cells. We show that the motif robustly maintains the expression of a synthetic transcription factor at tunable levels even when it is perturbed by increased degradation or its interaction network structure is perturbed by a negative feedback loop with an RNA-binding protein. We further demonstrate an improved regulatory strategy by augmenting the antithetic integral motif with additional negative feedback to realize antithetic proportional–integral control. We show that this motif produces robust perfect adaptation while also reducing the variance of the regulated synthetic transcription factor. We demonstrate that the integral and proportional–integral feedback motifs can mitigate the impact of gene expression burden, and we computationally explore their use in cell therapy. We believe that the engineering of precise and robust perfect adaptation will enable substantial advances in industrial biotechnology and cell-based therapeutics.

A synthetic synthesis to explore animal evolution and development

Identifying the general principles by which genotypes are converted into phenotypes remains a challenge in the post-genomic era. We still lack a predictive understanding of how genes shape interactions among cells and tissues in response to signalling and environmental cues, and hence how regulatory networks generate the phenotypic variation required for adaptive evolution. Here, we discuss how techniques borrowed from synthetic biology may facilitate a systematic exploration of evolvability across biological scales. Synthetic approaches permit controlled manipulation of both endogenous and fully engineered systems, providing a flexible platform for investigating causal mechanisms in vivo. Combining synthetic approaches with multi-level phenotyping (phenomics) will supply a detailed, quantitative characterization of how internal and external stimuli shape the morphology and behaviour of living organisms. We advocate integrating high-throughput experimental data with mathematical and computational techniques from a variety of disciplines in order to pursue a comprehensive theory of evolution.

This article is part of the theme issue ‘Genetic basis of adaptation and speciation: from loci to causative mutations’.

Synthetic RNA-based post-transcriptional expression control methods and genetic circuits

RNA-based synthetic genetic circuits provide an alternative for traditional transcription-based circuits in applications where genomic integration is to be avoided. Incorporating various post-transcriptional control methods into such circuits allows for controlling the behaviour of the circuit through the detection of certain biomolecular inputs or reconstituting defined circuit behaviours, thus manipulating cellular functions. In this review, recent developments of various types of post-transcriptional control methods in mammalian cells are discussed as well as auxiliary components that allow for the creation and development of mRNA-based switches. How such post-transcriptional switches are combined into synthetic circuits as well as their applications in biomedical and preclinical settings are also described. Finally, we examine the challenges that need to be surmounted before RNA-based synthetic circuits can be reliably deployed into clinical settings.

Robust and tunable signal processing in mammalian cells via engineered covalent modification cycles

Engineered signaling networks can impart cells with new functionalities useful for directing differentiation and actuating cellular therapies. For such applications, the engineered networks must be tunable, precisely regulate target gene expression, and be robust to perturbations within the complex context of mammalian cells. Here, we use bacterial two-component signaling proteins to develop synthetic phosphoregulation devices that exhibit these properties in mammalian cells. First, we engineer a synthetic covalent modification cycle based on kinase and phosphatase proteins derived from the bifunctional histidine kinase EnvZ, enabling analog tuning of gene expression via its response regulator OmpR. By regulating phosphatase expression with endogenous miRNAs, we demonstrate cell-type specific signaling responses and a new strategy for accurate cell type classification. Finally, we implement a tunable negative feedback controller via a small molecule-stabilized phosphatase, reducing output expression variance and mitigating the context-dependent effects of off-target regulation and resource competition. Our work lays the foundation for establishing tunable, precise, and robust control over cell behavior with synthetic signaling networks.

Double-edged role of resource competition in gene expression noise and control

Despite extensive investigation demonstrating that resource competition can significantly alter the deterministic behaviors of synthetic gene circuits, it remains unclear how resource competition contributes to the gene expression noise and how this noise can be controlled. Utilizing a two-gene circuit as a prototypical system, we uncover a surprising double-edged role of resource competition in gene expression noise: competition decreases noise through introducing a resource constraint but generates its own type of noise which we name as "resource competitive noise." Utilization of orthogonal resources enables retainment of the noise reduction conferred by resource constraint while removing the added resource competitive noise. The noise reduction effects are studied using three negative feedback types: negatively competitive regulation (NCR), local, and global controllers, each having four placement architectures in the protein biosynthesis pathway (mRNA or protein inhibition on transcription or translation). Our results show that both local and NCR controllers with mRNA-mediated inhibition are efficacious at reducing noise, with NCR controllers demonstrating a superior noise-reduction capability. We also find that combining feedback controllers with orthogonal resources can improve the local controllers. This work provides deep insights into the origin of stochasticity in gene circuits with resource competition and guidance for developing effective noise control strategies.

GAMES: A Dynamic Model Development Workflow for Rigorous Characterization of Synthetic Genetic Systems

Mathematical modeling is invaluable for advancing understanding and design of synthetic biological systems. However, the model development process is complicated and often unintuitive, requiring iteration on various computational tasks and comparisons with experimental data. Ad hoc model development can pose a barrier to reproduction and critical analysis of the development process itself, reducing the potential impact and inhibiting further model development and collaboration. To help practitioners manage these challenges, we introduce the Generation and Analysis of Models for Exploring Synthetic Systems (GAMES) workflow, which includes both automated and human-in-the-loop processes. We systematically consider the process of developing dynamic models, including model formulation, parameter estimation, parameter identifiability, experimental design, model reduction, model refinement, and model selection. We demonstrate the workflow with a case study on a chemically responsive transcription factor. The generalizable workflow presented in this tutorial can enable biologists to more readily build and analyze models for various applications.

Trade-Offs in Biosensor Optimization for Dynamic Pathway Engineering

Recent progress in synthetic biology allows the construction of dynamic control circuits for metabolic engineering. This technology promises to overcome many challenges encountered in traditional pathway engineering, thanks to its ability to self-regulate gene expression in response to bioreactor perturbations. The central components in these control circuits are metabolite biosensors that read out pathway signals and actuate enzyme expression. However, the construction of metabolite biosensors is a major bottleneck for strain design, and a key challenge is to understand the relation between biosensor dose-response curves and pathway performance. Here we employ multiobjective optimization to quantify performance trade-offs that arise in the design of metabolite biosensors. Our approach reveals strategies for tuning dose-response curves along an optimal trade-off between production flux and the cost of an increased expression burden on the host. We explore properties of control architectures built in the literature and identify their advantages and caveats in terms of performance and robustness to growth conditions and leaky promoters. We demonstrate the optimality of a control circuit for glucaric acid production in Escherichia coli, which has been shown to increase the titer by 2.5-fold as compared to static designs. Our results lay the groundwork for the automated design of control circuits for pathway engineering, with applications in the food, energy, and pharmaceutical sectors.

Preprint articles as a tool for teaching data analysis and scientific communication

The skill of analyzing and interpreting research data is central to the scientific process, yet it is one of the hardest skills for students to master. While instructors can coach students through the analysis of data that they have either generated themselves or obtained from published articles, the burgeoning availability of preprint articles provides a new potential pedagogical tool. We developed a new method in which students use a cognitive apprenticeship model to uncover how experts analyzed a paper and compare the professional’s cognitive approach to their own. Specifically, students first critique research data themselves and then identify changes between the preprint and final versions of the paper that were likely the results of peer review. From this activity, students reported diverse insights into the processes of data presentation, peer review, and scientific publishing. Analysis of preprint articles is therefore a valuable new tool to strengthen students’ information literacy and understanding of the process of science.