Modular construction of mammalian gene circuits using TALE transcriptional repressors

Designer TALEs enable discovery of cell death-inducer genes

Transcription activator-like effectors (TALEs) in plant-pathogenic Xanthomonas bacteria activate expression of plant genes and support infection or cause a resistance response. PthA4AT is a TALE with a particularly short DNA-binding domain harboring only 7.5 repeats which triggers cell death in Nicotiana benthamiana; however, the genetic basis for this remains unknown. To identify possible target genes of PthA4AT that mediate cell death in N. benthamiana, we exploited the modularity of TALEs to stepwise enhance their specificity and reduce potential target sites. Substitutions of individual repeats suggested that PthA4AT-dependent cell death is sequence specific. Stepwise addition of repeats to the C-terminal or N-terminal end of the repeat region narrowed the sequence requirements in promoters of target genes. Transcriptome profiling and in silico target prediction allowed the isolation of two cell death inducer genes, which encode a patatin-like protein and a bifunctional monodehydroascorbate reductase/carbonic anhydrase protein. These two proteins are not linked to known TALE-dependent resistance genes. Our results show that the aberrant expression of different endogenous plant genes can cause a cell death reaction, which supports the hypothesis that TALE-dependent executor resistance genes can originate from various plant processes. Our strategy further demonstrates the use of TALEs to scan genomes for genes triggering cell death and other relevant phenotypes.

Cell factory engineering: Challenges and opportunities for synthetic biology applications

The production of high-quality recombinant proteins is critical to maintaining a continuous supply of biopharmaceuticals, such as therapeutic antibodies. Engineering mammalian cell factories presents a number of limitations typically associated with the proteotoxic stress induced upon aberrant accumulation of off-pathway protein folding intermediates, which eventually culminate in the induction of apoptosis. In this review, we will discuss advances in cell engineering and their applications at different hierarchical levels of control of the expression of recombinant proteins, from transcription and translational to posttranslational modifications and subcellular trafficking. We also highlight challenges and unique opportunities to apply modern synthetic biology tools to the design of programmable cell factories for improved biomanufacturing of therapeutic proteins.

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.

gDesigner: computational design of synthetic gRNAs for Cas12a-based transcriptional repression in mammalian cells

Synthetic networks require complex intertwined genetic regulation often relying on transcriptional activation or repression of target genes. CRISPRi-based transcription factors facilitate the programmable modulation of endogenous or synthetic promoter activity and the process can be optimised by using software to select appropriate gRNAs and limit non-specific gene modulation. Here, we develop a computational software pipeline, gDesigner, that enables the automated selection of orthogonal gRNAs with minimized off-target effects and promoter crosstalk. We next engineered a Lachnospiraceae bacterium Cas12a (dLbCas12a)-based repression system that downregulates target gene expression by means of steric hindrance of the cognate promoter. Finally, we generated a library of orthogonal synthetic dCas12a-repressed promoters and experimentally demonstrated it in HEK293FT, U2OS and H1299 cells lines. Our system expands the toolkit of mammalian synthetic promoters with a new complementary and orthogonal CRISPRi-based system, ultimately enabling the design of synthetic promoter libraries for multiplex gene perturbation that facilitate the understanding of complex cellular phenotypes.

The Contribution of the Minimal Promoter Element to the Activity of Synthetic Promoters Mediating CAR Expression in the Tumor Microenvironment

Harnessing immune effector cells to benefit cancer patients is becoming more and more prevalent in recent years. However, the increasing number of different therapeutic approaches, such as chimeric antigen receptors and armored chimeric antigen receptors, requires constant adjustments of the transgene expression levels. We have previously demonstrated it is possible to achieve spatial and temporal control of transgene expression as well as tailoring the inducing agents using the Chimeric Antigen Receptor Tumor Induced Vector (CARTIV) platform. Here we describe the next level of customization in our promoter platform. We have tested the functionality of three different minimal promoters, representing three different promoters’ strengths, leading to varying levels of CAR expression and primary T cell function. This strategy shows yet another level of CARTIV gene regulation that can be easily integrated into existing CAR T systems.

PERSIST platform provides programmable RNA regulation using CRISPR endoRNases

Regulated transgene expression is an integral component of gene therapies, cell therapies and biomanufacturing. However, transcription factor-based regulation, upon which most applications are based, suffers from complications such as epigenetic silencing that limit expression longevity and reliability. Constitutive transgene transcription paired with post-transcriptional gene regulation could combat silencing, but few such RNA- or protein-level platforms exist. Here we develop an RNA-regulation platform we call "PERSIST" which consists of nine CRISPR-specific endoRNases as RNA-level activators and repressors as well as modular OFF- and ON-switch regulatory motifs. We show that PERSIST-regulated transgenes exhibit strong OFF and ON responses, resist silencing for at least two months, and can be readily layered to construct cascades, logic functions, switches and other sophisticated circuit topologies. The orthogonal, modular and composable nature of this platform as well as the ease in constructing robust and predictable gene circuits promises myriad applications in gene and cell therapies.

CRISPR signal conductor 2.0 for redirecting cellular information flow

A key challenge in designing intelligent artificial gene circuits is generating flexible connections between arbitrary components and directly coupling them with endogenous signaling pathways. The CRISPR signal conductor based on conditionally inducible artificial transcriptional regulators can link classic cellular protein signals with targeted gene expression, but there are still problems with multiple signal processing and gene delivery. With the discovery and characterization of new Cas systems and long noncoding RNA (lncRNA) functional motifs, and because of the compatibility of guide RNA with noncoding RNA elements at multiple sites, it is increasingly possible to solve these problems. In this study, we developed CRISPR signal conductor version 2.0 by integrating various lncRNA functional motifs into different parts of the crRNA in the CRISPR-dCasΦ system. This system can directly regulate the expression of target genes by recruiting cellular endogenous transcription factors and efficiently sense a variety of protein signals that are not detected by a classical synthetic system. The new system solved the problems of background leakage and insensitive signaling responses and enabled the construction of logic gates with as many as six input signals, which can be used to specifically target cancer cells. By rewiring endogenous signaling networks, we further demonstrated the effectiveness and biosafety of this system for in vivo cancer gene therapy.

In silico and in vitro protocols for quantifying gene expression noise modulated by microRNAs

Characterizing the noise modulation pattern of microRNA is valuable for both microRNA function analysis and synthetic biology applications. Here we propose a coarse-grained model to simulate how the properties of microRNAs, competing RNAs, and microRNA response elements affect gene expression noise. We also detail an experimental protocol based on synthetic gene circuits and flow cytometry to quantify the noise. This framework is easy-to-use for the study and application of both microRNA and gene expression noise.

For complete details on the use and execution of this protocol, please refer to Wei et al. (2021).

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Simulate how microRNA modulates gene expression noise

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Consider the impact of competing RNAs and microRNA target composition to noise

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Quantify gene expression noise by synthetic gene circuits and flow cytometer

Single-cell Transcriptomes Reveal Characteristics of MicroRNA in Gene Expression Noise Reduction

Isogenic cells growing in identical environments show cell-to-cell variations because of the stochasticity in gene expression. High levels of variation or noise can disrupt robust gene expression and result in tremendous consequences for cell behaviors. In this work, we showed evidence from single-cell RNA sequencing data analysis that microRNAs (miRNAs) can reduce gene expression noise at the mRNA level in mouse cells. We identified that the miRNA expression level, number of targets, target pool abundance, and miRNA–target interaction strength are the key features contributing to noise repression. miRNAs tend to work together in cooperative subnetworks to repress target noise synergistically in a cell type-specific manner. By building a physical model of post-transcriptional regulation and observing in synthetic gene circuits, we demonstrated that accelerated degradation with elevated transcriptional activation of the miRNA target provides resistance to extrinsic fluctuations. Together, through the integrated analysis of single-cell RNA and miRNA expression profiles, we demonstrated that miRNAs are important post-transcriptional regulators for reducing gene expression noise and conferring robustness to biological processes.

Control of mammalian cell-based devices with genetic programming

Synthetic biology increasingly enables the construction of sophisticated functions in mammalian cells. A particularly promising frontier combines concepts drawn from industrial process control engineering-which is used to confer and balance properties such as stability and efficiency-with understanding as to how living systems have evolved to perform similar tasks with biological components. In this review, we first survey the state-of-the-art for both technologies and strategies available for genetic programming in mammalian cells. We then discuss recent progress in implementing programming objectives inspired by engineered and natural control mechanisms. Finally, we consider the transformative role of model-guided design in the present and future construction of customized mammalian cell functions for applications in biotechnology, medicine, and fundamental research.

Characterizing microRNA-mediated modulation of gene expression noise and its effect on synthetic gene circuits

MicroRNAs (miRNAs) have been shown to modulate gene expression noise, but less is known about how miRNAs with different properties may regulate noise differently. Here, we investigate the role of competing RNAs and the composition of miRNA response elements (MREs) in modulating noise. We find that weak competing RNAs could introduce lower noise than strong competing RNAs. In comparison with a single MRE, both repetitive and composite MREs can reduce the noise at low expression, but repetitive MREs can elevate the noise remarkably at high expression. We further observed the behavior of a synthetic cell-type classifier with miRNAs as inputs and find that miRNAs and MREs that could introduce higher noise tend to enhance cell state transition. These results provide a systematic and quantitative understanding of the function of miRNAs in controlling gene expression noise and the utilization of miRNAs to modulate the behavior of synthetic gene circuits.

Designer membraneless organelles sequester native factors for control of cell behavior

Subcellular compartmentalization of macromolecules increases flux and prevents inhibitory interactions to control biochemical reactions. Inspired by this functionality, we sought to build designer compartments that function as hubs to regulate the flow of information through cellular control systems. We report a synthetic membraneless organelle platform to control endogenous cellular activities through sequestration and insulation of native proteins. We engineer and express a disordered protein scaffold to assemble micron size condensates and recruit endogenous clients via genomic tagging with high-affinity dimerization motifs. By relocalizing up to ninety percent of a targeted enzymes to synthetic condensates, we efficiently control cellular behaviors, including proliferation, division, and cytoskeletal organization. Further, we demonstrate multiple strategies for controlled cargo release from condensates to switch cells between functional states. These synthetic organelles offer a powerful and generalizable approach to modularly control cell decision-making in a variety of model systems with broad applications for cellular engineering.

Quantitative characterization of recombinase-based digitizer circuits enables predictable amplification of biological signals

Many synthetic gene circuits are restricted to single-use applications or require iterative refinement for incorporation into complex systems. One example is the recombinase-based digitizer circuit, which has been used to improve weak or leaky biological signals. Here we present a workflow to quantitatively define digitizer performance and predict responses to different input signals. Using a combination of signal-to-noise ratio (SNR), area under a receiver operating characteristic curve (AUC), and fold change (FC), we evaluate three small-molecule inducible digitizer designs demonstrating FC up to 508x and SNR up to 3.77 dB. To study their behavior further and improve modularity, we develop a mixed phenotypic/mechanistic model capable of predicting digitizer configurations that amplify a synNotch cell-to-cell communication signal (Δ SNR up to 2.8 dB). We hope the metrics and modeling approaches here will facilitate incorporation of these digitizers into other systems while providing an improved workflow for gene circuit characterization.

Context-aware synthetic biology by controller design: Engineering the mammalian cell

The rise of systems biology has ushered a new paradigm: the view of the cell as a system that processes environmental inputs to drive phenotypic outputs. Synthetic biology provides a complementary approach, allowing us to program cell behavior through the addition of synthetic genetic devices into the cellular processor. These devices, and the complex genetic circuits they compose, are engineered using a design-prototype-test cycle, allowing for predictable device performance to be achieved in a context-dependent manner. Within mammalian cells, context effects impact device performance at multiple scales, including the genetic, cellular, and extracellular levels. In order for synthetic genetic devices to achieve predictable behaviors, approaches to overcome context dependence are necessary. Here, we describe control systems approaches for achieving context-aware devices that are robust to context effects. We then consider cell fate programing as a case study to explore the potential impact of context-aware devices for regenerative medicine applications.

Recent Advances in Cellular and Molecular Bioengineering for Building and Translation of Biological Systems

In January of 2020, the Biomedical Engineering Society (BMES)- Cellular and Molecular Bioengineering (CMBE) conference was held in Puerto Rico and themed “Vision 2020: Emerging Technologies to Elucidate the Rule of Life.” The annual BME-CMBE conference gathered worldwide leaders and discussed successes and challenges in engineering biological systems and their translation. The goal of this report is to present the research frontiers in this field and provide perspectives on successful engineering and translation towards the clinic. We hope that this report serves as a constructive guide in shaping the future of research and translation of engineered biological systems.

Synthetic Biological Circuits within an Orthogonal Central Dogma

Synthetic biology strives to reliably control cellular behavior, typically in the form of user-designed interactions of biological components to produce a predetermined output. Engineered circuit components are frequently derived from natural sources and are therefore often hampered by inadvertent interactions with host machinery, most notably within the host central dogma. Reliable and predictable gene circuits require the targeted reduction or elimination of these undesirable interactions to mitigate negative consequences on host fitness and develop context-independent bioactivities. Here, we review recent advances in biological orthogonalization, namely the insulation of researcher-dictated bioactivities from host processes, with a focus on systematic developments that may culminate in the creation of an orthogonal central dogma and novel cellular functions.

How Retroactivity Affects the Behavior of Incoherent Feedforward Loops

An incoherent feedforward loop (IFFL) is a network motif known for its ability to accelerate responses and generate pulses. It remains an open question to understand the behavior of IFFLs in contexts with high levels of retroactivity, where an upstream transcription factor binds to numerous downstream binding sites. Here we study the behavior of IFFLs by simulating and comparing ODE models with different levels of retroactivity. We find that increasing retroactivity in an IFFL can increase, decrease, or keep the network's response time and pulse amplitude constant. This suggests that increasing retroactivity, traditionally considered an impediment to designing robust synthetic systems, could be exploited to improve the performance of IFFLs. In contrast, we find that increasing retroactivity in a negative autoregulated circuit can only slow the response. The ability of an IFFL to flexibly handle retroactivity may have contributed to its significant abundance in both bacterial and eukaryotic regulatory networks.

Precise T cell recognition programs designed by transcriptionally linking multiple receptors

Living cells often identify their correct partner or target cells by integrating information from multiple receptors, achieving levels of recognition that are difficult to obtain with individual molecular interactions. In this study, we engineered a diverse library of multireceptor cell-cell recognition circuits by using synthetic Notch receptors to transcriptionally interconnect multiple molecular recognition events. These synthetic circuits allow engineered T cells to integrate extra- and intracellular antigen recognition, are robust to heterogeneity, and achieve precise recognition by integrating up to three different antigens with positive or negative logic. A three-antigen AND gate composed of three sequentially linked receptors shows selectivity in vivo, clearing three-antigen tumors while ignoring related two-antigen tumors. Daisy-chaining multiple molecular recognition events together in synthetic circuits provides a powerful way to engineer cellular-level recognition.

An endoribonuclease-based feedforward controller for decoupling resource-limited genetic modules in mammalian cells

Synthetic biology has the potential to bring forth advanced genetic devices for applications in healthcare and biotechnology. However, accurately predicting the behavior of engineered genetic devices remains difficult due to lack of modularity, wherein a device's output does not depend only on its intended inputs but also on its context. One contributor to lack of modularity is loading of transcriptional and translational resources, which can induce coupling among otherwise independently-regulated genes. Here, we quantify the effects of resource loading in engineered mammalian genetic systems and develop an endoribonuclease-based feedforward controller that can adapt the expression level of a gene of interest to significant resource loading in mammalian cells. Near-perfect adaptation to resource loads is facilitated by high production and catalytic rates of the endoribonuclease. Our design is portable across cell lines and enables predictable tuning of controller function. Ultimately, our controller is a general-purpose device for predictable, robust, and context-independent control of gene expression.

Strategies for simultaneous and successive delivery of RNA

Advanced non-viral gene delivery experiments often require co-delivery of multiple nucleic acids. Therefore, the availability of reliable and robust co-transfection methods and defined selection criteria for their use in, e.g., expression of multimeric proteins or mixed RNA/DNA delivery is of utmost importance. Here, we investigated different co- and successive transfection approaches, with particular focus on in vitro transcribed messenger RNA (IVT-mRNA). Expression levels and patterns of two fluorescent protein reporters were determined, using different IVT-mRNA doses, carriers, and cell types. Quantitative parameters determining the efficiency of co-delivery were analyzed for IVT-mRNAs premixed before nanocarrier formation (integrated co-transfection) and when simultaneously transfecting cells with separately formed nanocarriers (parallel co-transfection), which resulted in a much higher level of expression heterogeneity for the two reporters. Successive delivery of mRNA revealed a lower transfection efficiency in the second transfection round. All these differences proved to be more pronounced for low mRNA doses. Concurrent delivery of siRNA with mRNA also indicated the highest co-transfection efficiency for integrated method. However, the maximum efficacy was shown for successive delivery, due to the kinetically different peak output for the two discretely operating entities. Our findings provide guidance for selection of the co-delivery method best suited to accommodate experimental requirements, highlighting in particular the nucleic acid dose-response dependence on co-delivery on the single-cell level.

Genetic circuit characterization by inferring RNA polymerase movement and ribosome usage

To perform their computational function, genetic circuits change states through a symphony of genetic parts that turn regulator expression on and off. Debugging is frustrated by an inability to characterize parts in the context of the circuit and identify the origins of failures. Here, we take snapshots of a large genetic circuit in different states: RNA-seq is used to visualize circuit function as a changing pattern of RNA polymerase (RNAP) flux along the DNA. Together with ribosome profiling, all 54 genetic parts (promoters, ribozymes, RBSs, terminators) are parameterized and used to inform a mathematical model that can predict circuit performance, dynamics, and robustness. The circuit behaves as designed; however, it is riddled with genetic errors, including cryptic sense/antisense promoters and translation, attenuation, incorrect start codons, and a failed gate. While not impacting the expected Boolean logic, they reduce the prediction accuracy and could lead to failures when the parts are used in other designs. Finally, the cellular power (RNAP and ribosome usage) required to maintain a circuit state is calculated. This work demonstrates the use of a small number of measurements to fully parameterize a regulatory circuit and quantify its impact on host.

Molecular and DNA Artificial Neural Networks via Fractional Coding

This article considers implementation of artificial neural networks (ANNs) using molecular computing and DNA based on fractional coding. Prior work had addressed molecular two-layer ANNs with binary inputs and arbitrary weights. In prior work using fractional coding, a simple molecular perceptron that computes sigmoid of scaled weighted sum of the inputs was presented where the inputs and the weights lie between [-1,1]. Even for computing the perceptron, the prior approach suffers from two major limitations. First, it cannot compute the sigmoid of the weighted sum, but only the sigmoid of the scaled weighted sum. Second, many machine learning applications require the coefficients to be arbitrarily positive and negative numbers that are not bounded between [-1,1]; such numbers cannot be handled by the prior perceptron using fractional coding. This paper makes four contributions. First molecular perceptrons that can handle arbitrary weights and can compute sigmoid of the weighted sums are presented. Thus, these molecular perceptrons are ideal for regression applications and multi-layer ANNs. A new molecular divider is introduced and is used to compute sigmoid(ax) where . Second, based on fractional coding, a molecular artificial neural network (ANN) with one hidden layer is presented. Third, a trained ANN classifier with one hidden layer from seizure prediction application from electroencephalogram is mapped to molecular reactions and DNA and their performances are presented. Fourth, molecular activation functions for rectified linear unit (ReLU) and softmax are also presented.

The COMET toolkit for composing customizable genetic programs in mammalian cells

Engineering mammalian cells to carry out sophisticated and customizable genetic programs requires a toolkit of multiple orthogonal and well-characterized transcription factors (TFs). To address this need, we develop the COmposable Mammalian Elements of Transcription (COMET)-an ensemble of TFs and promoters that enable the design and tuning of gene expression to an extent not, to the best of our knowledge, previously possible. COMET currently comprises 44 activating and 12 inhibitory zinc-finger TFs and 83 cognate promoters, combined in a framework that readily accommodates new parts. This system can tune gene expression over three orders of magnitude, provides chemically inducible control of TF activity, and enables single-layer Boolean logic. We also develop a mathematical model that provides mechanistic insights into COMET performance characteristics. Altogether, COMET enables the design and construction of customizable genetic programs in mammalian cells.

A 'poly-transfection' method for rapid, one-pot characterization and optimization of genetic systems

Biological research is relying on increasingly complex genetic systems and circuits to perform sophisticated operations in living cells. Performing these operations often requires simultaneous delivery of many genes, and optimizing the stoichiometry of these genes can yield drastic improvements in performance. However, sufficiently sampling the large design space of gene expression stoichiometries in mammalian cells using current methods is cumbersome, complex, or expensive. We present a ‘poly-transfection’ method as a simple yet high-throughput alternative that enables comprehensive evaluation of genetic systems in a single, readily-prepared transfection sample. Each cell in a poly-transfection represents an independent measurement at a distinct gene expression stoichiometry, fully leveraging the single-cell nature of transfection experiments. We first benchmark poly-transfection against co-transfection, showing that titration curves for commonly-used regulators agree between the two methods. We then use poly-transfections to efficiently generate new insights, for example in CRISPRa and synthetic miRNA systems. Finally, we use poly-transfection to rapidly engineer a difficult-to-optimize miRNA-based cell classifier for discriminating cancerous cells. One-pot evaluation enabled by poly-transfection accelerates and simplifies the design of genetic systems, providing a new high-information strategy for interrogating biology.

Oncolytic adenovirus programmed by synthetic gene circuit for cancer immunotherapy

Improving efficacy of oncolytic virotherapy remains challenging due to difficulty increasing specificity and immune responses against cancer and limited understanding of its population dynamics. Here, we construct programmable and modular synthetic gene circuits to control adenoviral replication and release of immune effectors selectively in hepatocellular carcinoma cells in response to multiple promoter and microRNA inputs. By performing mouse model experiments and computational simulations, we find that replicable adenovirus has a superior tumor-killing efficacy than non-replicable adenovirus. We observe a synergistic effect on promoting local lymphocyte cytotoxicity and systematic vaccination in immunocompetent mouse models by combining tumor lysis and secretion of immunomodulators. Furthermore, our computational simulations show that oncolytic virus which encodes immunomodulators can exert a more robust therapeutic efficacy than combinatorial treatment with oncolytic virus and immune effector. Our results provide an effective strategy to engineer oncolytic adenovirus, which may lead to innovative immunotherapies for a variety of cancers.

It is difficult to improve the efficacy of oncolytic virotherapy due to immune system responses and limited understanding of population dynamics. Here the authors use synthetic biology gene circuits to control adenoviral replication and release of immunomodulators in hepatocellular carcinoma cells.

Transcribe this way: Rap1 confers promoter directionality by repressing divergent transcription

In eukaryotes, divergent transcription is a major source of noncoding RNAs. Recent studies have uncovered that in yeast, the transcription factor Rap1 restricts transcription in the divergent direction and thereby controls promoter directionality. Here, we summarize these findings, propose regulatory principles, and discuss the implications for eukaryotic gene regulation.

Protein-based parts and devices that respond to intracellular and extracellular signals in mammalian cells

Synthetic biology aims to rewire cellular activities and functionality by implementing genetic circuits with high biocomputing capabilities. Recent efforts led to the development of smart sensing interfaces which integrate multiple inputs to activate desired outputs in a highly specific and sensitive manner. In this review, we highlight protein-based interfaces that sense intracellular or extracellular cues providing information about dynamic environmental changes and cellular state. We will also discuss different mechanisms of regulation of gene expression connected to the sensors to develop diagnostic and therapeutic devices. We conclude discussing challenges and opportunities for biomedical applications of synthetic mammalian protein-based devices.

A CRISPR/Cas9-based central processing unit to program complex logic computation in human cells

Controlling gene expression with sophisticated logic gates has been and remains one of the central aims of synthetic biology. However, conventional implementations of biocomputers use central processing units (CPUs) assembled from multiple protein-based gene switches, limiting the programming flexibility and complexity that can be achieved within single cells. Here, we introduce a CRISPR/Cas9-based core processor that enables different sets of user-defined guide RNA inputs to program a single transcriptional regulator (dCas9-KRAB) to perform a wide range of bitwise computations, from simple Boolean logic gates to arithmetic operations such as the half adder. Furthermore, we built a dual-core CPU combining two orthogonal core processors in a single cell. In principle, human cells integrating multiple orthogonal CRISPR/Cas9-based core processors could offer enormous computational capacity.

Engineered Cell-Based Therapeutics: Synthetic Biology Meets Immunology

Synthetic Biology has enabled new approaches to several medical applications including the development of immunotherapies based on bioengineered cells, and most notably the engineering of T-cells with tumor-targeting receptors, the Chimeric Antigen Receptor (CAR)-T cells. CAR-T-cells have successfully treated blood tumors such as large B-cell lymphoma and promise a new scenario of therapeutic interventions also for solid tumors. Learning the lesson from CAR-T cells, we can foster the reprogramming of T lymphocytes with enhanced survival and functional activity in depressing tumor microenvironment, or to challenge diseases such as infections, autoimmune and chronic inflammatory disorders. This review will focus on the most updated bioengineering approaches to increase control, and safety of T-cell activity and to immunomodulate the extracellular microenvironment to augment immune responses. We will also discuss on applications beyond cancer treatment with implications toward the understanding and cure of a broader range of diseases by means of mammalian cells engineering.

Polarized displacement by transcription activator-like effectors for regulatory circuits

The interplay between DNA-binding proteins plays an important role in transcriptional regulation and could increase the precision and complexity of designed regulatory circuits. Here we show that a transcription activator-like effector (TALE) can displace another TALE protein from DNA in a highly polarized manner, displacing only the 3'- but not 5'-bound overlapping or adjacent TALE. We propose that the polarized displacement by TALEs is based on its multipartite nature of binding to DNA. The polarized TALE displacement provides strategies for the specific regulation of gene expression, for construction of all two-input Boolean genetic logic circuits based on the robust propagation of the displacement across multiple neighboring sites, for displacement of zinc finger-based transcription factors and for suppression of Cas9-gRNA-mediated genome cleavage, enriching the synthetic biology toolbox and contributing to the understanding of the underlying principles of the facilitated displacement.

Repression of Divergent Noncoding Transcription by a Sequence-Specific Transcription Factor

Many active eukaryotic gene promoters exhibit divergent noncoding transcription, but the mechanisms restricting expression of these transcripts are not well understood. Here, we demonstrate how a sequence-specific transcription factor represses divergent noncoding transcription at highly expressed genes in yeast. We find that depletion of the transcription factor Rap1 induces noncoding transcription in a large fraction of Rap1-regulated gene promoters. Specifically, Rap1 prevents transcription initiation at cryptic promoters near its binding sites, which is uncoupled from transcription regulation in the protein-coding direction. We further provide evidence that Rap1 acts independently of previously described chromatin-based mechanisms to repress cryptic or divergent transcription. Finally, we show that divergent transcription in the absence of Rap1 is elicited by the RSC chromatin remodeler. We propose that a sequence-specific transcription factor limits access of basal transcription machinery to regulatory elements and adjacent sequences that act as divergent cryptic promoters, thereby providing directionality toward productive transcription.

A revolutionary tool: CRISPR technology plays an important role in construction of intelligentized gene circuits

With the development of synthetic biology, synthetic gene circuits have shown great applied potential in medicine, biology, and as commodity chemicals. An ultimate challenge in the construction of gene circuits is the lack of effective, programmable, secure and sequence-specific gene editing tools. The clustered regularly interspaced short palindromic repeat (CRISPR) system, a CRISPR-associated RNA-guided endonuclease Cas9 (CRISPR-associated protein 9)-targeted genome editing tool, has recently been applied in engineering gene circuits for its unique properties-operability, high efficiency and programmability. The traditional single-targeted therapy cannot effectively distinguish tumour cells from normal cells, and gene therapy for single targets has poor anti-tumour effects, which severely limits the application of gene therapy. Currently, the design of gene circuits using tumour-specific targets based on CRISPR/Cas systems provides a new way for precision cancer therapy. Hence, the application of intelligentized gene circuits based on CRISPR technology effectively guarantees the safety, efficiency and specificity of cancer therapy. Here, we assessed the use of synthetic gene circuits and if the CRISPR system could be used, especially artificial switch-inducible Cas9, to more effectively target and treat tumour cells. Moreover, we also discussed recent advances, prospectives and underlying challenges in CRISPR-based gene circuit development.

Engineered dCas9 with reduced toxicity in bacteria: implications for genetic circuit design

Large synthetic genetic circuits require the simultaneous expression of many regulators. Deactivated Cas9 (dCas9) can serve as a repressor by having a small guide RNA (sgRNA) direct it to bind a promoter. The programmability and specificity of RNA:DNA basepairing simplifies the generation of many orthogonal sgRNAs that, in theory, could serve as a large set of regulators in a circuit. However, dCas9 is toxic in many bacteria, thus limiting how high it can be expressed, and low concentrations are quickly sequestered by multiple sgRNAs. Here, we construct a non-toxic version of dCas9 by eliminating PAM (protospacer adjacent motif) binding with a R1335K mutation (dCas9*) and recovering DNA binding by fusing it to the PhlF repressor (dCas9*_PhlF). Both the 30 bp PhlF operator and 20 bp sgRNA binding site are required to repress a promoter. The larger region required for recognition mitigates toxicity in Escherichia coli, allowing up to 9600 ± 800 molecules of dCas9*_PhlF per cell before growth or morphology are impacted, as compared to 530 ± 40 molecules of dCas9. Further, PhlF multimerization leads to an increase in average cooperativity from n = 0.9 (dCas9) to 1.6 (dCas9*_PhlF). A set of 30 orthogonal sgRNA-promoter pairs are characterized as NOT gates; however, the simultaneous use of multiple sgRNAs leads to a monotonic decline in repression and after 15 are co-expressed the dynamic range is <10-fold. This work introduces a non-toxic variant of dCas9, critical for its use in applications in metabolic engineering and synthetic biology, and exposes a limitation in the number of regulators that can be used in one cell when they rely on a shared resource.

Scaling up genetic circuit design for cellular computing: advances and prospects

Synthetic biology aims to engineer and redesign biological systems for useful real-world applications in biomanufacturing, biosensing and biotherapy following a typical design-build-test cycle. Inspired from computer science and electronics, synthetic gene circuits have been designed to exhibit control over the flow of information in biological systems. Two types are Boolean logic inspired TRUE or FALSE digital logic and graded analog computation. Key principles for gene circuit engineering include modularity, orthogonality, predictability and reliability. Initial circuits in the field were small and hampered by a lack of modular and orthogonal components, however in recent years the library of available parts has increased vastly. New tools for high throughput DNA assembly and characterization have been developed enabling rapid prototyping, systematic in situ characterization, as well as automated design and assembly of circuits. Recently implemented computing paradigms in circuit memory and distributed computing using cell consortia will also be discussed. Finally, we will examine existing challenges in building predictable large-scale circuits including modularity, context dependency and metabolic burden as well as tools and methods used to resolve them. These new trends and techniques have the potential to accelerate design of larger gene circuits and result in an increase in our basic understanding of circuit and host behaviour.

Computing Mathematical Functions using DNA via Fractional Coding

This paper discusses the implementation of mathematical functions such as exponentials, trigonometric functions, the sigmoid function and the perceptron function with molecular reactions in general, and DNA strand displacement reactions in particular. The molecular constructs for these functions are predicated on a novel representation for input and output values: a fractional encoding, in which values are represented by the relative concentrations of two molecular types, denoted as type-1 and type-0. This representation is inspired by a technique from digital electronic design, termed stochastic logic, in which values are represented by the probability of 1's in a stream of randomly generated 0's and 1's. Research in the electronic realm has shown that a variety of complex functions can be computed with remarkably simple circuitry with this stochastic approach. This paper demonstrates how stochastic electronic designs can be translated to molecular circuits. It presents molecular implementations of mathematical functions that are considerably more complex than any shown to date. All designs are validated using mass-action simulations of the chemical kinetics of DNA strand displacement reactions.

Programming gene and engineered-cell therapies with synthetic biology

Gene and engineered-cell therapies promise to treat diseases by genetically modifying cells to carry out therapeutic tasks. Although the field has had some success in treating monogenic disorders and hematological malignancies, current approaches are limited to overexpression of one or a few transgenes, constraining the diseases that can be treated with this approach and leading to potential concerns over safety and efficacy. Synthetic gene networks can regulate the dosage, timing, and localization of gene expression and therapeutic activity in response to small molecules and disease biomarkers. Such "programmable" gene and engineered-cell therapies will provide new interventions for incurable or difficult-to-treat diseases.

Functional Characterization of Insulation Effect for Synthetic Gene Circuits in Mammalian Cells

Insulators are noncoding gene regulatory elements in eukaryotic genome, which function as chromatin partitioning boundaries, and block interference across different chromatin domains. To facilitate modular construction of synthetic gene circuit that is usually composed of multiple transcription cassettes, unwanted cross-regulations between different cassettes should be avoided. Here, we developed a quantitative method to characterize the functional effect of three insulators on the cross-regulations of six promoters in mammalian cells. We showed that the unwanted cross-regulations displayed a threshold-like effect, and the threshold position varied along with the context of promoters and insulators. We tested the function of insulators in both cascade and sensory switch circuits assembled in episomal plasmid vectors, and showed that the insulation effect was mainly revealed on the first regulatory layer of the cascade circuit. A deviation on the response curve of the sensory switch circuit with or without insulators was observed, but response intensity of some sensory switch circuits were not affected. Therefore, our results provided a general guide on the selection of insulators with varying promoters in episomal synthetic gene circuits in mammalian cells, which may be useful to reduce the effect of the unwanted cross-regulations.

Split Cas9, Not Hairs - Advancing the Therapeutic Index of CRISPR Technology

The discovery that the bacterial CRISPR/Cas9 system can be translated into mammalian cells continues to have an unprecedented impact on the biomedical research community, as it largely facilitates efforts to experimentally interrogate or therapeutically modify the cellular genome. In particular, CRISPR promises the ability to correct disease-associated genetic defects, or to target and destroy invading foreign DNA, in a simple, efficient, and selective manner directly in affected human cells or tissues. Here, we highlight a set of exciting new strategies that aim at further increasing the therapeutic index of CRISPR technologies, by reducing the size of Cas9 expression cassettes and thus enhancing their compatibility with viral gene delivery vectors. Specifically, we discuss the concept of splitCas9 whereby the Cas9 holo-protein is segregated into two parts that are expressed individually and reunited in the cell by various means, including use of 1) the gRNA as a scaffold for Cas9 assembly; 2) the rapamycin-controlled FKBP/FRB system; 3) the light-regulated Magnet system; or 4) inteins. We describe how these avenues, despite pursuing the identical aim, differ in critical features comprising the extent of spatio-temporal control of CRISPR activity, and discuss additional improvements to their efficiency or specificity that should foster their clinical translation.

Exploring the Potential Application of Short Non-Coding RNA-Based Genetic Circuits in Chinese Hamster Ovary Cells

The majority of cell engineering for recombinant protein production to date has relied on traditional genetic engineering strategies, such as gene overexpression and gene knock-outs, to substantially improve the production capabilities of Chinese Hamster Ovary (CHO) cells. However, further improvements in cellular productivity or control over product quality is likely to require more sophisticated rational approaches to coordinate and balance cellular pathways. For these strategies to be implemented, novel molecular tools need to be developed to facilitate more refined control of gene expression. Multiple gene control strategies are developed over the last decades in the field of synthetic biology, including DNA and RNA-based systems, which allows tight and timely control over gene expression. microRNAs has received a lot of attention over the last decade in the CHO field and are used to engineer and improve CHO cells. In this review we focus on microRNA-based gene control systems and discuss their potential use as tools rather than targets in order to gain better control over gene expression.

Mammalian Synthetic Biology: Engineering Biological Systems

The programming of new functions into mammalian cells has tremendous application in research and medicine. Continued improvements in the capacity to sequence and synthesize DNA have rapidly increased our understanding of mechanisms of gene function and regulation on a genome-wide scale and have expanded the set of genetic components available for programming cell biology. The invention of new research tools, including targetable DNA-binding systems such as CRISPR/Cas9 and sensor-actuator devices that can recognize and respond to diverse chemical, mechanical, and optical inputs, has enabled precise control of complex cellular behaviors at unprecedented spatial and temporal resolution. These tools have been critical for the expansion of synthetic biology techniques from prokaryotic and lower eukaryotic hosts to mammalian systems. Recent progress in the development of genome and epigenome editing tools and in the engineering of designer cells with programmable genetic circuits is expanding approaches to prevent, diagnose, and treat disease and to establish personalized theranostic strategies for next-generation medicines. This review summarizes the development of these enabling technologies and their application to transforming mammalian synthetic biology into a distinct field in research and medicine.

Synthetic Gene Expression Circuits for Designing Precision Tools in Oncology

Precision medicine in oncology needs to enhance its capabilities to match diagnostic and therapeutic technologies to individual patients. Synthetic biology streamlines the design and construction of functionalized devices through standardization and rational engineering of basic biological elements decoupled from their natural context. Remarkable improvements have opened the prospects for the availability of synthetic devices of enhanced mechanism clarity, robustness, sensitivity, as well as scalability and portability, which might bring new capabilities in precision cancer medicine implementations. In this review, we begin by presenting a brief overview of some of the major advances in the engineering of synthetic genetic circuits aimed to the control of gene expression and operating at the transcriptional, post-transcriptional/translational, and post-translational levels. We then focus on engineering synthetic circuits as an enabling methodology for the successful establishment of precision technologies in oncology. We describe significant advancements in our capabilities to tailor synthetic genetic circuits to specific applications in tumor diagnosis, tumor cell- and gene-based therapy, and drug delivery.

Towards combinatorial transcriptional engineering

The modular nature of the transcriptional unit makes it possible to design robust modules with predictable input-output characteristics using a ‘parts- off a shelf’ approach. Customized regulatory circuits composed of multiple such transcriptional units have immense scope for application in diverse fields of basic and applied research. Synthetic transcriptional engineering seeks to construct such genetic cascades. Here, we discuss the three principle strands of transcriptional engineering: promoter and transcriptional factor engineering, and programming inducibilty into synthetic modules. In this context, we review the scope and limitations of some recent technologies that seek to achieve these ends. Our discussion emphasizes a requirement for rational combinatorial engineering principles and the promise this approach holds for the future development of this field.

Computational Sequence Design with R2oDNA Designer

Recently developed DNA assembly methods have enabled the rapid and simultaneous assembly of multiple parts to create complex synthetic gene circuits. A number of groups have proposed the use of computationally designed orthogonal spacer sequences to guide the ordered assembly of parts using overlap-directed or homologous recombination-based methods. This approach is particularly useful for assembling multiple parts with repetitive elements. Orthogonal spacer sequences (sometimes called UNSs-unique nucleotide sequences) also have a number of other potential uses including in the design of synthetic promoters regulated by novel regulatory elements.

Model-guided combinatorial optimization of complex synthetic gene networks

Constructing gene circuits that satisfy quantitative performance criteria has been a long-standing challenge in synthetic biology. Here, we show a strategy for optimizing a complex three-gene circuit, a novel proportional miRNA biosensor, using predictive modeling to initiate a search in the phase space of sensor genetic composition. We generate a library of sensor circuits using diverse genetic building blocks in order to access favorable parameter combinations and uncover specific genetic compositions with greatly improved dynamic range. The combination of high-throughput screening data and the data obtained from detailed mechanistic interrogation of a small number of sensors was used to validate the model. The validated model facilitated further experimentation, including biosensor reprogramming and biosensor integration into larger networks, enabling in principle arbitrary logic with miRNA inputs using normal form circuits. The study reveals how model-guided generation of genetic diversity followed by screening and model validation can be successfully applied to optimize performance of complex gene networks without extensive prior knowledge.

Construction and Characterization of a Synthetic MicroRNA Cluster for Multiplex RNA Interference in Mammalian Cells

RNA interference (RNAi) technology is widely used in basic and translational research. By mimicking a natural primary microRNA (pri-miRNA) cluster, multiple engineered hairpins can be transcribed as a single transcript from the same Pol II promoter, enabling the formation of multiplex RNAi in mammalian cells. However, constructing a synthetic miRNA cluster is still time-consuming, and the processing and function of a miRNA cluster are incompletely understood. Here, we identified a miRNA precursor architecture that allows precise miRNA maturation. We established a hierarchical cloning method for the efficient construction of a synthetic miRNA cluster harboring up to 18 miRNA precursors. We demonstrated that the maturation and function of individual miRNA precursors were independent of their positions in the cluster. We then analyzed the integration efficiency of miRNA clusters having a varied number of miRNA precursors by using CRISPR/Cas9-mediated integration, a piggyBac transposon system, and a lentiviral system. This synthetic miRNA cluster system provides an important tool for multiplex RNAi in mammalian cells.

Integration and exchange of split dCas9 domains for transcriptional controls in mammalian cells

Programmable and precise regulation of dCas9 functions in response to multiple molecular signals by using synthetic gene circuits will expand the application of the CRISPR-Cas technology. However, the application of CRISPR-Cas therapeutic circuits is still challenging due to the restrictive cargo size of existing viral delivery vehicles. Here, we construct logic AND circuits by integrating multiple split dCas9 domains, which is useful to reduce the size of synthetic circuits. In addition, we engineer sensory switches by exchanging split dCas9 domains, allowing differential regulations on one gene, or activating two different genes in response to cell-type specific microRNAs. Therefore, we provide a valuable split-dCas9 toolkit to engineer complex transcription controls, which may inspire new biomedical applications.

Molecular engineering of Cas9 has the potential to expand the application of CRISPR-Cas technology. Here, Ma et al. show that dCas9 can be split and reconstituted in human cells and use a domain swapping strategy to engineer custom Cas9-based logic circuits and sensory switches.