Designed cell consortia as fragrance-programmable analog-to-digital converters

Small-Molecule Regulators for Gene Switches to Program Mammalian Cell Behaviour

Synthetic or natural small molecules have been extensively employed as trigger signals or inducers to regulate engineered gene circuits introduced into living cells in order to obtain desired outputs in a controlled and predictable manner. Here, we provide an overview of small molecules used to drive synthetic-biology-based gene circuits in mammalian cells, together with examples of applications at different levels of control, including regulation of DNA manipulation, RNA synthesis and editing, and protein synthesis, maturation, and trafficking. We also discuss the therapeutic potential of these small-molecule-responsive gene circuits, focusing on the advantages and disadvantages of using small molecules as triggers, the mechanisms involved, and the requirements for selecting suitable molecules, including efficiency, specificity, orthogonality, and safety. Finally, we explore potential future directions for translation of these devices to clinical medicine.

An electrogenetic interface to program mammalian gene expression by direct current

Wearable electronic devices are playing a rapidly expanding role in the acquisition of individuals' health data for personalized medical interventions; however, wearables cannot yet directly program gene-based therapies because of the lack of a direct electrogenetic interface. Here we provide the missing link by developing an electrogenetic interface that we call direct current (DC)-actuated regulation technology (DART), which enables electrode-mediated, time- and voltage-dependent transgene expression in human cells using DC from batteries. DART utilizes a DC supply to generate non-toxic levels of reactive oxygen species that act via a biosensor to reversibly fine-tune synthetic promoters. In a proof-of-concept study in a type 1 diabetic male mouse model, a once-daily transdermal stimulation of subcutaneously implanted microencapsulated engineered human cells by energized acupuncture needles (4.5 V DC for 10 s) stimulated insulin release and restored normoglycemia. We believe this technology will enable wearable electronic devices to directly program metabolic interventions.

Blood-Glucose-Powered Metabolic Fuel Cell for Self-Sufficient Bioelectronics

Currently available bioelectronic devices consume too much power to be continuously operated on rechargeable batteries, and are often powered wirelessly, with attendant issues regarding reliability, convenience, and mobility. Thus, the availability of a robust, self-sufficient, implantable electrical power generator that works under physiological conditions would be transformative for many applications, from driving bioelectronic implants and prostheses to programing cellular behavior and patients' metabolism. Here, capitalizing on a new copper-containing, conductively tuned 3D carbon nanotube composite, an implantable blood-glucose-powered metabolic fuel cell is designed that continuously monitors blood-glucose levels, converts excess glucose into electrical power during hyperglycemia, and produces sufficient energy (0.7 mW cm^-2 , 0.9 V, 50 mm glucose) to drive opto- and electro-genetic regulation of vesicular insulin release from engineered beta cells. It is shown that this integration of blood-glucose monitoring with elimination of excessive blood glucose by combined electro-metabolic conversion and insulin-release-mediated cellular consumption enables the metabolic fuel cell to restore blood-glucose homeostasis in an automatic, self-sufficient, and closed-loop manner in an experimental model of type-1 diabetes.

Engineered Living Materials For Sustainability

Recent advances in synthetic biology and materials science have given rise to a new form of materials, namely engineered living materials (ELMs), which are composed of living matter or cell communities embedded in self-regenerating matrices of their own or artificial scaffolds. Like natural materials such as bone, wood, and skin, ELMs, which possess the functional capabilities of living organisms, can grow, self-organize, and self-repair when needed. They also spontaneously perform programmed biological functions upon sensing external cues. Currently, ELMs show promise for green energy production, bioremediation, disease treatment, and fabricating advanced smart materials. This review first introduces the dynamic features of natural living systems and their potential for developing novel materials. We then summarize the recent research progress on living materials and emerging design strategies from both synthetic biology and materials science perspectives. Finally, we discuss the positive impacts of living materials on promoting sustainability and key future research directions.

A Logically Reversible Double Feynman Gate with Molecular Engineered Bacteria Arranged in an Artificial Neural Network-Type Architecture

Reversible logic gates are the key components of reversible computing that map inputs and outputs in a certain one-to-one pattern so that the output signals can reveal the pattern of the input signals. One of the main research foci of reversible computing is the implementation of basic reversible gates by various modalities. Though true thermodynamic reversibility cannot be attained within living cells, the high energy efficiency of biological reactions inspires the implementation of reversible computation in living cells. The implementation of synthetic genetic circuits is mostly based on conventional irreversible computing, and the implementation of logical reversibility in living cells is rare. Here, we constructed a 3-input-3-output synthetic genetic reversible double Feynman logic gate with a population of genetically engineered E. coli cells. Instead of following hierarchical electronic design principles, we adapted the concept of artificial neural networks (ANN) and built a single-layer artificial network-type architecture with five different engineered bacteria, named bactoneurons. We used three extracellular chemicals as input signals and the expression of three fluorescence proteins as the output signals. The cellular devices, which combine the input chemical signals linearly and pass them through a nonlinear activation function and represent specific bactoneurons, were built by designing and creating small synthetic genetic networks inside E. coli. The weights of each of the inputs and biases of individual bactoneurons in the bacterial ANN were adjusted by optimizing the synthetic genetic networks. When arranging the five bactoneurons through an ANN-type architecture, the system generated a double Feynman gate function at the population level. To our knowledge, this is the first reversible double Feynman gate realization with living cells. This work may have significance in development of biocomputer technology, reversible computation, ANN wetware, and synthetic biology.

Synthetic memory circuits for stable cell reprogramming in plants

Plant biotechnology predominantly relies on a restricted set of genetic parts with limited capability to customize spatiotemporal and conditional expression patterns. Synthetic gene circuits have the potential to integrate multiple customizable input signals through a processing unit constructed from biological parts to produce a predictable and programmable output. Here we present a suite of functional recombinase-based gene circuits for use in plants. We first established a range of key gene circuit components compatible with plant cell functionality. We then used these to develop a range of operational logic gates using the identify function (activation) and negation function (repression) in Arabidopsis protoplasts and in vivo, demonstrating their utility for programmable manipulation of transcriptional activity in a complex multicellular organism. Specifically, using recombinases and plant control elements, we activated transgenes in YES, OR and AND gates and repressed them in NOT, NOR and NAND gates; we also implemented the A NIMPLY B gate that combines activation and repression. Through use of genetic recombination, these circuits create stable long-term changes in expression and recording of past stimuli. This highly compact programmable gene circuit platform provides new capabilities for engineering sophisticated transcriptional programs and previously unrealized traits into plants.

Synthetic neuromorphic computing in living cells

Computational properties of neuronal networks have been applied to computing systems using simplified models comprising repeated connected nodes, e.g., perceptrons, with decision-making capabilities and flexible weighted links. Analogously to their revolutionary impact on computing, neuro-inspired models can transform synthetic gene circuit design in a manner that is reliable, efficient in resource utilization, and readily reconfigurable for different tasks. To this end, we introduce the perceptgene, a perceptron that computes in the logarithmic domain, which enables efficient implementation of artificial neural networks in Escherichia coli cells. We successfully modify perceptgene parameters to create devices that encode a minimum, maximum, and average of analog inputs. With these devices, we create multi-layer perceptgene circuits that compute a soft majority function, perform an analog-to-digital conversion, and implement a ternary switch. We also create a programmable perceptgene circuit whose computation can be modified from OR to AND logic using small molecule induction. Finally, we show that our approach enables circuit optimization via artificial intelligence algorithms.

Synthetic Genetic Reversible Feynman Gate in a Single E. coli Cell and Its Application in Bacterial to Mammalian Cell Information Transfer

Reversible computing is a nonconventional form of computing where the inputs and outputs are mapped in a unique one-to-one fashion. Reversible logic gates in single living cells have not been demonstrated. Here, we constructed a synthetic genetic reversible Feynman gate in single E. coli cells, and the input-output relations were measured in a clonal population. The inputs were extracellular chemicals, isopropyl β-d-1-thiogalactopyranoside (IPTG), and anhydrotetracycline (aTc), and the outputs were two fluorescence proteins. We developed a simple mathematical model and simulation to capture the essential features of the circuit and experimentally demonstrated that the behavior of the circuit was ultrasensitive and predictive. We showed an application by creating an intercellular Feynman gate, where input information from bacteria was computed and transferred to HeLa cells through shRNAs delivery and the output signals were observed as silencing of native AKT1 and CTNNB1 genes. The introduction of reversible logics in synthetic biology is new, and given that one-to-one input-output mapping, such reversible genetic systems might have applications in sensing, diagnostics, cellular computing, and synthetic biology.

A single layer artificial neural network type architecture with molecular engineered bacteria for reversible and irreversible computing

Here, we adapted the basic concept of artificial neural networks (ANNs) and experimentally demonstrate a broadly applicable single layer ANN type architecture with molecular engineered bacteria to perform complex irreversible computing like multiplexing, de-multiplexing, encoding, decoding, majority functions, and reversible computing like Feynman and Fredkin gates. The encoder and majority functions and reversible computing were experimentally implemented within living cells for the first time. We created cellular devices, which worked as artificial neuro-synapses in bacteria, where input chemical signals were linearly combined and processed through a non-linear activation function to produce fluorescent protein outputs. To create such cellular devices, we established a set of rules by correlating truth tables, mathematical equations of ANNs, and cellular device design, which unlike cellular computing, does not require a circuit diagram and the equation directly correlates the design of the cellular device. To our knowledge this is the first adaptation of ANN type architecture with engineered cells. This work may have significance in establishing a new platform for cellular computing, reversible computing and in transforming living cells as ANN-enabled hardware.

Distributed Computing with Engineered Bacteria and Its Application in Solving Chemically Generated 2 × 2 Maze Problems

This work presented an application of genetic distributed computing, where an abstract computational problem was mapped on a complex truth table and solved using simple genetic circuits distributed among various cell populations. Maze generating and solving are challenging problems in mathematics and computing. Here, we mapped all the input-output matrices of a 2 × 2 mathematical maze on a 4-input-4-output truth table. The logic values of four chemical inputs determined the 16 different 2 × 2 maze problems on a chemical space. We created six multi-input synthetic genetic AND gates, which distributed among six cell populations and organized in a single layer. Those cell populations in a mixed culture worked as a computational solver, which solved the chemically generated maze problems by expressing or not expressing four different fluorescent proteins. The three available "solutions" were visualized by glowing bacteria, and for the 13 "no solution" cases, no bacteria glowed. Thus, our system not only solved the maze problems but also showed the number of solvable and unsolvable problems. This work may have significance in cellular computation and synthetic biology.

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.

A versatile plasmid architecture for mammalian synthetic biology (VAMSyB)

Current molecular cloning strategies generally lack inter-compatibility, are not strictly modular, or are not applicable to engineer multi-gene expression vectors for transient and stable integration. A standardized molecular cloning platform would advance research, for example, by promoting exchange of vectors between groups. Here, we present a versatile plasmid architecture for mammalian synthetic biology, which we designate VAMSyB, consisting of a three-tier vector family. Tier-1 is designed for easy engineering of fusion constructs, as well as easy swapping of genes and modules to tune the functionality of the vector. Tier-2 is designed for transient multi-gene expression, and is constructed by directly transferring the engineered expression cassettes from tier-1 vectors. Tier-3 enables stable integration into a mammalian host cell through viral transduction, transposons, or homology-directed recombination via CRISPR. This VAMSyB architecture is expected to have broad applicability in the field of mammalian synthetic biology. The VAMSyB collection of plasmids will be available through Addgene.

A guide to the design of synthetic gene networks in mammalian cells

Synthetic biology aims to harness natural and synthetic biological parts and engineering them in new combinations and systems, producing novel therapies, diagnostics, bioproduction systems, and providing information on the mechanism of function of biological systems. Engineering cell function requires the rewiring or de novo construction of cell information processing networks. Using natural and synthetic signal processing elements, researchers have demonstrated a wide array of signal sensing, processing and propagation modules, using transcription, translation, or post-translational modification to program new function. The toolbox for synthetic network design is ever-advancing and has still ample room to grow. Here, we review the diversity of synthetic gene networks, types of building modules, techniques of regulation, and their applications.

Design of Multipartite Transcription Factors for Multiplexed Logic Genome Integration Control in Mammalian Cells

Synthetic biology relies on rapid and efficient methods to stably integrate DNA payloads encoding for synthetic biological systems into the genome of living cells. The size of designed biological systems increases with their complexity, and novel methods are needed that enable efficient and simultaneous integration of multiple payloads into single cells. By assembling natural and synthetic protein–protein dimerization domains, we have engineered a set of multipartite transcription factors for driving heterologous target gene expression. With the distribution of single parts of multipartite transcription factors on piggyback transposon-based donor plasmids, we have created a logic genome integration control (LOGIC) system that allows for efficient one-step selection of stable mammalian cell lines with up to three plasmids. LOGIC significantly enhances the efficiency of multiplexed payload integration in mammalian cells compared to traditional cotransfection and may advance cell line engineering in synthetic biology and biotechnology.

Protease circuits for processing biological information

Engineered biocircuits designed with biological components have the capacity to expand and augment living functions. Here we demonstrate that proteases can be integrated into digital or analog biocircuits to process biological information. We first construct peptide-caged liposomes that treat protease activity as two-valued (i.e., signal is 0 or 1) operations to construct the biological equivalent of Boolean logic gates, comparators and analog-to-digital converters. We use these modules to assemble a cell-free biocircuit that can combine with bacteria-containing blood, quantify bacteria burden, and then calculate and unlock a selective drug dose. By contrast, we treat protease activity as multi-valued (i.e., signal is between 0 and 1) by controlling the degree to which a pool of enzymes is shared between two target substrates. We perform operations on these analog values by manipulating substrate concentrations and combine these operations to solve the mathematical problem Learning Parity with Noise (LPN). These results show that protease activity can be used to process biological information by binary Boolean logic, or as multi-valued analog signals under conditions where substrate resources are shared.

Molecular parts and genetic circuits for metabolic engineering of microorganisms

Microbial conversion of biomass into value-added biochemicals is a highly sustainable process compared to petroleum-based production. In this regard, microorganisms have been engineered via simple overexpression or deletion of metabolic genes to facilitate the production. However, the producer microorganisms require complex regulatory circuits to maximize productivity and performance. To address this issue, diverse genetic circuits have been developed that allow cells to minimize their metabolic burden, overcome metabolic imbalances and respond to a dynamically changing environment. In this review, we briefly explain the basic strategy for constructing genetic circuits by assembling molecular parts such as input, operation and output modules. Next, we describe recent applications of the circuits in the metabolic engineering of microorganisms to improve biochemical production. Beyond those achievements, genetic circuits will facilitate more innovative approaches to future strain development through mining and engineering new genetic elements and improving the complexity of genetic circuit design.

Designing cell function: assembly of synthetic gene circuits for cell biology applications

Synthetic biology is the discipline of engineering application-driven biological functionalities that were not evolved by nature. Early breakthroughs of cell engineering, which were based on ectopic (over)expression of single sets of transgenes, have already had a revolutionary impact on the biotechnology industry, regenerative medicine and blood transfusion therapies. Now, we require larger-scale, rationally assembled genetic circuits engineered to programme and control various human cell functions with high spatiotemporal precision in order to solve more complex problems in applied life sciences, biomedicine and environmental sciences. This will open new possibilities for employing synthetic biology to advance personalized medicine by converting cells into living therapeutics to combat hitherto intractable diseases.

An improved Tet-on system in microRNA overexpression and CRISPR/Cas9-mediated gene editing

Background

Tetracycline (Tet)-regulated expression system has become a widely applied tool to control gene activity. This study aimed to improve the Tet-on system with superior regulatory characteristics.

Results

By comprehensively comparing factors of transactivators, Tet-responsive elements (TREs), orientations of induced expression cassette, and promoters controlling the transactivator, we developed an optimal Tet-on system with enhanced inducible efficiency and lower leakiness. With the system, we successfully performed effective inducible and reversible expression of microRNA, and presented a more precise and easily reproducible fine-tuning for confirming the target of a miRNA. Finally, the system was applied in CRISPR/Cas9-mediated knockout of nuclear factor of activated T cells-5 (NFAT5), a protective transcription factor in cellular osmoregulation.

Conclusions

This study established an improved Tet-on system for powerful and stringent gene regulation in functional genetic studies.

Electronic supplementary material

The online version of this article (10.1186/s40104-019-0354-5) contains supplementary material, which is available to authorized users.

A modular degron library for synthetic circuits in mammalian cells

Tight control over protein degradation is a fundamental requirement for cells to respond rapidly to various stimuli and adapt to a fluctuating environment. Here we develop a versatile, easy-to-handle library of destabilizing tags (degrons) for the precise regulation of protein expression profiles in mammalian cells by modulating target protein half-lives in a predictable manner. Using the well-established tetracycline gene-regulation system as a model, we show that the dynamics of protein expression can be tuned by fusing appropriate degron tags to gene regulators. Next, we apply this degron library to tune a synthetic pulse-generating circuit in mammalian cells. With this toolbox we establish a set of pulse generators with tailored pulse lengths and magnitudes of protein expression. This methodology will prove useful in the functional roles of essential proteins, fine-tuning of gene-expression systems, and enabling a higher complexity in the design of synthetic biological systems in mammalian cells.

A Self-Actuated Cellular Protein Delivery Machine

Engineered bacterial cells have great promise to solve global problems, yet they are hampered by a lack of convenient strategy for controlled protein release. A well-controlled protein translocation through cellular membranes is essential for cell-based protein delivery. Here we have developed a controlled protein release system by programming a bacterial autotransporter system named Ag43. Ag43 protein is engineered by adding a protease digestion site between its translocation and cargo domains. Once it is displayed on the cell surface, we managed to release the cargo proteins in defined conditions by processing environmental signals. The protein release in terms of time and quantity can be controlled through changing the inducer conditions. We thought that the release system can be adopted for complex genetic circuitries due to its simplicity. We implemented the protein release system to develop a cellular device that is able to release proteins in a sequence response to ordered chemical signals. We envision that development of genetically controlled protein release systems will improve the applications of synthetic organisms in cell based therapies, especially for cases with a need for controlled protein release using the cues from the biological environment.

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.

In vivo biosensors: mechanisms, development, and applications

In vivo biosensors can recognize and respond to specific cellular stimuli. In recent years, biosensors have been increasingly used in metabolic engineering and synthetic biology, because they can be implemented in synthetic circuits to control the expression of reporter genes in response to specific cellular stimuli, such as a certain metabolite or a change in pH. There are many types of natural sensing devices, which can be generally divided into two main categories: protein-based and nucleic acid-based. Both can be obtained either by directly mining from natural genetic components or by engineering the existing genetic components for novel specificity or improved characteristics. A wide range of new technologies have enabled rapid engineering and discovery of new biosensors, which are paving the way for a new era of biotechnological progress. Here, we review recent advances in the design, optimization, and applications of in vivo biosensors in the field of metabolic engineering and synthetic biology.

Synthetic gene circuits for the detection, elimination and prevention of disease

In living organisms, naturally evolved sensors that constantly monitor and process environmental cues trigger corrective actions that enable the organisms to cope with changing conditions. Such natural processes have inspired biologists to construct synthetic living sensors and signalling pathways, by repurposing naturally occurring proteins and by designing molecular building blocks de novo, for customized diagnostics and therapeutics. In particular, designer cells that employ user-defined synthetic gene circuits to survey disease biomarkers and to autonomously re-adjust unbalanced pathological states can coordinate the production of therapeutics, with controlled timing and dosage. Furthermore, tailored genetic networks operating in bacterial or human cells have led to cancer remission in experimental animal models, owing to the network's unprecedented specificity. Other applications of designer cells in infectious, metabolic and autoimmune diseases are also being explored. In this Review, we describe the biomedical applications of synthetic gene circuits in major disease areas, and discuss how the first genetically engineered devices developed on the basis of synthetic-biology principles made the leap from the laboratory to the clinic.

Designer cells programming quorum-sensing interference with microbes

Quorum sensing is a promising target for next-generation anti-infectives designed to address evolving bacterial drug resistance. The autoinducer-2 (AI-2) is a key quorum-sensing signal molecule which regulates bacterial group behaviors and is recognized by many Gram-negative and Gram-positive bacteria. Here we report a synthetic mammalian cell-based microbial-control device that detects microbial chemotactic formyl peptides through a formyl peptide sensor (FPS) and responds by releasing AI-2. The microbial-control device was designed by rewiring an artificial receptor-based signaling cascade to a modular biosynthetic AI-2 production platform. Mammalian cells equipped with the microbial-control gene circuit detect formyl peptides secreted from various microbes with high sensitivity and respond with robust AI-2 production, resulting in control of quorum sensing-related behavior of pathogenic Vibrio harveyi and attenuation of biofilm formation by the human pathogen Candida albicans. The ability to manipulate mixed microbial populations through fine-tuning of AI-2 levels may provide opportunities for future anti-infective strategies.

Treatment of chronic pain by designer cells controlled by spearmint aromatherapy

Current treatment options for chronic pain are often associated with dose-limiting toxicities, or lead to drug tolerance or addiction. Here, we describe a pain management strategy, based on cell-engineering principles and inspired by synthetic biology, consisting of microencapsulated human designer cells that produce huwentoxin-IV (a safe and potent analgesic peptide that selectively inhibits the pain-triggering voltage-gated sodium channel Na_V1.7) in response to volatile spearmint aroma and in a dose-dependent manner. Spearmint sensitivity was achieved by ectopic expression of the R-carvone-responsive olfactory receptor OR1A1 rewired via an artificial G-protein deflector to induce the expression of a secretion-engineered and stabilized huwentoxin-IV variant. In a model of chronic inflammatory and neuropathic pain, mice bearing the designer cells showed reduced pain-associated behaviour on oral intake or inhalation-based intake of spearmint essential oil, and absence of cardiovascular, immunogenic and behavioural side effects. Our proof-of-principle findings indicate that therapies based on engineered cells can achieve robust, tunable and on-demand analgesia for the long-term management of chronic pain.

Scaling Computation and Memory in Living Cells

The semiconductor revolution that began in the 20th century has transformed society. Key to this revolution has been the integrated circuit, which enabled exponential scaling of computing devices using silicon-based transistors over many decades. Analogously, decreasing costs in DNA sequencing and synthesis, along with the development of robust genetic circuits, are enabling a "biocomputing revolution". First-generation gene circuits largely relied on assembling various transcriptional regulatory elements to execute digital and analog computing functions in living cells. Basic design rules and computational tools have since been derived so that such circuits can be scaled in order to implement complex computations. In the past five years, great strides have been made in expanding the biological programming toolkit to include recombinase- and CRISPR-based gene circuits that execute complex cellular logic and memory. Recent advances have enabled increasingly dense computing and memory circuits to function in living cells while expanding the application of these circuits from bacteria to eukaryotes, including human cells, for a wide range of uses.

Sensing and responding to allergic response cytokines through a genetically encoded circuit

While constantly rising, the prevalence of allergies is globally one of the highest among chronic diseases. Current treatments of allergic diseases include the application of anti-histamines, immunotherapy, steroids, and anti-immunoglobulin E (IgE) antibodies. Here we report mammalian cells engineered with a synthetic signaling cascade able to monitor extracellular pathophysiological levels of interleukin 4 and interleukin 13, two main cytokines orchestrating allergic inflammation. Upon activation of transgenic cells by these cytokines, designed ankyrin repeat protein (DARPin) E2_79, a non-immunogenic protein binding human IgE, is secreted in a precisely controlled and reversible manner. Using human whole blood cell culturing, we demonstrate that the mammalian dual T helper 2 cytokine sensor produces sufficient levels of DARPin E2_79 to dampen histamine release in allergic subjects exposed to allergens. Hence, therapeutic gene networks monitoring disease-associated cytokines coupled with in situ production, secretion and systemic delivery of immunomodulatory biologics may foster advances in the treatment of allergies.

The standard treatment for an allergic response is anti-histamines, steroids and anti-IgE antibodies. Here the authors present a genetic circuit that senses IL-4 and IL-13 and responses with DARPin production to bind IgE.

Optogenerapy: When bio-electronic implant enters the modern syringe era

Resort to medications dates back million years ago with the use of medicinal plants. In the nineteenth century, significant contributions in medicine appeared in different domains, among which the invention of a specific drug delivery device; the syringe. Nowadays, injection therapy of bio-manufactured drugs is routine practice for chronic diseases but remains constraining and painful. New emerging advanced therapies invest in genetic, electronics and cell-based therapy for addressing unmet needs for the caregivers and the patient. As digital process in health (eHealth) gains momentum, connected advanced bio-electronic devices now offer new strategies for personalized injection therapies. In this review, we take a journey along the genesis path of a new drug delivery system: the Optogenerapy, a synergy between optogenetic and gene therapy. Inside a bio-electronic implant, electronics and optogenetics are interfaced by light as a traceless inducer signal. By controlling a synthetic optogenetic pathway in the cell, therapeutics delivery can be fine-tuned with a precise spatiotemporal control. The technology holds promise of a new modern syringe era capable of producing a drug of interest at will directly inside the patient.

Enabling tools for high-throughput detection of metabolites: Metabolic engineering and directed evolution applications

Within the Design-Build-Test Cycle for strain engineering, rapid product detection and selection strategies remain challenging and limit overall throughput. Here we summarize a wide variety of modalities that transduce chemical concentrations into easily measured absorbance, luminescence, and fluorescence signals. Specifically, we cover protein-based biosensors (including transcription factors), nucleic acid-based biosensors, coupled enzyme reactions, bioorthogonal chemistry, and fluorescent and chromogenic dyes and substrates as modalities for detection. We focus on the use of these methods for strain engineering and enzyme discovery and conclude with remarks on the current and future state of biosensor development for application in the metabolic engineering field.

Synthetic biology-inspired therapies for metabolic diseases

Our ability to engineer mammalian cells with effective therapeutic behaviors has brought new hope for treating metabolic diseases. Synthetic gene networks have been customized to interface with the host metabolism, discriminate between healthy and diseased states, and respond by producing an adjusted dose of the therapeutic molecule. Such devices have the potential to treat a range of dysfunctions that are simply not addressable using conventional therapies. Recently, the repurposing of native signaling pathways has formed the basis of autonomous therapeutic programs genetically installed in mammalian cells and has greatly expanded the possibilities to effectively tackle metabolic disorders. Here, we outline network topologies that have been successfully validated in animal models of metabolic diseases and discuss future developments that will be important for bringing this technology closer to clinical application.

Mammalian synthetic biology in the age of genome editing and personalized medicine

The recent expansion of molecular tool kits has propelled synthetic biology toward the design of increasingly sophisticated mammalian systems. Specifically, advances in genome editing, protein engineering, and circuitry design have enabled the programming of cells for diverse applications, including regenerative medicine and cancer immunotherapy. The ease with which molecular and cellular interactions can be harnessed promises to yield novel approaches to elucidate genetic interactions, program cellular functions, and design therapeutic interventions. Here, we review recent advancements in the development of enabling technologies and the practical applications of mammalian synthetic biology.