Synthetic biology moving into the clinic

A fungicide-responsive kinase as a tool for synthetic cell fate regulation

Engineered biological systems that precisely execute defined tasks have major potential for medicine and biotechnology. For instance, gene- or cell-based therapies targeting pathogenic cells may replace time- and resource-intensive drug development. Engineering signal transduction systems is a promising, yet presently underexplored approach. Here, we exploit a fungicide-responsive heterologous histidine kinase for pathway engineering and synthetic cell fate regulation in the budding yeast Saccharomyces cerevisiae. Rewiring the osmoregulatory Hog1 MAPK signalling system generates yeast cells programmed to execute three different tasks. First, a synthetic negative feedback loop implemented by employing the fungicide-responsive kinase and a fungicide-resistant derivative reshapes the Hog1 activation profile, demonstrating how signalling dynamics can be engineered. Second, combinatorial integration of different genetic parts including the histidine kinases, a pathway activator and chemically regulated promoters enables control of yeast growth and/or gene expression in a two-input Boolean logic manner. Finally, we implemented a genetic ‘suicide attack’ system, in which engineered cells eliminate target cells and themselves in a specific and controllable manner. Taken together, fungicide-responsive kinases can be applied in different constellations to engineer signalling behaviour. Sensitizing engineered cells to existing chemicals may be generally useful for future medical and biotechnological applications.

Constructing de novo H2O2 signaling via induced protein proximity

A new chemical strategy has been developed to generate de novo signaling pathways that link a signaling molecule, H2O2, to different downstream cellular events in mammalian cells. This approach combines the reactivity-based H2O2 sensing with the chemically induced protein proximity technology. By chemically modifying abscisic acid with an H2O2-sensitive boronate ester probe, novel H2O2 signaling pathways can be engineered to induce transcription, protein translocation and membrane ruffle formation upon exogenous or endogenous H2O2 stimulation. This strategy has also been successfully applied to gibberellic acid, which provides the potential to build signaling networks based on orthogonal cell stimuli.

A chemical switch for controlling viral infectivity

Chemically triggered molecular switches for controlling the fate and function of biological systems are fundamental to the emergence of synthetic biology and the development of biomedical applications. We here present the first chemically triggered switch for controlling the infectivity of adeno-associated viral (AAV) vectors.

Multi-input distributed classifiers for synthetic genetic circuits

For practical construction of complex synthetic genetic networks able to perform elaborate functions it is important to have a pool of relatively simple modules with different functionality which can be compounded together. To complement engineering of very different existing synthetic genetic devices such as switches, oscillators or logical gates, we propose and develop here a design of synthetic multi-input classifier based on a recently introduced distributed classifier concept. A heterogeneous population of cells acts as a single classifier, whose output is obtained by summarizing the outputs of individual cells. The learning ability is achieved by pruning the population, instead of tuning parameters of an individual cell. The present paper is focused on evaluating two possible schemes of multi-input gene classifier circuits. We demonstrate their suitability for implementing a multi-input distributed classifier capable of separating data which are inseparable for single-input classifiers, and characterize performance of the classifiers by analytical and numerical results. The simpler scheme implements a linear classifier in a single cell and is targeted at separable classification problems with simple class borders. A hard learning strategy is used to train a distributed classifier by removing from the population any cell answering incorrectly to at least one training example. The other scheme implements a circuit with a bell-shaped response in a single cell to allow potentially arbitrary shape of the classification border in the input space of a distributed classifier. Inseparable classification problems are addressed using soft learning strategy, characterized by probabilistic decision to keep or discard a cell at each training iteration. We expect that our classifier design contributes to the development of robust and predictable synthetic biosensors, which have the potential to affect applications in a lot of fields, including that of medicine and industry.

Spatial and functional heterogeneities shape collective behavior of tumor-immune networks

Tumor growth involves a dynamic interplay between cancer cells and host cells, which collectively form a tumor microenvironmental network that either suppresses or promotes tumor growth under different conditions. The transition from tumor suppression to tumor promotion is mediated by a tumor-induced shift in the local immune state, and despite the clinical challenge this shift poses, little is known about how such dysfunctional immune states are initiated. Clinical and experimental observations have indicated that differences in both the composition and spatial distribution of different cell types and/or signaling molecules within the tumor microenvironment can strongly impact tumor pathogenesis and ultimately patient prognosis. How such “functional” and “spatial” heterogeneities confer such effects, however, is not known. To investigate these phenomena at a level currently inaccessible by direct observation, we developed a computational model of a nascent metastatic tumor capturing salient features of known tumor-immune interactions that faithfully recapitulates key features of existing experimental observations. Surprisingly, over a wide range of model formulations, we observed that heterogeneity in both spatial organization and cell phenotype drove the emergence of immunosuppressive network states. We determined that this observation is general and robust to parameter choice by developing a systems-level sensitivity analysis technique, and we extended this analysis to generate other parameter-independent, experimentally testable hypotheses. Lastly, we leveraged this model as an in silico test bed to evaluate potential strategies for engineering cell-based therapies to overcome tumor associated immune dysfunction and thereby identified modes of immune modulation predicted to be most effective. Collectively, this work establishes a new integrated framework for investigating and modulating tumor-immune networks and provides insights into how such interactions may shape early stages of tumor formation.

Over the course of tumor growth, cancer cells interact with normal cells via processes that are difficult to understand by experiment alone. This challenge is particularly pronounced at early stages of tumor formation, when experimental observation is most limited. Elucidating such interactions could inform both understanding of cancer and clinical practice. To address this need we developed a computational model capturing the current understanding of how individual metastatic tumor cells and immune cells sense and contribute to the tumor environment, which in turn enabled us to investigate the complex, collective behavior of these systems. Surprisingly, we discovered that tumor escape from immune control was enhanced by the existence of small differences (or heterogeneities) in the responses of individual immune cells to their environment, as well as by heterogeneities in the way that cells and the molecules they secrete are arranged in space. These conclusions held true over a range of model formulations, suggesting that this is a general feature of these tumor-immune networks. Finally, we used this model as a test bed to evaluate potential strategies for enhancing immunological control of early tumors, ultimately predicting that specifically modulating tumor-associated immune dysfunction may be more effective than simply enhanced tumor killing.

A universal strategy for regulating mRNA translation in prokaryotic and eukaryotic cells

We describe a simple strategy to control mRNA translation in both prokaryotic and eukaryotic cells which relies on a unique protein–RNA interaction. Specifically, we used the Pumilio/FBF (PUF) protein to repress translation by binding in between the ribosome binding site (RBS) and the start codon (in Escherichia coli), or by binding to the 5′ untranslated region of target mRNAs (in mammalian cells). The design principle is straightforward, the extent of translational repression can be tuned and the regulator is genetically encoded, enabling the construction of artificial signal cascades. We demonstrate that this approach can also be used to regulate polycistronic mRNAs; such regulation has rarely been achieved in previous reports. Since the regulator used in this study is a modular RNA-binding protein, which can be engineered to target different 8-nucleotide RNA sequences, our strategy could be used in the future to target endogenous mRNAs for regulating metabolic flows and signaling pathways in both prokaryotic and eukaryotic cells.

Cancer and the microbiota

A host's microbiota may increase, diminish, or have no effect at all on cancer susceptibility. Assigning causal roles in cancer to specific microbes and microbiotas, unraveling host-microbiota interactions with environmental factors in carcinogenesis, and exploiting such knowledge for cancer diagnosis and treatment are areas of intensive interest. This Review considers how microbes and the microbiota may amplify or mitigate carcinogenesis, responsiveness to cancer therapeutics, and cancer-associated complications.

Inducible suppression of global translation by overuse of rare codons

Recently, artificial gene networks have been developed in synthetic biology to control gene expression and make organisms as controllable as robots. Here, I present an artificial posttranslational gene-silencing system based on the codon usage bias and low tRNA content corresponding to minor codons. I engineered the green fluorescent protein (GFP) gene to inhibit translation indirectly with the lowest-usage codons to monopolize various minor tRNAs (lgfp). The expression of lgfp interfered nonspecifically with the growth of Escherichia coli, Saccharomyces cerevisiae, human HeLa cervical cancer cells, MCF7 breast cancer cells, and HEK293 kidney cells, as well as phage and adenovirus expansion. Furthermore, insertion of lgfp downstream of a phage response promoter conferred phage resistance on E. coli. Such engineered gene silencers could act as components of biological networks capable of functioning with suitable promoters in E. coli, S. cerevisiae, and human cells to control gene expression. The results presented here show general suppressor artificial genes for live cells and viruses. This robust system provides a gene expression or cell growth control device for artificially synthesized gene networks.

On the road to synthetic life: the minimal cell and genome-scale engineering

Synthetic biology employs rational engineering principles to build biological systems from the libraries of standard, well characterized biological parts. Biological systems designed and built by synthetic biologists fulfill a plethora of useful purposes, ranging from better healthcare and energy production to biomanufacturing. Recent advancements in the synthesis, assembly and "booting-up" of synthetic genomes and in low and high-throughput genome engineering have paved the way for engineering on the genome-wide scale. One of the key goals of genome engineering is the construction of minimal genomes consisting solely of essential genes (genes indispensable for survival of living organisms). Besides serving as a toolbox to understand the universal principles of life, the cell encoded by minimal genome could be used to build a stringently controlled "cell factory" with a desired phenotype. This review provides an update on recent advances in the genome-scale engineering with particular emphasis on the engineering of minimal genomes. Furthermore, it presents an ongoing discussion to the scientific community for better suitability of minimal or robust cells for industrial applications.

Applications of synthetic gene networks

Synthetic gene networks have evolved from simple proof-of-concept circuits to complex therapy-oriented networks over the past 15 years. This advancement has greatly facilitated the expansion of the emerging field of synthetic biology. In this review, we highlight the main applications ofsynthetic gene networks in understanding biological design principles, developing biosensors for diagnosis, producing industrial and biomedical compounds, and treating human diseases. Finally, we outline current challenges and future prospects of synthetic gene networks for advancing practical applications.

Genome engineering using a synthetic gene circuit in Bacillus subtilis

Genome engineering without leaving foreign DNA behind requires an efficient counter-selectable marker system. Here, we developed a genome engineering method in Bacillus subtilis using a synthetic gene circuit as a counter-selectable marker system. The system contained two repressible promoters (B. subtilis xylA (P_xyl) and spac (P_spac)) and two repressor genes (lacI and xylR). P_xyl-lacI was integrated into the B. subtilis genome with a target gene containing a desired mutation. The xylR and P_spac–chloramphenicol resistant genes (cat) were located on a helper plasmid. In the presence of xylose, repression of XylR by xylose induced LacI expression, the LacIs repressed the P_spac promoter and the cells become chloramphenicol sensitive. Thus, to survive in the presence of chloramphenicol, the cell must delete P_xyl-lacI by recombination between the wild-type and mutated target genes. The recombination leads to mutation of the target gene. The remaining helper plasmid was removed easily under the chloramphenicol absent condition. In this study, we showed base insertion, deletion and point mutation of the B. subtilis genome without leaving any foreign DNA behind. Additionally, we successfully deleted a 2-kb gene (amyE) and a 38-kb operon (ppsABCDE). This method will be useful to construct designer Bacillus strains for various industrial applications.

Synthetic Biology: A Bridge between Artificial and Natural Cells

Artificial cells are simple cell-like entities that possess certain properties of natural cells. In general, artificial cells are constructed using three parts: (1) biological membranes that serve as protective barriers, while allowing communication between the cells and the environment; (2) transcription and translation machinery that synthesize proteins based on genetic sequences; and (3) genetic modules that control the dynamics of the whole cell. Artificial cells are minimal and well-defined systems that can be more easily engineered and controlled when compared to natural cells. Artificial cells can be used as biomimetic systems to study and understand natural dynamics of cells with minimal interference from cellular complexity. However, there remain significant gaps between artificial and natural cells. How much information can we encode into artificial cells? What is the minimal number of factors that are necessary to achieve robust functioning of artificial cells? Can artificial cells communicate with their environments efficiently? Can artificial cells replicate, divide or even evolve? Here, we review synthetic biological methods that could shrink the gaps between artificial and natural cells. The closure of these gaps will lead to advancement in synthetic biology, cellular biology and biomedical applications.

Systematic transfer of prokaryotic sensors and circuits to mammalian cells

Prokaryotic regulatory proteins respond to diverse signals and represent a rich resource for building synthetic sensors and circuits. The TetR family contains >10(5) members that use a simple mechanism to respond to stimuli and bind distinct DNA operators. We present a platform that enables the transfer of these regulators to mammalian cells, which is demonstrated using human embryonic kidney (HEK293) and Chinese hamster ovary (CHO) cells. The repressors are modified to include nuclear localization signals (NLS) and responsive promoters are built by incorporating multiple operators. Activators are also constructed by modifying the protein to include a VP16 domain. Together, this approach yields 15 new regulators that demonstrate 19- to 551-fold induction and retain both the low levels of crosstalk in DNA binding specificity observed between the parent regulators in Escherichia coli, as well as their dynamic range of activity. By taking advantage of the DAPG small molecule sensing mediated by the PhlF repressor, we introduce a new inducible system with 50-fold induction and a threshold of 0.9 μM DAPG, which is comparable to the classic Dox-induced TetR system. A set of NOT gates is constructed from the new repressors and their response function quantified. Finally, the Dox- and DAPG- inducible systems and two new activators are used to build a synthetic enhancer (fuzzy AND gate), requiring the coordination of 5 transcription factors organized into two layers. This work introduces a generic approach for the development of mammalian genetic sensors and circuits to populate a toolbox that can be applied to diverse applications from biomanufacturing to living therapeutics.

Hierarchical Stochastic Simulation Algorithm for SBML Models of Genetic Circuits

This paper describes a hierarchical stochastic simulation algorithm, which has been implemented within iBioSim, a tool used to model, analyze, and visualize genetic circuits. Many biological analysis tools flatten out hierarchy before simulation, but there are many disadvantages associated with this approach. First, the memory required to represent the model can quickly expand in the process. Second, the flattening process is computationally expensive. Finally, when modeling a dynamic cellular population within iBioSim, inlining the hierarchy of the model is inefficient since models must grow dynamically over time. This paper discusses a new approach to handle hierarchy on the fly to make the tool faster and more memory-efficient. This approach yields significant performance improvements as compared to the former flat analysis method.

Programming the group behaviors of bacterial communities with synthetic cellular communication

Synthetic biology is a newly emerged research discipline that focuses on the engineering of novel cellular behaviors and functionalities through the creation of artificial gene circuits. One important class of synthetic circuits currently under active development concerns the programming of bacterial cellular communication and collective population-scale behaviors. Because of the ubiquity of cell-cell interactions within bacterial communities, having an ability of engineering these circuits is vital to programming robust cellular behaviors. Here, we highlight recent advances in communication-based synthetic gene circuits by first discussing natural communication systems and then surveying various functional engineered circuits, including those for population density control, temporal synchronization, spatial organization, and ecosystem formation. We conclude by summarizing recent advances, outlining existing challenges, and discussing potential applications and future opportunities.

A platform for rapid prototyping of synthetic gene networks in mammalian cells

Mammalian synthetic biology may provide novel therapeutic strategies, help decipher new paths for drug discovery and facilitate synthesis of valuable molecules. Yet, our capacity to genetically program cells is currently hampered by the lack of efficient approaches to streamline the design, construction and screening of synthetic gene networks. To address this problem, here we present a framework for modular and combinatorial assembly of functional (multi)gene expression vectors and their efficient and specific targeted integration into a well-defined chromosomal context in mammalian cells. We demonstrate the potential of this framework by assembling and integrating different functional mammalian regulatory networks including the largest gene circuit built and chromosomally integrated to date (6 transcription units, 27kb) encoding an inducible memory device. Using a library of 18 different circuits as a proof of concept, we also demonstrate that our method enables one-pot/single-flask chromosomal integration and screening of circuit libraries. This rapid and powerful prototyping platform is well suited for comparative studies of genetic regulatory elements, genes and multi-gene circuits as well as facile development of libraries of isogenic engineered cell lines.

The scientific quest for lasting youth: prospects for curing aging

People have always sought eternal life and everlasting youth. Recent technological breakthroughs and our growing understanding of aging have given strength to the idea that a cure for human aging can eventually be developed. As such, it is crucial to debate the long-term goals and potential impact of the field. Here, I discuss the scientific prospect of eradicating human aging. I argue that curing aging is scientifically possible and not even the most challenging enterprise in the biosciences. Developing the means to abolish aging is also an ethical endeavor because the goal of biomedical research is to allow people to be as healthy as possible for as long as possible. There is no evidence, however, that we are near to developing the technologies permitting radical life extension. One major difficulty in aging research is the time and costs it takes to do experiments and test interventions. I argue that unraveling the functioning of the genome and developing predictive computer models of human biology and disease are essential to increase the accuracy of medical interventions, including in the context of life extension, and exponential growth in informatics and genomics capacity might lead to rapid progress. Nonetheless, developing the tools for significantly modifying human biology is crucial to intervening in a complex process like aging. Yet in spite of advances in areas like regenerative medicine and gene therapy, the development of clinical applications has been slow and this remains a key hurdle for achieving radical life extension in the foreseeable future.

Integration of microfluidics into the synthetic biology design flow

One goal of synthetic biology is to design and build genetic circuits in living cells for a range of applications. Major challenges in these efforts include increasing the scalability and robustness of engineered biological systems and streamlining and automating the synthetic biology workflow of specification-design-assembly-verification. We present here a summary of the advances in microfluidic technology, particularly microfluidic large scale integration, that can be used to address the challenges facing each step of the synthetic biology workflow. Microfluidic technologies allow precise control over the flow of biological content within microscale devices, and thus may provide more reliable and scalable construction of synthetic biological systems. The integration of microfluidics and synthetic biology has the capability to produce rapid prototyping platforms for characterization of genetic devices, testing of biotherapeutics, and development of biosensors.

Unique nucleotide sequence-guided assembly of repetitive DNA parts for synthetic biology applications

Recombination-based DNA construction methods, such as Gibson assembly, have made it possible to easily and simultaneously assemble multiple DNA parts, and they hold promise for the development and optimization of metabolic pathways and functional genetic circuits. Over time, however, these pathways and circuits have become more complex, and the increasing need for standardization and insulation of genetic parts has resulted in sequence redundancies--for example, repeated terminator and insulator sequences--that complicate recombination-based assembly. We and others have recently developed DNA assembly methods, which we refer to collectively as unique nucleotide sequence (UNS)-guided assembly, in which individual DNA parts are flanked with UNSs to facilitate the ordered, recombination-based assembly of repetitive sequences. Here we present a detailed protocol for UNS-guided assembly that enables researchers to convert multiple DNA parts into sequenced, correctly assembled constructs, or into high-quality combinatorial libraries in only 2-3 d. If the DNA parts must be generated from scratch, an additional 2-5 d are necessary. This protocol requires no specialized equipment and can easily be implemented by a student with experience in basic cloning techniques.

A designer cell-based histamine-specific human allergy profiler

Allergic disorders are markedly increasing in industrialized countries. The identification of compounds that trigger the immunoglobulin E-dependent allergic reaction remains the key to limit patients’ exposure to critical allergens and improve their quality of life. Here we use synthetic biology principles to design a mammalian cell-based allergy profiler that scores the allergen-triggered release of histamine from whole-blood-derived human basophils. A synthetic signalling cascade engineered within the allergy profiler rewires histamine input to the production of reporter protein, thereby integrating histamine levels in whole-blood samples with remarkable sensitivity and a wide dynamic range, allowing for rapid results or long-term storage of output, respectively. This approach provides non-intrusive allergy profiles for the personalized medicine era.

The advancement of sensitive, accurate and non-invasive methods to identify the allergen that drives allergic disease in an individual remains a challenge. Here, the authors develop a synthetic biology approach using human designer cells to profile allergic reactions against an array of allergens measuring histamine release from whole blood.

Cloning and optimization of a nisin biosynthesis pathway for bacteriocin harvest

Nisin is an important antimicrobial peptide that has enormous applications in biotechnology. Despite many encouraging efforts, its overproduction has been a long-standing challenge due to the complexity of the underlying pathway and the difficulty in genetic modification of lactic acid bacteria. Here, we cloned an entire nisin biosynthesis pathway from a nisin-producing strain (Lactococcus lactis K29) into a plasmid and transplanted the plasmid into a nisin deficient strain Lactococcus lactis MG1363, resulting in successful heterologous expression of bioactive recombinant nisin. To increase nisin harvest, we also overexpressed nisA, a gene responsible for nisin precursor production, with a set of constitutive promoters. To further optimize nisin yield, we minimized the metabolic cost of the engineered strains by integrating nisA overexpression cassettes and the recombinant pathway into a single circuit. With our rational construction and optimization, our engineered optimized strain is able to produce bioactive nisin with a yield of 1098 IU/mL, which is more than six times higher than that of the original strain.

A closed-loop synthetic gene circuit for the treatment of diet-induced obesity in mice

Diet-induced obesity is a lifestyle-associated medical condition that increases the risk of developing cardiovascular disease, type 2 diabetes and certain types of cancer. Here we report the design of a closed-loop genetic circuit that constantly monitors blood fatty acid levels in the setting of diet-associated hyperlipidemia and coordinates reversible and adjustable expression of the clinically licensed appetite-suppressing peptide hormone pramlintide. Grafting of the peroxisome proliferator-activated receptor-α onto the phloretin-responsive repressor TtgR produces a synthetic intracellular lipid-sensing receptor (LSR) that reversibly induces chimeric TtgR-specific promoters in a fatty acid-adjustable manner. Mice with diet-induced obesity in which microencapsulated cells engineered for LSR-driven expression of pramlintide are implanted show significant reduction in food consumption, blood lipid levels and body weight when put on a high-fat diet. Therapeutic designer circuits that monitor levels of pathologic metabolites and link these with the tailored expression of protein pharmaceuticals may provide new opportunities for the treatment of metabolic disorders.

Synthetic microbial consortia: from systematic analysis to construction and applications

Synthetic biology is an emerging research field that focuses on using rational engineering strategies to program biological systems, conferring on them new functions and behaviours. By developing genetic parts and devices based on transcriptional, translational, post-translational modules, many genetic circuits and metabolic pathways had been programmed in single cells. Extending engineering capabilities from single-cell behaviours to multicellular microbial consortia represents a new frontier of synthetic biology. Herein, we first reviewed binary interaction modes of microorganisms in microbial consortia and their underlying molecular mechanisms, which lay the foundation of programming cell-cell interactions in synthetic microbial consortia. Systems biology studies on cellular systems enable systematic understanding of diverse physiological processes of cells and their interactions, which in turn offer insights into the optimal design of synthetic consortia. Based on such fundamental understanding, a comprehensive array of synthetic microbial consortia constructed in the last decade were reviewed, including isogenic microbial communities programmed by quorum sensing-based cell-cell communications, sender-receiver microbial communities with one-way communications, and microbial ecosystems wired by two-way (bi-directional) communications. Furthermore, many applications including using synthetic microbial consortia for distributed bio-computations, chemicals and bioenergy production, medicine and human health, and environments were reviewed. Synergistic development of systems and synthetic biology will provide both a thorough understanding of naturally occurring microbial consortia and rational engineering of these complicated consortia for novel applications.

CRISPR transcriptional repression devices and layered circuits in mammalian cells

A key obstacle to creating sophisticated genetic circuits has been the lack of scalable device libraries. Here we present a modular transcriptional repression architecture based on clustered regularly interspaced palindromic repeats (CRISPR) system and examine approaches for regulated expression of guide RNAs in human cells. Subsequently we demonstrate that CRISPR regulatory devices can be layered to create functional cascaded circuits, which provide a valuable toolbox for engineering purposes.

Principles of genetic circuit design

Cells navigate environments, communicate and build complex patterns by initiating gene expression in response to specific signals. Engineers seek to harness this capability to program cells to perform tasks or create chemicals and materials that match the complexity seen in nature. This Review describes new tools that aid the construction of genetic circuits. Circuit dynamics can be influenced by the choice of regulators and changed with expression 'tuning knobs'. We collate the failure modes encountered when assembling circuits, quantify their impact on performance and review mitigation efforts. Finally, we discuss the constraints that arise from circuits having to operate within a living cell. Collectively, better tools, well-characterized parts and a comprehensive understanding of how to compose circuits are leading to a breakthrough in the ability to program living cells for advanced applications, from living therapeutics to the atomic manufacturing of functional materials.

Bacteriophage-based synthetic biology for the study of infectious diseases

Since their discovery, bacteriophages have contributed enormously to our understanding of molecular biology as model systems. Furthermore, bacteriophages have provided many tools that have advanced the fields of genetic engineering and synthetic biology. Here, we discuss bacteriophage-based technologies and their application to the study of infectious diseases. New strategies for engineering genomes have the potential to accelerate the design of novel phages as therapies, diagnostics, and tools. Though almost a century has elapsed since their discovery, bacteriophages continue to have a major impact on modern biological sciences, especially with the growth of multidrug-resistant bacteria and interest in the microbiome.

Synthesizing genetic sequential logic circuit with clock pulse generator

Background

Rhythmic clock widely occurs in biological systems which controls several aspects of cell physiology. For the different cell types, it is supplied with various rhythmic frequencies. How to synthesize a specific clock signal is a preliminary but a necessary step to further development of a biological computer in the future.

Results

This paper presents a genetic sequential logic circuit with a clock pulse generator based on a synthesized genetic oscillator, which generates a consecutive clock signal whose frequency is an inverse integer multiple to that of the genetic oscillator. An analogous electronic waveform-shaping circuit is constructed by a series of genetic buffers to shape logic high/low levels of an oscillation input in a basic sinusoidal cycle and generate a pulse-width-modulated (PWM) output with various duty cycles. By controlling the threshold level of the genetic buffer, a genetic clock pulse signal with its frequency consistent to the genetic oscillator is synthesized. A synchronous genetic counter circuit based on the topology of the digital sequential logic circuit is triggered by the clock pulse to synthesize the clock signal with an inverse multiple frequency to the genetic oscillator. The function acts like a frequency divider in electronic circuits which plays a key role in the sequential logic circuit with specific operational frequency.

Conclusions

A cascaded genetic logic circuit generating clock pulse signals is proposed. Based on analogous implement of digital sequential logic circuits, genetic sequential logic circuits can be constructed by the proposed approach to generate various clock signals from an oscillation signal.

Synthetic therapeutic gene circuits in mammalian cells

In the emerging field of synthetic biology, scientists are focusing on designing and creating functional devices, systems, and organisms with novel functions by engineering and assembling standardised biological building blocks. The progress of synthetic biology has significantly advanced the design of functional gene networks that can reprogram metabolic activities in mammalian cells and provide new therapeutic opportunities for future gene- and cell-based therapies. In this review, we describe the most recent advances in synthetic mammalian gene networks designed for biomedical applications, including how these synthetic therapeutic gene circuits can be assembled to control signalling networks and applied to treat metabolic disorders, cancer, and immune diseases. We conclude by discussing the various challenges and future prospects of using synthetic mammalian gene networks for disease therapy.

Building synthetic memory

Cellular memory - conversion of a transient signal into a sustained response - is a common feature of biological systems. Synthetic biologists aim to understand and re-engineer such systems in a reliable and predictable manner. Synthetic memory circuits have been designed and built in vitro and in vivo based on diverse mechanisms, such as oligonucleotide hybridization, recombination, transcription, phosphorylation, and RNA editing. Thus far, building these circuits has helped us explore the basic principles required for stable memory and ask novel biological questions. Here we discuss strategies for building synthetic memory circuits, their use as research tools, and future applications of these devices in medicine and industry.

A versatile cis-acting inverter module for synthetic translational switches

Artificial genetic switches have been designed and tuned individually in living cells. A method to directly invert an existing OFF switch to an ON switch should be highly convenient to construct complex circuits from well-characterized modules, but developing such a technique has remained a challenge. Here we present a cis-acting RNA module to invert the function of a synthetic translational OFF switch to an ON switch in mammalian cells. This inversion maintains the property of the parental switch in response to a particular input signal. In addition, we demonstrate simultaneous and specific expression control of both the OFF and ON switches. The module fits the criteria of universality and expands the versatility of mRNA-based information processing systems developed for artificially controlling mammalian cellular behaviour.

Artificial genetic circuits have been designed to enable precise control of cellular behaviour and phenotypes. Saito and colleagues present a new RNA module that can invert the function of a translational OFF to an ON switch and demonstrate its utility in mammalian cells.

Analog synthetic biology

We analyse the pros and cons of analog versus digital computation in living cells. Our analysis is based on fundamental laws of noise in gene and protein expression, which set limits on the energy, time, space, molecular count and part-count resources needed to compute at a given level of precision. We conclude that analog computation is significantly more efficient in its use of resources than deterministic digital computation even at relatively high levels of precision in the cell. Based on this analysis, we conclude that synthetic biology must use analog, collective analog, probabilistic and hybrid analog-digital computational approaches; otherwise, even relatively simple synthetic computations in cells such as addition will exceed energy and molecular-count budgets. We present schematics for efficiently representing analog DNA-protein computation in cells. Analog electronic flow in subthreshold transistors and analog molecular flux in chemical reactions obey Boltzmann exponential laws of thermodynamics and are described by astoundingly similar logarithmic electrochemical potentials. Therefore, cytomorphic circuits can help to map circuit designs between electronic and biochemical domains. We review recent work that uses positive-feedback linearization circuits to architect wide-dynamic-range logarithmic analog computation in Escherichia coli using three transcription factors, nearly two orders of magnitude more efficient in parts than prior digital implementations.

Realizing the potential of synthetic biology

Synthetic biology, despite still being in its infancy, is increasingly providing valuable information for applications in the clinic, the biotechnology industry and in basic molecular research. Both its unique potential and the challenges it presents have brought together the expertise of an eclectic group of scientists, from cell biologists to engineers. In this Viewpoint article, five experts discuss their views on the future of synthetic biology, on its main achievements in basic and applied science, and on the bioethical issues that are associated with the design of new biological systems.

Biomedically relevant circuit-design strategies in mammalian synthetic biology

The development and progress in synthetic biology has been remarkable. Although still in its infancy, synthetic biology has achieved much during the past decade. Improvements in genetic circuit design have increased the potential for clinical applicability of synthetic biology research. What began as simple transcriptional gene switches has rapidly developed into a variety of complex regulatory circuits based on the transcriptional, translational and post-translational regulation. Instead of compounds with potential pharmacologic side effects, the inducer molecules now used are metabolites of the human body and even members of native cell signaling pathways. In this review, we address recent progress in mammalian synthetic biology circuit design and focus on how novel designs push synthetic biology toward clinical implementation. Groundbreaking research on the implementation of optogenetics and intercellular communications is addressed, as particularly optogenetics provides unprecedented opportunities for clinical application. Along with an increase in synthetic network complexity, multicellular systems are now being used to provide a platform for next-generation circuit design.

How to make a synthetic multicellular computer

Biological systems perform computations at multiple scales and they do so in a robust way. Engineering metaphors have often been used in order to provide a rationale for modeling cellular and molecular computing networks and as the basis for their synthetic design. However, a major constraint in this mapping between electronic and wet computational circuits is the wiring problem. Although wires are identical within electronic devices, they must be different when using synthetic biology designs. Moreover, in most cases the designed molecular systems cannot be reused for other functions. A new approximation allows us to simplify the problem by using synthetic cellular consortia where the output of the computation is distributed over multiple engineered cells. By evolving circuits in silico, we can obtain the minimal sets of Boolean units required to solve the given problem at the lowest cost using cellular consortia. Our analysis reveals that the basic set of logic units is typically non-standard. Among the most common units, the so called inverted IMPLIES (N-Implies) appears to be one of the most important elements along with the NOT and AND functions. Although NOR and NAND gates are widely used in electronics, evolved circuits based on combinations of these gates are rare, thus suggesting that the strategy of combining the same basic logic gates might be inappropriate in order to easily implement synthetic computational constructs. The implications for future synthetic designs, the general view of synthetic biology as a standard engineering domain, as well as potencial drawbacks are outlined.

Creating biological nanomaterials using synthetic biology

Synthetic biology is a new discipline that combines science and engineering approaches to precisely control biological networks. These signaling networks are especially important in fields such as biomedicine and biochemical engineering. Additionally, biological networks can also be critical to the production of naturally occurring biological nanomaterials, and as a result, synthetic biology holds tremendous potential in creating new materials. This review introduces the field of synthetic biology, discusses how biological systems naturally produce materials, and then presents examples and strategies for incorporating synthetic biology approaches in the development of new materials. In particular, strategies for using synthetic biology to produce both organic and inorganic nanomaterials are discussed. Ultimately, synthetic biology holds the potential to dramatically impact biological materials science with significant potential applications in medical systems.

Drug-loaded nanoparticles induce gene expression in human pluripotent stem cell derivatives

Tissue engineering and advanced manufacturing of human stem cells requires a suite of tools to control gene expression spatiotemporally in culture. Inducible gene expression systems offer cell-extrinsic control, typically through addition of small molecules, but small molecule inducers typically contain few functional groups for further chemical modification. Doxycycline (DXC), a potent small molecule inducer of tetracycline (Tet) transgene systems, was conjugated to a hyperbranched dendritic polymer (Boltorn H40) and subsequently reacted with polyethylene glycol (PEG). The resulting PEG-H40-DXC nanoparticle exhibited pH-sensitive drug release behavior and successfully controlled gene expression in stem-cell-derived fibroblasts with a Tet-On system. While free DXC inhibited fibroblast proliferation and matrix metalloproteinase (MMP) activity, PEG-H40-DXC nanoparticles maintained higher fibroblast proliferation levels and MMP activity. The results demonstrate that the PEG-H40-DXC nanoparticle system provides an effective tool to controlling gene expression in human stem cell derivatives.

Engineering protein-responsive mRNA switch in mammalian cells

Engineering of translation provides an alternative regulatory layer for controlling transgene expression in addition to transcriptional regulation. Synthetic mRNA switches that modulate translation of a target gene of interest in response to an intracellular protein could be a key regulator to construct a genetic circuit. Insertion of a protein binding RNA sequence in the 5' UTR of mRNA would allow for the generation of a protein-responsive RNA switch. Here we describe the design principle of the switch and methods for tuning and analyzing its translational activity in mammalian cells.

Innate immunity in disease: insights from mathematical modeling and analysis

The acute inflammatory response is a complex defense mechanism that has evolved to respond rapidly to injury, infection, and other disruptions in homeostasis. This robust responsiveness to biological stress likely endows the host with increased fitness, but over-robust or inadequate inflammation predisposes the host to various diseases. Importantly, well-compartmentalized inflammation is generally beneficial, but spillover of inflammation into the blood is a hallmark-and likely also a driver-of self-maintaining inflammation. The blood is also a key entry point and immunological interface for vectors of parasitic diseases, diseases that themselves incite systemic inflammation. The complex role of inflammation in health and disease has made this biological system difficult to understand comprehensively and modulate rationally for therapeutic purposes. Consequently, systems approaches have been applied in order to characterize dynamical properties and identify key control points in inflammation. This process begins with the collection of high-dimensional, experimental, and clinical data, followed by data reduction and data-driven modeling that finally informs mechanistic computational models for analysis, prediction, and rational modulation. These studies have suggested that the overall architecture of the inflammatory response includes a multiscale positive feedback from inflammation → tissue damage → inflammation, which is often inadequately controlled by negative feedback from anti-inflammatory mediators. Given the importance of the blood interface for the inflammatory response, and the accessibility of this compartment both as an immunological sampling reservoir for vectors as well as for diagnosis and therapy, we suggest that any rational efforts at modulating inflammation via the blood compartment must involve computational modeling.

Engineered cell-based therapies: a vanguard of design-driven medicine

Engineered cell-based therapies are uniquely capable of performing sophisticated therapeutic functions in vivo, and this strategy is yielding promising clinical benefits for treating cancer. In this review, we discuss key opportunities and challenges for engineering customized cellular functions using cell-based therapy for cancer as a representative case study. We examine the historical development of chimeric antigen receptor (CAR) therapies as an illustration of the engineering design cycle. We also consider the potential roles that the complementary disciplines of systems biology and synthetic biology may play in realizing safe and effective treatments for a broad range of patients and diseases. In particular, we discuss how systems biology may facilitate both fundamental research and clinical translation, and we describe how the emerging field of synthetic biology is providing novel modalities for building customized cellular functions to overcome existing clinical barriers. Together, these approaches provide a powerful set of conceptual and experimental tools for transforming information into understanding, and for translating understanding into novel therapeutics to establish a new framework for design-driven medicine.

Regulatory RNAs: charming gene management styles for synthetic biology applications

RNAs have many important functional properties, including that they are independently controllable and highly tunable. As a result of these advantageous properties, their use in a myriad of sophisticated devices has been widely explored. Yet, the exploitation of RNAs for synthetic applications is highly dependent on the ability to characterize the many new molecules that continue to be discovered by large-scale sequencing and high-throughput screening techniques. In this review, we present an exhaustive survey of the most recent synthetic bacterial riboswitches and small RNAs while emphasizing their virtues in gene expression management. We also explore the use of these RNA components as building blocks in the RNA synthetic biology toolbox and discuss examples of synthetic RNA components used to rewire bacterial regulatory circuitry. We anticipate that this field will expand its catalog of smart devices by mimicking and manipulating natural RNA mechanisms and functions.

Multi-input regulation and logic with T7 promoters in cells and cell-free systems

Engineered gene circuits offer an opportunity to harness biological systems for biotechnological and biomedical applications. However, reliance on native host promoters for the construction of circuit elements, such as logic gates, can make the implementation of predictable, independently functioning circuits difficult. In contrast, T7 promoters offer a simple orthogonal expression system for use in a variety of cellular backgrounds and even in cell-free systems. Here we develop a T7 promoter system that can be regulated by two different transcriptional repressors for the construction of a logic gate that functions in cells and in cell-free systems. We first present LacI repressible T7lacO promoters that are regulated from a distal lac operator site for repression. We next explore the positioning of a tet operator site within the T7lacO framework to create T7 promoters that respond to tet and lac repressors and realize an IMPLIES gate. Finally, we demonstrate that these dual input sensitive promoters function in an E. coli cell-free protein expression system. Our results expand the utility of T7 promoters in cell based as well as cell-free synthetic biology applications.