Synthetic biology: an emerging engineering discipline

Synthetic biology outside the cell: linking computational tools to cell-free systems

As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

Automatic validation of computational models using pseudo-3D spatio-temporal model checking

BACKGROUND

Computational models play an increasingly important role in systems biology for generating predictions and in synthetic biology as executable prototypes/designs. For real life (clinical) applications there is a need to scale up and build more complex spatio-temporal multiscale models; these could enable investigating how changes at small scales reflect at large scales and viceversa. Results generated by computational models can be applied to real life applications only if the models have been validated first. Traditional in silico model checking techniques only capture how non-dimensional properties (e.g. concentrations) evolve over time and are suitable for small scale systems (e.g. metabolic pathways). The validation of larger scale systems (e.g. multicellular populations) additionally requires capturing how spatial patterns and their properties change over time, which are not considered by traditional non-spatial approaches.

RESULTS

We developed and implemented a methodology for the automatic validation of computational models with respect to both their spatial and temporal properties. Stochastic biological systems are represented by abstract models which assume a linear structure of time and a pseudo-3D representation of space (2D space plus a density measure). Time series data generated by such models is provided as input to parameterised image processing modules which automatically detect and analyse spatial patterns (e.g. cell) and clusters of such patterns (e.g. cellular population). For capturing how spatial and numeric properties change over time the Probabilistic Bounded Linear Spatial Temporal Logic is introduced. Given a collection of time series data and a formal spatio-temporal specification the model checker Mudi ( http://mudi.modelchecking.org ) determines probabilistically if the formal specification holds for the computational model or not. Mudi is an approximate probabilistic model checking platform which enables users to choose between frequentist and Bayesian, estimate and statistical hypothesis testing based validation approaches. We illustrate the expressivity and efficiency of our approach based on two biological case studies namely phase variation patterning in bacterial colony growth and the chemotactic aggregation of cells.

CONCLUSIONS

The formal methodology implemented in Mudi enables the validation of computational models against spatio-temporal logic properties and is a precursor to the development and validation of more complex multidimensional and multiscale models.

Protease-based synthetic sensing and signal amplification

The bottom-up design of protein-based signaling networks is a key goal of synthetic biology; yet, it remains elusive due to our inability to tailor-make signal transducers and receptors that can be readily compiled into defined signaling networks. Here, we report a generic approach for the construction of protein-based molecular switches based on artficially autoinhibited proteases. Using structure-guided design and directed protein evolution, we created signal transducers based on artificially autoinhibited proteases that can be activated following site-specific proteolysis and also demonstrate the modular design of an allosterically regulated protease receptor following recombination with an affinity clamp peptide receptor. Notably, the receptor's mode of action can be varied from >5-fold switch-OFF to >30-fold switch-ON solely by changing the length of the connecting linkers, demonstrating a high functional plasticity not previously observed in naturally occurring receptor systems. We also create an integrated signaling circuit based on two orthogonal autoinhibited protease units that can propagate and amplify molecular queues generated by the protease receptor. Finally, we present a generic two-component receptor architecture based on proximity-based activation of two autoinhibited proteases. Overall, the approach allows the design of protease-based signaling networks that, in principle, can be connected to any biological process.

Synthetic biology looks good on paper

Tremendous progress has been made in the design and implementation of synthetic gene circuits, but real-world applications of such circuits have been limited. Cell-free circuits embedded on paper developed by Pardee et al. promise to deliver specific and rapid diagnostics on a low-cost, highly scalable platform.

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.

Artificially constructed quorum-sensing circuits are used for subtle control of bacterial population density

Vibrio fischeri is a typical quorum-sensing bacterium for which lux box, luxR, and luxI have been identified as the key elements involved in quorum sensing. To decode the quorum-sensing mechanism, an artificially constructed cell–cell communication system has been built. In brief, the system expresses several programmed cell-death BioBricks and quorum-sensing genes driven by the promoters lux pR and P_lacO-1 in Escherichia coli cells. Their transformation and expression was confirmed by gel electrophoresis and sequencing. To evaluate its performance, viable cell numbers at various time periods were investigated. Our results showed that bacteria expressing killer proteins corresponding to ribosome binding site efficiency of 0.07, 0.3, 0.6, or 1.0 successfully sensed each other in a population-dependent manner and communicated with each other to subtly control their population density. This was also validated using a proposed simple mathematical model.

Total synthesis of a eukaryotic chromosome: Redesigning and SCRaMbLE-ing yeast

A team of US researchers recently reported the design, assembly and in vivo functionality of a synthetic chromosome III (SynIII) for the yeast Saccharomyces cerevisiae. The synthetic chromosome was assembled bottom-up from DNA oligomers by teams of students working over several years with researchers as the first part of an international synthetic yeast genome project. Embedded into the sequence of the synthetic chromosome are multiple design changes that include a novel in-built recombination scheme that can be induced to catalyse intra-chromosomal rearrangements in a variety of different conditions. This system, along with the other synthetic sequence changes, is intended to aid researchers develop a deeper understanding of how genomes function and find new ways to exploit yeast in future biotechnologies. The landmark of the first synthesised designer eukaryote chromosome, and the power of its massively parallel recombination system, provide new perspectives on the future of synthetic biology and genome research.

Improving fatty acids production by engineering dynamic pathway regulation and metabolic control

Global energy demand and environmental concerns have stimulated increasing efforts to produce carbon-neutral fuels directly from renewable resources. Microbially derived aliphatic hydrocarbons, the petroleum-replica fuels, have emerged as promising alternatives to meet this goal. However, engineering metabolic pathways with high productivity and yield requires dynamic redistribution of cellular resources and optimal control of pathway expression. Here we report a genetically encoded metabolic switch that enables dynamic regulation of fatty acids (FA) biosynthesis in Escherichia coli. The engineered strains were able to dynamically compensate the critical enzymes involved in the supply and consumption of malonyl-CoA and efficiently redirect carbon flux toward FA biosynthesis. Implementation of this metabolic control resulted in an oscillatory malonyl-CoA pattern and a balanced metabolism between cell growth and product formation, yielding 15.7- and 2.1-fold improvement in FA titer compared with the wild-type strain and the strain carrying the uncontrolled metabolic pathway. This study provides a new paradigm in metabolic engineering to control and optimize metabolic pathways facilitating the high-yield production of other malonyl-CoA-derived compounds.

Synthetic biology as it relates to CAM photosynthesis: challenges and opportunities

To meet future food and energy security needs, which are amplified by increasing population growth and reduced natural resource availability, metabolic engineering efforts have moved from manipulating single genes/proteins to introducing multiple genes and novel pathways to improve photosynthetic efficiency in a more comprehensive manner. Biochemical carbon-concentrating mechanisms such as crassulacean acid metabolism (CAM), which improves photosynthetic, water-use, and possibly nutrient-use efficiency, represent a strategic target for synthetic biology to engineer more productive C3 crops for a warmer and drier world. One key challenge for introducing multigene traits like CAM onto a background of C3 photosynthesis is to gain a better understanding of the dynamic spatial and temporal regulatory events that underpin photosynthetic metabolism. With the aid of systems and computational biology, vast amounts of experimental data encompassing transcriptomics, proteomics, and metabolomics can be related in a network to create dynamic models. Such models can undergo simulations to discover key regulatory elements in metabolism and suggest strategic substitution or augmentation by synthetic components to improve photosynthetic performance and water-use efficiency in C3 crops. Another key challenge in the application of synthetic biology to photosynthesis research is to develop efficient systems for multigene assembly and stacking. Here, we review recent progress in computational modelling as applied to plant photosynthesis, with attention to the requirements for CAM, and recent advances in synthetic biology tool development. Lastly, we discuss possible options for multigene pathway construction in plants with an emphasis on CAM-into-C3 engineering.

Molecular eyes: proteins that transform light into biological information

Most biological photoreceptors are protein/cofactor complexes that induce a physiological reaction upon absorption of a photon. Therefore, these proteins represent signal converters that translate light into biological information. Researchers use this property to stimulate and study various biochemical processes conveniently and non-invasively by the application of light, an approach known as optogenetics. Here, we summarize the recent experimental progress on the family of blue light receptors using FAD (BLUF) receptors. Several BLUF photoreceptors modulate second messenger levels and thus represent highly interesting tools for optogenetic application. In order to activate a coupled effector protein, the flavin-binding pocket of the BLUF domain undergoes a subtle rearrangement of the hydrogen network upon blue light absorption. The hydrogen bond switch is facilitated by the ultrafast light-induced proton-coupled electron transfer (PCET) between a tyrosine and the flavin in less than a nanosecond and remains stable on a long enough timescale for biochemical reactions to take place. The cyclic nature of the photoinduced reaction makes BLUF domains powerful model systems to study protein/cofactor interaction, protein-modulated PCET and novel mechanisms of biological signalling. The ultrafast nature of the photoconversion as well as the subtle structural rearrangement requires sophisticated spectroscopic and molecular biological methods to study and understand this highly intriguing signalling process.

Gene circuit performance characterization and resource usage in a cell-free "breadboard"

The many successes of synthetic biology have come in a manner largely different from those in other engineering disciplines; in particular, without well-characterized and simplified prototyping environments to play a role analogous to wind-tunnels in aerodynamics and breadboards in electrical engineering. However, as the complexity of synthetic circuits increases, the benefits--in cost savings and design cycle time--of a more traditional engineering approach can be significant. We have recently developed an in vitro "breadboard" prototyping platform based on E. coli cell extract that allows biocircuits to operate in an environment considerably simpler than, but functionally similar to, in vivo. The simplicity of this system makes it a promising tool for rapid biocircuit design and testing, as well as for probing fundamental aspects of gene circuit operation normally masked by cellular complexity. In this work, we characterize the cell-free breadboard using real-time and simultaneous measurements of transcriptional and translational activities of a small set of reporter genes and a transcriptional activation cascade. We determine the effects of promoter strength, gene concentration, and nucleoside triphosphate concentration on biocircuit properties, and we isolate the specific contributions of essential biomolecular resources-core RNA polymerase and ribosomes-to overall performance. Importantly, we show how limits on resources, particularly those involved in translation, are manifested as reduced expression in the presence of orthogonal genes that serve as additional loads on the system.

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.

Multiplexed and programmable regulation of gene networks with an integrated RNA and CRISPR/Cas toolkit in human cells

RNA-based regulation and CRISPR/Cas transcription factors (CRISPR-TFs) have the potential to be integrated for the tunable modulation of gene networks. A major limitation of this methodology is that guide RNAs (gRNAs) for CRISPR-TFs can only be expressed from RNA polymerase III promoters in human cells, limiting their use for conditional gene regulation. We present new strategies that enable expression of functional gRNAs from RNA polymerase II promoters and multiplexed production of proteins and gRNAs from a single transcript in human cells. We use multiple RNA regulatory strategies, including RNA-triple-helix structures, introns, microRNAs, and ribozymes, with Cas9-based CRISPR-TFs and Cas6/Csy4-based RNA processing. Using these tools, we efficiently modulate endogenous promoters and implement tunable synthetic circuits, including multistage cascades and RNA-dependent networks that can be rewired with Csy4 to achieve complex behaviors. This toolkit can be used for programming scalable gene circuits and perturbing endogenous networks for biology, therapeutic, and synthetic biology applications.

Enhancing the specificity of recombinase-mediated genome engineering through dimer interface redesign

Despite recent advances in genome engineering made possible by the emergence of site-specific endonucleases, there remains a need for tools capable of specifically delivering genetic payloads into the human genome. Hybrid recombinases based on activated catalytic domains derived from the resolvase/invertase family of serine recombinases fused to Cys₂-His₂ zinc-finger or TAL effector DNA-binding domains are a class of reagents capable of achieving this. The utility of these enzymes, however, has been constrained by their low overall targeting specificity, largely due to the formation of side-product homodimers capable of inducing off-target modifications. Here, we combine rational design and directed evolution to re-engineer the serine recombinase dimerization interface and generate a recombinase architecture that reduces formation of these undesirable homodimers by >500-fold. We show that these enhanced recombinases demonstrate substantially improved targeting specificity in mammalian cells and achieve rates of site-specific integration similar to those previously reported for site-specific nucleases. Additionally, we show that enhanced recombinases exhibit low toxicity and promote the delivery of the human coagulation factor IX and α-galactosidase genes into endogenous genomic loci with high specificity. These results provide a general means for improving hybrid recombinase specificity by protein engineering and illustrate the potential of these enzymes for basic research and therapeutic applications.

Engineering reduced evolutionary potential for synthetic biology

The field of synthetic biology seeks to engineer reliable and predictable behaviors in organisms from collections of standardized genetic parts. However, unlike other types of machines, genetically encoded biological systems are prone to changes in their designed sequences due to mutations in their DNA sequences after these devices are constructed and deployed. Thus, biological engineering efforts can be confounded by undesired evolution that rapidly breaks the functions of parts and systems, particularly when they are costly to the host cell to maintain. Here, we explain the fundamental properties that determine the evolvability of biological systems. Then, we use this framework to review current efforts to engineer the DNA sequences that encode synthetic biology devices and the genomes of their microbial hosts to reduce their ability to evolve and therefore increase their genetic reliability so that they maintain their intended functions over longer timescales.

Characterization of a SAM-dependent fluorinase from a latent biosynthetic pathway for fluoroacetate and 4-fluorothreonine formation in Nocardia brasiliensis

Fluorination has been widely used in chemical synthesis, but is rare in nature. The only known biological fluorination scope is represented by the fl pathway from Streptomyces cattleya that produces fluoroacetate (FAc) and 4-fluorothreonine (4-FT). Here we report the identification of a novel pathway for FAc and 4-FT biosynthesis from the actinomycetoma-causing pathogen Nocardia brasiliensis ATCC 700358. The new pathway shares overall conservation with the fl pathway in S. cattleya. Biochemical characterization of the conserved domains revealed a novel fluorinase NobA that can biosynthesize 5’-fluoro-5’-deoxyadenosine (5’-FDA) from inorganic fluoride and S-adenosyl-l-methionine (SAM). The NobA shows similar halide specificity and characteristics to the fluorination enzyme FlA of the fl pathway. Kinetic parameters for fluoride ( K _m 4153 μM, k _cat 0.073 min ^-1) and SAM ( K _m 416 μM, k _cat 0.139 min ^-1) have been determined, revealing that NobA is slightly (2.3 fold) slower than FlA. Upon sequence comparison, we finally identified a distinct loop region in the fluorinases that probably accounts for the disparity of fluorination activity.

Translational cross talk in gene networks

It has been shown experimentally that competition for limited translational resources by upstream mRNAs can lead to an anticorrelation between protein counts. Here, we investigate a stochastic model for this phenomenon, in which gene transcripts of different types compete for a finite pool of ribosomes. Throughout, we utilize concepts from the theory of multiclass queues to describe a qualitative shift in protein count statistics as the system transitions from being underloaded (ribosomes exceed transcripts in number) to being overloaded (transcripts exceed ribosomes in number). The exact analytical solution of a simplified stochastic model, in which the numbers of competing mRNAs and ribosomes are fixed, exhibits weak positive correlations between steady-state protein counts when total transcript count slightly exceeds ribosome count, whereas the solution can exhibit strong negative correlations when total transcript count significantly exceeds ribosome count. Extending this analysis, we find approximate but reasonably accurate solutions for a more realistic model, in which abundances of mRNAs and ribosomes are allowed to fluctuate randomly. Here, ribosomal fluctuations contribute positively and mRNA fluctuations contribute negatively to correlations, and when mRNA fluctuations dominate ribosomal fluctuations, a strong anticorrelation extremum reliably occurs near the transition from the underloaded to the overloaded regime.

Synthetic circuit of inositol phosphorylceramide synthase in Leishmania : a chemical biology approach

Building circuits and studying their behavior in cells is a major goal of systems and synthetic biology. Synthetic biology enables the precise control of cellular states for systems studies, the discovery of novel parts, control strategies, and interactions for the design of robust synthetic systems. To the best of our knowledge, there are no literature reports for the synthetic circuit construction for protozoan parasites. This paper describes the construction of genetic circuit for the targeted enzyme inositol phosphorylceramide synthase belonging to the protozoan parasite Leishmania. To explore the dynamic nature of the circuit designed, simulation was done followed by circuit validation by qualitative and quantitative approaches. The genetic circuit designed for inositol phosphorylceramide synthase (Biomodels Database-MODEL1208030000) shows responsiveness, oscillatory and bistable behavior, together with intrinsic robustness.

Nanotechnology: emerging tools for biology and medicine

Nanotechnology encompasses structures comparable in size with biomolecules and enables new ways to measure and detect biology, perturb cells, and treat patients. Here, Wong et al. review nanotechnology-based approaches for precisely measuring and perturbing living systems that may yield unexpected insights into systems biology as well as new therapeutic strategies for personalized medicine.

Historically, biomedical research has been based on two paradigms. First, measurements of biological behaviors have been based on bulk assays that average over large populations. Second, these behaviors have then been crudely perturbed by systemic administration of therapeutic treatments. Nanotechnology has the potential to transform these paradigms by enabling exquisite structures comparable in size with biomolecules as well as unprecedented chemical and physical functionality at small length scales. Here, we review nanotechnology-based approaches for precisely measuring and perturbing living systems. Remarkably, nanotechnology can be used to characterize single molecules or cells at extraordinarily high throughput and deliver therapeutic payloads to specific locations as well as exhibit dynamic biomimetic behavior. These advances enable multimodal interfaces that may yield unexpected insights into systems biology as well as new therapeutic strategies for personalized medicine.

What Symbionts Teach us about Modularity

The main goal of Synthetic Biology (SB) is to apply engineering principles to biotechnology in order to make life easier to engineer. These engineering principles include modularity: decoupling of complex systems into smaller, orthogonal sub-systems that can be used in a range of different applications. The successful use of modules in engineering is expected to be reproduced in synthetic biological systems. But the difficulties experienced up to date with SB approaches question the short-term feasibility of designing life. Considering the “engineerable” nature of life, here we discuss the existence of modularity in natural living systems, particularly in symbiotic interactions, and compare the behavior of such systems, with those of engineered modules. We conclude that not only is modularity present but it is also common among living structures, and that symbioses are a new example of module-like sub-systems having high similarity with modularly designed ones. However, we also detect and stress fundamental differences between man-made and biological modules. Both similarities and differences should be taken into account in order to adapt SB design to biological laws.

Tunable and multifunctional eukaryotic transcription factors based on CRISPR/Cas

Transcriptional regulation is central to the complex behavior of natural biological systems and synthetic gene circuits. Platforms for the scalable, tunable, and simple modulation of transcription would enable new abilities to study natural systems and implement artificial capabilities in living cells. Previous approaches to synthetic transcriptional regulation have relied on engineering DNA-binding proteins, which necessitate multistep processes for construction and optimization of function. Here, we show that the CRISPR/Cas system of Streptococcus pyogenes can be programmed to direct both activation and repression to natural and artificial eukaryotic promoters through the simple engineering of guide RNAs with base-pairing complementarity to target DNA sites. We demonstrate that the activity of CRISPR-based transcription factors (crisprTFs) can be tuned by directing multiple crisprTFs to different positions in natural promoters and by arraying multiple crisprTF-binding sites in the context of synthetic promoters in yeast and human cells. Furthermore, externally controllable regulatory modules can be engineered by layering gRNAs with small molecule-responsive proteins. Additionally, single nucleotide substitutions within promoters are sufficient to render them orthogonal with respect to the same gRNA-guided crisprTF. We envision that CRISPR-based eukaryotic gene regulation will enable the facile construction of scalable synthetic gene circuits and open up new approaches for mapping natural gene networks and their effects on complex cellular phenotypes.

The centrality of RNA for engineering gene expression

Synthetic biology holds promise as both a framework for rationally engineering biological systems and a way to revolutionize how we fundamentally understand them. Essential to realizing this promise is the development of strategies and tools to reliably and predictably control and characterize sophisticated patterns of gene expression. Here we review the role that RNA can play towards this goal and make a case for why this versatile, designable, and increasingly characterizable molecule is one of the most powerful substrates for engineering gene expression at our disposal. We discuss current natural and synthetic RNA regulators of gene expression acting at key points of control – transcription, mRNA degradation, and translation. We also consider RNA structural probing and computational RNA structure predication tools as a way to study RNA structure and ultimately function. Finally, we discuss how next-generation sequencing methods are being applied to the study of RNA and to the characterization of RNA's many properties throughout the cell.

Expanding the scope of site-specific recombinases for genetic and metabolic engineering

Site-specific recombinases are tremendously valuable tools for basic research and genetic engineering. By promoting high-fidelity DNA modifications, site-specific recombination systems have empowered researchers with unprecedented control over diverse biological functions, enabling countless insights into cellular structure and function. The rigid target specificities of many sites-specific recombinases, however, have limited their adoption in fields that require highly flexible recognition abilities. As a result, intense effort has been directed toward altering the properties of site-specific recombination systems by protein engineering. Here, we review key developments in the rational design and directed molecular evolution of site-specific recombinases, highlighting the numerous applications of these enzymes across diverse fields of study.

Enhanced expression of codon optimized interferon gamma in CHO cells

The human interferon-gamma (IFN-γ) is a potential drug candidate for treating various diseases due to its immunomodulatory properties. The efficient production of this protein can be achieved through a popular industrial host, Chinese hamster ovary (CHO) cells. However, recombinant expression of foreign proteins is typically suboptimal possibly due to the usage of non-native codon patterns within the coding sequence. Therefore, we demonstrated the application of a recently developed codon optimization approach to design synthetic IFN-γ coding sequences for enhanced heterologous expression in CHO cells. For codon optimization, earlier studies suggested to establish the target usage distribution pattern in terms of selected design parameters such as individual codon usage (ICU) and codon context (CC), mainly based on the host's highly expressed genes. However, our RNA-Seq based transcriptome profiling indicated that the ICU and CC distribution patterns of different gene expression classes in CHO cell are relatively similar, unlike other microbial expression hosts, Escherichia coli and Saccharomyces cerevisiae. This finding was further corroborated through the in vivo expression of various ICU and CC optimized IFN-γ in CHO cells. Interestingly, the CC-optimized genes exhibited at least 13-fold increase in expression level compared to the wild-type IFN-γ while a maximum of 10-fold increase was observed for the ICU-optimized genes. Although design criteria based on individual codons, such as ICU, have been widely used for gene optimization, our experimental results suggested that codon context is relatively more effective parameter for improving recombinant IFN-γ expression in CHO cells.

Synthetic biology of antimicrobial discovery

Antibiotic discovery has a storied history. From the discovery of penicillin by Sir Alexander Fleming to the relentless quest for antibiotics by Selman Waksman, the stories have become like folklore used to inspire future generations of scientists. However, recent discovery pipelines have run dry at a time when multidrug-resistant pathogens are on the rise. Nature has proven to be a valuable reservoir of antimicrobial agents, which are primarily produced by modularized biochemical pathways. Such modularization is well suited to remodeling by an interdisciplinary approach that spans science and engineering. Herein, we discuss the biological engineering of small molecules, peptides, and non-traditional antimicrobials and provide an overview of the growing applicability of synthetic biology to antimicrobials discovery.

Towards a whole-cell modeling approach for synthetic biology

Despite rapid advances over the last decade, synthetic biology lacks the predictive tools needed to enable rational design. Unlike established engineering disciplines, the engineering of synthetic gene circuits still relies heavily on experimental trial-and-error, a time-consuming and inefficient process that slows down the biological design cycle. This reliance on experimental tuning is because current modeling approaches are unable to make reliable predictions about the in vivo behavior of synthetic circuits. A major reason for this lack of predictability is that current models view circuits in isolation, ignoring the vast number of complex cellular processes that impinge on the dynamics of the synthetic circuit and vice versa. To address this problem, we present a modeling approach for the design of synthetic circuits in the context of cellular networks. Using the recently published whole-cell model of Mycoplasma genitalium, we examined the effect of adding genes into the host genome. We also investigated how codon usage correlates with gene expression and find agreement with existing experimental results. Finally, we successfully implemented a synthetic Goodwin oscillator in the whole-cell model. We provide an updated software framework for the whole-cell model that lays the foundation for the integration of whole-cell models with synthetic gene circuit models. This software framework is made freely available to the community to enable future extensions. We envision that this approach will be critical to transforming the field of synthetic biology into a rational and predictive engineering discipline.

Introduction to focus issue: quantitative approaches to genetic networks

All cells of living organisms contain similar genetic instructions encoded in the organism's DNA. In any particular cell, the control of the expression of each different gene is regulated, in part, by binding of molecular complexes to specific regions of the DNA. The molecular complexes are composed of protein molecules, called transcription factors, combined with various other molecules such as hormones and drugs. Since transcription factors are coded by genes, cellular function is partially determined by genetic networks. Recent research is making large strides to understand both the structure and the function of these networks. Further, the emerging discipline of synthetic biology is engineering novel gene circuits with specific dynamic properties to advance both basic science and potential practical applications. Although there is not yet a universally accepted mathematical framework for studying the properties of genetic networks, the strong analogies between the activation and inhibition of gene expression and electric circuits suggest frameworks based on logical switching circuits. This focus issue provides a selection of papers reflecting current research directions in the quantitative analysis of genetic networks. The work extends from molecular models for the binding of proteins, to realistic detailed models of cellular metabolism. Between these extremes are simplified models in which genetic dynamics are modeled using classical methods of systems engineering, Boolean switching networks, differential equations that are continuous analogues of Boolean switching networks, and differential equations in which control is based on power law functions. The mathematical techniques are applied to study: (i) naturally occurring gene networks in living organisms including: cyanobacteria, Mycoplasma genitalium, fruit flies, immune cells in mammals; (ii) synthetic gene circuits in Escherichia coli and yeast; and (iii) electronic circuits modeling genetic networks using field-programmable gate arrays. Mathematical analyses will be essential for understanding naturally occurring genetic networks in diverse organisms and for providing a foundation for the improved development of synthetic genetic networks.

Emerging tools for synthetic genome design

Synthetic biology is an emerging discipline for designing and synthesizing predictable, measurable, controllable, and transformable biological systems. These newly designed biological systems have great potential for the development of cheaper drugs, green fuels, biodegradable plastics, and targeted cancer therapies over the coming years. Fortunately, our ability to quickly and accurately engineer biological systems that behave predictably has been dramatically expanded by significant advances in DNA-sequencing, DNA-synthesis, and DNA-editing technologies. Here, we review emerging technologies and methodologies in the field of building designed biological systems, and we discuss their future perspectives.

Synthetic biology: lessons from engineering yeast MAPK signalling pathways

All living cells respond to external stimuli and execute specific physiological responses through signal transduction pathways. Understanding the mechanisms controlling signalling pathways is important for diagnosing and treating diseases and for reprogramming cells with desired functions. Although many of the signalling components in the budding yeast Saccharomyces cerevisiae have been identified by genetic studies, many features concerning the dynamic control of pathway activity, cross-talk, cell-to-cell variability or robustness against perturbation are still incompletely understood. Comparing the behaviour of engineered and natural signalling pathways offers insight complementary to that achievable with standard genetic and molecular studies. Here, we review studies that aim at a deeper understanding of signalling design principles and generation of novel signalling properties by engineering the yeast mitogen-activated protein kinase (MAPK) pathways. The underlying approaches can be applied to other organisms including mammalian cells and offer opportunities for building synthetic pathways and functionalities useful in medicine and biotechnology.

Synthetic biology: advancing the design of diverse genetic systems

A major objective of synthetic biology is to make the process of designing genetically encoded biological systems more systematic, predictable, robust, scalable, and efficient. Examples of genetic systems in the field vary widely in terms of operating hosts, compositional approaches, and network complexity, ranging from simple genetic switches to search-and-destroy systems. While significant advances in DNA synthesis capabilities support the construction of pathway- and genome-scale programs, several design challenges currently restrict the scale of systems that can be reasonably designed and implemented. Thus, while synthetic biology offers much promise in developing systems to address challenges faced in the fields of manufacturing, environment and sustainability, and health and medicine, the realization of this potential is currently limited by the diversity of available parts and effective design frameworks. As researchers make progress in bridging this design gap, advances in the field hint at ever more diverse applications for biological systems.

Synthetic circuits integrating logic and memory in living cells

Logic and memory are essential functions of circuits that generate complex, state-dependent responses. Here we describe a strategy for efficiently assembling synthetic genetic circuits that use recombinases to implement Boolean logic functions with stable DNA-encoded memory of events. Application of this strategy allowed us to create all 16 two-input Boolean logic functions in living Escherichia coli cells without requiring cascades comprising multiple logic gates. We demonstrate long-term maintenance of memory for at least 90 cell generations and the ability to interrogate the states of these synthetic devices with fluorescent reporters and PCR. Using this approach we created two-bit digital-to-analog converters, which should be useful in biotechnology applications for encoding multiple stable gene expression outputs using transient inputs of inducers. We envision that this integrated logic and memory system will enable the implementation of complex cellular state machines, behaviors and pathways for therapeutic, diagnostic and basic science applications.

Engineered cell-cell communication and its applications

Over the past several decades, biologists have become more appreciative of the fundamental role of intercellular communication in natural systems spanning prokaryotic biofilms to eukaryotic developmental systems and neurological networks. From an engineering perspective, the use of cell-cell communication provides an opportunity to engineer more complex and robust functions using cellular components. Indeed, this strategy has been adopted in synthetic biology in the creation of diverse gene circuits that program spatiotemporal dynamics in one or multiple populations. Gene circuits such as these may offer insights regarding basic biological questions and motifs or serve as a basis for novel applications.

Assembly of multi-gene pathways and combinatorial pathway libraries through ePathBrick vectors

As an emerging discipline, synthetic biology is becoming increasingly important to design, construct, and optimize metabolic pathways leading to desired phenotypes such as overproduction of biofuels and pharmaceuticals in genetically tractable organisms. We have recently developed a versatile gene assembly platform ePathBricks supporting the modular assembly of multi-gene pathway components and combinatorial generation of pathway diversities. In this protocol, we will detail the process to assemble a seven gene flavonoid pathway (~9 kb) on one single ePathBrick vector. We will also demonstrate that a three-gene flavonoid pathway can be easily diversified to 54 pathway equivalents differing in pathway configuration and gene order; coupled with high-throughput screening techniques, we envision that this combinatorial strategy would greatly improve our ability to exploit the full potential of microbial cell factories for recombinant metabolite production.

Cultural evolutionary tipping points in the storage and transmission of information

Human culture has evolved through a series of major tipping points in information storage and communication. The first was the appearance of language, which enabled communication between brains and allowed humans to specialize in what they do and to participate in complex mating games. The second was information storage outside the brain, most obviously expressed in the "Upper Paleolithic Revolution" - the sudden proliferation of cave art, personal adornment, and ritual in Europe some 35,000-45,000 years ago. More recently, this storage has taken the form of writing, mass media, and now the Internet, which is arguably overwhelming humans' ability to discern relevant information. The third tipping point was the appearance of technology capable of accumulating and manipulating vast amounts of information outside humans, thus removing them as bottlenecks to a seemingly self-perpetuating process of knowledge explosion. Important components of any discussion of cultural evolutionary tipping points are tempo and mode, given that the rate of change, as well as the kind of change, in information storage and transmission has not been constant over the previous million years.

Maintaining system homeostasis: the third law of Newtonian immunology

Because of the potent effector mechanisms of the immune system, the potential for self-destructive immune responses is especially high and many negative regulatory modalities exist to prevent excessive tissue damage. This Commentary places such regulatory mechanisms in the larger context of system organization on many scales. The sometimes counterintuitive nature of feedback control is discussed and a case is made for greater attention to quantitative spatiotemporal aspects of regulation, rather than limiting the discussion to the qualitative descriptions of pathways that dominate at present.

Engineering plant metabolism into microbes: from systems biology to synthetic biology

Plant metabolism represents an enormous repository of compounds that are of pharmaceutical and biotechnological importance. Engineering plant metabolism into microbes will provide sustainable solutions to produce pharmaceutical and fuel molecules that could one day replace substantial portions of the current fossil-fuel based economy. Metabolic engineering entails targeted manipulation of biosynthetic pathways to maximize yields of desired products. Recent advances in Systems Biology and the emergence of Synthetic Biology have accelerated our ability to design, construct and optimize cell factories for metabolic engineering applications. Progress in predicting and modeling genome-scale metabolic networks, versatile gene assembly platforms and delicate synthetic pathway optimization strategies has provided us exciting opportunities to exploit the full potential of cell metabolism. In this review, we will discuss how systems and synthetic biology tools can be integrated to create tailor-made cell factories for efficient production of natural products and fuel molecules in microorganisms.