SYNTHETIC BIOLOGY. Emergent genetic oscillations in a synthetic microbial consortium

Synthetic Biology Tools to Engineer Microbial Communities for Biotechnology

Microbial consortia have been used in biotechnology processes, including fermentation, waste treatment, and agriculture, for millennia. Today, synthetic biologists are increasingly engineering microbial consortia for diverse applications, including the bioproduction of medicines, biofuels, and biomaterials from inexpensive carbon sources. An improved understanding of natural microbial ecosystems, and the development of new tools to construct synthetic consortia and program their behaviors, will vastly expand the functions that can be performed by communities of interacting microorganisms. Here, we review recent advancements in synthetic biology tools and approaches to engineer synthetic microbial consortia, discuss ongoing and emerging efforts to apply consortia for various biotechnological applications, and suggest future applications.

The art of vector engineering: towards the construction of next-generation genetic tools

When recombinant DNA technology was developed more than 40 years ago, no one could have imagined the impact it would have on both society and the scientific community. In the field of genetic engineering, the most important tool developed was the plasmid vector. This technology has been continuously expanding and undergoing adaptations. Here, we provide a detailed view following the evolution of vectors built throughout the years destined to study microorganisms and their peculiarities, including those whose genomes can only be revealed through metagenomics. We remark how synthetic biology became a turning point in designing these genetic tools to create meaningful innovations. We have placed special focus on the tools for engineering bacteria and fungi (both yeast and filamentous fungi) and those available to construct metagenomic libraries. Based on this overview, future goals would include the development of modular vectors bearing standardized parts and orthogonally designed circuits, a task not fully addressed thus far. Finally, we present some challenges that should be overcome to enable the next generation of vector design and ways to address it.

Role of quorum sensing and chemical communication in fungal biotechnology and pathogenesis

Microbial cells do not live in isolation in their environment, but rather they communicate with each other using chemical signals. This sophisticated mode of cell-to-cell signalling, known as quorum sensing, was first discovered in bacteria, and coordinates the behaviour of microbial population behaviour in a cell-density-dependent manner. More recently, these mechanisms have been described in eukaryotes, particularly in fungi, where they regulate processes such as pathogenesis, morphological differentiation, secondary metabolite production and biofilm formation. In this manuscript, we review the information available to date on these processes in yeast, dimorphic fungi and filamentous fungi. We analyse the diverse chemical 'languages' used by different groups of fungi, their possible cross-talk and interkingdom interactions with other organisms. We discuss the existence of these mechanisms in multicellular organisms, the ecophysiological role of QS in fungal colonisation and the potential applications of these mechanisms in biotechnology and pathogenesis.

Simple organizing principles in microbial communities

There is a great deal of interest in discovering the principles that organize microbial communities, to better understand the structure and diversity of these communities in the natural world. Recent conceptual and technical advances have shown how simple organizing principles can give rise to surprising diversity and complex patterns in these consortia. Understanding competition, cooperation, and communication among microbes has provided novel insights into the structure and behavior of microbial collectives, and the use of simple animal models has advanced our understanding of microbial ecology in the host. These multidisciplinary efforts to understand and predict the properties of microbial communities will be critical in the development of microbial ecology as an applied science.

A scalable peptide-GPCR language for engineering multicellular communication

Engineering multicellularity is one of the next breakthroughs for Synthetic Biology. A key bottleneck to building multicellular systems is the lack of a scalable signaling language with a large number of interfaces that can be used simultaneously. Here, we present a modular, scalable, intercellular signaling language in yeast based on fungal mating peptide/G-protein-coupled receptor (GPCR) pairs harnessed from nature. First, through genome-mining, we assemble 32 functional peptide-GPCR signaling interfaces with a range of dose-response characteristics. Next, we demonstrate that these interfaces can be combined into two-cell communication links, which serve as assembly units for higher-order communication topologies. Finally, we show 56 functional, two-cell links, which we use to assemble three- to six-member communication topologies and a three-member interdependent community. Importantly, our peptide-GPCR language is scalable and tunable by genetic encoding, requires minimal component engineering, and should be massively scalable by further application of our genome mining pipeline or directed evolution.

Waveforms of molecular oscillations reveal circadian timekeeping mechanisms

Circadian clocks play a pivotal role in orchestrating numerous physiological and developmental events. Waveform shapes of the oscillations of protein abundances can be informative about the underlying biochemical processes of circadian clocks. We derive a mathematical framework where waveforms do reveal hidden biochemical mechanisms of circadian timekeeping. We find that the cost of synthesizing proteins with particular waveforms can be substantially reduced by rhythmic protein half-lives over time, as supported by previous plant and mammalian data, as well as our own seedling experiment. We also find that previously enigmatic, cyclic expression of positive arm components within the mammalian and insect clocks allows both a broad range of peak time differences between protein waveforms and the symmetries of the waveforms about the peak times. Such various peak-time differences may facilitate tissue-specific or developmental stage-specific multicellular processes. Our waveform-guided approach can be extended to various biological oscillators, including cell-cycle and synthetic genetic oscillators.

Hang-Hyun Jo et al. derive a mathematical framework for analyzing circadian clock waveforms. Using data from plants and animals, they find that waveforms of clock protein profiles provide important information about the biochemical mechanisms of circadian timekeeping.

Protein sequestration versus Hill-type repression in circadian clock models

Circadian (∼24 h) clocks are self-sustained endogenous oscillators with which organisms keep track of daily and seasonal time. Circadian clocks frequently rely on interlocked transcriptional-translational feedback loops to generate rhythms that are robust against intrinsic and extrinsic perturbations. To investigate the dynamics and mechanisms of the intracellular feedback loops in circadian clocks, a number of mathematical models have been developed. The majority of the models use Hill functions to describe transcriptional repression in a way that is similar to the Goodwin model. Recently, a new class of models with protein sequestration-based repression has been introduced. Here, the author discusses how this new class of models differs dramatically from those based on Hill-type repression in several fundamental aspects: conditions for rhythm generation, robust network designs and the periods of coupled oscillators. Consistently, these fundamental properties of circadian clocks also differ among Neurospora, Drosophila, and mammals depending on their key transcriptional repression mechanisms (Hill-type repression or protein sequestration). Based on both theoretical and experimental studies, this review highlights the importance of careful modelling of transcriptional repression mechanisms in molecular circadian clocks.

A Synthetic Microbial Operational Amplifier

Synthetic biology has created oscillators, latches, logic gates, logarithmically linear circuits, and load drivers that have electronic analogs in living cells. The ubiquitous operational amplifier, which allows circuits to operate robustly and precisely has not been built with biomolecular parts. As in electronics, a biological operational-amplifier could greatly improve the predictability of circuits despite noise and variability, a problem that all cellular circuits face. Here, we show how to create a synthetic three-stage inducer-input operational amplifier with a fast CRISPR-based differential-input push-pull stage, a slow transcription-and-translation amplification stage, and a fast-enzymatic output stage. Our "Bio-OpAmp" uses only 5 proteins including dCas9. It expands the toolkit of fundamental analog circuits in synthetic biology and provides a simple circuit motif for robust and precise molecular homeostasis.

Characterization of diverse homoserine lactone synthases in Escherichia coli

Quorum sensing networks have been identified in over one hundred bacterial species to date. A subset of these networks regulate group behaviors, such as bioluminescence, virulence, and biofilm formation, by sending and receiving small molecules called homoserine lactones (HSLs). Bioengineers have incorporated quorum sensing pathways into genetic circuits to connect logical operations. However, the development of higher-order genetic circuitry is inhibited by crosstalk, in which one quorum sensing network responds to HSLs produced by a different network. Here, we report the construction and characterization of a library of ten synthases including some that are expected to produce HSLs that are incompatible with the Lux pathway, and therefore show no crosstalk. We demonstrated their function in a common lab chassis, Escherichia coli BL21, and in two contexts, liquid and solid agar cultures, using decoupled Sender and Receiver pathways. We observed weak or strong stimulation of a Lux receiver by longer-chain or shorter-chain HSL-generating Senders, respectively. We also considered the under-investigated risk of unintentional release of incompletely deactivated HSLs in biological waste. We found that HSL-enriched media treated with bleach were still bioactive, while autoclaving deactivates LuxR induction. This work represents the most extensive comparison of quorum signaling synthases to date and greatly expands the bacterial signaling toolkit while recommending practices for disposal based on empirical, quantitative evidence.

Predicting Transcriptional Output of Synthetic Multi-input Promoters

Recent advances in synthetic biology have led to a wealth of well-characterized genetic parts. As parts libraries grow, so too does the potential to create novel multi-input promoters that integrate disparate signals to determine transcriptional output. Our ability to construct such promoters will outpace our ability to characterize promoter performance, due to the vast number of input combinations. In this study, we examine the input-output relations of recently developed synthetic multi-input promoters and describe two methods for predicting their behavior. The first method uses 1-dimensional induction data obtained from experiments on single-input systems to predict the n-dimensional induction responses of systems with n inputs. We demonstrate that this approach accurately predicts Boolean (on/off) responses of multi-input systems consisting of novel chimeric transcription factors and hybrid promoters in Escherichia coli. The second method uses only a small amount of multi-input response data to accurately predict analog system response over the entire landscape of input combinations. Taken together, these methods facilitate the design of synthetic circuits that utilize multi-input promoters.

Controlled communication between physically separated bacterial populations in a microfluidic device

The engineering of microbial systems increasingly strives to achieve a co-existence and co-functioning of different populations. By creating interactions, one can utilize combinations of cells where each population has a specialized function, such as regulation or sharing of metabolic burden. Here we describe a microfluidic system that enables long-term and independent growth of fixed and distinctly separate microbial populations, while allowing communication through a thin nano-cellulose filter. Using quorum-sensing signaling, we can couple the populations and show that this leads to a rapid and stable connection over long periods of time. We continue to show that this control over communication can be utilized to drive nonlinear responses. The coupling of separate populations, standardized interaction, and context-independent function lay the foundation for the construction of increasingly complex community-wide dynamic genetic regulatory mechanisms.

Tools for engineering coordinated system behaviour in synthetic microbial consortia

Advancing synthetic biology to the multicellular level requires the development of multiple cell-to-cell communication channels that propagate information with minimal signal interference. The development of quorum-sensing devices, the cornerstone technology for building microbial communities with coordinated system behaviour, has largely focused on cognate acyl-homoserine lactone (AHL)/transcription factor pairs, while the use of non-cognate pairs as a design feature has received limited attention. Here, we demonstrate a large library of AHL-receiver devices, with all cognate and non-cognate chemical signal interactions quantified, and we develop a software tool that automatically selects orthogonal communication channels. We use this approach to identify up to four orthogonal channels in silico, and experimentally demonstrate the simultaneous use of three channels in co-culture. The development of multiple non-interfering cell-to-cell communication channels is an enabling step that facilitates the design of synthetic consortia for applications including distributed bio-computation, increased bioprocess efficiency, cell specialisation and spatial organisation.

The engineering of synthetic microbial communities necessitates the use of synthetic, orthogonal cell-to-cell communication channels. Here the authors present a library of characterised AHL-receiver devices and a software tool for the automatic identification of non-interfering chemical communication channels.

Phase-sensitive excitability of a limit cycle

The classical notion of excitability refers to an equilibrium state that shows under the influence of perturbations a nonlinear threshold-like behavior. Here, we extend this concept by demonstrating how periodic orbits can exhibit a specific form of excitable behavior where the nonlinear threshold-like response appears only after perturbations applied within a certain part of the periodic orbit, i.e., the excitability happens to be phase-sensitive. As a paradigmatic example of this concept, we employ the classical FitzHugh-Nagumo system. The relaxation oscillations, appearing in the oscillatory regime of this system, turn out to exhibit a phase-sensitive nonlinear threshold-like response to perturbations, which can be explained by the nonlinear behavior in the vicinity of the canard trajectory. Triggering the phase-sensitive excitability of the relaxation oscillations by noise, we find a characteristic non-monotone dependence of the mean spiking rate of the relaxation oscillation on the noise level. We explain this non-monotone dependence as a result of an interplay of two competing effects of the increasing noise: the growing efficiency of the excitation and the degradation of the nonlinear response.

Information transmission in microbial and fungal communication: from classical to quantum

Microbes have their own communication systems. Secretion and reception of chemical signaling molecules and ion-channels mediated electrical signaling mechanism are yet observed two special ways of information transmission in microbial community. In this article, we address the aspects of various crucial machineries which set the backbone of microbial cell-to-cell communication process such as quorum sensing mechanism (bacterial and fungal), quorum sensing regulated biofilm formation, gene expression, virulence, swarming, quorum quenching, role of noise in quorum sensing, mathematical models (therapy model, evolutionary model, molecular mechanism model and many more), synthetic bacterial communication, bacterial ion-channels, bacterial nanowires and electrical communication. In particular, we highlight bacterial collective behavior with classical and quantum mechanical approaches (including quantum information). Moreover, we shed a new light to introduce the concept of quantum synthetic biology and possible cellular quantum Turing test.

Lighting up yeast cell factories by transcription factor-based biosensors

Our ability to rewire cellular metabolism for the sustainable production of chemicals, fuels and therapeutics based on microbial cell factories has advanced rapidly during the last two decades. Especially the speed and precision by which microbial genomes can be engineered now allow for more advanced designs to be implemented and tested. However, compared to the methods developed for engineering cell factories, the methods developed for testing the performance of newly engineered cell factories in high throughput are lagging far behind, which consequently impacts the overall biomanufacturing process. For this purpose, there is a need to develop new techniques for screening and selection of best-performing cell factory designs in multiplex. Here we review the current status of the sourcing, design and engineering of biosensors derived from allosterically regulated transcription factors applied to the biotechnology work-horse budding yeast Saccharomyces cerevisiae. We conclude by providing a perspective on the most important challenges and opportunities lying ahead in order to harness the full potential of biosensor development for increasing both the throughput of cell factory development and robustness of overall bioprocesses.

Understanding Biological Regulation Through Synthetic Biology

Engineering synthetic gene regulatory circuits proceeds through iterative cycles of design, building, and testing. Initial circuit designs must rely on often-incomplete models of regulation established by fields of reductive inquiry—biochemistry and molecular and systems biology. As differences in designed and experimentally observed circuit behavior are inevitably encountered, investigated, and resolved, each turn of the engineering cycle can force a resynthesis in understanding of natural network function. Here, we outline research that uses the process of gene circuit engineering to advance biological discovery. Synthetic gene circuit engineering research has not only refined our understanding of cellular regulation but furnished biologists with a toolkit that can be directed at natural systems to exact precision manipulation of network structure. As we discuss, using circuit engineering to predictively reorganize, rewire, and reconstruct cellular regulation serves as the ultimate means of testing and understanding how cellular phenotype emerges from systems-level network function.

Synthetic Biology Makes Polymer Materials Count

Synthetic biology applies engineering concepts to build cellular systems that perceive and process information. This is achieved by assembling genetic modules according to engineering design principles. Recent advance in the field has contributed optogenetic switches for controlling diverse biological functions in response to light. Here, the concept is introduced to apply synthetic biology switches and design principles for the synthesis of multi-input-processing materials. This is exemplified by the synthesis of a materials system that counts light pulses. Guided by a quantitative mathematical model, functional synthetic biology-derived modules are combined into a polymer framework resulting in a biohybrid materials system that releases distinct output molecules specific to the number of input light pulses detected. Further demonstration of modular extension yields a light pulse-counting materials system to sequentially release different enzymes catalyzing a multistep biochemical reaction. The resulting smart materials systems can provide novel solutions as integrated sensors and actuators with broad perspectives in fundamental and applied research.

Quantitative Investigation of the Role of Intra-/Intercellular Dynamics in Bacterial Quorum Sensing

Bacteria utilize diffusible signals to regulate population density-dependent coordinated gene expression in a process called quorum sensing (QS). While the intracellular regulatory mechanisms of QS are well-understood, the effect of spatiotemporal changes in the population configuration on the sensitivity and robustness of the QS response remains largely unexplored. Using a microfluidic device, we quantitatively characterized the emergent behavior of a population of swimming E. coli bacteria engineered with the lux QS system and a GFP reporter. We show that the QS activation time follows a power law with respect to bacterial population density, but this trend is disrupted significantly by microscale variations in population configuration and genetic circuit noise. We then developed a computational model that integrates population dynamics with genetic circuit dynamics to enable accurate (less than 7% error) quantitation of the bacterial QS activation time. Through modeling and experimental analyses, we show that changes in spatial configuration of swimming bacteria can drastically alter the QS activation time, by up to 22%. The integrative model developed herein also enables examination of the performance robustness of synthetic circuits with respect to growth rate, circuit sensitivity, and the population's initial size and spatial structure. Our framework facilitates quantitative tuning of microbial systems performance through rational engineering of synthetic ribosomal binding sites. We have demonstrated this through modulation of QS activation time over an order of magnitude. Altogether, we conclude that predictive engineering of QS-based bacterial systems requires not only the precise temporal modulation of gene expression (intracellular dynamics) but also accounting for the spatiotemporal changes in population configuration (intercellular dynamics).

Computational analysis of the oscillatory behavior at the translation level induced by mRNA levels oscillations due to finite intracellular resources

Recent studies have demonstrated how the competition for the finite pool of available gene expression factors has important effect on fundamental gene expression aspects. In this study, based on a whole-cell model simulation of translation in S. cerevisiae, we evaluate for the first time the expected effect of mRNA levels fluctuations on translation due to the finite pool of ribosomes. We show that fluctuations of a single gene or a group of genes mRNA levels induce periodic behavior in all S. cerevisiae translation factors and aspects: the ribosomal densities and the translation rates of all S. cerevisiae mRNAs oscillate. We numerically measure the oscillation amplitudes demonstrating that fluctuations of endogenous and heterologous genes can cause a significant fluctuation of up to 50% in the steady-state translation rates of the rest of the genes. Furthermore, we demonstrate by synonymous mutations that oscillating the levels of mRNAs that experience high ribosomal occupancy (e.g. ribosomal “traffic jam”) induces the largest impact on the translation of the S. cerevisiae genome.

The results reported here should provide novel insights and principles related to the design of synthetic gene expression circuits and related to the evolutionary constraints shaping gene expression of endogenous genes.

Each cell contains a limited number of macromolecules and factors that participate in the gene expression process. These expression resources are shared between the different molecules that encode the genetic code, resulting in non-trivial couplings and competitions between the different gene expression stages. Such competitions should be considered when analyzing the cellular economy of the cell, the genome evolution, and the design of synthetic expression circuits. Here we study the effect of couplings and competitions for ribosomes by performing a whole-cell simulation of translation of S. cerevisiae, with parameters estimated from experimental data. We demonstrate that by periodically changing the mRNA levels of a single gene (endogenous or heterologous) or a set of genes, the translation of all S. cerevisiae genes are affected in a periodic manner. We numerically estimate the exact impact of the mRNA levels periodicity on the translation process dynamics, as well as on the dynamics of the free ribosomal pool and the way it is affected by parameters such as the codon composition of the oscillating gene, its initiation rate and mRNA levels. Furthermore, we show that the codon compositions of synthetically highly expressed heterologous genes that are expected to oscillate must be carefully considered. For example, synonymous mutations resulting in “traffic jams” of ribosomes along the fluctuated mRNAs may cause significant fluctuations of up to 50% in the steady-state translation rates of all genes.

Role of metabolic spatiotemporal dynamics in regulating biofilm colony expansion

Cell fate determination is typically regulated by biological networks, yet increasing evidences suggest that cell-cell communication and environmental stresses play crucial roles in the behavior of a cell population. A recent microfluidic experiment showed that the metabolic codependence of two cell populations generates a collective oscillatory dynamic during the expansion of a Bacillus subtilis biofilm. We develop a modeling framework for the spatiotemporal dynamics of the associated metabolic circuit for cells in a colony. We elucidate the role of metabolite diffusion and the need of two distinct cell populations to observe oscillations. Uniquely, this description captures the onset and thereafter stable oscillatory dynamics during expansion and predicts the existence of damping oscillations under various environmental conditions. This modeling scheme provides insights to understand how cells integrate the information from external signaling and cell-cell communication to determine the optimal survival strategy and/or maximize cell fitness in a multicellular system.

Dynamics of Bacterial Gene Regulatory Networks

The ability of bacterial cells to adjust their gene expression program in response to environmental perturbation is often critical for their survival. Recent experimental advances allowing us to quantitatively record gene expression dynamics in single cells and in populations coupled with mathematical modeling enable mechanistic understanding on how these responses are shaped by the underlying regulatory networks. Here, we review how the combination of local and global factors affect dynamical responses of gene regulatory networks. Our goal is to discuss the general principles that allow extrapolation from a few model bacteria to less understood microbes. We emphasize that, in addition to well-studied effects of network architecture, network dynamics are shaped by global pleiotropic effects and cell physiology.

Rational engineering of synthetic microbial systems: from single cells to consortia

One promise of synthetic biology is to provide solutions for biomedical and industrial problems by rational design of added functionality in living systems. Microbes are at the forefront of this biological engineering endeavor due to their general ease of handling and their relevance in many potential applications from fermentation to therapeutics. In recent years, the field has witnessed an explosion of novel regulatory tools, from synthetic orthogonal transcription factors to posttranslational mechanisms for increased control over the behavior of synthetic circuits. Tool development has been paralleled by the discovery of principles that enable increased modularity and the management of host-circuit interactions. Engineered cell-to-cell communication bridges the scales from intracellular to population-level coordination. These developments facilitate the translation of more than a decade of circuit design into applications.

Long negative feedback loop enhances period tunability of biological oscillators

Oscillatory phenomena play a major role in organisms. In some biological oscillations such as cell cycles and heartbeats, the period can be tuned without significant changes in the amplitude. This property is called (period) tunability, one of the prominent features of biological oscillations. However, how biological oscillators produce tunable oscillations remains largely unexplored. We tackle this question using computational experiments. It has been reported that positive-plus-negative feedback oscillators produce tunable oscillations through the hysteresis-based mechanism. First, in this study, we confirmed that positive-plus-negative feedback oscillators generate tunable oscillations. Second, we found that tunability is positively correlated with the dynamic range of oscillations. Third, we showed that long negative feedback oscillators without any additional positive feedback loops can produce tunable oscillations. Finally, we computationally demonstrated that by lengthening the negative feedback loop, the Repressilator, known as a non-tunable synthetic gene oscillator, can be converted into a tunable oscillator. This work provides synthetic biologists with clues to design tunable gene oscillators.

Design of Adjacent Transcriptional Regions to Tune Gene Expression and Facilitate Circuit Construction

Polycistronic architecture is common for synthetic gene circuits, however, it remains unknown how expression of one gene is affected by the presence of other genes/noncoding regions in the operon, termed adjacent transcriptional regions (ATR). Here, we constructed synthetic operons with a reporter gene flanked by different ATRs, and we found that ATRs with high GC content, small size, and low folding energy lead to high gene expression. Based on these results, we built a model of gene expression and generated a metric that takes into account ATRs. We used the metric to design and construct logic gates with low basal expression and high sensitivity and nonlinearity. Furthermore, we rationally designed synthetic 5'ATRs with different GC content and sizes to tune protein expression levels over a 300-fold range and used these to build synthetic toggle switches with varying basal expression and degrees of bistability. Our comprehensive model and gene expression metric could facilitate the future engineering of more complex synthetic gene circuits.

Programmed hierarchical patterning of bacterial populations

Modern genetic tools allow the dissection and emulation of fundamental mechanisms shaping morphogenesis in multicellular organisms. Several synthetic genetic circuits for control of multicellular patterning have been reported to date. However, hierarchical induction of gene expression domains has received little attention from synthetic biologists, despite its importance in biological self-organization. Here we report a synthetic genetic system implementing population-based AND-logic for programmed autonomous induction of bacterial gene expression domains. We develop a ratiometric assay for bacteriophage T7 RNA polymerase activity and use it to systematically characterize different intact and split enzyme variants. We then utilize the best-performing variant to build a three-color patterning system responsive to two different homoserine lactones. We validate the AND gate-like behavior of this system both in cell suspension and in surface culture. Finally, we use the synthetic circuit in a membrane-based spatial assay to demonstrate programmed hierarchical patterning of gene expression across bacterial populations.

Metabolic Feedback Circuits Provide Rapid Control of Metabolite Dynamics

Metabolism constitutes the basis of life, and the dynamics of metabolism dictate various cellular processes. However, exactly how metabolite dynamics are controlled remains poorly understood. By studying an engineered fatty acid-producing pathway as a model, we found that upon transcription activation a metabolic product from an unregulated pathway required seven cell cycles to reach to its steady state level, with the speed mostly limited by enzyme expression dynamics. To overcome this limit, we designed metabolic feedback circuits (MeFCs) with three different architectures, and experimentally measured and modeled their metabolite dynamics. Our engineered MeFCs could dramatically shorten the rise-time of metabolites, decreasing it by as much as 12-fold. The findings of this study provide a systematic understanding of metabolite dynamics in different architectures of MeFCs and have potentially immense applications in designing synthetic circuits to improve the productivities of engineered metabolic pathways.

Cell-Free and In Vivo Characterization of Lux, Las, and Rpa Quorum Activation Systems in E. coli

Synthetic biologists have turned toward quorum systems as a path for building sophisticated microbial consortia that exhibit group decision making. Currently, however, even the most complex consortium circuits rely on only one or two quorum sensing systems, greatly restricting the available design space. High-throughput characterization of available quorum sensing systems is useful for finding compatible sets of systems that are suitable for a defined circuit architecture. Recently, cell-free systems have gained popularity as a test-bed for rapid prototyping of genetic circuitry. We take advantage of the transcription-translation cell-free system to characterize three commonly used Lux-type quorum activators, Lux, Las, and Rpa. We then compare the cell-free characterization to results obtained in vivo. We find significant genetic crosstalk in both the Las and Rpa systems and substantial signal crosstalk in Lux activation. We show that cell-free characterization predicts crosstalk observed in vivo.

Reconfigurable Analog Signal Processing by Living Cells

Living cells are known for their capacity for versatile signal processing, particularly the ability to respond differently to the same stimuli using biochemical networks that integrate environmental signals and reconfigure their dynamic responses. However, the complexity of natural biological networks confounds the discovery of fundamental mechanisms behind versatile signaling. Here, we study one specific aspect of reconfigurable signal processing in which a minimal biological network integrates two signals, using one to reconfigure the network's transfer function with respect to the other, producing an emergent switch between induction and repression. In contrast to known mechanisms, the new mechanism reconfigures transfer functions through genetic networks without extensive protein-protein interactions. These results provide a novel explanation for the versatility of genetic programs, and suggest a new mechanism of signal integration that may govern flexibility and plasticity of gene expression.

Tuning the dynamic range of bacterial promoters regulated by ligand-inducible transcription factors

One challenge for synthetic biologists is the predictable tuning of genetic circuit regulatory components to elicit desired outputs. Gene expression driven by ligand-inducible transcription factor systems must exhibit the correct ON and OFF characteristics: appropriate activation and leakiness in the presence and absence of inducer, respectively. However, the dynamic range of a promoter (i.e., absolute difference between ON and OFF states) is difficult to control. We report a method that tunes the dynamic range of ligand-inducible promoters to achieve desired ON and OFF characteristics. We build combinatorial sets of AraC-and LasR-regulated promoters containing -10 and -35 sites from synthetic and Escherichia coli promoters. Four sequence combinations with diverse dynamic ranges were chosen to build multi-input transcriptional logic gates regulated by two and three ligand-inducible transcription factors (LacI, TetR, AraC, XylS, RhlR, LasR, and LuxR). This work enables predictable control over the dynamic range of regulatory components.

Diversity-Function Relationships in Natural, Applied, and Engineered Microbial Ecosystems

The connection between ecosystem function and taxonomic diversity has been of interest and relevance to macroecologists for decades. After many years of lagging behind due to the difficulty of assigning both taxonomy and function to poorly distinguishable microscopic cells, microbial ecology now has access to a suite of powerful molecular tools which allow its practitioners to generate data relating to diversity and function of a microbial community on an unprecedented scale. Instead, the problem facing today's microbial ecologists is coupling the ease of generation of these datasets with the formulation and testing of workable hypotheses relating the diversity and function of environmental, host-associated, and engineered microbial communities. Here, we review the current state of knowledge regarding the links between taxonomic alpha- and beta-diversity and ecosystem function, comparing our knowledge in this area to that obtained by macroecologists who use more traditional techniques. We consider the methodologies that can be applied to study these properties and how successful they are at linking function to diversity, using examples from the study of model microbial ecosystems, methanogenic bioreactors (anaerobic digesters), and host-associated microbiota. Finally, we assess ways in which our newly acquired understanding might be used to manipulate diversity in ecosystems of interest in order to improve function for the benefit of us or the environment in general through the provision of ecosystem services.

3D Printing of Living Responsive Materials and Devices

3D printing has been intensively explored to fabricate customized structures of responsive materials including hydrogels, liquid-crystal elastomers, shape-memory polymers, and aqueous droplets. Herein, a new method and material system capable of 3D-printing hydrogel inks with programed bacterial cells as responsive components into large-scale (3 cm), high-resolution (30 μm) living materials, where the cells can communicate and process signals in a programmable manner, are reported. The design of 3D-printed living materials is guided by quantitative models that account for the responses of programed cells in printed microstructures of hydrogels. Novel living devices are further demonstrated, enabled by 3D printing of programed cells, including logic gates, spatiotemporally responsive patterning, and wearable devices.

Nanomechanical Force Mapping of Restricted Cell-To-Cell Collisions Oscillating between Contraction and Relaxation

Contact-mediated cell migration strongly determines the invasiveness of the corresponding cells, collective migration, and morphogenesis. The quantitative study of cellular response upon contact relies on cell-to-cell collision, which rarely occurs in conventional cell culture. Herein, we developed a strategy to activate a robust cell-to-cell collision within smooth muscle cell pairs. Nanomechanical traction force mapping reveals that the collision process is promoted by the oscillatory modulations between contraction and relaxation and orientated by the filopodial bridge composed of nanosized contractile machinery. This strategy can enhance the occurrence of cell-to-cell collision, which renders it advantageous over traditional methods that utilize micropatterned coating to confine cell pairs. Furthermore, modulation of the balance between cell tugging force and traction force can determine the repolarization of cells and thus the direction of cell migration. Overall, our approach could help to reveal the mechanistic contribution in cell motility and provide insights in tissue engineering.

Beyond the Michaelis-Menten equation: Accurate and efficient estimation of enzyme kinetic parameters

Examining enzyme kinetics is critical for understanding cellular systems and for using enzymes in industry. The Michaelis-Menten equation has been widely used for over a century to estimate the enzyme kinetic parameters from reaction progress curves of substrates, which is known as the progress curve assay. However, this canonical approach works in limited conditions, such as when there is a large excess of substrate over enzyme. Even when this condition is satisfied, the identifiability of parameters is not always guaranteed, and often not verifiable in practice. To overcome such limitations of the canonical approach for the progress curve assay, here we propose a Bayesian approach based on an equation derived with the total quasi-steady-state approximation. In contrast to the canonical approach, estimates obtained with this proposed approach exhibit little bias for any combination of enzyme and substrate concentrations. Importantly, unlike the canonical approach, an optimal experiment to identify parameters with certainty can be easily designed without any prior information. Indeed, with this proposed design, the kinetic parameters of diverse enzymes with disparate catalytic efficiencies, such as chymotrypsin, fumarase, and urease, can be accurately and precisely estimated from a minimal amount of timecourse data. A publicly accessible computational package performing such accurate and efficient Bayesian inference for enzyme kinetics is provided.

The spatiotemporal system dynamics of acquired resistance in an engineered microecology

Great strides have been made in the understanding of complex networks; however, our understanding of natural microecologies is limited. Modelling of complex natural ecological systems has allowed for new findings, but these models typically ignore the constant evolution of species. Due to the complexity of natural systems, unanticipated interactions may lead to erroneous conclusions concerning the role of specific molecular components. To address this, we use a synthetic system to understand the spatiotemporal dynamics of growth and to study acquired resistance in vivo. Our system differs from earlier synthetic systems in that it focuses on the evolution of a microecology from a killer-prey relationship to coexistence using two different non-motile Escherichia coli strains. Using empirical data, we developed the first ecological model emphasising the concept of the constant evolution of species, where the survival of the prey species is dependent on location (distance from the killer) or the evolution of resistance. Our simple model, when expanded to complex microecological association studies under varied spatial and nutrient backgrounds may help to understand the complex relationships between multiple species in intricate natural ecological networks. This type of microecological study has become increasingly important, especially with the emergence of antibiotic-resistant pathogens.

A Tug-of-War Mechanism for Pattern Formation in a Genetic Network

Synthesizing spatial patterns with genetic networks is an ongoing challenge in synthetic biology. A successful demonstration of pattern formation would imply a better understanding of systems in the natural world and advance applications in synthetic biology. In developmental systems, transient patterning may suffice in order to imprint instructions for long-term development. In this paper we show that transient but persistent patterns can emerge from a realizable synthetic gene network based on a toggle switch. We show that a bistable system incorporating diffusible molecules can generate patterns that resemble Turing patterns but are distinctly different in the underlying mechanism: diffusion of mutually inhibiting molecules creates a prolonged "tug-of-war" between patches of cells at opposing bistable states. The patterns are transient but longer wavelength patterns persist for extended periods of time. Analysis of a representative small scale model implies the eigenvalues of the persistent modes are just above the threshold of stability. The results are verified through simulation of biologically relevant models.

The Timing of Transcriptional Regulation in Synthetic Gene Circuits

Transcription factors and their target promoters are central to synthetic biology. By arranging these components into novel gene regulatory circuits, synthetic biologists have been able to create a wide variety of phenotypes, including bistable switches, oscillators, and logic gates. However, transcription factors (TFs) do not instantaneously regulate downstream targets. After the gene encoding a TF is turned on, the gene must first be transcribed, the transcripts must be translated, and sufficient TF must accumulate in order to bind operator sites of the target promoter. The time to complete this process, here called the "signaling time," is a critical aspect in the design of dynamic regulatory networks, yet it remains poorly characterized. In this work, we measured the signaling time of two TFs in Escherichia coli commonly used in synthetic biology: the activator AraC and the repressor LacI. We found that signaling times can range from a few to tens of minutes, and are affected by the expression rate of the TF. Our single-cell data also show that the variability of the signaling time increases with its mean. To validate these signaling time measurements, we constructed a two-step genetic cascade, and showed that the signaling time of the full cascade can be predicted from those of its constituent steps. These results provide concrete estimates for the time scales of transcriptional regulation in living cells, which are important for understanding the dynamics of synthetic transcriptional gene circuits.

Systems and synthetic biology approaches in understanding biological oscillators

Background

Self-sustained oscillations are a ubiquitous and vital phenomenon in living systems. From primitive single-cellular bacteria to the most sophisticated organisms, periodicities have been observed in a broad spectrum of biological processes such as neuron firing, heart beats, cell cycles, circadian rhythms, etc. Defects in these oscillators can cause diseases from insomnia to cancer. Elucidating their fundamental mechanisms is of great significance to diseases, and yet challenging, due to the complexity and diversity of these oscillators.

Results

Approaches in quantitative systems biology and synthetic biology have been most effective by simplifying the systems to contain only the most essential regulators. Here, we will review major progress that has been made in understanding biological oscillators using these approaches. The quantitative systems biology approach allows for identification of the essential components of an oscillator in an endogenous system. The synthetic biology approach makes use of the knowledge to design the simplest, de novo oscillators in both live cells and cell-free systems. These synthetic oscillators are tractable to further detailed analysis and manipulations.

Conclusion

With the recent development of biological and computational tools, both approaches have made significant achievements.

BSim 2.0: An Advanced Agent-Based Cell Simulator

Agent-based models (ABMs) provide a number of advantages relative to traditional continuum modeling approaches, permitting incorporation of great detail and realism into simulations, allowing in silico tracking of single-cell behaviors and correlation of these with emergent effects at the macroscopic level. In this study we present BSim 2.0, a radically new version of BSim, a computational ABM framework for modeling dynamics of bacteria in typical experimental environments including microfluidic chemostats. This is facilitated through the implementation of new methods including cells with capsular geometry that are able to physically and chemically interact with one another, a realistic model of cellular growth, a delay differential equation solver, and realistic environmental geometries.

Droplet microfluidics for synthetic biology

Synthetic biology is an interdisciplinary field that aims to engineer biological systems for useful purposes. Organism engineering often requires the optimization of individual genes and/or entire biological pathways (consisting of multiple genes). Advances in DNA sequencing and synthesis have recently begun to enable the possibility of evaluating thousands of gene variants and hundreds of thousands of gene combinations. However, such large-scale optimization experiments remain cost-prohibitive to researchers following traditional molecular biology practices, which are frequently labor-intensive and suffer from poor reproducibility. Liquid handling robotics may reduce labor and improve reproducibility, but are themselves expensive and thus inaccessible to most researchers. Microfluidic platforms offer a lower entry price point alternative to robotics, and maintain high throughput and reproducibility while further reducing operating costs through diminished reagent volume requirements. Droplet microfluidics have shown exceptional promise for synthetic biology experiments, including DNA assembly, transformation/transfection, culturing, cell sorting, phenotypic assays, artificial cells and genetic circuits.

Logic Synthesis of Recombinase-Based Genetic Circuits

A synthetic approach to biology is a promising technique for various applications. Recent advancements have demonstrated the feasibility of constructing synthetic two-input logic gates in Escherichia coli cells with long-term memory based on DNA inversion induced by recombinases. Moreover, recent evidences indicate that DNA inversion mediated by genome editing tools is possible. Powerful genome editing technologies, such as CRISPR-Cas9 systems, have great potential to be exploited to implement large-scale recombinase-based circuits. What remains unclear is how to construct arbitrary Boolean functions based on these emerging technologies. In this paper, we lay the theoretical foundation formalizing the connection between recombinase-based genetic circuits and Boolean functions. It enables systematic construction of any given Boolean function using recombinase-based logic gates. We further develop a methodology leveraging existing electronic design automation (EDA) tools to automate the synthesis of complex recombinase-based genetic circuits with respect to area and delay optimization. In silico experimental results demonstrate the applicability of our proposed methods as a useful tool for recombinase-based genetic circuit synthesis and optimization.

Programmable assembly of pressure sensors using pattern-forming bacteria

Biological systems can generate microstructured materials that combine organic and inorganic components and possess diverse physical and chemical properties. However, these natural processes in materials fabrication are not readily programmable. Here, we use a synthetic-biology approach to mimic such natural processes to assemble patterned materials.. We demonstrate programmable fabrication of three-dimensional (3D) materials by printing engineered self-patterning bacteria on permeable membranes that serve as a structural scaffold. Application of gold nanoparticles to the colonies creates hybrid organic-inorganic dome structures. The dynamics of the dome structures' response to pressure is determined by their geometry (colony size, dome height and pattern), which is easily modified by varying the properties of the membrane (e.g., pore size and hydrophobicity). We generate resettable pressure sensors that process signals in response to varying pressure intensity and duration.

Evidence of mixotrophic carbon-capture by n-butanol-producer Clostridium beijerinckii

Recent efforts to combat increasing greenhouse gas emissions include their capture into advanced biofuels, such as butanol. Traditionally, biobutanol research has been centered solely on its generation from sugars. Our results show partial re-assimilation of CO₂ and H₂ by n-butanol-producer C. beijerinckii. This was detected as synchronous CO₂/H₂ oscillations by direct (real-time) monitoring of their fermentation gasses. Additional functional analysis demonstrated increased total carbon recovery above heterotrophic values associated to mixotrophic assimilation of synthesis gas (H₂, CO₂ and CO). This was further confirmed using ¹³C-Tracer experiments feeding ¹³CO₂ and measuring the resulting labeled products. Genome- and transcriptome-wide analysis revealed transcription of key C-1 capture and additional energy conservation genes, including partial Wood-Ljungdahl and complete reversed pyruvate ferredoxin oxidoreductase / pyruvate-formate-lyase-dependent (rPFOR/Pfl) pathways. Therefore, this report provides direct genetic and physiological evidences of mixotrophic inorganic carbon-capture by C. beijerinckii.

Heterogeneity in Pure Microbial Systems: Experimental Measurements and Modeling

Cellular heterogeneity influences bioprocess performance in ways that until date are not completely elucidated. In order to account for this phenomenon in the design and operation of bioprocesses, reliable analytical and mathematical descriptions are required. We present an overview of the single cell analysis, and the mathematical modeling frameworks that have potential to be used in bioprocess control and optimization, in particular for microbial processes. In order to be suitable for bioprocess monitoring, experimental methods need to be high throughput and to require relatively short processing time. One such method used successfully under dynamic conditions is flow cytometry. Population balance and individual based models are suitable modeling options, the latter one having in particular a good potential to integrate the various data collected through experimentation. This will be highly beneficial for appropriate process design and scale up as a more rigorous approach may prevent a priori unwanted performance losses. It will also help progressing synthetic biology applications to industrial scale.

Synthetic biology meets tissue engineering

Classical tissue engineering is aimed mainly at producing anatomically and physiologically realistic replacements for normal human tissues. It is done either by encouraging cellular colonization of manufactured matrices or cellular recolonization of decellularized natural extracellular matrices from donor organs, or by allowing cells to self-organize into organs as they do during fetal life. For repair of normal bodies, this will be adequate but there are reasons for making unusual, non-evolved tissues (repair of unusual bodies, interface to electromechanical prostheses, incorporating living cells into life-support machines). Synthetic biology is aimed mainly at engineering cells so that they can perform custom functions: applying synthetic biological approaches to tissue engineering may be one way of engineering custom structures. In this article, we outline the ‘embryological cycle’ of patterning, differentiation and morphogenesis and review progress that has been made in constructing synthetic biological systems to reproduce these processes in new ways. The state-of-the-art remains a long way from making truly synthetic tissues, but there are now at least foundations for future work.