Oscillations by minimal bacterial suicide circuits reveal hidden facets of host-circuit physiology

Engineering functional materials through bacteria-assisted living grafting

Functionalizing materials with biomacromolecules such as enzymes has broad applications in biotechnology and biomedicine. Here, we introduce a grafting method mediated by living cells to functionalize materials. We use polymeric scaffolds to trap engineered bacteria and micron-sized particles with chemical groups serving as active sites for grafting. The bacteria synthesize the desired protein for grafting and autonomously lyse to release it. The released functional moieties are locally grafted onto the active sites, generating the materials engineered by living grafting (MELGs). MELGs are resilient to perturbations because of both the bonding and the regeneration of functional domains synthesized by living cells. The programmability of the bacteria enables us to fabricate MELGs that can respond to external input, decompose a pollutant, reconstitute synthetic pathways for natural product synthesis, and purify mismatched DNA. Our work establishes a bacteria-assisted grafting strategy to functionalize materials with a broad range of biological activities in an integrated, flexible, and modular manner. A record of this paper's transparent peer review process is included in the supplemental information.

Self-lysis microbial consortia for predictable multi-proteins assembly

The scope of bioengineering is expanding from the design of single strain to the microbial communities, allowing for the division-of-labor in synthesizing the multi-protein systems. Predicting the composition of the final product during the biomanufacturing process, however, can be difficult. Consortia-based manufacturing has the potential to boost production efficiency, but this benefit primarily holds in the upstream. The current format of downstream process heavily relies on the centralized facility, and is not economical and flexible to address the demands in small-scale. Here, we present a concise and manageable platform to enable the multi-protein system assembly. We engineer a self-lysis microbial consortium, where each strain lyses autonomously at high densities and produces a single protein component. The product fraction can be precisely tuned by varying the inoculation ratio. Utilizing this platform, we assemble a classical 34-component PURE (protein synthesis using recombinant elements) system. We have further optimized the downstream process of the biomanufacturing by incorporating the porous structure of polymeric materials. The encapsulated autolysis consortium can produce and release the proteins while maintaining the cell factories enclosed in the materials by exporting the multi-protein system for collection. Our research provides a novel approach to the flexible and controllable production of multi-protein systems, opening up new possibilities for pathway assembly and portable biomanufacturing.

Autoencoder neural networks enable low dimensional structure analyses of microbial growth dynamics

The ability to effectively represent microbiome dynamics is a crucial challenge in their quantitative analysis and engineering. By using autoencoder neural networks, we show that microbial growth dynamics can be compressed into low-dimensional representations and reconstructed with high fidelity. These low-dimensional embeddings are just as effective, if not better, than raw data for tasks such as identifying bacterial strains, predicting traits like antibiotic resistance, and predicting community dynamics. Additionally, we demonstrate that essential dynamical information of these systems can be captured using far fewer variables than traditional mechanistic models. Our work suggests that machine learning can enable the creation of concise representations of high-dimensional microbiome dynamics to facilitate data analysis and gain new biological insights.

Polyaromatic hydrocarbons (PAHs) in the water environment: A review on toxicity, microbial biodegradation, systematic biological advancements, and environmental fate

Polycyclic aromatic hydrocarbons (PAHs) are considered a major class of organic contaminants or pollutants, which are poisonous, mutagenic, genotoxic, and/or carcinogenic. Due to their ubiquitous occurrence and recalcitrance, PAHs-related pollution possesses significant public health and environmental concerns. Increasing the understanding of PAHs' negative impacts on ecosystems and human health has encouraged more researchers to focus on eliminating these pollutants from the environment. Nutrients available in the aqueous phase, the amount and type of microbes in the culture, and the PAHs' nature and molecular characteristics are the common factors influencing the microbial breakdown of PAHs. In recent decades, microbial community analyses, biochemical pathways, enzyme systems, gene organization, and genetic regulation related to PAH degradation have been intensively researched. Although xenobiotic-degrading microbes have a lot of potential for restoring the damaged ecosystems in a cost-effective and efficient manner, their role and strength to eliminate the refractory PAH compounds using innovative technologies are still to be explored. Recent analytical biochemistry and genetically engineered technologies have aided in improving the effectiveness of PAHs' breakdown by microorganisms, creating and developing advanced bioremediation techniques. Optimizing the key characteristics like the adsorption, bioavailability, and mass transfer of PAH boosts the microorganisms' bioremediation performance, especially in the natural aquatic water bodies. This review's primary goal is to provide an understanding of recent information about how PAHs are degraded and/or transformed in the aquatic environment by halophilic archaea, bacteria, algae, and fungi. Furthermore, the removal mechanisms of PAH in the marine/aquatic environment are discussed in terms of the recent systemic advancements in microbial degradation methodologies. The review outputs would assist in facilitating the development of new insights into PAH bioremediation.

Complete biodegradation of the oldest organic herbicide 2,4-Dichlorophenoxyacetic acid by engineering Escherichia coli

After nearly 80 years of extensive application, the oldest organic herbicide 2,4-dichlorophenoxyacetic acid (2,4-D) has caused many problems of environmental pollution and ecological deterioration. Bioremediation is an ideal method for pollutant treatment. However, difficult screening and preparation of efficient degradation bacteria have largely hindered its application in 2,4-D remediation. We have created a novel engineering Escherichia coli with a reconstructed complete degradation pathway of 2,4-D to solve the problem of screening highly efficient degradation bacteria in this study. The results of fluorescence quantitative PCR demonstrated that all nine genes in the degradation pathway were successfully expressed in the engineered strain. The engineered strains can quickly and completely degrade 0.5 mM 2, 4-D within 6 h. Inspiring, the engineered strains grew with 2,4-D as the sole carbon source. By using the isotope tracing method, the metabolites of 2,4-D were found incorporated into the tricarboxylic acid cycle in the engineering strain. Scanning electron microscopy showed that 2,4-D had less damage on the engineered bacteria than the wild-type strain. Engineered strain can also rapidly and completely remedy 2,4-D pollution in natural water and soil. Assembling the metabolic pathways of pollutants through synthetic biology was an effective method to create pollutant-degrading bacteria for bioremediation.

Biotechnological methods to remove microplastics: a review

Microplastics pollution is major threat to ecosystems and is impacting abiotic and biotic components. Microplastics are diverse and highly complex contaminants that transport other contaminants and microbes. Current methods to remove microplastics include biodegradation, incineration, landfilling, and recycling. Here we review microplastics with focus on sources, toxicity, and biodegradation. We discuss the role of algae, fungi, bacteria in the biodegradation, and we present biotechnological methods to enhance degradation, e.g., gene editing tools and bioinformatics.

Hydrogel microcapsules containing engineered bacteria for sustained production and release of protein drugs

Subcutaneous administration of sustained-release formulations is a common strategy for protein drugs, which avoids first pass effect and has high bioavailability. However, conventional sustained-release strategies can only load a limited amount of drug, leading to insufficient durability. Herein, we developed microcapsules based on engineered bacteria for sustained release of protein drugs. Engineered bacteria were carried in microcapsules for subcutaneous administration, with a production-lysis circuit for sustained protein production and release. Administrated in diabetic rats, engineered bacteria microcapsules was observed to smoothly release Exendin-4 for 2 weeks and reduce blood glucose. In another example, by releasing subunit vaccines with bacterial microcomponents as vehicles, engineered bacterial microcapsules activated specific immunity in mice and achieved tumor prevention. The engineered bacteria microcapsules have potential to durably release protein drugs and show versatility on the size of drugs. It might be a promising design strategy for long-acting in situ drug factory.

Engineering consortia by polymeric microbial swarmbots

Synthetic microbial consortia represent a new frontier for synthetic biology given that they can solve more complex problems than monocultures. However, most attempts to co-cultivate these artificial communities fail because of the winner-takes-all in nutrients competition. In soil, multiple species can coexist with a spatial organization. Inspired by nature, here we show that an engineered spatial segregation method can assemble stable consortia with both flexibility and precision. We create microbial swarmbot consortia (MSBC) by encapsulating subpopulations with polymeric microcapsules. The crosslinked structure of microcapsules fences microbes, but allows the transport of small molecules and proteins. MSBC method enables the assembly of various synthetic communities and the precise control over the subpopulations. These capabilities can readily modulate the division of labor and communication. Our work integrates the synthetic biology and material science to offer insights into consortia assembly and serve as foundation to diverse applications from biomanufacturing to engineered photosynthesis.

Most attempts to co-cultivate the artificial microbial communities fail mostly due to the mismatched rates of consumption and production of nutrients among subpopulations. Here, the authors develop a microbial swarmbot mediated spatial segregation method to assemble stably coexisting consortia with both flexibility and precision.

Context-Dependent Stability and Robustness of Genetic Toggle Switches with Leaky Promoters

Multistable switches are ubiquitous building blocks in both systems and synthetic biology. Given their central role, it is thus imperative to understand how their fundamental properties depend not only on the tunable biophysical properties of the switches themselves, but also on their genetic context. To this end, we reveal in this article how these factors shape the essential characteristics of toggle switches implemented using leaky promoters such as their stability and robustness to noise, both at single-cell and population levels. In particular, our results expose the roles that competition for scarce transcriptional and translational resources, promoter leakiness, and cell-to-cell heterogeneity collectively play. For instance, the interplay between protein expression from leaky promoters and the associated cost of relying on shared cellular resources can give rise to tristable dynamics even in the absence of positive feedback. Similarly, we demonstrate that while promoter leakiness always acts against multistability, resource competition can be leveraged to counteract this undesirable phenomenon. Underpinned by a mechanistic model, our results thus enable the context-aware rational design of multistable genetic switches that are directly translatable to experimental considerations, and can be further leveraged during the synthesis of large-scale genetic systems using computer-aided biodesign automation platforms.

Synthetically engineered microbial scavengers for enhanced bioremediation

Microbial bioremediation has gained attention as a cheap, efficient, and sustainable technology to manage the increasing environmental pollution. Since microorganisms in nature are not evolved to degrade pollutants, there is an increasing demand for developing safer and more efficient pollutant-scavengers for enhanced bioremediation. In this review, we introduce the strategies and technologies developed in the field of synthetic biology and their applications to the construction of microbial scavengers with improved efficiency of biodegradation while minimizing the impact of genetically engineered microbial scavengers on ecosystems. In addition, we discuss recent achievements in the biodegradation of fastidious pollutants, greenhouse gases, and microplastics using engineered microbial scavengers. Using synthetic microbial scavengers and multidisciplinary technologies, toxic pollutants could be more easily eliminated, and the environment could be more efficiently recovered.

Quantifying the optimal strategy of population control of quorum sensing network in Escherichia coli

Biological functions of bacteria can be regulated by monitoring their own population density induced by the quorum sensing system. However, quantitative insight into the system’s dynamics and regulatory mechanism remain challenging. Here, we construct a comprehensive mathematical model of the synthetic quorum sensing circuit that controls population density in Escherichia coli. Simulations agree well with experimental results obtained under different ribosome-binding site (RBS) efficiencies. We present a quantitative description of the component dynamics and show how the components respond to isopropyl-β-D-1-thiogalactopyranoside (IPTG) induction. The optimal IPTG-induction range for efficiently controlling population density is quantified. The controllable area of population density by acyl-homoserine lactone (AHL) permeability is quantified as well, indicating that high AHL permeability should be treated with a high dose of IPTG, while low AHL permeability should be induced with low dose for efficiently controlling. Unexpectedly, an oscillatory behavior of the growth curve is observed with proper RBS-binding strengths and the oscillation is greatly restricted by the bacterial death induced by toxic metabolic by-products. Moreover, we identify that the mechanism underlying the emergence of oscillation is determined by the negative feedback loop structure within the signaling. Bifurcation analysis and landscape theory are further employed to study the stochastic dynamic and global stability of the system, revealing two faces of toxic metabolic by-products in controlling oscillatory behavior. Overall, our study presents a quantitative basis for understanding and new insights into the control mechanism of quorum sensing system, providing possible clues to guide the development of more rational control strategy.

Living fabrication of functional semi-interpenetrating polymeric materials

Cell-mediated living fabrication has great promise for generating materials with versatile, programmable functions. Here, we demonstrate the engineering of living materials consisting of semi-interpenetrating polymer networks (sIPN). The fabrication process is driven by the engineered bacteria encapsulated in a polymeric microcapsule, which serves as the initial scaffold. The bacteria grow and undergo programmed lysis in a density-dependent manner, releasing protein monomers decorated with reactive tags. Those protein monomers polymerize with each other to form the second polymeric component that is interlaced with the initial crosslinked polymeric scaffold. The formation of sIPN serves the dual purposes of enhancing the mechanical property of the living materials and anchoring effector proteins for diverse applications. The material is resilient to perturbations because of the continual assembly of the protein mesh from the monomers released by the engineered bacteria. We demonstrate the adoption of the platform to protect gut microbiota in animals from antibiotic-mediated perturbations. Our work lays the foundation for programming functional living materials for diverse applications.

Homologous Quorum Sensing Regulatory Circuit: A Dual-Input Genetic Controller for Modulating Quorum Sensing-Mediated Protein Expression in E. coli

We developed a hybrid synthetic circuit that co-opts the genetic regulation of the native bacterial quorum sensing autoinducer-2 and imposes an extra external controller for maintaining tightly controlled gene expression. This dual-input genetic controller was mathematically modeled and, by design, can be operated in three modes: a constitutive mode that enables consistent and high levels of expression; a tightly repressed mode in which there is very little background expression; and an inducible mode in which concentrations of two signals (arabinose and autoinducer-2) determine the net amplification of the gene(s)-of-interest. We demonstrate the utility of the circuit for the controlled expression of human granulocyte macrophage colony stimulating factor in an engineered probiotic E. coli. This dual-input genetic controller is the first homologous AI-2 quorum sensing circuit that has the ability to be operated in three different modes. We believe it has the potential for wide-ranging biotechnological applications due its versatile features.

Biosynthesis of inorganic nanomaterials using microbial cells and bacteriophages

Inorganic nanomaterials are widely used in chemical, electronics, photonics, energy and medical industries. Preparing a nanomaterial (NM) typically requires physical and/or chemical methods that involve harsh and environmentally hazardous conditions. Recently, wild-type and genetically engineered microorganisms have been harnessed for the biosynthesis of inorganic NMs under mild and environmentally friendly conditions. Microorganisms such as microalgae, fungi and bacteria, as well as bacteriophages, can be used as biofactories to produce single-element and multi-element inorganic NMs. This Review describes the emerging area of inorganic NM biosynthesis, emphasizing the mechanisms of inorganic-ion reduction and detoxification, while also highlighting the proteins and peptides involved. We show how analysing a Pourbaix diagram can help us devise strategies for the predictive biosynthesis of NMs with high producibility and crystallinity and also describe how to control the size and morphology of the product. Here, we survey biosynthetic inorganic NMs of 55 elements and their applications in catalysis, energy harvesting and storage, electronics, antimicrobials and biomedical therapy. Furthermore, a step-by-step flow chart is presented to aid the design and biosynthesis of inorganic NMs employing microbial cells. Future research in this area will add to the diversity of available inorganic NMs but should also address scalability and purity.

Genetically engineered control of phenotypic structure in microbial colonies

Rapid advances in cellular engineering^1,2 have positioned synthetic biology to address therapeutic^3,4 and industrial⁵ problems, but a substantial obstacle is the myriad of unanticipated cellular responses in heterogeneous real-world environments such as the gut^6,7, solid tumours^8,9, bioreactors¹⁰ or soil¹¹. Complex interactions between the environment and cells often arise through non-uniform nutrient availability, which generates bidirectional coupling as cells both adjust to and modify their local environment through phenotypic differentiation^12,13. Although synthetic spatial gene expression patterns^14-17 have been explored under homogeneous conditions, the mutual interaction of gene circuits, growth phenotype and the environment remains a challenge. Here, we design gene circuits that sense and control phenotypic structure in microcolonies containing both growing and dormant bacteria. We implement structure modulation by coupling different downstream modules to a tunable sensor that leverages Escherichia coli's stress response and is activated on growth arrest. One is an actuator module that slows growth and thereby alters nutrient gradients. Environmental feedback in this circuit generates robust cycling between growth and dormancy in the interior of the colony, as predicted by a spatiotemporal computational model. We also use the sensor to drive an inducible gating module for selective gene expression in non-dividing cells, which allows us to radically alter population structure by eliminating the dormant phenotype with a 'stress-gated lysis circuit'. Our results establish a strategy to leverage and control microbial colony structure for synthetic biology applications in complex environments.

Versatile biomanufacturing through stimulus-responsive cell-material feedback

Small-scale production of biologics has great potential for enhancing the accessibility of biomanufacturing. By exploiting cell-material feedback, we have designed a concise platform to achieve versatile production, analysis and purification of diverse proteins and protein complexes. The core of our technology is a microbial swarmbot, which consists of a stimulus-sensitive polymeric microcapsule encapsulating engineered bacteria. By sensing the confinement, the bacteria undergo programmed partial lysis at a high local density. Conversely, the encapsulating material shrinks responding to the changing chemical environment caused by cell growth, squeezing out the protein products released by bacterial lysis. This platform is then integrated with downstream modules to enable quantification of enzymatic kinetics, purification of diverse proteins, quantitative control of protein interactions and assembly of functional protein complexes and multienzyme metabolic pathways. Our work demonstrates the use of the cell-material feedback to engineer a modular and flexible platform with sophisticated yet well-defined programmed functions.

Gene networks that compensate for crosstalk with crosstalk

Crosstalk is a major challenge to engineering sophisticated synthetic gene networks. A common approach is to insulate signal-transduction pathways by minimizing molecular-level crosstalk between endogenous and synthetic genetic components, but this strategy can be difficult to apply in the context of complex, natural gene networks and unknown interactions. Here, we show that synthetic gene networks can be engineered to compensate for crosstalk by integrating pathway signals, rather than by pathway insulation. We demonstrate this principle using reactive oxygen species (ROS)-responsive gene circuits in Escherichia coli that exhibit concentration-dependent crosstalk with non-cognate ROS. We quantitatively map the degree of crosstalk and design gene circuits that introduce compensatory crosstalk at the gene network level. The resulting gene network exhibits reduced crosstalk in the sensing of the two different ROS. Our results suggest that simple network motifs that compensate for pathway crosstalk can be used by biological networks to accurately interpret environmental signals.

Crosstalk between genetic circuits is a major challenge for engineering sophisticated networks. Here the authors design networks that compensate for crosstalk by integrating, not insulating, pathways.

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.

A stabilized microbial ecosystem of self-limiting bacteria using synthetic quorum-regulated lysis

Microbial ecologists are increasingly turning to small, synthesized ecosystems1-5 as a reductionist tool to probe the complexity of native microbiomes6,7. Concurrently, synthetic biologists have gone from single-cell gene circuits8-11 to controlling whole populations using intercellular signalling12-16. The intersection of these fields is giving rise to new approaches in waste recycling17, industrial fermentation18, bioremediation19 and human health16,20. These applications share a common challenge7 well-known in classical ecology21,22-stability of an ecosystem cannot arise without mechanisms that prohibit the faster-growing species from eliminating the slower. Here, we combine orthogonal quorum-sensing systems and a population control circuit with diverse self-limiting growth dynamics to engineer two 'ortholysis' circuits capable of maintaining a stable co-culture of metabolically competitive Salmonella typhimurium strains in microfluidic devices. Although no successful co-cultures are observed in a two-strain ecology without synthetic population control, the 'ortholysis' design dramatically increases the co-culture rate from 0% to approximately 80%. Agent-based and deterministic modelling reveal that our system can be adjusted to yield different dynamics, including phase-shifted, antiphase or synchronized oscillations, as well as stable steady-state population densities. The 'ortholysis' approach establishes a paradigm for constructing synthetic ecologies by developing stable communities of competitive microorganisms without the need for engineered co-dependency.

Synchronized cycles of bacterial lysis for in vivo delivery

The pervasive view of bacteria as strictly pathogenic has given way to an appreciation of the widespread prevalence of beneficial microbes within the human body^1–3. Given this milieu, it is perhaps inevitable that some bacteria would evolve to preferentially grow in environments that harbor disease and thus provide a natural platform for the development of engineered therapies^4–6. Such therapies could benefit from bacteria that are programmed to limit bacterial growth while continually producing and releasing cytotoxic agents in situ^7–10. Here, we engineer a clinically relevant bacterium to lyse synchronously at a threshold population density and to release genetically encoded cargo. Following quorum lysis, a small number of surviving bacteria reseed the growing population, thus leading to pulsatile delivery cycles. We use microfluidic devices to characterize the engineered lysis strain and we demonstrate its potential as a drug delivery platform via co-culture with human cancer cells in vitro. As a proof of principle, we track the bacterial population dynamics in ectopic syngeneic colorectal tumors in mice. The lysis strain exhibits pulsatile population dynamics in vivo, with mean bacterial luminescence that remained two orders of magnitude lower than an unmodified strain. Finally, guided by previous findings that certain bacteria can enhance the efficacy of standard therapies¹¹, we orally administer the lysis strain, alone or in combination with a clinical chemotherapeutic, to a syngeneic transplantation model of hepatic colorectal metastases. We find that the combination of both circuit-engineered bacteria and chemotherapy leads to a notable reduction of tumor activity along with a marked survival benefit over either therapy alone. Our approach establishes a methodology for leveraging the tools of synthetic biology to exploit the natural propensity for certain bacteria to colonize disease sites.

Build to understand: synthetic approaches to biology

In this review we discuss how synthetic biology facilitates the task of investigating genetic circuits that are observed in naturally occurring biological systems. Specifically, we give examples where experimentation with synthetic gene circuits has been used to understand four fundamental mechanisms intrinsic to development and disease: multistability, stochastic gene expression, oscillations, and cell-cell communication. Within each area, we also discuss how mathematical modeling has been employed as an essential tool to guide the design of novel gene circuits and as a theoretical basis for exploring circuit topologies exhibiting robust behaviors in the presence of noise.

Circumvention of Learning Increases Intoxication Efficacy of Nematicidal Engineered Bacteria

Synthetic biology holds promise to engineer systems to treat diseases. One critical, yet underexplored, facet of designing such systems is the interplay between the system and the pathogen. Understanding this interplay may be critical to increasing efficacy and overcoming resistance against the system. Using the principles of synthetic biology, we engineer a strain of Escherichia coli to attract and intoxicate the nematode Caenorhabditis elegans. Our bacteria are engineered with a toxin module, which intoxicates the nematode upon ingestion, and an attraction module, which serves to attract and increase the feeding rate of the nematodes. When independently implemented, these modules successfully intoxicate and attract the worms, respectively. However, in combination, the efficacy of our bacteria is significantly reduced due to aversive associative learning in C. elegans. Guided by mathematical modeling, we dynamically regulate module induction to increase intoxication by circumventing learning. Our results detail the creation of a novel nematicidal bacterium that may have application against nematodes, unravel unique constraints on circuit dynamics that are governed by C. elegans physiology, and add to the growing list of design and implementation considerations associated with synthetic biology.

Addressing biological uncertainties in engineering gene circuits

Synthetic biology has grown tremendously over the past fifteen years. It represents a new strategy to develop biological understanding and holds great promise for diverse practical applications. Engineering of a gene circuit typically involves computational design of the circuit, selection of circuit components, and test and optimization of circuit functions. A fundamental challenge in this process is the predictable control of circuit function due to multiple layers of biological uncertainties. These uncertainties can arise from different sources. We categorize these uncertainties into incomplete quantification of parts, interactions between heterologous components and the host, or stochastic dynamics of chemical reactions and outline potential design strategies to minimize or exploit them.

A noisy linear map underlies oscillations in cell size and gene expression in bacteria

During bacterial growth, a cell approximately doubles in size before division, after which it splits into two daughter cells. This process is subjected to the inherent perturbations of cellular noise and thus requires regulation for cell-size homeostasis. The mechanisms underlying the control and dynamics of cell size remain poorly understood owing to the difficulty in sizing individual bacteria over long periods of time in a high-throughput manner. Here we measure and analyse long-term, single-cell growth and division across different Escherichia coli strains and growth conditions. We show that a subset of cells in a population exhibit transient oscillations in cell size with periods that stretch across several (more than ten) generations. Our analysis reveals that a simple law governing cell-size control-a noisy linear map-explains the origins of these cell-size oscillations across all strains. This noisy linear map implements a negative feedback on cell-size control: a cell with a larger initial size tends to divide earlier, whereas one with a smaller initial size tends to divide later. Combining simulations of cell growth and division with experimental data, we demonstrate that this noisy linear map generates transient oscillations, not just in cell size, but also in constitutive gene expression. Our work provides new insights into the dynamics of bacterial cell-size regulation with implications for the physiological processes involved.

Dynamic control and quantification of bacterial population dynamics in droplets

Culturing and measuring bacterial population dynamics are critical to develop insights into gene regulation or bacterial physiology. Traditional methods, based on bulk culture to obtain such quantification, have the limitations of higher cost/volume of reagents, non-amendable to small size of population and more laborious manipulation. To this end, droplet-based microfluidics represents a promising alternative that is cost-effective and high-throughput. However, difficulties in manipulating the droplet environment and monitoring encapsulated bacterial population for long-term experiments limit its utilization. To overcome these limitations, we used an electrode-free injection technology to modulate the chemical environment in droplets. This ability is critical for precise control of bacterial dynamics in droplets. Moreover, we developed a trapping device for long-term monitoring of population dynamics in individual droplets for at least 240 h. We demonstrated the utility of this new microfluidic system by quantifying population dynamics of natural and engineered bacteria. Our approach can further improve the analysis for systems and synthetic biology in terms of manipulability and high temporal resolution.

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.

Synthetic biological networks

Despite their obvious relationship and overlap, the field of physics is blessed with many insightful laws, while such laws are sadly absent in biology. Here we aim to discuss how the rise of a more recent field known as synthetic biology may allow us to more directly test hypotheses regarding the possible design principles of natural biological networks and systems. In particular, this review focuses on synthetic gene regulatory networks engineered to perform specific functions or exhibit particular dynamic behaviors. Advances in synthetic biology may set the stage to uncover the relationship of potential biological principles to those developed in physics.

Hidden hysteresis - population dynamics can obscure gene network dynamics

Background

Positive feedback is a common motif in gene regulatory networks. It can be used in synthetic networks as an amplifier to increase the level of gene expression, as well as a nonlinear module to create bistable gene networks that display hysteresis in response to a given stimulus. Using a synthetic positive feedback-based tetracycline sensor in E. coli, we show that the population dynamics of a cell culture has a profound effect on the observed hysteretic response of a population of cells with this synthetic gene circuit.

Results

The amount of observable hysteresis in a cell culture harboring the gene circuit depended on the initial concentration of cells within the culture. The magnitude of the hysteresis observed was inversely related to the dilution procedure used to inoculate the subcultures; the higher the dilution of the cell culture, lower was the observed hysteresis of that culture at steady state. Although the behavior of the gene circuit in individual cells did not change significantly in the different subcultures, the proportion of cells exhibiting high levels of steady-state gene expression did change.

Although the interrelated kinetics of gene expression and cell growth are unpredictable at first sight, we were able to resolve the surprising dilution-dependent hysteresis as a result of two interrelated phenomena - the stochastic switching between the ON and OFF phenotypes that led to the cumulative failure of the gene circuit over time, and the nonlinear, logistic growth of the cell in the batch culture.

Conclusions

These findings reinforce the fact that population dynamics cannot be ignored in analyzing the dynamics of gene networks. Indeed population dynamics may play a significant role in the manifestation of bistability and hysteresis, and is an important consideration when designing synthetic gene circuits intended for long-term application.

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.

A programmable microenvironment for cellular studies via microfluidics-generated double emulsions

High throughput cellular studies require small sample volume to reduce costs and enhance sensitivity. Microfluidics-generated water-in-oil (W/O) single emulsion droplet systems, in particular, provide uniform, well defined and discrete microenvironment for cell culture, screening, and sorting. However, these single emulsion droplets are incapable of continuous supply of nutrient molecule and are not compatible with aqueous phase-based analysis. A solution is to entrap W/O droplets in another aqueous phase, forming water-in-oil-in-water (W/O/W) double emulsions. The external aqueous phase efficiently prevents desiccation and reduces the amount of organic component, and yet retaining the advantages of compartmentalization. The internal environment can also be programmed dynamically without the need of rupturing the droplets. In this study, we explore the potential application of W/O/W double emulsion droplets for cell cultivation, genetic activation and study of more complicated biological events such as bacteria quorum-sensing as an example. This study demonstrates the advantages and potential application of double emulsion for the study of complex biological processes.

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.

Engineering microbial systems to explore ecological and evolutionary dynamics

A major goal of biological research is to provide a mechanistic understanding of diverse biological processes. To this end, synthetic biology offers a powerful approach, whereby biological questions can be addressed in a well-defined framework. By constructing simple gene circuits, such studies have generated new insights into the design principles of gene regulatory networks. Recently, this strategy has been applied to analyze ecological and evolutionary questions, where population-level interactions are critical. Here, we highlight recent development of such systems and discuss how they were used to address problems in ecology and evolutionary biology. As illustrated by these examples, synthetic ecosystems provide a unique platform to study ecological and evolutionary phenomena that are challenging to study in their natural contexts.

A synthetic biology approach to understanding cellular information processing

The survival of cells and organisms requires proper responses to environmental signals. These responses are governed by cellular networks, which serve to process diverse environmental cues. Biological networks often contain recurring network topologies called "motifs". It has been recognized that the study of such motifs allows one to predict the response of a biological network and thus cellular behavior. However, studying a single motif in complete isolation of all other network motifs in a natural setting is difficult. Synthetic biology has emerged as a powerful approach to understanding the dynamic properties of network motifs. In addition to testing existing theoretical predictions, construction and analysis of synthetic gene circuits has led to the discovery of novel motif dynamics, such as how the combination of simple motifs can lead to autonomous dynamics or how noise in transcription and translation can affect the dynamics of a motif. Here, we review developments in synthetic biology as they pertain to increasing our understanding of cellular information processing. We highlight several types of dynamic behaviors that diverse motifs can generate, including the control of input/output responses, the generation of autonomous spatial and temporal dynamics, as well as the influence of noise in motif dynamics and cellular behavior.

The PLOS ONE synthetic biology collection: six years and counting

Since it was launched in 2006, PLOS ONE has published over fifty articles illustrating the many facets of the emerging field of synthetic biology. This article reviews these publications by organizing them into broad categories focused on DNA synthesis and assembly techniques, the development of libraries of biological parts, the use of synthetic biology in protein engineering applications, and the engineering of gene regulatory networks and metabolic pathways. Finally, we review articles that describe enabling technologies such as software and modeling, along with new instrumentation. In order to increase the visibility of this body of work, the papers have been assembled into the PLOS ONE Synthetic Biology Collection (www.ploscollections.org/synbio). Many of the innovative features of the PLOS ONE web site will help make this collection a resource that will support a lively dialogue between readers and authors of PLOS ONE synthetic biology papers. The content of the collection will be updated periodically by including relevant articles as they are published by the journal. Thus, we hope that this collection will continue to meet the publishing needs of the synthetic biology community.

Competition for catalytic resources alters biological network dynamics

Genetic regulation networks orchestrate many complex cellular behaviors. Dynamic operations that take place within cells are thus dependent on the gene expression machinery, enabled by powerful enzymes such as polymerases, ribosomes, or nucleases. These generalist enzymes typically process many different substrates, potentially leading to competitive situations: by saturating the common enzyme, one substrate may down-regulate its competitors. However, most theoretical or experimental models simply omit these effects, focusing on the pattern of genetic regulatory interactions as the main determinant of network function. We show here that competition effects have important outcomes, which can be spotted within the global dynamics of experimental systems. Further we demonstrate that enzyme saturation creates a layer of cross couplings that may foster, but also hamper, the expected behavior of synthetic biology constructs.

Quantitative analysis of the spatiotemporal dynamics of a synthetic predator-prey ecosystem

A major focus in synthetic biology is the rational design and implementation of gene circuits to control dynamics of individual cells and, increasingly, cellular populations. Population-level control is highlighted in recent studies which attempt to design and implement synthetic ecosystems (or engineered microbial consortia). On the one hand, these engineered systems may serve as a critical technological foundation for practical applications. On the other hand, they may serve as well-defined model systems to examine biological questions of broad relevance. Here, using a synthetic predator-prey ecosystem as an example, we illustrate the basic experimental techniques involved in system implementation and characterization. By extension, these techniques are applicable to the analysis of other microbial-based synthetic or natural ecosystems.

Programming microbial population dynamics by engineered cell-cell communication

A major aim of synthetic biology is to program novel cellular behavior using engineered gene circuits. Early endeavors focused on building simple circuits that fulfill simple functions, such as logic gates, bistable toggle switches, and oscillators. These gene circuits have primarily focused on single-cell behaviors since they operate intracellularly. Thus, they are often susceptible to cell-cell variations due to stochastic gene expression. Cell-cell communication offers an efficient strategy to coordinate cellular behavior at the population level. To this end, we review recent advances in engineering cell-cell communication to achieve reliable population dynamics, spanning from communication within single species to multispecies, from one-way sender-receiver communication to two-way communication in synthetic microbial ecosystems. These engineered systems serve as well-defined model systems to better understand design principles of their naturally occurring counterparts and to facilitate novel biotechnology applications.

Growth-rate dependence reveals design principles of plasmid copy number control

Genetic circuits in bacteria are intimately coupled to the cellular growth rate as many parameters of gene expression are growth-rate dependent. Growth-rate dependence can be particularly pronounced for genes on plasmids; therefore the native regulatory systems of a plasmid such as its replication control system are characterized by growth-rate dependent parameters and regulator concentrations. This natural growth-rate dependent variation of regulator concentrations can be used for a quantitative analysis of the design of such regulatory systems. Here we analyze the growth-rate dependence of parameters of the copy number control system of ColE1-type plasmids in E. coli. This analysis allows us to infer the form of the control function and suggests that the Rom protein increases the sensitivity of control.

Using noisy gene expression mediated by engineered adenovirus to probe signaling dynamics in mammalian cells

Perturbations from environmental, genetic, and pharmacological sources can generate heterogeneous biological responses, even in genetically identical cells. Although these differences have important consequences on cell physiology and survival, they are often subsumed in measurements that average over the population. Here, we describe in detail how variability in adenoviral-mediated gene expression provides an effective means to map dose responses of signaling pathways. Cell-cell variability is inherent in gene delivery methods used in cell biology, which makes this approach adaptable to many existing experimental systems. We also discuss strategies to quantify biologically relevant inputs and outputs.