Spatiotemporal modulation of biodiversity in a synthetic chemical-mediated ecosystem

Construction of Synthetic Microbial Ecosystems and the Regulation of Population Proportion

With the development of synthetic biology, the design and application of microbial consortia have received increasing attention. However, the construction of synthetic ecosystems is still hampered by our limited ability to rapidly develop microbial consortia with the required dynamics and functions. By using modular design, we constructed synthetic competitive and symbiotic ecosystems with Escherichia coli. Two ecological relationships were realized by reconfiguring the layout between the communication and effect modules. Furthermore, we designed inducible synthetic ecosystems to regulate subpopulation ratios. With the addition of different inducers, a wide range of strain ratios between subpopulations was achieved. These inducible synthetic ecosystems enabled a larger volume of population regulation and simplified culture conditions. The synthetic ecosystems we constructed combined both basic and applied functionalities and expanded the toolkit of synthetic biology research.

Modulation of microbial community dynamics by spatial partitioning

Microbial communities inhabit spatial architectures that divide a global environment into isolated or semi-isolated local environments, which leads to the partitioning of a microbial community into a collection of local communities. Despite its ubiquity and great interest in related processes, how and to what extent spatial partitioning affects the structures and dynamics of microbial communities is poorly understood. Using modeling and quantitative experiments with simple and complex microbial communities, we demonstrate that spatial partitioning modulates the community dynamics by altering the local interaction types and global interaction strength. Partitioning promotes the persistence of populations with negative interactions but suppresses those with positive interactions. For a community consisting of populations with both positive and negative interactions, an intermediate level of partitioning maximizes the overall diversity of the community. Our results reveal a general mechanism underlying the maintenance of microbial diversity and have implications for natural and engineered communities.

Periodically Disturbing the Spatial Structure of Biofilms Can Affect the Production of an Essential Virulence Factor in Pseudomonas aeruginosa

Understanding the environmental factors that affect the production of virulence factors has major implications in evolution and medicine. While spatial structure is important in virulence factor production, observations of this relationship have occurred in undisturbed or continuously disturbed environments. However, natural environments are subject to periodic fluctuations, including changes in physical forces, which could alter the spatial structure of bacterial populations and impact virulence factor production. Using Pseudomonas aeruginosa PA14, we periodically applied a physical force to biofilms and examined production of pyoverdine. Intermediate frequencies of disturbance reduced the amount of pyoverdine produced compared to undisturbed or frequently disturbed conditions. To explore the generality of this finding, we examined how an intermediate disturbance frequency affected pyoverdine production in 21 different strains of P. aeruginosa. Periodic disturbance increased, decreased, or did not change the amount of pyoverdine produced relative to undisturbed populations. Mathematical modeling predicts that interactions between pyoverdine synthesis rate and biofilm density determine the amount of pyoverdine synthesized. When the pyoverdine synthesis rates are high, depletion of the biofilm due to disturbance reduces the accumulation of pyoverdine. At intermediate synthesis rates, production of pyoverdine increases during disturbance as bacteria dispersed into the planktonic state enjoy increased growth and pyoverdine production rates. At low synthesis rates, disturbance does not alter the amount of pyoverdine produced since disturbance-driven access to nutrients does not augment pyoverdine synthesis. Our results suggest that environmental conditions shape robustness in the production of virulence factors and may lead to novel approaches to treat infections.

IMPORTANCE Virulence factors are required to cause infections. Previous work has shown that the spatial organization of a population, such as a biofilm, can increase the production of some virulence factors, including pyoverdine, which is produced by Pseudomonas aeruginosa. Pyoverdine is essential for the infection process, and reducing its production can limit infections. We have discovered that periodically changing the spatial structure of a biofilm of P. aeruginosa strain PA14 using a physical force can reduce the production of pyoverdine. A mathematical model suggests that this is due to the disruption of spatial organization. Using additional strains of P. aeruginosa isolated from patients and the environment, we use experiments and modeling to show that this reduction in pyoverdine is due to interactions between biofilm density and the synthesis rate of pyoverdine. Our results identify conditions where pyoverdine production is reduced and may lead to novel ways to treat infections.

The spatial organization of microbial communities during range expansion

Microbes in nature often live in dense and diverse communities exhibiting a variety of spatial structures. Microbial range expansion is a universal ecological process that enables populations to form spatial patterns. It can be driven by both passive and active processes, for example, mechanical forces from cell growth and bacterial motility. In this review, we provide a taste of recent creative and sophisticated efforts being made to address basic questions in spatial ecology and pattern formation during range expansion. We especially highlight the role of motility to shape community structures, and discuss the research challenges and future directions.

Combinational quorum sensing devices for dynamic control in cross-feeding cocultivation

Quorum sensing (QS) offers cell density dependent dynamic regulations in cell culture through devices such as synchronized lysis circuit (SLC) and metabolic toggle switch (MTS). However, there is still a lack of studies on cocultivation with a combination of different QS-based devices. Taking the production of isopropanol and salidroside as case studies, we have mathematically modeled a comprehensive set of QS-regulated cocultivation schemes and constructed experimental combinations of QS devices, respectively, to evaluate their feasibility and optimality for regulating growth competition and corporative production. Glucose split ratio is proposed for the analysis of competition between cell growth and targeted production. Results show that the combination of different QS devices across multiple members offers a new tool with the potential to effectively coordinate synthetic microbial consortia for achieving high product titer in cross-feeding cocultivation. It is also evident that the performance of such systems is significantly affected by dynamic characteristics of chosen QS devices, carbon source control and the operational settings. This study offers insights for future applications of combinational QS devices in synthetic microbial consortia.

Projection Microstereolithographic Microbial Bioprinting for Engineered Biofilms

Microbes are critical drivers of all ecosystems and many biogeochemical processes, yet little is known about how the three-dimensional (3D) organization of these dynamic organisms contributes to their overall function. To probe how biofilm structure affects microbial activity, we developed a technique for patterning microbes in 3D geometries using projection stereolithography to bioprint microbes within hydrogel architectures. Bacteria were printed and monitored for biomass accumulation, demonstrating postprint viability of cells using this technique. We verified our ability to integrate biological and geometric complexity by fabricating a printed biofilm with two E. coli strains expressing different fluorescence. Finally, we examined the target application of microbial absorption of metal ions to investigate geometric effects on both the metal sequestration efficiency and the uranium sensing capability of patterned engineered Caulobacter crescentus strains. This work represents the first demonstration of the stereolithographic printing of microbials and presents opportunities for future work of engineered biofilms and other complex 3D structured cultures.

Survival of the weakest in non-transitive asymmetric interactions among strains of E. coli

Hierarchical organization in ecology, whereby interactions are nested in a manner that leads to a dominant species, naturally result in the exclusion of all but the dominant competitor. Alternatively, non-hierarchical competitive dynamics, such as cyclical interactions, can sustain biodiversity. Here, we designed a simple microbial community with three strains of E. coli that cyclically interact through (i) the inhibition of protein production, (ii) the digestion of genomic DNA, and (iii) the disruption of the cell membrane. We find that intrinsic differences in these three major mechanisms of bacterial warfare lead to an unbalanced community that is dominated by the weakest strain. We also use a computational model to describe how the relative toxin strengths, initial fractional occupancies, and spatial patterns affect the maintenance of biodiversity. The engineering of active warfare between microbial species establishes a framework for exploration of the underlying principles that drive complex ecological interactions.

The maintenance of ecological diversity depends on the strength and direction of competitive interactions, but these interactions are difficult to study in microbial communities. Here the authors use engineered E. coli strains to show that competitively weak strains can persist when pairwise interactions are asymmetrical.

Blue-Light-Switchable Bacterial Cell-Cell Adhesions Enable the Control of Multicellular Bacterial Communities

Although the fundamental importance and biotechnological potential of multibacterial communities, also called biofilms, are well-known, our ability to control them is limited. We present a new way of dynamically controlling bacteria-bacteria adhesions by using blue light and how these photoswitchable adhesions can be used to regulate multicellularity and associated bacterial behavior. To achieve this, the photoswitchable proteins nMagHigh and pMagHigh were expressed on bacterial surfaces as adhesins to allow multicellular clusters to assemble under blue light and reversibly disassemble in the dark. Regulation of the bacterial cell-cell adhesions with visible light provides unique advantages including high spatiotemporal control, tunability, and noninvasive remote regulation. Moreover, these photoswitchable adhesions make it possible to regulate collective bacterial functions including aggregation, quorum sensing, biofilm formation, and metabolic cross-feeding between auxotrophic bacteria with light. Overall, the photoregulation of bacteria-bacteria adhesions provides a new way of studying bacterial cell biology and will enable the design of biofilms for biotechnological applications.

Quorum sensing for population-level control of bacteria and potential therapeutic applications

Quorum sensing (QS), a microbial cell-to-cell communication process, dynamically regulates a variety of metabolism and physiological activities. In this review, we provide an update on QS applications based on autoinducer molecules including acyl-homoserine lactones (AHLs), auto-inducing peptides (AIPs), autoinducer 2 (AI-2) and indole in population-level control of bacteria, and highlight the potential in developing novel clinical therapies. We summarize the development in the combination of various genetic circuits such as genetic oscillators, toggle switches and logic gates with AHL-based QS devices in Gram-negative bacteria. An overview is then offered to the state-of-the-art of much less researched applications of AIP-based QS devices with Gram-positive bacteria, followed by a review of the applications of AI-2 and indole based QS for interspecies communication among microbial communities. Building on these general-purpose QS applications, we highlight the disruptions and manipulations of QS devices as potential clinical therapies for diseases caused by biofilm formation, antibiotic resistance and the phage invasion. The last part of reviewed literature is dedicated to mathematical modelling for QS applications. Finally, the key challenges and future perspectives of QS applications in monoclonal synthetic biology and synthetic ecology are discussed.

Formation of phage lysis patterns and implications on co-propagation of phages and motile host bacteria

Coexistence of bacteriophages, or phages, and their host bacteria plays an important role in maintaining the microbial communities. In natural environments with limited nutrients, motile bacteria can actively migrate towards locations of richer resources. Although phages are not motile themselves, they can infect motile bacterial hosts and spread in space via the hosts. Therefore, in a migrating microbial community coexistence of bacteria and phages implies their co-propagation in space. Here, we combine an experimental approach and mathematical modeling to explore how phages and their motile host bacteria coexist and co-propagate. When lytic phages encountered motile host bacteria in our experimental set up, a sector-shaped lysis zone formed. Our mathematical model indicates that local nutrient depletion and the resulting inhibition of proliferation and motility of bacteria and phages are the key to formation of the observed lysis pattern. The model further reveals the straight radial boundaries in the lysis pattern as a telltale sign for coexistence and co-propagation of bacteria and phages. Emergence of such a pattern, albeit insensitive to extrinsic factors, requires a balance between intrinsic biological properties of phages and bacteria, which likely results from coevolution of phages and bacteria.

Bacterial coexistence driven by motility and spatial competition

Elucidating elementary mechanisms that underlie bacterial diversity is central to ecology^1,2 and microbiome research³. Bacteria are known to coexist by metabolic specialization⁴, cooperation⁵ and cyclic warfare^6-8. Many species are also motile⁹, which is studied in terms of mechanism^10,11, benefit^12,13, strategy^14,15, evolution^16,17 and ecology^18,19. Indeed, bacteria often compete for nutrient patches that become available periodically or by random disturbances^2,20,21. However, the role of bacterial motility in coexistence remains unexplored experimentally. Here we show that-for mixed bacterial populations that colonize nutrient patches-either population outcompetes the other when low in relative abundance. This inversion of the competitive hierarchy is caused by active segregation and spatial exclusion within the patch: a small fast-moving population can outcompete a large fast-growing population by impeding its migration into the patch, while a small fast-growing population can outcompete a large fast-moving population by expelling it from the initial contact area. The resulting spatial segregation is lost for weak growth-migration trade-offs and a lack of virgin space, but is robust to population ratio, density and chemotactic ability, and is observed in both laboratory and wild strains. These findings show that motility differences and their trade-offs with growth are sufficient to promote diversity, and suggest previously undescribed roles for motility in niche formation and collective expulsion-containment strategies beyond individual search and survival.

Model reduction enables Turing instability analysis of large reaction-diffusion models

Synthesizing a genetic network which generates stable Turing patterns is one of the great challenges of synthetic biology, but a significant obstacle is the disconnect between the mathematical theory and the biological reality. Current mathematical understanding of patterning is typically restricted to systems of two or three chemical species, for which equations are tractable. However, when models seek to combine descriptions of intercellular signal diffusion and intracellular biochemistry, plausible genetic networks can consist of dozens of interacting species. In this paper, we suggest a method for reducing large biochemical systems that relies on removing the non-diffusible species, leaving only the diffusibles in the model. Such model reduction enables analysis to be conducted on a smaller number of differential equations. We provide conditions to guarantee that the full system forms patterns if the reduced system does, and vice versa. We confirm our technique with three examples: the Brusselator, an example proposed by Turing, and a biochemically plausible patterning system consisting of 17 species. These examples show that our method significantly simplifies the study of pattern formation in large systems where several species can be considered immobile.

Emerging strategies for engineering microbial communities

From biosynthesis to bioremediation, microbes have been engineered to address a variety of biotechnological applications. A promising direction in these endeavors is harnessing the power of designer microbial consortia that consist of multiple populations with well-defined interactions. Consortia can accomplish tasks that are difficult or potentially impossible to achieve using monocultures. Despite their potential, the rules underlying microbial community maintenance and function (i.e. the task the consortium is engineered to carry out) are not well defined, though rapid progress is being made. This limited understanding is in part due to the greater challenges associated with increased complexity when dealing with multi-population interactions. Here, we review key features and design strategies that emerge from the analysis of both natural and engineered microbial communities. These strategies can provide new insights into natural consortia and expand the toolbox available to engineers working to develop novel synthetic consortia.

Designing Spatially Distributed Gene Regulatory Networks To Elicit Contrasting Patterns

Pattern formation and differential interactions are important for microbial consortia to divide labor and perform complex functions. To obtain further insight into such interactions, we present a computational method for simulating physically separated microbial colonies, each implementing different gene regulatory networks. We validate our theory by experimentally demonstrating control over gene expression patterns in a diffusion-mediated lateral inhibition circuit. We highlight the importance of spatial arrangement as a control knob for modulating system behavior. Our systematic approach provides a foundation for future applications that require understanding and engineering of multistrain microbial communities for sophisticated, synergistic functions.

A unifying framework for interpreting and predicting mutualistic systems

Coarse-grained rules are widely used in chemistry, physics and engineering. In biology, however, such rules are less common and under-appreciated. This gap can be attributed to the difficulty in establishing general rules to encompass the immense diversity and complexity of biological systems. Furthermore, even when a rule is established, it is often challenging to map it to mechanistic details and to quantify these details. Here we report a framework that addresses these challenges for mutualistic systems. We first deduce a general rule that predicts the various outcomes of mutualistic systems, including coexistence and productivity. We further develop a standardized machine-learning-based calibration procedure to use the rule without the need to fully elucidate or characterize their mechanistic underpinnings. Our approach consistently provides explanatory and predictive power with various simulated and experimental mutualistic systems. Our strategy can pave the way for establishing and implementing other simple rules for biological systems.

Computing with biological switches and clocks

The complex dynamics of biological systems is primarily driven by molecular interactions that underpin the regulatory networks of cells. These networks typically contain positive and negative feedback loops, which are responsible for switch-like and oscillatory dynamics, respectively. Many computing systems rely on switches and clocks as computational modules. While the combination of such modules in biological systems leads to a variety of dynamical behaviours, it is also driving development of new computing algorithms. Here we present a historical perspective on computation by biological systems, with a focus on switches and clocks, and discuss parallels between biology and computing. We also outline our vision for the future of biological computing.

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.

Bacterially driven cadmium sulfide precipitation on porous membranes: Toward platforms for photocatalytic applications

The emerging field of biofabrication capitalizes on nature's ability to create materials with a wide range of well-defined physical and electronic properties. Particularly, there is a current push to utilize programmed, self-organization of living cells for material fabrication. However, much research is still necessary at the interface of synthetic biology and materials engineering to make biofabrication a viable technique to develop functional devices. Here, the authors exploit the ability of Escherichia coli to contribute to material fabrication by designing and optimizing growth platforms to direct inorganic nanoparticle (NP) synthesis, specifically cadmium sulfide (CdS) NPs, onto porous polycarbonate membranes. Additionally, current, nonbiological, chemical synthesis methods for CdS NPs are typically energy intensive and use high concentrations of hazardous cadmium precursors. Using biosynthesis methods through microorganisms could potentially alleviate these issues by precipitating NPs with less energy and lower concentrations of toxic precursors. The authors adopted extracellular precipitation strategies to form CdS NPs on the membranes as bacterial/membrane composites and characterized them by spectroscopic and imaging methods, including energy dispersive spectroscopy, and scanning and transmission electron microscopy. This method allowed us to control the localization of NP precipitation throughout the layered bacterial/membrane composite, by varying the timing of the cadmium precursor addition. Additionally, the authors demonstrated the photodegradation of methyl orange using the CdS functionalized porous membranes, thus confirming the photocatalytic properties of these composites for eventual translation to device development. If combined with the genetically programmed self-organization of cells, this approach promises to directly pattern CdS nanostructures on solid supports.

Synthetic microbial ecology and the dynamic interplay between microbial genotypes

Assemblages of microbial genotypes growing together can display surprisingly complex and unexpected dynamics and result in community-level functions and behaviors that are not readily expected from analyzing each genotype in isolation. This complexity has, at least in part, inspired a discipline of synthetic microbial ecology. Synthetic microbial ecology focuses on designing, building and analyzing the dynamic behavior of ‘ecological circuits’ (i.e. a set of interacting microbial genotypes) and understanding how community-level properties emerge as a consequence of those interactions. In this review, we discuss typical objectives of synthetic microbial ecology and the main advantages and rationales of using synthetic microbial assemblages. We then summarize recent findings of current synthetic microbial ecology investigations. In particular, we focus on the causes and consequences of the interplay between different microbial genotypes and illustrate how simple interactions can create complex dynamics and promote unexpected community-level properties. We finally propose that distinguishing between active and passive interactions and accounting for the pervasiveness of competition can improve existing frameworks for designing and predicting the dynamics of microbial assemblages.

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.

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.

Cooperation and competition shape ecological resistance during periodic spatial disturbance of engineered bacteria

Cooperation is fundamental to the survival of many bacterial species. Previous studies have shown that spatial structure can both promote and suppress cooperation. Most environments where bacteria are found are periodically disturbed, which can affect the spatial structure of the population. Despite the important role that spatial disturbances play in maintaining ecological relationships, it remains unclear as to how periodic spatial disturbances affect bacteria dependent on cooperation for survival. Here, we use bacteria engineered with a strong Allee effect to investigate how the frequency of periodic spatial disturbances affects cooperation. We show that at intermediate frequencies of spatial disturbance, the ability of the bacterial population to cooperate is perturbed. A mathematical model demonstrates that periodic spatial disturbance leads to a tradeoff between accessing an autoinducer and accessing nutrients, which determines the ability of the bacteria to cooperate. Based on this relationship, we alter the ability of the bacteria to access an autoinducer. We show that increased access to an autoinducer can enhance cooperation, but can also reduce ecological resistance, defined as the ability of a population to resist changes due to disturbance. Our results may have implications in maintaining stability of microbial communities and in the treatment of infectious diseases.

Bacterial Communities: Interactions to Scale

In the environment, bacteria live in complex multispecies communities. These communities span in scale from small, multicellular aggregates to billions or trillions of cells within the gastrointestinal tract of animals. The dynamics of bacterial communities are determined by pairwise interactions that occur between different species in the community. Though interactions occur between a few cells at a time, the outcomes of these interchanges have ramifications that ripple through many orders of magnitude, and ultimately affect the macroscopic world including the health of host organisms. In this review we cover how bacterial competition influences the structures of bacterial communities. We also emphasize methods and insights garnered from culture-dependent pairwise interaction studies, metagenomic analyses, and modeling experiments. Finally, we argue that the integration of multiple approaches will be instrumental to future understanding of the underlying dynamics of bacterial communities.

Design, analysis and application of synthetic microbial consortia

The rapid development of synthetic biology has conferred almost perfect modification on single cells, and provided methodological support for synthesizing microbial consortia, which have a much wider application potential than synthetic single cells. Co-cultivating multiple cell populations with rational strategies based on interacting relationships within natural microbial consortia provides theoretical as well as experimental support for the successful obtaining of synthetic microbial consortia, promoting it into extensive research on both industrial applications in plenty of areas and also better understanding of natural microbial consortia. According to their composition complexity, synthetic microbial consortia are summarized in three aspects in this review and are discussed in principles of design and construction, insights and methods for analysis, and applications in energy, healthcare, etc.

Antibiotics as a selective driver for conjugation dynamics

It is generally assumed that antibiotics can promote horizontal gene transfer. However, because of a variety of confounding factors that complicate the interpretation of previous studies, the mechanisms by which antibiotics modulate horizontal gene transfer remain poorly understood. In particular, it is unclear whether antibiotics directly regulate the efficiency of horizontal gene transfer, serve as a selection force to modulate population dynamics after such gene transfer has occurred, or both. Here, we address this question by quantifying conjugation dynamics in the presence and absence of antibiotic-mediated selection. Surprisingly, we find that sublethal concentrations of antibiotics from the most widely used classes do not significantly increase the conjugation efficiency. Instead, our modelling and experimental results demonstrate that conjugation dynamics are dictated by antibiotic-mediated selection, which can both promote and suppress conjugation dynamics. Our findings suggest that the contribution of antibiotics to the promotion of horizontal gene transfer may have been overestimated. These findings have implications for designing effective antibiotic treatment protocols and for assessing the risks of antibiotic use.

Coupling spatial segregation with synthetic circuits to control bacterial survival

Engineered bacteria have great potential for medical and environmental applications. Fulfilling this potential requires controllability over engineered behaviors and scalability of the engineered systems. Here, we present a platform technology, microbial swarmbot, which employs spatial arrangement to control the growth dynamics of engineered bacteria. As a proof of principle, we demonstrated a safeguard strategy to prevent unintended bacterial proliferation. In particular, we adopted several synthetic gene circuits to program collective survival in Escherichia coli: the engineered bacteria could only survive when present at sufficiently high population densities. When encapsulated by permeable membranes, these bacteria can sense the local environment and respond accordingly. The cells inside the microbial swarmbot capsules will survive due to their high densities. Those escaping from a capsule, however, will be killed due to a decrease in their densities. We demonstrate that this design concept is modular and readily generalizable. Our work lays the foundation for engineering integrated and programmable control of hybrid biological–material systems for diverse applications.

Molecular-Level Tuning of Cellular Autonomy Controls the Collective Behaviors of Cell Populations

A rigorous understanding of how multicellular behaviors arise from the actions of single cells requires quantitative frameworks that bridge the gap between genetic circuits, the arrangement of cells in space, and population-level behaviors. Here, we provide such a framework for a ubiquitous class of multicellular systems-namely, "secrete-and-sense cells" that communicate by secreting and sensing a signaling molecule. By using formal, mathematical arguments and introducing the concept of a phenotype diagram, we show how these cells tune their degrees of autonomous and collective behavior to realize distinct single-cell and population-level phenotypes; these phenomena have biological analogs, such as quorum sensing or paracrine signaling. We also define the "entropy of population," a measurement of the number of arrangements that a population of cells can assume, and demonstrate how a decrease in the entropy of population accompanies the formation of ordered spatial patterns. Our conceptual framework ties together diverse systems, including tissues and microbes, with common principles.

Bacterial social interactions drive the emergence of differential spatial colony structures

Background

Social interactions have been increasingly recognized as one of the major factors that contribute to the dynamics and function of bacterial communities. To understand their functional roles and enable the design of robust synthetic consortia, one fundamental step is to determine the relationship between the social interactions of individuals and the spatiotemporal structures of communities.

Results

We present a systematic computational survey on this relationship for two-species communities by developing and utilizing a hybrid computational framework that combines discrete element techniques with reaction-diffusion equations. We found that deleterious interactions cause an increased variance in relative abundance, a drastic decrease in surviving lineages, and a rough expanding front. In contrast, beneficial interactions contribute to a reduced variance in relative abundance, an enhancement in lineage number, and a smooth expanding front. We also found that mutualism promotes spatial homogeneity and population robustness while competition increases spatial segregation and population fluctuations. To examine the generality of these findings, a large set of initial conditions with varying density and species abundance was tested and analyzed. In addition, a simplified mathematical model was developed to provide an analytical interpretation of the findings.

Conclusions

This work advances our fundamental understanding of bacterial social interactions and population structures and, simultaneously, benefits synthetic biology for facilitated engineering of artificial microbial consortia.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-015-0188-5) contains supplementary material, which is available to authorized users.

Artificial cell-cell communication as an emerging tool in synthetic biology applications

Cell-cell communication is a widespread phenomenon in nature, ranging from bacterial quorum sensing and fungal pheromone communication to cellular crosstalk in multicellular eukaryotes. These communication modes offer the possibility to control the behavior of an entire community by modifying the performance of individual cells in specific ways. Synthetic biology, i.e., the implementation of artificial functions within biological systems, is a promising approach towards the engineering of sophisticated, autonomous devices based on specifically functionalized cells. With the growing complexity of the functions performed by such systems, both the risk of circuit crosstalk and the metabolic burden resulting from the expression of numerous foreign genes are increasing. Therefore, systems based on a single type of cells are no longer feasible. Synthetic biology approaches with multiple subpopulations of specifically functionalized cells, wired by artificial cell-cell communication systems, provide an attractive and powerful alternative. Here we review recent applications of synthetic cell-cell communication systems with a specific focus on recent advances with fungal hosts.

Slow and steady wins the race: a bacterial exploitative competition strategy in fluctuating environments

One promising frontier for synthetic biology is the development of synthetic ecologies, whereby interacting species form an additional layer of connectivity for engineered gene circuits. Toward this goal, an important step is to understand different types of bacterial interactions in natural settings, among which competition is the most prevalent. By constructing a two-species population dynamics model, here, we mimicked bacterial growth in nature with resource-limited fluctuating environments and searched for optimal strategies for bacterial exploitative competition. In a simple game with two strategy options (constant or susceptible growth), we found that the species playing the constant growth strategy always outplays or is evenly matched with its competitor, suggesting that constant growth is a "no-loss" good bet. We also showed that adoption of sophisticated strategies enables a species to maximize its fitness when its competitor grows susceptibly. The pursuit of fitness maximization is, however, associated with potential loss if both species are capable of strategy adjustment, indicating an intrinsic risk-return trade-off. These findings offer new insights into bacterial competition and may also facilitate the engineering of microbial consortia for synthetic biology applications.

Programming the group behaviors of bacterial communities with synthetic cellular communication

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

Synthetic microbial consortia: from systematic analysis to construction and applications

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

Biomedically relevant circuit-design strategies in mammalian synthetic biology

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

How to make a synthetic multicellular computer

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

Systems approaches for synthetic biology: a pathway toward mammalian design

We review methods of understanding cellular interactions through computation in order to guide the synthetic design of mammalian cells for translational applications, such as regenerative medicine and cancer therapies. In doing so, we argue that the challenges of engineering mammalian cells provide a prime opportunity to leverage advances in computational systems biology. We support this claim systematically, by addressing each of the principal challenges to existing synthetic bioengineering approaches—stochasticity, complexity, and scale—with specific methods and paradigms in systems biology. Moreover, we characterize a key set of diverse computational techniques, including agent-based modeling, Bayesian network analysis, graph theory, and Gillespie simulations, with specific utility toward synthetic biology. Lastly, we examine the mammalian applications of synthetic biology for medicine and health, and how computational systems biology can aid in the continued development of these applications.

Temporal control of self-organized pattern formation without morphogen gradients in bacteria

Diverse mechanisms have been proposed to explain biological pattern formation. Regardless of their specific molecular interactions, the majority of these mechanisms require morphogen gradients as the spatial cue, which are either predefined or generated as a part of the patterning process. However, using Escherichia coli programmed by a synthetic gene circuit, we demonstrate here the generation of robust, self-organized ring patterns of gene expression in the absence of an apparent morphogen gradient. Instead of being a spatial cue, the morphogen serves as a timing cue to trigger the formation and maintenance of the ring patterns. The timing mechanism enables the system to sense the domain size of the environment and generate patterns that scale accordingly. Our work defines a novel mechanism of pattern formation that has implications for understanding natural developmental processes.

Transferring a synthetic gene circuit from yeast to mammalian cells

The emerging field of synthetic biology builds gene circuits for scientific, industrial, and therapeutic needs. Adaptability of synthetic gene circuits across different organisms could enable a synthetic biology pipeline, where circuits are designed in silico, characterized in microbes and reimplemented in mammalian settings for practical usage. However, the processes affecting gene circuit adaptability have not been systematically investigated. Here we construct a mammalian version of a negative feedback-based “linearizer” gene circuit previously developed in yeast. The first naïve mammalian prototype was non-functional, but a computational model suggested that we could recover function by improving gene expression and protein localization. After rationally developing and combining new parts as the model suggested, we regained function and could tune target gene expression in human cells linearly and precisely as in yeast. The steps we have taken should be generally relevant for transferring any gene circuit from yeast into mammalian cells.

Modeling spatiotemporal dynamics of bacterial populations

Quantitative modeling of spatiotemporal dynamics of cells facilitates understanding and engineering of biological systems. Using a synthetic bacterial ecosystem as a workbench, we present the approach to mathematically simulate the spatiotemporal population dynamics of the ecosystem. A description of ecosystem's genetic construction and model development is firstly given. Parameter estimation and computational approach for the derived partial differential equations (PDEs) are then given. Spatiotemporal pattern formation is computed by numerically solving the PDE model. Biodiversity of the ecosystem and its impacts by cellular seeding distance and motility are computed according to the cell distribution patterns.

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.

Enhancing E. coli tolerance towards oxidative stress via engineering its global regulator cAMP receptor protein (CRP)

Oxidative damage to microbial hosts often occurs under stressful conditions during bioprocessing. Classical strain engineering approaches are usually both time-consuming and labor intensive. Here, we aim to improve E. coli performance under oxidative stress via engineering its global regulator cAMP receptor protein (CRP), which can directly or indirectly regulate redox-sensing regulators SoxR and OxyR, and other ~400 genes in E. coli. Error-prone PCR technique was employed to introduce modifications to CRP, and three mutants (OM1~OM3) were identified with improved tolerance via H(2)O(2) enrichment selection. The best mutant OM3 could grow in 12 mM H(2)O(2) with the growth rate of 0.6 h(-1), whereas the growth of wild type was completely inhibited at this H(2)O(2) concentration. OM3 also elicited enhanced thermotolerance at 48°C as well as resistance against cumene hydroperoxide. The investigation about intracellular reactive oxygen species (ROS), which determines cell viability, indicated that the accumulation of ROS in OM3 was always lower than in WT with or without H(2)O(2) treatment. Genome-wide DNA microarray analysis has shown not only CRP-regulated genes have demonstrated great transcriptional level changes (up to 8.9-fold), but also RpoS- and OxyR-regulated genes (up to 7.7-fold). qRT-PCR data and enzyme activity assay suggested that catalase (katE) could be a major antioxidant enzyme in OM3 instead of alkyl hydroperoxide reductase or superoxide dismutase. To our knowledge, this is the first work on improving E. coli oxidative stress resistance by reframing its transcription machinery through its native global regulator. The positive outcome of this approach may suggest that engineering CRP can be successfully implemented as an efficient strain engineering alternative for E. coli.