Synthetic cooperation in engineered yeast populations

Engineering ecosystems and synthetic ecologies

Microbial ecosystems play an important role in nature. Engineering these systems for industrial, medical, or biotechnological purposes are important pursuits for synthetic biologists and biological engineers moving forward. Here we provide a review of recent progress in engineering natural and synthetic microbial ecosystems. We highlight important forward engineering design principles, theoretical and quantitative models, new experimental and manipulation tools, and possible applications of microbial ecosystem engineering. We argue that simply engineering individual microbes will lead to fragile homogenous populations that are difficult to sustain, especially in highly heterogeneous and unpredictable environments. Instead, engineered microbial ecosystems are likely to be more robust and able to achieve complex tasks at the spatial and temporal resolution needed for truly programmable biology.

Competition, not cooperation, dominates interactions among culturable microbial species

Microbial cells secrete numerous enzymes, scavenging molecules, and signals that can promote the growth and survival of other cells around them [1-4]. This observation is consistent with the evolution of cooperation within species [5], and there is now an increasing emphasis on the importance of cooperation between different microbial species [4, 6]. We lack, however, a systematic test of the importance of mutually positive interactions between different species, which is vital for assessing the commonness and importance of cooperative evolution in natural communities. Here, we study the extent of mutually positive interaction among bacterial strains isolated from a common aquatic environment. Using data collected from two independent experiments evaluating community productivity across diversity gradients, we show that (1) in pairwise species combinations, the great majority of interactions are net negative and (2) there is no evidence that strong higher-order positive effects arise when more than two species are mixed together. Our data do not exclude the possibility of positive effects in one direction where one species gains at the expense of another, i.e., predator-prey-like interactions. However, these do not constitute cooperation and our analysis suggests that the typical result of adaptation to other microbial species will be competitive, rather than cooperative, phenotypes.

Neutrophils and macrophages: the main partners of phagocyte cell systems

Biological cellular systems are groups of cells sharing a set of characteristics, mainly key function and origin. Phagocytes are crucial in the host defense against microbial infection. The previously proposed phagocyte cell systems including the most recent and presently prevailing one, the mononuclear phagocyte system (MPS), grouped mononuclear cells but excluded neutrophils, creating an unacceptable situation. As neutrophils are archetypical phagocytes that must be members of comprehensive phagocyte systems, Silva recently proposed the creation of a myeloid phagocyte system (MYPS) that adds neutrophils to the MPS. The phagocytes grouped in the MYPS include the leukocytes neutrophils, inflammatory monocytes, macrophages, and immature myeloid DCs. Here the justifications behind the inclusion of neutrophils in a phagocyte system is expanded and the MYPS are further characterized as a group of dedicated phagocytic cells that function in an interacting and cooperative way in the host defense against microbial infection. Neutrophils and macrophages are considered the main arms of this system.

Synthetic approaches to understanding biological constraints

Microbes can be readily cultured and their genomes can be easily manipulated. For these reasons, laboratory systems of unicellular organisms are increasingly used to develop and test theories about biological constraints, which manifest themselves at different levels of biological organization, from optimal gene-expression levels to complex individual and social behaviors. The quantitative description of biological constraints has recently advanced in several areas, such as the formulation of global laws governing the entire economy of a cell, the direct experimental measurement of the trade-offs leading to optimal gene expression, the description of naturally occurring fitness landscapes, and the appreciation of the requirements for a stable bacterial ecosystem.

Stochastic simulations of a synthetic bacteria-yeast ecosystem

BACKGROUND

The field of synthetic biology has greatly evolved and numerous functions can now be implemented by artificially engineered cells carrying the appropriate genetic information. However, in order for the cells to robustly perform complex or multiple tasks, co-operation between them may be necessary. Therefore, various synthetic biological systems whose functionality requires cell-cell communication are being designed. These systems, microbial consortia, are composed of engineered cells and exhibit a wide range of behaviors. These include yeast cells whose growth is dependent on one another, or bacteria that kill or rescue each other, synchronize, behave as predator-prey ecosystems or invade cancer cells.

RESULTS

In this paper, we study a synthetic ecosystem comprising of bacteria and yeast that communicate with and benefit from each other using small diffusible molecules. We explore the behavior of this heterogeneous microbial consortium, composed of Saccharomyces cerevisiae and Escherichia coli cells, using stochastic modeling. The stochastic model captures the relevant intra-cellular and inter-cellular interactions taking place in and between the eukaryotic and prokaryotic cells. Integration of well-characterized molecular regulatory elements into these two microbes allows for communication through quorum sensing. A gene controlling growth in yeast is induced by bacteria via chemical signals and vice versa. Interesting dynamics that are common in natural ecosystems, such as obligatory and facultative mutualism, extinction, commensalism and predator-prey like dynamics are observed. We investigate and report on the conditions under which the two species can successfully communicate and rescue each other.

CONCLUSIONS

This study explores the various behaviors exhibited by the cohabitation of engineered yeast and bacterial cells. The way that the model is built allows for studying the dynamics of any system consisting of two species communicating with one another via chemical signals. Therefore, key information acquired by our model may potentially drive the experimental design of various synthetic heterogeneous ecosystems.

Natural strategies for the spatial optimization of metabolism in synthetic biology

Metabolism is a highly interconnected web of chemical reactions that power life. Though the stoichiometry of metabolism is well understood, the multidimensional aspects of metabolic regulation in time and space remain difficult to define, model and engineer. Complex metabolic conversions can be performed by multiple species working cooperatively and exchanging metabolites via structured networks of organisms and resources. Within cells, metabolism is spatially regulated via sequestration in subcellular compartments and through the assembly of multienzyme complexes. Metabolic engineering and synthetic biology have had success in engineering metabolism in the first and second dimensions, designing linear metabolic pathways and channeling metabolic flux. More recently, engineering of the third dimension has improved output of engineered pathways through isolation and organization of multicell and multienzyme complexes. This review highlights natural and synthetic examples of three-dimensional metabolism both inter- and intracellularly, offering tools and perspectives for biological design.

Computational systems biology and in silico modeling of the human microbiome

The human microbiome is a complex biological system with numerous interacting components across multiple organizational levels. The assembly, ecology and dynamics of the microbiome and its contribution to the development, physiology and nutrition of the host are clearly affected not only by the set of genes or species in the microbiome but also by the way these genes are linked across numerous pathways and by the interactions between the various species. To date, however, most studies of the human microbiome have focused on characterizing the composition of the microbiome and on comparative analyses, whereas significantly less effort has been directed at elucidating, characterizing and modeling these interactions and on studying the microbiome as a complex, interconnected and cohesive system. Here, specifically, I highlight the pressing need for the development of predictive system-level models and for a system-level understanding of the microbiome, and discuss potential computational frameworks for metagenomic-based modeling of the microbiome at the cellular, ecological and supra-organismal level. I review some preliminary attempts at constructing such models and examine the challenges and hurdles that such modeling efforts face. I also discuss possible future applications and research avenues that such metagenomic systems biology and predictive system-level models may facilitate.

A programmable Escherichia coli consortium via tunable symbiosis

Synthetic microbial consortia that can mimic natural systems have the potential to become a powerful biotechnology for various applications. One highly desirable feature of these consortia is that they can be precisely regulated. In this work we designed a programmable, symbiotic circuit that enables continuous tuning of the growth rate and composition of a synthetic consortium. We implemented our general design through the cross-feeding of tryptophan and tyrosine by two E. coli auxotrophs. By regulating the expression of genes related to the export or production of these amino acids, we were able to tune the metabolite exchanges and achieve a wide range of growth rates and strain ratios. In addition, by inverting the relationship of growth/ratio vs. inducer concentrations, we were able to "program" the co-culture for pre-specified attributes with the proper addition of inducing chemicals. This programmable proof-of-concept circuit or its variants can be applied to more complex systems where precise tuning of the consortium would facilitate the optimization of specific objectives, such as increasing the overall efficiency of microbial production of biofuels or pharmaceuticals.

Towards synthetic microbial consortia for bioprocessing

The use of microbial consortia for bioprocessing has been limited by our ability to reliably control community composition and function simultaneously. Recent advances in synthetic biology have enabled population-level coordination and control of ecosystem stability and dynamics. Further, new experimental and computational tools for screening and predicting community behavior have also been developed. The integration of synthetic biology with metabolic engineering at the community level is vital to our ability to apply system-level approaches to building and optimizing synthetic consortia for bioprocessing applications. This review details new methods, tools and opportunities that together have the potential to enable a new paradigm of bioprocessing using synthetic microbial consortia.

OptCom: a multi-level optimization framework for the metabolic modeling and analysis of microbial communities

Microorganisms rarely live isolated in their natural environments but rather function in consolidated and socializing communities. Despite the growing availability of high-throughput sequencing and metagenomic data, we still know very little about the metabolic contributions of individual microbial players within an ecological niche and the extent and directionality of interactions among them. This calls for development of efficient modeling frameworks to shed light on less understood aspects of metabolism in microbial communities. Here, we introduce OptCom, a comprehensive flux balance analysis framework for microbial communities, which relies on a multi-level and multi-objective optimization formulation to properly describe trade-offs between individual vs. community level fitness criteria. In contrast to earlier approaches that rely on a single objective function, here, we consider species-level fitness criteria for the inner problems while relying on community-level objective maximization for the outer problem. OptCom is general enough to capture any type of interactions (positive, negative or combinations thereof) and is capable of accommodating any number of microbial species (or guilds) involved. We applied OptCom to quantify the syntrophic association in a well-characterized two-species microbial system, assess the level of sub-optimal growth in phototrophic microbial mats, and elucidate the extent and direction of inter-species metabolite and electron transfer in a model microbial community. We also used OptCom to examine addition of a new member to an existing community. Our study demonstrates the importance of trade-offs between species- and community-level fitness driving forces and lays the foundation for metabolic-driven analysis of various types of interactions in multi-species microbial systems using genome-scale metabolic models.

Developing symbiotic consortia for lignocellulosic biofuel production

The search for petroleum alternatives has motivated intense research into biological breakdown of lignocellulose to produce liquid fuels such as ethanol. Degradation of lignocellulose for biofuel production is a difficult process which is limited by, among other factors, the recalcitrance of lignocellulose and biological toxicity of the products. Consolidated bioprocessing has been suggested as an efficient and economical method of producing low value products from lignocellulose; however, it is not clear whether this would be accomplished more efficiently with a single organism or community of organisms. This review highlights examples of mixtures of microbes in the context of conceptual models for developing symbiotic consortia for biofuel production from lignocellulose. Engineering a symbiosis within consortia is a putative means of improving both process efficiency and stability relative to monoculture. Because microbes often interact and exist attached to surfaces, quorum sensing and biofilm formation are also discussed in terms of consortia development and stability. An engineered, symbiotic culture of multiple organisms may be a means of assembling a novel combination of metabolic capabilities that can efficiently produce biofuel from lignocellulose.

Programming stress-induced altruistic death in engineered bacteria

Programmed death is often associated with a bacterial stress response. This behavior appears paradoxical, as it offers no benefit to the individual. This paradox can be explained if the death is 'altruistic': the killing of some cells can benefit the survivors through release of 'public goods'. However, the conditions where bacterial programmed death becomes advantageous have not been unambiguously demonstrated experimentally. Here, we determined such conditions by engineering tunable, stress-induced altruistic death in the bacterium Escherichia coli. Using a mathematical model, we predicted the existence of an optimal programmed death rate that maximizes population growth under stress. We further predicted that altruistic death could generate the 'Eagle effect', a counter-intuitive phenomenon where bacteria appear to grow better when treated with higher antibiotic concentrations. In support of these modeling insights, we experimentally demonstrated both the optimality in programmed death rate and the Eagle effect using our engineered system. Our findings fill a critical conceptual gap in the analysis of the evolution of bacterial programmed death, and have implications for a design of antibiotic treatment.

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.

Reverse Ecology: from systems to environments and back

The structure of complex biological systems reflects not only their function but also the environments in which they evolved and are adapted to. Reverse Ecology-an emerging new frontier in Evolutionary Systems Biology-aims to extract this information and to obtain novel insights into an organism's ecology. The Reverse Ecology framework facilitates the translation of high-throughput genomic data into large-scale ecological data, and has the potential to transform ecology into a high-throughput field. In this chapter, we describe some of the pioneering work in Reverse Ecology, demonstrating how system-level analysis of complex biological networks can be used to predict the natural habitats of poorly characterized microbial species, their interactions with other species, and universal patterns governing the adaptation of organisms to their environments. We further present several studies that applied Reverse Ecology to elucidate various aspects of microbial ecology, and lay out exciting future directions and potential future applications in biotechnology, biomedicine, and ecological engineering.

Parts plus pipes: synthetic biology approaches to metabolic engineering

Synthetic biologists combine modular biological "parts" to create higher-order devices. Metabolic engineers construct biological "pipes" by optimizing the microbial conversion of basic substrates to desired compounds. Many scientists work at the intersection of these two philosophies, employing synthetic devices to enhance metabolic engineering efforts. These integrated approaches promise to do more than simply improve product yields; they can expand the array of products that are tractable to produce biologically. In this review, we explore the application of synthetic biology techniques to next-generation metabolic engineering challenges, as well as the emerging engineering principles for biological design.

A computational exploration of bacterial metabolic diversity identifying metabolic interactions and growth-efficient strain communities

Background

Metabolic interactions involve the exchange of metabolic products among microbial species. Most microbes live in communities and usually rely on metabolic interactions to increase their supply for nutrients and better exploit a given environment. Constraint-based models have successfully analyzed cellular metabolism and described genotype-phenotype relations. However, there are only a few studies of genome-scale multi-species interactions. Based on genome-scale approaches, we present a graph-theoretic approach together with a metabolic model in order to explore the metabolic variability among bacterial strains and identify and describe metabolically interacting strain communities in a batch culture consisting of two or more strains. We demonstrate the applicability of our approach to the bacterium E. coli across different single-carbon-source conditions.

Results

A different diversity graph is constructed for each growth condition. The graph-theoretic properties of the constructed graphs reflect the inherent high metabolic redundancy of the cell to single-gene knockouts, reveal mutant-hubs of unique metabolic capabilities regarding by-production, demonstrate consistent metabolic behaviors across conditions and show an evolutionary difficulty towards the establishment of polymorphism, while suggesting that communities consisting of strains specifically adapted to a given condition are more likely to evolve. We reveal several strain communities of improved growth relative to corresponding monocultures, even though strain communities are not modeled to operate towards a collective goal, such as the community growth and we identify the range of metabolites that are exchanged in these batch co-cultures.

Conclusions

This study provides a genome-scale description of the metabolic variability regarding by-production among E. coli strains under different conditions and shows how metabolic differences can be used to identify metabolically interacting strain communities. This work also extends the existing stoichiometric models in order to describe batch co-cultures and provides the extent of metabolic interactions in a strain community revealing their importance for growth.

Social interaction in synthetic and natural microbial communities

How do molecular networks at the single-cell level define collective cell behavior? This Review discusses recent studies on synthetic and natural microbial communities that dissect the molecular and dynamical mechanisms underlying microbial social evolution.

Social interaction among cells is essential for multicellular complexity. But how do molecular networks within individual cells confer the ability to interact? And how do those same networks evolve from the evolutionary conflict between individual- and population-level interests? Recent studies have dissected social interaction at the molecular level by analyzing both synthetic and natural microbial populations. These studies shed new light on the role of population structure for the evolution of cooperative interactions and revealed novel molecular mechanisms that stabilize cooperation among cells. New understanding of populations is changing our view of microbial processes, such as pathogenesis and antibiotic resistance, and suggests new ways to fight infection by exploiting social interaction. The study of social interaction is also challenging established paradigms in cancer evolution and immune system dynamics. Finding similar patterns in such diverse systems suggests that the same ‘social interaction motifs' may be general to many cell populations.

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.

How sulphate-reducing microorganisms cope with stress: lessons from systems biology

Sulphate-reducing microorganisms (SRMs) are a phylogenetically diverse group of anaerobes encompassing distinct physiologies with a broad ecological distribution. As SRMs have important roles in the biogeochemical cycling of carbon, nitrogen, sulphur and various metals, an understanding of how these organisms respond to environmental stresses is of fundamental and practical importance. In this Review, we highlight recent applications of systems biology tools in studying the stress responses of SRMs, particularly Desulfovibrio spp., at the cell, population, community and ecosystem levels. The syntrophic lifestyle of SRMs is also discussed, with a focus on system-level analyses of adaptive mechanisms. Such information is important for understanding the microbiology of the global sulphur cycle and for developing biotechnological applications of SRMs for environmental remediation, energy production, biocorrosion control, wastewater treatment and mineral recovery.

Ecosystems biology of microbial metabolism

The metabolic capabilities of many environmentally and medically important microbes can be quantitatively explored using systems biology approaches to metabolic networks. Yet, as we learn more about the complex microbe-microbe and microbe-environment interactions in microbial communities, it is important to understand whether and how system-level approaches can be extended to the ecosystem level. Here we summarize recent work that addresses these challenges at multiple scales, starting from two-species natural and synthetic ecology models, up to biosphere-level approaches. Among the many fascinating open challenges in this field is whether the integration of high throughput sequencing methods and mathematical models will help us capture emerging principles of ecosystem-level metabolic organization and evolution.

Microbial linguistics: perspectives and applications of microbial cell-to-cell communication

Inter-cellular communication via diffusible small molecules is a defining character not only of multicellular forms of life but also of single-celled organisms. A large number of bacterial genes are regulated by the change of chemical milieu mediated by the local population density of its own species or others. The cell density-dependent "autoinducer" molecules regulate the expression of those genes involved in genetic competence, biofilm formation and persistence, virulence, sporulation, bioluminescence, antibiotic production, and many others. Recent innovations in recombinant DNA technology and micro-/nano-fluidics systems render the genetic circuitry responsible for cell-to-cell communication feasible to and malleable via synthetic biological approaches. Here we review the current understanding of the molecular biology of bacterial intercellular communication and the novel experimental protocols and platforms used to investigate this phenomenon. A particular emphasis is given to the genetic regulatory circuits that provide the standard building blocks which constitute the syntax of the biochemical communication network. Thus, this review gives focus to the engineering principles necessary for rewiring bacterial chemo-communication for various applications, ranging from population-level gene expression control to the study of host-pathogen interactions.

Towards a synthetic chloroplast

Background

The evolution of eukaryotic cells is widely agreed to have proceeded through a series of endosymbiotic events between larger cells and proteobacteria or cyanobacteria, leading to the formation of mitochondria or chloroplasts, respectively. Engineered endosymbiotic relationships between different species of cells are a valuable tool for synthetic biology, where engineered pathways based on two species could take advantage of the unique abilities of each mutualistic partner.

Results

We explored the possibility of using the photosynthetic bacterium Synechococcus elongatus PCC 7942 as a platform for studying evolutionary dynamics and for designing two-species synthetic biological systems. We observed that the cyanobacteria were relatively harmless to eukaryotic host cells compared to Escherichia coli when injected into the embryos of zebrafish, Danio rerio, or taken up by mammalian macrophages. In addition, when engineered with invasin from Yersinia pestis and listeriolysin O from Listeria monocytogenes, S. elongatus was able to invade cultured mammalian cells and divide inside macrophages.

Conclusion

Our results show that it is possible to engineer photosynthetic bacteria to invade the cytoplasm of mammalian cells for further engineering and applications in synthetic biology. Engineered invasive but non-pathogenic or immunogenic photosynthetic bacteria have great potential as synthetic biological devices.

Using artificial systems to explore the ecology and evolution of symbioses

The web of life is weaved from diverse symbiotic interactions between species. Symbioses vary from antagonistic interactions such as competition and predation to beneficial interactions such as mutualism. What are the bases for the origin and persistence of symbiosis? What affects the ecology and evolution of symbioses? How do symbiotic interactions generate ecological patterns? How do symbiotic partners evolve and coevolve? Many of these questions are difficult to address in natural systems. Artificial systems, from abstract to living, have been constructed to capture essential features of natural symbioses and to address these key questions. With reduced complexity and increased controllability, artificial systems can serve as useful models for natural systems. We review how artificial systems have contributed to our understanding of symbioses.

Cooperative adaptation to establishment of a synthetic bacterial mutualism

To understand how two organisms that have not previously been in contact can establish mutualism, it is first necessary to examine temporal changes in their phenotypes during the establishment of mutualism. Instead of tracing back the history of known, well-established, natural mutualisms, we experimentally simulated the development of mutualism using two genetically-engineered auxotrophic strains of Escherichia coli, which mimic two organisms that have never met before but later establish mutualism. In the development of this synthetic mutualism, one strain, approximately 10 hours after meeting the partner strain, started oversupplying a metabolite essential for the partner's growth, eventually leading to the successive growth of both strains. This cooperative phenotype adaptively appeared only after encountering the partner strain but before the growth of the strain itself. By transcriptome analysis, we found that the cooperative phenotype of the strain was not accompanied by the local activation of the biosynthesis and transport of the oversupplied metabolite but rather by the global activation of anabolic metabolism. This study demonstrates that an organism has the potential to adapt its phenotype after the first encounter with another organism to establish mutualism before its extinction. As diverse organisms inevitably encounter each other in nature, this potential would play an important role in the establishment of a nascent mutualism in nature.

Emergent cooperation in microbial metabolism

Mixed microbial communities exhibit emergent biochemical properties not found in clonal monocultures. We report a new type of synthetic genetic interaction, synthetic mutualism in trans (SMIT), in which certain pairs of auxotrophic Escherichia coli mutants complement one another's growth by cross-feeding essential metabolites. We find significant metabolic synergy in 17% of 1035 such pairs tested, with SMIT partners identified throughout the metabolic network. Cooperative phenotypes show more growth on average by aiding the proliferation of their conjugate partner, thereby expanding the source of their own essential metabolites. We construct a quantitative, predictive, framework for describing SMIT interactions as governed by stoichiometric models of the metabolic networks of the interacting strains.

Dynamics in the mixed microbial concourse

Isolated, clonal populations of cells are rarely found in nature. The emergent properties of microbial consortia present a challenge for the systems approach to biology, as chances for competition, communication, or collaboration multiply with the number of interacting agents. This review focuses on recent work on intercourse within biofilms, among quorum-sensing populations, and between cross-feeding metabolic cooperators. New tools from synthetic biology allow microbial interactions to be designed and tightly controlled, creating valuable model systems. We address both natural and synthetic partnerships, with an emphasis on how system behaviors derive from the properties of their components. Essential features of microbial biology arose in the context of a very mixed culture and cannot be understood without unscrambling it.

Environments that induce synthetic microbial ecosystems

Interactions between microbial species are sometimes mediated by the exchange of small molecules, secreted by one species and metabolized by another. Both one-way (commensal) and two-way (mutualistic) interactions may contribute to complex networks of interdependencies. Understanding these interactions constitutes an open challenge in microbial ecology, with applications ranging from the human microbiome to environmental sustainability. In parallel to natural communities, it is possible to explore interactions in artificial microbial ecosystems, e.g. pairs of genetically engineered mutualistic strains. Here we computationally generate artificial microbial ecosystems without re-engineering the microbes themselves, but rather by predicting their growth on appropriately designed media. We use genome-scale stoichiometric models of metabolism to identify media that can sustain growth for a pair of species, but fail to do so for one or both individual species, thereby inducing putative symbiotic interactions. We first tested our approach on two previously studied mutualistic pairs, and on a pair of highly curated model organisms, showing that our algorithms successfully recapitulate known interactions, robustly predict new ones, and provide novel insight on exchanged molecules. We then applied our method to all possible pairs of seven microbial species, and found that it is always possible to identify putative media that induce commensalism or mutualism. Our analysis also suggests that symbiotic interactions may arise more readily through environmental fluctuations than genetic modifications. We envision that our approach will help generate microbe-microbe interaction maps useful for understanding microbial consortia dynamics and evolution, and for exploring the full potential of natural metabolic pathways for metabolic engineering applications.

An environment-sensitive synthetic microbial ecosystem

Microbial ecosystems have been widely used in industrial production, but the inter-relationships of organisms within them haven't been completely clarified due to complex composition and structure of natural microbial ecosystems. So it is challenging for ecologists to get deep insights on how ecosystems function and interplay with surrounding environments. But the recent progresses in synthetic biology show that construction of artificial ecosystems where relationships of species are comparatively clear could help us further uncover the meadow of those tiny societies. By using two quorum-sensing signal transduction circuits, this research designed, simulated and constructed a synthetic ecosystem where various population dynamics formed by changing environmental factors. Coherent experimental data and mathematical simulation in our study show that different antibiotics levels and initial cell densities can result in correlated population dynamics such as extinction, obligatory mutualism, facultative mutualism and commensalism. This synthetic ecosystem provides valuable information for addressing questions in ecology and may act as a chassis for construction of more complex microbial ecosystems.

Experimental evolution in yeast: a practical guide

Experimental evolution refers to a broad range of studies in which selection pressures are applied to populations. In some applications, particular traits are desired, while in others the subject of study is the mechanisms of evolution or the different modes of behavior between systems. This chapter will explore the range of studies falling under the experimental evolution umbrella, and their relative merits for different types of applications. Practical aspects of experimental evolution will also be discussed, including commercial suppliers, analysis methods, and best laboratory practices.

Novel cooperation experimentally evolved between species

Cooperation violates the view of "nature red in tooth and claw" that prevails in our understanding of evolution, yet examples of cooperation abound. Most work has focused on maintenance of cooperation within a single species through mechanisms such as kin selection. The factors necessary for the evolutionary origin of aiding unrelated individuals such as members of another species have not been experimentally tested. Here, I demonstrate that cooperation between species can be evolved in the laboratory if (1) there is preexisting reciprocation or feedback for cooperation, and (2) reciprocation is preferentially received by cooperative genotypes. I used a two species system involving Salmonella enterica ser. Typhimurium and an Escherichia coli mutant unable to synthesize an essential amino acid. In lactose media Salmonella consumes metabolic waste from E. coli, thus creating a mechanism of reciprocation for cooperation. Growth in a spatially structured environment assured that the benefits of cooperation were preferentially received by cooperative genotypes. Salmonella evolved to aid E. coli by excreting a costly amino acid, however this novel cooperation disappeared if the waste consumption or spatial structure were removed. This study builds on previous work to demonstrate an experimental origin of interspecific cooperation, and to test the factors necessary for such interactions to arise.

Rapid evolution of stability and productivity at the origin of a microbial mutualism

Mutualistic interactions are taxonomically and functionally diverse. Despite their ubiquity, however, the basic ecological and evolutionary processes underlying their origin and maintenance are poorly understood. A major reason for this is the lack of an experimentally tractable model system. We examine the evolution of an experimentally imposed obligate mutualism between sulfate-reducing and methanogenic microorganisms that have no known history of previous interaction. Twenty-four independent pairings (cocultures) of the bacterium Desulfovibrio vulgaris and the archaeon Methanococcus maripaludis were established and followed for 300 community doublings in two environments, one allowing for the development of a heterogeneous distribution of resources and the other not. Evolved cocultures grew up to 80% faster and were up to 30% more productive (biomass yield per mole of substrate) than the ancestors. The evolutionary process was marked by periods of significant instability leading to extinction of two of the cocultures, but it resulted in more stable, efficient, and productive mutualisms for most replicated pairings. Comparisons of evolved cocultures with those assembled from one evolved mutualist and one ancestral mutualist showed that evolution of both species contributed to improved productivity. Surprisingly, however, overall improvements in growth rate and yield were less than the sum of the individual contributions, suggesting antagonistic interactions between mutations from the coevolved populations. Physical constraints on the transfer of metabolites in the evolution environment affected the evolution of M. maripaludis, but not of D. vulgaris. Together, these results demonstrate that challenges can imperil nascent obligate mutualisms and demonstrate the evolutionary responses that enable their persistence and future evolution.

Microbial metropolis

Microorganisms can form tightly knit communities such as biofilms. Many others include marine snow, anaerobic digester granules, the ginger beer plant and bacterial colonies. This chapter is devoted to a survey of the main properties of these communities, with an emphasis on biofilms. We start with attachment to surfaces and the nature of adhesion. The growing community then forms within a matrix, generally of organic macromolecules. Inevitably the environment within such a matrix is different from that outside. Organisms respond by forming crowd-detection and response units; these quorum sensing systems act as switches between planktonic life and the dramatically altered conditions found inside microbial aggregates. The community then matures and changes and may even fail and disappear. Antimicrobial resistance is discussed as an example of multicellular behavior. The multicellular lifestyle has been modeled mathematically and responded to powerful molecular biological techniques. Latterly, microbial systems have been used as models for fundamental evolutionary processes, mostly because of their high rates of reproduction and the ease of genetic manipulation. The life of most microbes is a duality between the yin of the community and the yang of planktonic existence. Sadly far less research has been devoted to adaptation to free-living forms than in the opposite direction.

Spatiotemporal modulation of biodiversity in a synthetic chemical-mediated ecosystem

Biodiversity, or the relative abundance of species, measures the persistence of an ecosystem. To better understand its modulation, we analyzed the spatial and temporal dynamics of a synthetic, chemical-mediated ecosystem that consisted of two engineered Escherichia coli populations. Depending on the specific experimental conditions implemented, the dominant interaction between the two populations could be competition for nutrients or predation due to engineered communication. While the two types of interactions resulted in different spatial patterns, they demonstrated a common trend in terms of the modulation of biodiversity. Specifically, biodiversity decreased with increasing cellular motility if the segregation distance between the two populations was comparable to the length scale of the chemical-mediated interaction. Otherwise, biodiversity was insensitive to cellular motility. Our results suggested a simple criterion for predicting the modulation of biodiversity by habitat partitioning and cellular motility in chemical-mediated ecosystems.

Association between competition and obligate mutualism in a chemostat

In this paper, we consider a simple chemostat model involving two obligate mutualistic species feeding on a limiting substrate. Systems of differential equations are proposed as models of this association. A detailed qualitative analysis is carried out. We show the existence of a domain of coexistence, which is a set of initial conditions in which both species survive. We demonstrate, under certain supplementary assumptions, the uniqueness of the stable equilibrium point which corresponds to the coexistence of the two species.

Flipping DNA to generate and regulate microbial consortia

Communities of interdependent microbes, found in diverse natural contexts, have recently attracted the attention of bioengineers. Such consortia have potential applications in biosynthesis, with metabolic tasks distributed over several phenotypes, and in live-cell microbicide therapies where phenotypic diversity might aid in immune evasion. Here we investigate one route to generate synthetic microbial consortia and to regulate their phenotypic diversity, through programmed genetic interconversions. In our theoretical model, genotypes involve ordered combinations of DNA elements representing promoters, protein-coding genes, and transcription terminators; genotypic interconversions are driven by a recombinase enzyme that inverts DNA segments; and selectable phenotypes correspond to distinct patterns of gene expression. We analyze the microbial population as it evolves along a graph whose nodes are distinct genotypes and whose edges are interconversions. We show that the steady-state proportion of each genotype depends on its own growth advantage, as well as on its connectivity to other genotypes. Multiple phenotypes with identical or distinct growth rates can be indefinitely maintained in the population, while their proportion can be regulated by varying the rate of DNA flipping. Recombinase-based synthetic constructs have already been implemented; the graph-theoretic framework developed here will be useful in adapting them to generate microbial consortia.

Engineering multicellular systems by cell-cell communication

Synthetic biology encompasses the design of new biological parts and systems as well as the modulation of existing biological networks to generate novel functions. In recent years, increasing emphasis has been placed on the engineering of population-level behaviors using cell-cell communication. From the engineering perspective, cell-cell communication serves as a versatile regulatory module that enables coordination among cells in and between populations and facilitates the generation of reliable dynamics. In addition to exploring biological 'design principles' via the construction of increasingly complex dynamics, communication-based synthetic systems can be used as well-defined model systems to study ecological and social interactions such as competition, cooperation, and predation. Here we discuss the dynamic properties of cell-cell communication modules, how they can be engineered for synthetic circuit design, and applications of these systems.

The second wave of synthetic biology: from modules to systems

Synthetic biology is a research field that combines the investigative nature of biology with the constructive nature of engineering. Efforts in synthetic biology have largely focused on the creation and perfection of genetic devices and small modules that are constructed from these devices. But to view cells as true 'programmable' entities, it is now essential to develop effective strategies for assembling devices and modules into intricate, customizable larger scale systems. The ability to create such systems will result in innovative approaches to a wide range of applications, such as bioremediation, sustainable energy production and biomedical therapies.

Decoding biological principles using gene circuits

A major flavor of synthetic biology is the creation of artificial gene circuits to perform user-defined tasks. One aspect of this area is to realize ever-increasingly more complicated circuit behavior. Such efforts have led to the identification and evaluation of design strategies that enable robust control of dynamics in single cells and in cell populations. On the other hand, there is increasing emphasis on using artificial systems programmed by simple circuits to explore fundamental biological questions of broad significance.

Snowdrift game dynamics and facultative cheating in yeast

The origin of cooperation is a central challenge to our understanding of evolution1–3. Microbial interactions can be manipulated in ways that animal interactions cannot, thus leading to growing interest in microbial models of cooperation4–10 and competition11,12. In order for the budding yeast S. cerevisiae to grow on sucrose, the disaccharide must first be hydrolyzed by the enzyme invertase13,14. This hydrolysis reaction is performed outside of the cytoplasm in the periplasmic space between the plasma membrane and the cell wall. Here we demonstrate that the vast majority (~99%) of the monosaccharides created by sucrose hydrolysis diffuse away before they can be imported into the cell, thus making invertase production and secretion a cooperative behavior15,16. A mutant cheater strain that does not produce invertase is able to take advantage of and invade a population of wildtype cooperator cells. However, over a wide range of conditions, the wildtype cooperator can also invade a population of cheater cells. Therefore, we observe coexistence between the two strains in well-mixed culture at steady state resulting from the fact that rare strategies outperform common strategies—the defining features of what game theorists call the snowdrift game17. A model of the cooperative interaction incorporating nonlinear benefits explains the origin of this coexistence. We are able to alter the outcome of the competition by varying either the cost of cooperation or the glucose concentration in the media. Finally, we note that glucose repression of invertase expression in wildtype cells produces a strategy which is optimal for the snowdrift game—wildtype cells cooperate only when competing against cheater cells.

Simpson's paradox in a synthetic microbial system

The maintenance of "public" or "common good" producers is a major question in the evolution of cooperation. Because nonproducers benefit from the shared resource without bearing its cost of production, they may proliferate faster than producers. We established a synthetic microbial system consisting of two Escherichia coli strains of common-good producers and nonproducers. Depending on the population structure, which was varied by forming groups with different initial compositions, an apparently paradoxical situation could be attained in which nonproducers grew faster within each group, yet producers increased overall. We show that a simple way to generate the variance required for this effect is through stochastic fluctuations via population bottlenecks. The synthetic approach described here thus provides a way to study generic mechanisms of natural selection.