A programmable Escherichia coli consortium via tunable symbiosis

Automated adjustment of metabolic niches enables the control of natural and engineered microbial co-cultures

Much attention has focused on understanding microbial interactions leading to stable co-cultures. In this work, substrate pulsing was performed to promote better control of the metabolic niches (MNs) corresponding to each species, leading to the continuous co-cultivation of diverse microbial organisms. We used a cell-machine interface, which allows adjustment of the temporal profile of two MNs according to a rhythm, ensuring the successive growth of two species, in our case, a yeast and a bacterium. The resulting approach, called 'automated adjustment of metabolic niches' (AAMN), was effective for stabilizing both cooperative and competitive co-cultures. AAMN can be considered an enabling technology for the deployment of co-cultures in bioprocesses, demonstrated here based on the continuous bioproduction of p-coumaric acid. The data accumulated suggest that AAMN could be used not only for a wider range of biological systems, but also to gain fundamental insights into microbial interaction mechanisms.

Long-term homeostasis in microbial consortia via auxotrophic cross-feeding

Synthetic microbial consortia are collections of multiple strains or species of engineered organisms living in a shared ecosystem. Because they can separate metabolic tasks among different strains, synthetic microbial consortia have myriad applications in developing biomaterials, biomanufacturing, and biotherapeutics. However, synthetic consortia often require burdensome control mechanisms to ensure that the members of the community remain at the correct proportions. This is especially true in continuous culture systems in which slight differences in growth rates can lead to extinctions. Here, we present a simple method for controlling consortia proportions using cross-feeding in continuous auxotrophic co-culture. We use mutually auxotrophic E. coli with different essential gene deletions and regulate the growth rates of members of the consortium via cross-feeding of the missing nutrients in each strain. We demonstrate precise regulation of the co-culture steady-state ratio by exogenous addition of the missing nutrients. We also model the co-culture's behavior using a system of ordinary differential equations that enable us to predict its response to changes in nutrient concentrations. Our work provides a powerful tool for consortia proportion control with minimal metabolic costs to the constituent strains.

A Study of the Community Relationships Between Methanotrophs and Their Satellites Using Constraint-Based Modeling Approach

Biotechnology continues to drive innovation in the production of pharmaceuticals, biofuels, and other valuable compounds, leveraging the power of microbial systems for enhanced yield and sustainability. Genome-scale metabolic (GSM) modeling has become an essential approach in this field, which enables a guide for targeting genetic modifications and the optimization of metabolic pathways for various industrial applications. While single-species GSM models have traditionally been employed to optimize strains like Escherichia coli and Lactococcus lactis, the integration of these models into community-based approaches is gaining momentum. Herein, we present a pipeline for community metabolic modeling with a user-friendly GUI, applying it to analyze interactions between Methylococcus capsulatus, a biotechnologically important methanotroph, and Escherichia coli W3110 under oxygen- and nitrogen-limited conditions. We constructed models with unmodified and homoserine-producing E. coli strains using the pipeline implemented in the original BioUML platform. The E. coli strain primarily utilized acetate from M. capsulatus under oxygen limitation. However, homoserine produced by E. coli significantly reduced acetate secretion and the community growth rate. This homoserine was taken up by M. capsulatus, converted to threonine, and further exchanged as amino acids. In nitrogen-limited modeling conditions, nitrate and ammonium exchanges supported the nitrogen needs, while carbon metabolism shifted to fumarate and malate, enhancing E. coli TCA cycle activity in both cases, with and without modifications. The presence of homoserine altered cross-feeding dynamics, boosting amino acid exchanges and increasing pyruvate availability for M. capsulatus. These findings suggest that homoserine production by E. coli optimizes resource use and has potential for enhancing microbial consortia productivity.

Engineered cross-feeding creates inter- and intra-species synthetic yeast communities with enhanced bioproduction

Microorganisms can be engineered to sustainably produce a variety of products including fuels, pharmaceuticals, materials, and food. However, highly engineered strains often result in low production yield, due to undesired effects such as metabolic burden and the toxicity of intermediates. Drawing inspiration from natural ecosystems, the construction of a synthetic community with division of labor can offer advantages for bioproduction. This approach involves dividing specific tasks among community members, thereby enhancing the functionality of each member. In this study, we identify six pairs out of fifteen composed of six auxotrophs of Yarrowia lipolytica that spontaneously form robust syntrophic and synergistic communities. We characterize the stability and growth dynamics of these communities. Furthermore, we validate the existence of syntrophic interactions between two yeast species, Y. lipolytica and Saccharomyces cerevisiae, and find a strain combination, Δtrp2 and Δtrp4, forming a stable syntrophic community between two species. Subsequently, we introduce a 3-hydroxypropionic acid (3-HP) biosynthesis pathway into the syntrophic community by dividing the pathway among different strains. Our results demonstrate improved production of 3-HP in both intra- and interspecies communities compared to monocultures. Our results show the stable formation of synthetic syntrophic communities, and their potential in improving bioproduction processes.

Kinetics-based inference of environment-dependent microbial interactions and their dynamic variation

Microbial communities in nature are dynamically evolving as member species change their interactions subject to environmental variations. Accounting for such context-dependent dynamic variations in interspecies interactions is critical for predictive ecological modeling. In the absence of generalizable theoretical foundations, we lack a fundamental understanding of how microbial interactions are driven by environmental factors, significantly limiting our capability to predict and engineer community dynamics and function. To address this issue, we propose a novel theoretical framework that allows us to represent interspecies interactions as an explicit function of environmental variables (such as substrate concentrations) by combining growth kinetics and a generalized Lotka-Volterra model. A synergistic integration of these two complementary models leads to the prediction of alterations in interspecies interactions as the outcome of dynamic balances between positive and negative influences of microbial species in mixed relationships. The effectiveness of our method was experimentally demonstrated using a synthetic consortium of two Escherichia coli mutants that are metabolically dependent (due to an inability to synthesize essential amino acids) but competitively grow on a shared substrate. The analysis of the E. coli binary consortium using our model not only showed how interactions between the two amino acid auxotrophic mutants are controlled by the dynamic shifts in limiting substrates but also enabled quantifying previously uncharacterizable complex aspects of microbial interactions, such as asymmetry in interactions. Our approach can be extended to other ecological systems to model their environment-dependent interspecies interactions from growth kinetics.IMPORTANCEModeling environment-controlled interspecies interactions through separate identification of positive and negative influences of microbes in mixed relationships is a new capability that can significantly improve our ability to understand, predict, and engineer the complex dynamics of microbial communities. Moreover, the prediction of microbial interactions as a function of environmental variables can serve as valuable benchmark data to validate modeling and network inference tools in microbial ecology, the development of which has often been impeded due to the lack of ground truth information on interactions. While demonstrated against microbial data, the theory developed in this work is readily applicable to general community ecology to predict interactions among macroorganisms, such as plants and animals, as well as microorganisms.

Xylose and shikimate transporters facilitates microbial consortium as a chassis for benzylisoquinoline alkaloid production

Plant-sourced aromatic amino acid (AAA) derivatives are a vast group of compounds with broad applications. Here, we present the development of a yeast consortium for efficient production of (S)-norcoclaurine, the key precursor for benzylisoquinoline alkaloid biosynthesis. A xylose transporter enables the concurrent mixed-sugar utilization in Scheffersomyces stipitis, which plays a crucial role in enhancing the flux entering the highly regulated shikimate pathway located upstream of AAA biosynthesis. Two quinate permeases isolated from Aspergillus niger facilitates shikimate translocation to the co-cultured Saccharomyces cerevisiae that converts shikimate to (S)-norcoclaurine, resulting in the maximal titer (11.5 mg/L), nearly 110-fold higher than the titer reported for an S. cerevisiae monoculture. Our findings magnify the potential of microbial consortium platforms for the economical de novo synthesis of complex compounds, where pathway modularization and compartmentalization in distinct specialty strains enable effective fine-tuning of long biosynthetic pathways and diminish intermediate buildup, thereby leading to increases in production.

Construction of stable microbial consortia for effective biochemical synthesis

Microbial consortia can complete otherwise arduous tasks through the cooperation of multiple microbial species. This concept has been applied to produce commodity chemicals, natural products, and biofuels. However, metabolite incompatibility and growth competition can make the microbial composition unstable, and fluctuating microbial populations reduce the efficiency of chemical production. Thus, controlling the populations and regulating the complex interactions between different strains are challenges in constructing stable microbial consortia. This Review discusses advances in synthetic biology and metabolic engineering to control social interactions within microbial cocultures, including substrate separation, byproduct elimination, crossfeeding, and quorum-sensing circuit design. Additionally, this Review addresses interdisciplinary strategies to improve the stability of microbial consortia and provides design principles for microbial consortia to enhance chemical production.

Controlling microbial co-culture based on substrate pulsing can lead to stability through differential fitness advantages

Microbial consortia are an exciting alternative for increasing the performances of bioprocesses for the production of complex metabolic products. However, the functional properties of microbial communities remain challenging to control, considering the complex interaction mechanisms occurring between co-cultured microbial species. Indeed, microbial communities are highly dynamic and can adapt to changing environmental conditions through complex mechanisms, such as phenotypic diversification. We focused on stabilizing a co-culture of Saccharomyces cerevisiae and Escherichia coli in continuous cultures. Our preliminary data pointed out that transient diauxic shifts could lead to stable co-culture by providing periodic fitness advantages to the yeast. Based on a computational toolbox called MONCKS (for MONod-type Co-culture Kinetic Simulation), we were able to predict the dynamics of diauxic shift for both species based on a cybernetic approach. This toolbox was further used to predict the frequency of diauxic shift to be applied to reach co-culture stability. These simulations were successfully reproduced experimentally in continuous bioreactors with glucose pulsing. Finally, based on a bet-hedging reporter, we observed that the yeast population exhibited an increased phenotypic diversification process in co-culture compared with mono-culture, suggesting that this mechanism could be the basis of the metabolic fitness of the yeast.

Being able to manipulate the dynamics of microbial co-cultures is a technical challenge that need to be addressed in order to get a deeper insight about how microbial communities are evolving in their ecological context, as well as for exploiting the potential offered by such communities in an applied context e.g., for setting up more robust bioprocesses relying on the use of several microbial species. In this study, we used continuous cultures of bacteria (E. coli) and yeast (S. cerevisiae) in order to demonstrate that a simple nutrient pulsing strategy can be used for adjusting the composition of the community with time. As expected, during growth on glucose, E. coli quickly outcompeted S. cerevisiae. However, when glucose is pulsed into the culture, increased metabolic fitness of the yeast was observed upon reconsumption of the main side metabolites i.e., acetate and ethanol, leading to a robust oscillating growth profile for both species. The optimal pulsing frequency was predicted based on a cybernetic version of a Monod growth model taking into account the main metabolic routes involved in the process. Considering the limited number of metabolic details needed, this cybernetic approach could be generalized to other communities.

The effect of droplet size on syntrophic dynamics in droplet-enabled microbial co-cultivation

Co-cultivation in microfluidic droplets has emerged as a versatile tool for the study of natural and synthetic microbial communities. In particular, the identification and characterization of syntrophic interactions in these communities is attracting increasing interest due to their critical importance for the functioning of environmental and host-associated communities as well as new biotechnological applications. However, one critical parameter in droplet-enabled co-cultivation that has evaded appropriate evaluation is the droplet size. Given the same number of initial cells, a larger droplet size can increase the length scale secreted metabolites must diffuse as well as dilute the initial concentration of cells and exchanged metabolites, impacting the community dynamics. To evaluate the effect of droplet size on a spectrum of syntrophic interactions, we cultivated a synthetic model system consisting of two E. coli auxotrophs, whose interactions could be modulated through supplementation of related amino acids in the medium. Our results demonstrate that the droplet size impacts substantially numerous aspects of the growth of a cross-feeding bi-culture, particularly the growth capacity, maximum specific growth rate, and lag time, depending on the degree of the interaction. This work heavily suggests that one droplet size does not fit all types of interactions; this parameter should be carefully evaluated and chosen in experimental studies that aim to utilize droplet-enabled co-cultivation to characterize or elucidate microbial interactions.

Design of stable and self-regulated microbial consortia for chemical synthesis

Microbial coculture engineering has emerged as a promising strategy for biomanufacturing. Stability and self-regulation pose a significant challenge for the generation of intrinsically robust cocultures for large-scale applications. Here, we introduce the use of multi-metabolite cross-feeding (MMCF) to establish a close correlation between the strains and the design rules for selecting the appropriate metabolic branches. This leads to an intrinicially stable two-strain coculture where the population composition and the product titer are insensitive to the initial inoculation ratios. With an intermediate-responsive biosensor, the population of the microbial coculture is autonomously balanced to minimize intermediate accumulation. This static-dynamic strategy is extendable to three-strain cocultures, as demonstrated with de novo biosynthesis of silybin/isosilybin. This strategy is generally applicable, paving the way to the industrial application of microbial cocultures.

Stability and tunability are two desirable properties of microbial consortia-based bioproduction. Here, the authors integrate a caffeate-responsive biosensor into two and three strains coculture system to achieve autonomous regulation of strain ratios for coniferol and silybin/isosiltbin production, respectively.

De Novo Biosynthesis of D-p-Hydroxyphenylglycine by a Designed Cofactor Self-Sufficient Route and Co-culture Strategy

d-p-Hydroxyphenylglycine (D-HPG) is an important intermediate for the synthesis of β-lactam antibiotics with an annual market demand of thousands of tons. Currently, the main production processes are via chemical approaches. Although enzymatic conversion has been investigated for D-HPG production, synthesis of the substrate DL-hydroxyphenylhydantoin is still chemically based, which suffers from high pollution and harsh reaction conditions. In this study, one cofactor self-sufficient route for D-HPG production from l-phenylalanine was newly designed and the artificial pathway was functionalized by selecting suitable enzymes and adjusting their expressions in strain Pseudomonas putida KT2440. Notably, a new R-mandelate dehydrogenase from Lactococcus lactis with relatively high activity under pH neutral conditions was successfully mined to demonstrate the biosynthetic pathway in vivo. The performance of the engineered P. putida strain was further increased by enhancing cellular NAD availability and blocking l-phenylalanine consumption. Coupled with the l-phenylalanine producer, Escherichia coli strain ATCC 31884, a stable and interactive co-culture process was also developed by engineering a "cross-link auxotrophic" system to produce D-HPG directly from glucose. Thus, this study is the first approach for the de novo biosynthesis of D-HPG by engineering a non-natural pathway and lays the foundation for further improving the efficiency of D-HPG production via a green and sustainable route.

Construction of Environmental Synthetic Microbial Consortia: Based on Engineering and Ecological Principles

In synthetic biology, engineering principles are applied to system design. The development of synthetic microbial consortia represents the intersection of synthetic biology and microbiology. Synthetic community systems are constructed by co-cultivating two or more microorganisms under certain environmental conditions, with broad applications in many fields including ecological restoration and ecological theory. Synthetic microbial consortia tend to have high biological processing efficiencies, because the division of labor reduces the metabolic burden of individual members. In this review, we focus on the environmental applications of synthetic microbial consortia. Although there are many strategies for the construction of synthetic microbial consortia, we mainly introduce the most widely used construction principles based on cross-feeding. Additionally, we propose methods for constructing synthetic microbial consortia based on traits and spatial structure from the perspective of ecology to provide a basis for future work.

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.

Understanding Interaction Patterns within Deep-Sea Microbial Communities and Their Potential Applications

Environmental microbes living in communities engage in complex interspecies interactions that are challenging to decipher. Nevertheless, the interactions provide the basis for shaping community structure and functioning, which is crucial for ecosystem service. In addition, microbial interactions facilitate specific adaptation and ecological evolution processes particularly essential for microbial communities dwelling in resource-limiting habitats, such as the deep oceans. Recent technological and knowledge advancements provide an opportunity for the study of interactions within complex microbial communities, such as those inhabiting deep-sea waters and sediments. The microbial interaction studies provide insights into developing new strategies for biotechnical applications. For example, cooperative microbial interactions drive the degradation of complex organic matter such as chitins and celluloses. Such microbiologically-driven biogeochemical processes stimulate creative designs in many applied sciences. Understanding the interaction processes and mechanisms provides the basis for the development of synthetic communities and consequently the achievement of specific community functions. Microbial community engineering has many application potentials, including the production of novel antibiotics, biofuels, and other valuable chemicals and biomaterials. It can also be developed into biotechniques for waste processing and environmental contaminant bioremediation. This review summarizes our current understanding of the microbial interaction mechanisms and emerging techniques for inferring interactions in deep-sea microbial communities, aiding in future biotechnological and therapeutic applications.

Reprogramming microbial populations using a programmed lysis system to improve chemical production

Microbial populations are a promising model for achieving microbial cooperation to produce valuable chemicals. However, regulating the phenotypic structure of microbial populations remains challenging. In this study, a programmed lysis system (PLS) is developed to reprogram microbial cooperation to enhance chemical production. First, a colicin M -based lysis unit is constructed to lyse Escherichia coli. Then, a programmed switch, based on proteases, is designed to regulate the effective lysis unit time. Next, a PLS is constructed for chemical production by combining the lysis unit with a programmed switch. As a result, poly (lactate-co-3-hydroxybutyrate) production is switched from PLH synthesis to PLH release, and the content of free PLH is increased by 283%. Furthermore, butyrate production with E. coli consortia is switched from E. coli BUT003 to E. coli BUT004, thereby increasing butyrate production to 41.61 g/L. These results indicate the applicability of engineered microbial populations for improving the metabolic division of labor to increase the efficiency of microbial cell factories.

Assembling stable syntrophic Escherichia coli communities by comprehensively identifying beneficiaries of secreted goods

Metabolic cross-feeding frequently underlies mutualistic relationships in natural microbial communities and is often exploited to assemble synthetic microbial consortia. We systematically identified all single-gene knockouts suitable for imposing cross-feeding in Escherichia coli and used this information to assemble syntrophic communities. Most strains benefiting from shared goods were dysfunctional in biosynthesis of amino acids, nucleotides, and vitamins or mutants in central carbon metabolism. We tested cross-feeding potency in 1,444 strain pairs and mapped the interaction network between all functional groups of mutants. This network revealed that auxotrophs for vitamins are optimal cooperators. Lastly, we monitored how assemblies composed of dozens of auxotrophs change over time and observed that they rapidly and repeatedly coalesced to seven strain consortia composed primarily from vitamin auxotrophs. The composition of emerging consortia suggests that they were stabilized by multiple cross-feeding interactions. We conclude that vitamins are ideal shared goods since they optimize consortium growth while still imposing member co-dependence.

Emergent spatiotemporal population dynamics with cell-length control of synthetic microbial consortia

The increased complexity of synthetic microbial biocircuits highlights the need for distributed cell functionality due to concomitant increases in metabolic and regulatory burdens imposed on single-strain topologies. Distributed systems, however, introduce additional challenges since consortium composition and spatiotemporal dynamics of constituent strains must be robustly controlled to achieve desired circuit behaviors. Here, we address these challenges with a modeling-based investigation of emergent spatiotemporal population dynamics using cell-length control in monolayer, two-strain bacterial consortia. We demonstrate that with dynamic control of a strain's division length, nematic cell alignment in close-packed monolayers can be destabilized. We find that this destabilization confers an emergent, competitive advantage to smaller-length strains-but by mechanisms that differ depending on the spatial patterns of the population. We used complementary modeling approaches to elucidate underlying mechanisms: an agent-based model to simulate detailed mechanical and signaling interactions between the competing strains, and a reductive, stochastic lattice model to represent cell-cell interactions with a single rotational parameter. Our modeling suggests that spatial strain-fraction oscillations can be generated when cell-length control is coupled to quorum-sensing signaling in negative feedback topologies. Our research employs novel methods of population control and points the way to programming strain fraction dynamics in consortial synthetic biology.

Measurement Techniques to Resolve and Control Population Dynamics of Mixed-Culture Processes

Microbial mixed cultures are gaining increasing attention as biotechnological production systems, since they offer a large but untapped potential for future bioprocesses. Effects of secondary metabolite induction and advantages of labor division for the degradation of complex substrates offer new possibilities for process intensification. However, mixed cultures are highly complex, and, consequently, many biotic and abiotic parameters are required to be identified, characterized, and ideally controlled to establish a stable bioprocess. In this review, we discuss the advantages and disadvantages of existing measurement techniques for identifying, characterizing, monitoring, and controlling mixed cultures and highlight promising examples. Moreover, existing challenges and emerging technologies are discussed, which lay the foundation for novel analytical workflows to monitor mixed-culture bioprocesses.

Automated design of synthetic microbial communities

Microbial species rarely exist in isolation. In naturally occurring microbial systems there is strong evidence for a positive relationship between species diversity and productivity of communities. The pervasiveness of these communities in nature highlights possible advantages for genetically engineered strains to exist in cocultures as well. Building synthetic microbial communities allows us to create distributed systems that mitigate issues often found in engineering a monoculture, especially as functional complexity increases. Here, we demonstrate a methodology for designing robust synthetic communities that include competition for nutrients, and use quorum sensing to control amensal bacteriocin interactions in a chemostat environment. We computationally explore all two- and three- strain systems, using Bayesian methods to perform model selection, and identify the most robust candidates for producing stable steady state communities. Our findings highlight important interaction motifs that provide stability, and identify requirements for selecting genetic parts and further tuning the community composition.

Temperature regulation as a tool to program synthetic microbial community composition

Engineering of synthetic microbial communities is emerging as a powerful new paradigm for performing various industrially, medically, and environmentally important processes. To reach the fullest potential, however, this approach requires further development in many aspects, a key one being regulating the community composition. Here we leverage well-established mechanisms in ecology which govern the relative abundance of multispecies ecosystems and develop a new tool for programming the composition of synthetic microbial communities. Using a simple model system consisting of two microorganisms Escherichia coli and Pseudomonas putida, which occupy different but partially overlapping thermal niches, we demonstrated that temperature regulation could be used to enable coexistence and program the community composition. We first investigated a constant temperature regime and showed that different temperatures led to different community compositions. Next, we invented a new cycling temperature regime and showed that it can dynamically tune the microbial community, achieving a wide range of compositions depending on parameters that are readily manipulatable. Our work provides conclusive proof of concept that temperature regulation is a versatile and powerful tool capable of programming compositions of synthetic microbial communities.

From Microbial Communities to Distributed Computing Systems

A distributed biological system can be defined as a system whose components are located in different subpopulations, which communicate and coordinate their actions through interpopulation messages and interactions. We see that distributed systems are pervasive in nature, performing computation across all scales, from microbial communities to a flock of birds. We often observe that information processing within communities exhibits a complexity far greater than any single organism. Synthetic biology is an area of research which aims to design and build synthetic biological machines from biological parts to perform a defined function, in a manner similar to the engineering disciplines. However, the field has reached a bottleneck in the complexity of the genetic networks that we can implement using monocultures, facing constraints from metabolic burden and genetic interference. This makes building distributed biological systems an attractive prospect for synthetic biology that would alleviate these constraints and allow us to expand the applications of our systems into areas including complex biosensing and diagnostic tools, bioprocess control and the monitoring of industrial processes. In this review we will discuss the fundamental limitations we face when engineering functionality with a monoculture, and the key areas where distributed systems can provide an advantage. We cite evidence from natural systems that support arguments in favor of distributed systems to overcome the limitations of monocultures. Following this we conduct a comprehensive overview of the synthetic communities that have been built to date, and the components that have been used. The potential computational capabilities of communities are discussed, along with some of the applications that these will be useful for. We discuss some of the challenges with building co-cultures, including the problem of competitive exclusion and maintenance of desired community composition. Finally, we assess computational frameworks currently available to aide in the design of microbial communities and identify areas where we lack the necessary tools.

A mechanistic model of metabolic symbioses in microbes recapitulates experimental data and identifies a continuum of symbiotic interactions

Microbial symbioses based on nutrient exchange and interdependence are ubiquitous in nature and biotechnologically promising; however, an in-depth mathematical description of their exact underlying dynamics from first principles is still missing. Hence, in this paper a novel mechanistic mathematical model of such a relationship in a continuous chemostat culture is derived. In contrast to preceding works on the topic, only parameters which can be directly measured and understood from biological first principles are used, allowing for a higher degree of mechanistic understanding of the underlying processes compared to previous approaches. The predictive power of the model is validated by demonstrating that it accurately recapitulates both the temporal dynamics as well as the final state of a previously published cross-feeding experiment. The model is then used to examine the influence of the biological traits of the involved organisms on the position and stability of the equilibrium states of the system using bifurcation analyses. It is additionally demonstrated how manipulating the external metabolite concentrations of the system can shift the species interaction on a continuous spectrum ranging from mutualism over commensalism to parasitism. This further reinforces the idea of a continuous spectrum of symbiotic interactions as opposed to static and discrete categories. Finally, the practical implications of the results for the biotechnological application of such microbial consortia are discussed.

Investigating the dynamics of microbial consortia in spatially structured environments

The spatial organization of microbial communities arises from a complex interplay of biotic and abiotic interactions, and is a major determinant of ecosystem functions. Here we design a microfluidic platform to investigate how the spatial arrangement of microbes impacts gene expression and growth. We elucidate key biochemical parameters that dictate the mapping between spatial positioning and gene expression patterns. We show that distance can establish a low-pass filter to periodic inputs and can enhance the fidelity of information processing. Positive and negative feedback can play disparate roles in the synchronization and robustness of a genetic oscillator distributed between two strains to spatial separation. Quantification of growth and metabolite release in an amino-acid auxotroph community demonstrates that the interaction network and stability of the community are highly sensitive to temporal perturbations and spatial arrangements. In sum, our microfluidic platform can quantify spatiotemporal parameters influencing diffusion-mediated interactions in microbial consortia.

Fitness and Productivity Increase with Ecotypic Diversity among Escherichia coli Strains That Coevolved in a Simple, Constant Environment

The productivity of a biological community often correlates with its diversity. In the microbial world this phenomenon can sometimes be explained by positive, density-dependent interactions such as cross-feeding and syntrophy. These metabolic interactions help account for the astonishing variety of microbial life and drive many of the biogeochemical cycles without which life as we know it could not exist. While it is difficult to recapitulate experimentally how these interactions evolved among multiple taxa, we can explore in the laboratory how they arise within one. These experiments provide insight into how different bacterial ecotypes evolve and from these, possibly new "species." We have previously shown that in a simple, constant environment a single clone of Escherichia coli can give rise to a consortium of genetically and phenotypically differentiated strains, in effect, a set of ecotypes, that coexist by cross-feeding. We marked these different ecotypes and their shared ancestor by integrating fluorescent protein into their genomes and then used flow cytometry to show that each evolved strain is more fit than the shared ancestor, that pairs of evolved strains are fitter still, and that the entire consortium is the fittest of all. We further demonstrate that the rank order of fitness values agrees with estimates of yield, indicating that an experimentally evolved consortium more efficiently converts primary and secondary resources to offspring than its ancestor or any member acting in isolation.IMPORTANCE Polymicrobial consortia occur in both environmental and clinical settings. In many cases, diversity and productivity correlate in these consortia, especially when sustained by positive, density-dependent interactions. However, the evolutionary history of such entities is typically obscure, making it difficult to establish the relative fitness of consortium partners and to use those data to illuminate the diversity-productivity relationship. Here, we dissect an Escherichia coli consortium that evolved under continuous glucose limitation in the laboratory from a single common ancestor. We show that a partnership consisting of cross-feeding ecotypes is better able to secure primary and secondary resources and to convert those resources to offspring than the ancestral clone. Such interactions may be a prelude to a special form of syntrophy and are likely determinants of microbial community structure in nature, including those having clinical significance such as chronic infections.

Deep reinforcement learning for the control of microbial co-cultures in bioreactors

Multi-species microbial communities are widespread in natural ecosystems. When employed for biomanufacturing, engineered synthetic communities have shown increased productivity in comparison with monocultures and allow for the reduction of metabolic load by compartmentalising bioprocesses between multiple sub-populations. Despite these benefits, co-cultures are rarely used in practice because control over the constituent species of an assembled community has proven challenging. Here we demonstrate, in silico, the efficacy of an approach from artificial intelligence-reinforcement learning-for the control of co-cultures within continuous bioreactors. We confirm that feedback via a trained reinforcement learning agent can be used to maintain populations at target levels, and that model-free performance with bang-bang control can outperform a traditional proportional integral controller with continuous control, when faced with infrequent sampling. Further, we demonstrate that a satisfactory control policy can be learned in one twenty-four hour experiment by running five bioreactors in parallel. Finally, we show that reinforcement learning can directly optimise the output of a co-culture bioprocess. Overall, reinforcement learning is a promising technique for the control of microbial communities.

Engineered Interspecies Amino Acid Cross-Feeding Increases Population Evenness in a Synthetic Bacterial Consortium

In nature, microbes interact antagonistically, neutrally, or beneficially. To shed light on the effects of positive interactions in microbial consortia, we introduced metabolic dependencies and metabolite overproduction into four bacterial species. While antagonistic interactions govern the wild-type consortium behavior, the genetic modifications alleviated antagonistic interactions and resulted in beneficial interactions. Engineered cross-feeding increased population evenness, a component of ecological diversity, in different environments, including in a more complex gnotobiotic mouse gut environment. Our findings suggest that metabolite cross-feeding could be used as a tool for intentionally shaping microbial consortia in complex environments.IMPORTANCE Microbial communities are ubiquitous in nature. Bacterial consortia live in and on our body and in our environment, and more recently, biotechnology is applying microbial consortia for bioproduction. As part of our body, bacterial consortia influence us in health and disease. Microbial consortium function is determined by its composition, which in turn is driven by the interactions between species. Further understanding of microbial interactions will help us in deciphering how consortia function in complex environments and may enable us to modify microbial consortia for health and environmental benefits.

Syntrophic co-culture amplification of production phenotype for high-throughput screening of microbial strain libraries

Microbes can be engineered to synthesize a wide array of bioproducts, yet production phenotype evaluation remains a frequent bottleneck in the design-build-test cycle where strain development requires iterative rounds of library construction and testing. Here, we present Syntrophic Co-culture Amplification of Production phenotype (SnoCAP). Through a metabolic cross-feeding circuit, the production level of a target molecule is translated into highly distinguishable co-culture growth characteristics, which amplifies differences in production into highly distinguishable growth phenotypes. We demonstrate SnoCAP with the screening of Escherichia coli strains for production of two target molecules: 2-ketoisovalerate, a precursor of the drop-in biofuel isobutanol, and L-tryptophan. The dynamic range of the screening can be tuned by employing an inhibitory analog of the target molecule. Screening based on this framework requires compartmentalization of individual producers with the sensor strain. We explore three formats of implementation with increasing throughput capability: confinement in microtiter plates (102-104 assays/experiment), spatial separation on agar plates (104-105 assays/experiment), and encapsulation in microdroplets (105-107 assays/experiment). Using SnoCAP, we identified an efficient isobutanol production strain from a random mutagenesis library, reaching a final titer that is 5-fold higher than that of the parent strain. The framework can also be extended to screening for secondary metabolite production using a push-pull strategy. We expect that SnoCAP can be readily adapted to the screening of various microbial species, to improve production of a wide range of target molecules.

Advances in the development and application of microbial consortia for metabolic engineering

Recent advances in metabolic engineering enable the production of high-value chemicals via expressing complex biosynthetic pathways in a single microbial host. However, many engineered strains suffer from poor product yields due to redox imbalance and excess metabolic burden, and require compartmentalization of the pathway for optimal function. To address this problem, significant developments have been made towards co-cultivation of more than one engineered microbial strains to distribute metabolic burden between the co-cultivation partners and improve the product yield. In this emerging approach, metabolic pathway modules can be optimized separately in suitable hosts that will then be combined to enable optimal functionality of the complete pathway. This modular approach broadens the possibilities to fine tune sophisticated production platforms and thus achieve the biosynthesis of very complex compounds.

Here, we review the different applications and the overall potential of natural and artificial co-cultivation systems in metabolic engineering in order to improve bioproduction/bioconversion. In addition to the several advantages over monocultures, major challenges and opportunities associated with co-cultivation are also discussed in this review.

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Benefits of using co-cultivation system in metabolic engineering.

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Existence of natural consortia and their application.

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Recent advancement in co-cultivation methodology for bioproductions.

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Challenges in implementing microbial consortia for microbial biosynthesis.

Designing Metabolic Division of Labor in Microbial Communities

Microbes face a trade-off between being metabolically independent and relying on neighboring organisms for the supply of some essential metabolites. This balance of conflicting strategies affects microbial community structure and dynamics, with important implications for microbiome research and synthetic ecology. A "gedanken" (thought) experiment to investigate this trade-off would involve monitoring the rise of mutual dependence as the number of metabolic reactions allowed in an organism is increasingly constrained. The expectation is that below a certain number of reactions, no individual organism would be able to grow in isolation and cross-feeding partnerships and division of labor would emerge. We implemented this idealized experiment using in silico genome-scale models. In particular, we used mixed-integer linear programming to identify trade-off solutions in communities of Escherichia coli strains. The strategies that we found revealed a large space of opportunities in nuanced and nonintuitive metabolic division of labor, including, for example, splitting the tricarboxylic acid (TCA) cycle into two separate halves. The systematic computation of possible solutions in division of labor for 1-, 2-, and 3-strain consortia resulted in a rich and complex landscape. This landscape displayed a nonlinear boundary, indicating that the loss of an intracellular reaction was not necessarily compensated for by a single imported metabolite. Different regions in this landscape were associated with specific solutions and patterns of exchanged metabolites. Our approach also predicts the existence of regions in this landscape where independent bacteria are viable but are outcompeted by cross-feeding pairs, providing a possible incentive for the rise of division of labor. IMPORTANCE Understanding how microbes assemble into communities is a fundamental open issue in biology, relevant to human health, metabolic engineering, and environmental sustainability. A possible mechanism for interactions of microbes is through cross-feeding, i.e., the exchange of small molecules. These metabolic exchanges may allow different microbes to specialize in distinct tasks and evolve division of labor. To systematically explore the space of possible strategies for division of labor, we applied advanced optimization algorithms to computational models of cellular metabolism. Specifically, we searched for communities able to survive under constraints (such as a limited number of reactions) that would not be sustainable by individual species. We found that predicted consortia partition metabolic pathways in ways that would be difficult to identify manually, possibly providing a competitive advantage over individual organisms. In addition to helping understand diversity in natural microbial communities, our approach could assist in the design of synthetic consortia.

Synthetic Mutualism and the Intervention Dilemma

Ecosystems are complex networks of interacting individuals co-evolving with their environment. As such, changes to an interaction can influence the whole ecosystem. However, to predict the outcome of these changes, considerable understanding of processes driving the system is required. Synthetic biology provides powerful tools to aid this understanding, but these developments also allow us to change specific interactions. Of particular interest is the ecological importance of mutualism, a subset of cooperative interactions. Mutualism occurs when individuals of different species provide a reciprocal fitness benefit. We review available experimental techniques of synthetic biology focused on engineered synthetic mutualistic systems. Components of these systems have defined interactions that can be altered to model naturally occurring relationships. Integrations between experimental systems and theoretical models, each informing the use or development of the other, allow predictions to be made about the nature of complex relationships. The predictions range from stability of microbial communities in extreme environments to the collapse of ecosystems due to dangerous levels of human intervention. With such caveats, we evaluate the promise of synthetic biology from the perspective of ethics and laws regarding biological alterations, whether on Earth or beyond. Just because we are able to change something, should we?

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.

Engineered monoculture and co-culture of methylotrophic yeast for de novo production of monacolin J and lovastatin from methanol

As a promising one-carbon renewable substrate for industrial biotechnology, methanol has attracted much attention. However, engineering of microorganisms for industrial production of pharmaceuticals using a methanol substrate is still in infancy. In this study, the methylotrophic yeast Pichia pastoris was used to produce anti-hypercholesterolemia pharmaceuticals, lovastatin and its precursor monacolin J, from methanol. The biosynthetic pathways for monacolin J and lovastatin were first assembled and optimized in single strains using single copies of the relevant biosynthetic genes, and yields of 60.0mg/L monacolin J and 14.4mg/L lovastatin were obtained using methanol following pH controlled monoculture. To overcome limitations imposed by accumulation of intermediates and metabolic stress in monoculture, approaches using pathway splitting and co-culture were developed. Two pathway splitting strategies for monacolin J, and four for lovastatin were tested at different metabolic nodes. Biosynthesis of monacolin J and lovastatin was improved by 55% and 71%, respectively, when the upstream and downstream modules were separately accommodated in two different fluorescent strains, split at the metabolic node of dihydromonacolin L. However, pathway distribution at monacolin J blocked lovastatin biosynthesis in all designs, mainly due to its limited ability of crossing cellular membranes. Bioreactor fermentations were tested for the optimal co-culture strategies, and yields of 593.9mg/L monacolin J and 250.8mg/L lovastatin were achieved. This study provides an alternative method for production of monacolin J and lovastatin and reveals the potential of a methylotrophic yeast to produce complicated pharmaceuticals from methanol.

Determinism and Contingency Shape Metabolic Complementation in an Endosymbiotic Consortium

Bacterial endosymbionts and their insect hosts establish an intimate metabolic relationship. Bacteria offer a variety of essential nutrients to their hosts, whereas insect cells provide the necessary sources of matter and energy to their tiny metabolic allies. These nutritional complementations sustain themselves on a diversity of metabolite exchanges between the cell host and the reduced yet highly specialized bacterial metabolism—which, for instance, overproduces a small set of essential amino acids and vitamins. A well-known case of metabolic complementation is provided by the cedar aphid Cinara cedri that harbors two co-primary endosymbionts, Buchnera aphidicola BCc and Ca. Serratia symbiotica SCc, and in which some metabolic pathways are partitioned between different partners. Here we present a genome-scale metabolic network (GEM) for the bacterial consortium from the cedar aphid iBSCc. The analysis of this GEM allows us the confirmation of cases of metabolic complementation previously described by genome analysis (i.e., tryptophan and biotin biosynthesis) and the redefinition of an event of metabolic pathway sharing between the two endosymbionts, namely the biosynthesis of tetrahydrofolate. In silico knock-out experiments with iBSCc showed that the consortium metabolism is a highly integrated yet fragile network. We also have explored the evolutionary pathways leading to the emergence of metabolic complementation between reduced metabolisms starting from individual, complete networks. Our results suggest that, during the establishment of metabolic complementation in endosymbionts, adaptive evolution is significant in the case of tryptophan biosynthesis, whereas vitamin production pathways seem to adopt suboptimal solutions.

A stable genetic polymorphism underpinning microbial syntrophy

Syntrophies are metabolic cooperations, whereby two organisms co-metabolize a substrate in an interdependent manner. Many of the observed natural syntrophic interactions are mandatory in the absence of strong electron acceptors, such that one species in the syntrophy has to assume the role of electron sink for the other. While this presents an ecological setting for syntrophy to be beneficial, the potential genetic drivers of syntrophy remain unknown to date. Here, we show that the syntrophic sulfate-reducing species Desulfovibrio vulgaris displays a stable genetic polymorphism, where only a specific genotype is able to engage in syntrophy with the hydrogenotrophic methanogen Methanococcus maripaludis. This 'syntrophic' genotype is characterized by two genetic alterations, one of which is an in-frame deletion in the gene encoding for the ion-translocating subunit cooK of the membrane-bound COO hydrogenase. We show that this genotype presents a specific physiology, in which reshaping of energy conservation in the lactate oxidation pathway enables it to produce sufficient intermediate hydrogen for sustained M. maripaludis growth and thus, syntrophy. To our knowledge, these findings provide for the first time a genetic basis for syntrophy in nature and bring us closer to the rational engineering of syntrophy in synthetic microbial communities.

Estimating the probability of coexistence in cross-feeding communities

The dynamics of many microbial ecosystems are driven by cross-feeding interactions, in which metabolites excreted by some species are metabolised further by others. The population dynamics of such ecosystems are governed by frequency-dependent selection, which allows for stable coexistence of two or more species. We have analysed a model of cross-feeding based on the replicator equation, with the aim of establishing criteria for coexistence in ecosystems containing three species, given the information of the three species' ability to coexist in their three separate pairs, i.e. the long term dynamics in the three two-species component systems. The triple-system is studied statistically and the probability of coexistence in the species triplet is computed for two models of species interactions. The interaction parameters are modelled either as stochastically independent or organised in a hierarchy where any derived metabolite carries less energy than previous nutrients in the metabolic chain. We differentiate between different modes of coexistence with respect to the pair-wise dynamics of the species, and find that the probability of coexistence is close to 12 for triplet systems with three pair-wise coexistent pairs and for the so-called intransitive systems. Systems with two and one pair-wise coexistent pairs are more likely to exist for random interaction parameters, but are on the other hand much less likely to exhibit triplet coexistence. Hence we conclude that certain species triplets are, from a statistical point of view, rare, but if allowed to interact are likely to coexist. This knowledge might be helpful when constructing synthetic microbial communities for industrial purposes.

Living together in biofilms: the microbial cell factory and its biotechnological implications

In nature, bacteria alternate between two modes of growth: a unicellular life phase, in which the cells are free-swimming (planktonic), and a multicellular life phase, in which the cells are sessile and live in a biofilm, that can be defined as surface-associated microbial heterogeneous structures comprising different populations of microorganisms surrounded by a self-produced matrix that allows their attachment to inert or organic surfaces. While a unicellular life phase allows for bacterial dispersion and the colonization of new environments, biofilms allow sessile cells to live in a coordinated, more permanent manner that favors their proliferation. In this alternating cycle, bacteria accomplish two physiological transitions via differential gene expression: (i) from planktonic cells to sessile cells within a biofilm, and (ii) from sessile to detached, newly planktonic cells. Many of the innate characteristics of biofilm bacteria are of biotechnological interest, such as the synthesis of valuable compounds (e.g., surfactants, ethanol) and the enhancement/processing of certain foods (e.g., table olives). Understanding the ecology of biofilm formation will allow the design of systems that will facilitate making products of interest and improve their yields.

Exometabolomics Assisted Design and Validation of Synthetic Obligate Mutualism

Synthetic microbial ecology has the potential to enhance the productivity and resiliency of biotechnology processes compared to approaches using single isolates. Engineering microbial consortia is challenging; however, one approach that has attracted significant attention is the creation of synthetic obligate mutualism using auxotrophic mutants that depend on each other for exchange or cross-feeding of metabolites. Here, we describe the integration of mutant library fitness profiling with mass spectrometry based exometabolomics as a method for constructing synthetic mutualism based on cross-feeding. Two industrially important species lacking known ecological interactions, Zymomonas mobilis and Escherichia coli, were selected as the test species. Amino acid exometabolites identified in the spent medium of Z. mobilis were used to select three corresponding E. coli auxotrophs (proA, pheA and IlvA), as potential E. coli counterparts for the coculture. A pooled mutant fitness assay with a Z. mobilis transposon mutant library was used to identify mutants with improved growth in the presence of E. coli. An auxotroph mutant in a gene (ZMO0748) with sequence similarity to cysteine synthase A (cysK), was selected as the Z. mobilis counterpart for the coculture. Exometabolomic analysis of spent E. coli medium identified glutathione related metabolites as potentially available for rescue of the Z. mobilis cysteine synthase mutant. Three sets of cocultures between the Z. mobilis auxotroph and each of the three E. coli auxotrophs were monitored by optical density for growth and analyzed by flow cytometry to confirm high cell counts for each species. Taken together, our methods provide a technological framework for creating synthetic mutualisms combining existing screening based methods and exometabolomics for both the selection of obligate mutualism partners and elucidation of metabolites involved in auxotroph rescue.

Modular co-culture engineering, a new approach for metabolic engineering

With the development of metabolic engineering, employment of a selected microbial host for accommodation of a designed biosynthetic pathway to produce a target compound has achieved tremendous success in the past several decades. Yet, increasing requirements for sophisticated microbial biosynthesis call for establishment and application of more advanced metabolic engineering methodologies. Recently, important progress has been made towards employing more than one engineered microbial strains to constitute synthetic co-cultures and modularizing the biosynthetic labor between the co-culture members in order to improve bioproduction performance. This emerging approach, referred to as modular co-culture engineering in this review, presents a valuable opportunity for expanding the scope of the broad field of metabolic engineering. We highlight representative research accomplishments using this approach, especially those utilizing metabolic engineering tools for microbial co-culture manipulation. Key benefits and major challenges associated with modular co-culture engineering are also presented and discussed.

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.

Principles for designing synthetic microbial communities

Advances in synthetic biology to build microbes with defined and controllable properties are enabling new approaches to design and program multispecies communities. This emerging field of synthetic ecology will be important for many areas of biotechnology, bioenergy and bioremediation. This endeavor draws upon knowledge from synthetic biology, systems biology, microbial ecology and evolution. Fully realizing the potential of this discipline requires the development of new strategies to control the intercellular interactions, spatiotemporal coordination, robustness, stability and biocontainment of synthetic microbial communities. Here, we review recent experimental, analytical and computational advances to study and build multi-species microbial communities with defined functions and behavior for various applications. We also highlight outstanding challenges and future directions to advance this field.

Utilization and control of ecological interactions in polymicrobial infections and community-based microbial cell factories

Microbial activities are most often shaped by interactions between co-existing microbes within mixed-species communities. Dissection of the molecular mechanisms of species interactions within communities is a central issue in microbial ecology, and our ability to engineer and control microbial communities depends, to a large extent, on our knowledge of these interactions. This review highlights the recent advances regarding molecular characterization of microbe-microbe interactions that modulate community structure, activity, and stability, and aims to illustrate how these findings have helped us reach an engineering-level understanding of microbial communities in relation to both human health and industrial biotechnology.

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.

Biotechnological exploitation of microalgae

Microalgae are a diverse group of single-cell photosynthetic organisms that include cyanobacteria and a wide range of eukaryotic algae. A number of microalgae contain high-value compounds such as oils, colorants, and polysaccharides, which are used by the food additive, oil, and cosmetic industries, among others. They offer the potential for rapid growth under photoautotrophic conditions, and they can grow in a wide range of habitats. More recently, the development of genetic tools means that a number of species can be transformed and hence used as cell factories for the production of high-value chemicals or recombinant proteins. In this article, we review exploitation use of microalgae with a special emphasis on genetic engineering approaches to develop cell factories, and the use of synthetic ecology approaches to maximize productivity. We discuss the success stories in these areas, the hurdles that need to be overcome, and the potential for expanding the industry in general.

Synthetic Ecology of Microbes: Mathematical Models and Applications

As the indispensable role of natural microbial communities in many aspects of life on Earth is uncovered, the bottom-up engineering of synthetic microbial consortia with novel functions is becoming an attractive alternative to engineering single-species systems. Here, we summarize recent work on synthetic microbial communities with a particular emphasis on open challenges and opportunities in environmental sustainability and human health. We next provide a critical overview of mathematical approaches, ranging from phenomenological to mechanistic, to decipher the principles that govern the function, dynamics and evolution of microbial ecosystems. Finally, we present our outlook on key aspects of microbial ecosystems and synthetic ecology that require further developments, including the need for more efficient computational algorithms, a better integration of empirical methods and model-driven analysis, the importance of improving gene function annotation, and the value of a standardized library of well-characterized organisms to be used as building blocks of synthetic communities.