Stochastic simulations of a synthetic bacteria-yeast ecosystem

Synergistically promoting plant health by harnessing synthetic microbial communities and prebiotics

Soil-borne diseases cause serious economic losses in agriculture. Managing diseases with microbial preparations is an excellent approach to soil-borne disease prevention. However, microbial preparations often exhibit unstable effects, limiting their large-scale application. This review introduces and summarizes disease-suppressive soils, the relationship between carbon sources and the microbial community, and the application of human microbial preparation concepts to plant microbial preparations. We also propose an innovative synthetic microbial community assembly strategy with synergistic prebiotics to promote healthy plant growth and resistance to disease. In this review, a new approach is proposed to improve traditional microbial preparations; provide a better understanding of the relationships among carbon sources, beneficial microorganisms, and plants; and lay a theoretical foundation for developing new microbial preparations.

The genetic basis for adaptation of model-designed syntrophic co-cultures

Understanding the fundamental characteristics of microbial communities could have far reaching implications for human health and applied biotechnology. Despite this, much is still unknown regarding the genetic basis and evolutionary strategies underlying the formation of viable synthetic communities. By pairing auxotrophic mutants in co-culture, it has been demonstrated that viable nascent E. coli communities can be established where the mutant strains are metabolically coupled. A novel algorithm, OptAux, was constructed to design 61 unique multi-knockout E. coli auxotrophic strains that require significant metabolite uptake to grow. These predicted knockouts included a diverse set of novel non-specific auxotrophs that result from inhibition of major biosynthetic subsystems. Three OptAux predicted non-specific auxotrophic strains—with diverse metabolic deficiencies—were co-cultured with an L-histidine auxotroph and optimized via adaptive laboratory evolution (ALE). Time-course sequencing revealed the genetic changes employed by each strain to achieve higher community growth rates and provided insight into mechanisms for adapting to the syntrophic niche. A community model of metabolism and gene expression was utilized to predict the relative community composition and fundamental characteristics of the evolved communities. This work presents new insight into the genetic strategies underlying viable nascent community formation and a cutting-edge computational method to elucidate metabolic changes that empower the creation of cooperative communities.

Many basic characteristics underlying the establishment of cooperative growth in bacterial communities have not been studied in detail. The presented work sought to understand the adaptation of syntrophic communities by first employing a new computational method to generate a comprehensive catalog of E. coli auxotrophic mutants. Many of the knockouts in the catalog had the predicted effect of disabling a major biosynthetic process. As a result, these strains were predicted to be capable of growing when supplemented with many different individual metabolites (i.e., a non-specific auxotroph), but the strains would require a high amount of metabolic cooperation to grow in community. Three such non-specific auxotroph mutants from this catalog were co-cultured with a proven auxotrophic partner in vivo and evolved via adaptive laboratory evolution. In order to successfully grow, each strain in co-culture had to evolve under a pressure to grow cooperatively in its new niche. The non-specific auxotrophs further had to adapt to significant homeostatic changes in cell’s metabolic state caused by knockouts in metabolic genes. The genomes of the successfully growing communities were sequenced, thus providing unique insights into the genetic changes accompanying the formation and optimization of the viable communities. A computational model was further developed to predict how finite protein availability, a fundamental constraint on cell metabolism, could impact the composition of the community (i.e., the relative abundances of each community member).

Engineering microbial consortia by division of labor

During microbial applications, metabolic burdens can lead to a significant drop in cell performance. Novel synthetic biology tools or multi-step bioprocessing (e.g., fermentation followed by chemical conversions) are therefore needed to avoid compromised biochemical productivity from over-burdened cells. A possible solution to address metabolic burden is Division of Labor (DoL) via natural and synthetic microbial consortia. In particular, consolidated bioprocesses and metabolic cooperation for detoxification or cross feeding (e.g., vitamin C fermentation) have shown numerous successes in industrial level applications. However, distributing a metabolic pathway among proper hosts remains an engineering conundrum due to several challenges: complex subpopulation dynamics/interactions with a short time-window for stable production, suboptimal cultivation of microbial communities, proliferation of cheaters or low-producers, intermediate metabolite dilution, transport barriers between species, and breaks in metabolite channeling through biosynthesis pathways. To develop stable consortia, optimization of strain inoculations, nutritional divergence and crossing feeding, evolution of mutualistic growth, cell immobilization, and biosensors may potentially be used to control cell populations. Another opportunity is direct integration of non-bioprocesses (e.g., microbial electrosynthesis) to power cell metabolism and improve carbon efficiency. Additionally, metabolic modeling and ¹³C-metabolic flux analysis of mixed culture metabolism and cross-feeding offers a computational approach to complement experimental research for improved consortia performance.

Engineering Bacillus megaterium Strains To Secrete Cellulases for Synergistic Cellulose Degradation in a Microbial Community

Recent environmental concerns have intensified the need to develop systems to degrade waste biomass for use as an inexpensive carbon source for microbial chemical production. Current approaches to biomass utilization rely on pretreatment processes that include expensive enzymatic purification steps for the requisite cellulases. We aimed to engineer a synthetic microbial community to synergistically degrade cellulose by compartmentalizing the system with multiple specialized Bacillus megaterium strains. EGI1, an endoglucanase, and Cel9AT, a multimodular cellulase, were targeted for secretion from B. megaterium. A small library of signal peptides (SPs) with five amino acid linkers was selected to tag each cellulase for secretion from B. megaterium. Cellulase activity against amorphous cellulose was confirmed through a series of bioassays, and the most active SP constructs were identified as EGI1 with the LipA SP and Cel9AT with the YngK SP. The activity of the optimized cellulase secretion strains was characterized individually and in tandem to assess synergistic cellulolytic activity. The combination of EGI1 and Cel9AT yielded higher activity than either single cellulase. A coculture of EGI1 and Cel9AT secreting B. megaterium strains demonstrated synergistic behavior with higher activity than either monoculture. This cellulose degradation module can be further integrated with bioproduct synthesis modules to build complex systems for the production of high value molecules.

Maximum Entropy Prediction of Non-Equilibrium Stationary Distributions for Stochastic Reaction Networks with Oscillatory Dynamics

Many chemical reaction networks in biological systems present complex oscillatory dynamics. In systems such as regulatory gene networks, cell cycle, and enzymatic processes, the number of molecules involved is often far from the thermodynamic limit. Although stochastic models based on the probabilistic approach of the Chemical Master Equation (CME) have been proposed, studies in the literature have been limited by the challenges of solving the CME and the lack of computational power to perform large-scale stochastic simulations. In this paper, we show that the infinite set of stationary moment equations describing the stochastic Brusselator and Schnakenberg oscillatory reactions networks can be truncated and solved using maximization of the entropy of the distributions. The results from our numerical experiments compare with the distributions obtained from well-established kinetic Monte Carlo methods and suggest that the accuracy of the prediction increases exponentially with the closure order chosen for the system. We conclude that maximum entropy models can be used as an efficient closure scheme alternative for moment equations to predict the non-equilibrium stationary distributions of stochastic chemical reactions with oscillatory dynamics. This prediction is accomplished without any prior knowledge of the system dynamics and without imposing any biased assumptions on the mathematical relations among species involved.

The role of mRNA and protein stability in the function of coupled positive and negative feedback systems in eukaryotic cells

Oscillators and switches are important elements of regulation in biological systems. These are composed of coupling negative feedback loops, which cause oscillations when delayed, and positive feedback loops, which lead to memory formation. Here, we examine the behavior of a coupled feedback system, the Negative Autoregulated Frustrated bistability motif (NAF). This motif is a combination of two previously explored motifs, the frustrated bistability motif (FBM) and the negative auto regulation motif (NAR), which both can produce oscillations. The NAF motif was previously suggested to govern long term memory formation in animals, and was used as a synthetic oscillator in bacteria. We build a mathematical model to analyze the dynamics of the NAF motif. We show analytically that the NAF motif requires an asymmetry in the strengths of activation and repression links in order to produce oscillations. We show that the effect of time delays in eukaryotic cells, originating from mRNA export and protein import, are negligible in this system. Based on the reported protein and mRNA half-lives in eukaryotic cells, we find that even though the NAF motif possesses the ability for oscillations, it mostly promotes constant protein expression at the biologically relevant parameter regimes.

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

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

Agriculture and food animals as a source of antimicrobial-resistant bacteria

One of the major breakthroughs in the history of medicine is undoubtedly the discovery of antibiotics. Their use in animal husbandry and veterinary medicine has resulted in healthier and more productive farm animals, ensuring the welfare and health of both animals and humans. Unfortunately, from the first use of penicillin, the resistance countdown started to tick. Nowadays, the infections caused by antibiotic-resistant bacteria are increasing, and resistance to antibiotics is probably the major public health problem. Antibiotic use in farm animals has been criticized for contributing to the emergence of resistance. The use and misuse of antibiotics in farm animal settings as growth promoters or as nonspecific means of infection prevention and treatment has boosted antibiotic consumption and resistance among bacteria in the animal habitat. This reservoir of resistance can be transmitted directly or indirectly to humans through food consumption and direct or indirect contact. Resistant bacteria can cause serious health effects directly or via the transmission of the antibiotic resistance traits to pathogens, causing illnesses that are difficult to treat and that therefore have higher morbidity and mortality rates. In addition, the selection and proliferation of antibiotic-resistant strains can be disseminated to the environment via animal waste, enhancing the resistance reservoir that exists in the environmental microbiome. In this review, an effort is made to highlight the various factors that contribute to the emergence of antibiotic resistance in farm animals and to provide some insights into possible solutions to this major health issue.

Co-culture systems and technologies: taking synthetic biology to the next level

Co-culture techniques find myriad applications in biology for studying natural or synthetic interactions between cell populations. Such techniques are of great importance in synthetic biology, as multi-species cell consortia and other natural or synthetic ecology systems are widely seen to hold enormous potential for foundational research as well as novel industrial, medical and environmental applications with many proof-of-principle studies in recent years. What is needed for co-cultures to fulfil their potential? Cell-cell interactions in co-cultures are strongly influenced by the extracellular environment, which is determined by the experimental set-up, which therefore needs to be given careful consideration. An overview of existing experimental and theoretical co-culture set-ups in synthetic biology and adjacent fields is given here, and challenges and opportunities involved in such experiments are discussed. Greater focus on foundational technology developments for co-cultures is needed for many synthetic biology systems to realize their potential in both applications and answering biological questions.

Synthetic biology outside the cell: linking computational tools to cell-free systems

As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

Multiscale Models of Antibiotic Probiotics

The discovery of antibiotics is one of the most important advances in the history of humankind. For eighty years human life expectancy and standards of living improved greatly thanks to antibiotics. But bacteria have been fighting back, developing resistance to our most potent molecules. New, alternative strategies must be explored as antibiotic therapies become obsolete because of bacterial resistance. Mathematical models and simulations guide the development of complex technologies, such as aircrafts, bridges, communication systems and transportation systems. Herein, models are discussed that guide the development of new antibiotic technologies. These models span multiple molecular and cellular scales, and facilitate the development of a technology that addresses a significant societal challenge. We argue that simulations can be a creative source of knowledge.

A microbial model of economic trading and comparative advantage

The economic theory of comparative advantage postulates that beneficial trading relationships can be arrived at by two self-interested entities producing the same goods as long as they have opposing relative efficiencies in producing those goods. The theory predicts that upon entering trade, in order to maximize consumption both entities will specialize in producing the good they can produce at higher efficiency, that the weaker entity will specialize more completely than the stronger entity, and that both will be able to consume more goods as a result of trade than either would be able to alone. We extend this theory to the realm of unicellular organisms by developing mathematical models of genetic circuits that allow trading of a common good (specifically, signaling molecules) required for growth in bacteria in order to demonstrate comparative advantage interactions. In Conception 1, the experimenter controls production rates via exogenous inducers, allowing exploration of the parameter space of specialization. In Conception 2, the circuits self-regulate via feedback mechanisms. Our models indicate that these genetic circuits can demonstrate comparative advantage, and that cooperation in such a manner is particularly favored under stringent external conditions and when the cost of production is not overly high. Further work could involve implementing the models in living bacteria and searching for naturally occurring cooperative relationships between bacteria that conform to the principles of comparative advantage.

Bacterial sugar utilization gives rise to distinct single-cell behaviours

Inducible utilization pathways reflect widespread microbial strategies to uptake and consume sugars from the environment. Despite their broad importance and extensive characterization, little is known how these pathways naturally respond to their inducing sugar in individual cells. Here, we performed single-cell analyses to probe the behaviour of representative pathways in the model bacterium Escherichia coli. We observed diverse single-cell behaviours, including uniform responses (d-lactose, d-galactose, N-acetylglucosamine, N-acetylneuraminic acid), 'all-or-none' responses (d-xylose, l-rhamnose) and complex combinations thereof (l-arabinose, d-gluconate). Mathematical modelling and probing of genetically modified pathways revealed that the simple framework underlying these pathways - inducible transport and inducible catabolism - could give rise to most of these behaviours. Sugar catabolism was also an important feature, as disruption of catabolism eliminated tunable induction as well as enhanced memory of previous conditions. For instance, disruption of catabolism in pathways that respond to endogenously synthesized sugars led to full pathway induction even in the absence of exogenous sugar. Our findings demonstrate the remarkable flexibility of this simple biological framework, with direct implications for environmental adaptation and the engineering of synthetic utilization pathways as titratable expression systems and for metabolic engineering.

Design of synthetic microbial communities for biotechnological production processes

In their natural habitats microorganisms live in multi-species communities, in which the community members exhibit complex metabolic interactions. In contrast, biotechnological production processes catalyzed by microorganisms are usually carried out with single strains in pure cultures. A number of production processes, however, may be more efficiently catalyzed by the concerted action of microbial communities. This review will give an overview of organismic interactions between microbial cells and of biotechnological applications of microbial communities. It focuses on synthetic microbial communities that consist of microorganisms that have been genetically engineered. Design principles for such synthetic communities will be exemplified based on plausible scenarios for biotechnological production processes. These design principles comprise interspecific metabolic interactions via cross-feeding, regulation by interspecific signaling processes via metabolites and autoinducing signal molecules, and spatial structuring of synthetic microbial communities. In particular, the implementation of metabolic interdependencies, of positive feedback regulation and of inducible cell aggregation and biofilm formation will be outlined. Synthetic microbial communities constitute a viable extension of the biotechnological application of metabolically engineered single strains and enlarge the scope of microbial production processes.

Alternatives to antibiotics: a symposium on the challenges and solutions for animal production

Antibiotics are one of the most important medical discoveries of the 20th century and will remain an essential tool for treating animal and human diseases in the 21st century. However, antibiotic resistance among bacterial pathogens and concerns over their extensive use in food animals has garnered global interest in limiting antibiotic use in animal agriculture. Yet, limiting the availability of medical interventions to prevent and control animal diseases on the farm will directly impact global food security and safety as well as animal and human health. Insufficient attention has been given to the scientific breakthroughs and novel technologies that provide alternatives to antibiotics. The objectives of the symposium 'Alternatives to Antibiotics' were to highlight promising research results and novel technologies that could potentially lead to alternatives to conventional antibiotics, and assess challenges associated with their commercialization, and provide actionable strategies to support development of alternative antimicrobials. The symposium focused on the latest scientific breakthroughs and technologies that could provide new options and alternative strategies for preventing and treating diseases of animals. Some of these new technologies have direct applications as medical interventions for human health, but the focus of the symposium was animal production, animal health and food safety during food-animal production. Five subject areas were explored in detail through scientific presentations and expert panel discussions, including: (1) alternatives to antibiotics, lessons from nature; (2) immune modulation approaches to enhance disease resistance and to treat animal diseases; (3) gut microbiome and immune development, health and diseases; (4) alternatives to antibiotics for animal production; and (5) regulatory pathways to enable the licensure of alternatives to antibiotics.

Consortia-mediated bioprocessing of cellulose to ethanol with a symbiotic Clostridium phytofermentans/yeast co-culture

BACKGROUND

Lignocellulosic ethanol is a viable alternative to petroleum-based fuels with the added benefit of potentially lower greenhouse gas emissions. Consolidated bioprocessing (simultaneous enzyme production, hydrolysis and fermentation; CBP) is thought to be a low-cost processing scheme for lignocellulosic ethanol production. However, no single organism has been developed which is capable of high productivity, yield and titer ethanol production directly from lignocellulose. Consortia of cellulolytic and ethanologenic organisms could be an attractive alternate to the typical single organism approaches but implementation of consortia has a number of challenges (e.g., control, stability, productivity).

RESULTS

Ethanol is produced from α-cellulose using a consortium of C. phytofermentans and yeast that is maintained by controlled oxygen transport. Both Saccharomyces cerevisiae cdt-1 and Candida molischiana "protect" C. phytofermentans from introduced oxygen in return for soluble sugars released by C. phytofermentans hydrolysis. Only co-cultures were able to degrade filter paper when mono- and co-cultures were incubated at 30°C under semi-aerobic conditions. Using controlled oxygen delivery by diffusion through neoprene tubing at a calculated rate of approximately 8 μmol/L hour, we demonstrate establishment of the symbiotic relationship between C. phytofermentans and S. cerevisiae cdt-1 and maintenance of populations of 105 to 106 CFU/mL for 50 days. Comparable symbiotic population dynamics were observed in scaled up 500 mL bioreactors as those in 50 mL shake cultures. The conversion of α-cellulose to ethanol was shown to improve with additional cellulase indicating a limitation in hydrolysis rate. A co-culture of C. phytofermentans and S. cerevisiae cdt-1 with added endoglucanase produced approximately 22 g/L ethanol from 100 g/L α-cellulose compared to C. phytofermentans and S. cerevisiae cdt-1 mono-cultures which produced approximately 6 and 9 g/L, respectively.

CONCLUSION

This work represents a significant step toward developing consortia-based bioprocessing systems for lignocellulosic biofuels production which utilize scalable, environmentally-mediated symbiosis mechanisms to provide consortium stability.