Partners for life: building microbial consortia for the future

Rational construction of synthetic consortia: Key considerations and model-based methods for guiding the development of a novel biosynthesis platform

The rapid development of synthetic biology has significantly improved the capabilities of mono-culture systems in converting different substrates into various value-added bio-chemicals through metabolic engineering. However, overexpression of biosynthetic pathways in recombinant strains can impose a heavy metabolic burden on the host, resulting in imbalanced energy distribution and negatively affecting both cell growth and biosynthesis capacity. Synthetic consortia, consisting of two or more microbial species or strains with complementary functions, have emerged as a promising and efficient platform to alleviate the metabolic burden and increase product yield. However, research on synthetic consortia is still in its infancy, with numerous challenges regarding the design and construction of stable synthetic consortia. This review provides a comprehensive comparison of the advantages and disadvantages of mono-culture systems and synthetic consortia. Key considerations for engineering synthetic consortia based on recent advances are summarized, and simulation and computational tools for guiding the advancement of synthetic consortia are discussed. Moreover, further development of more efficient and cost-effective synthetic consortia with emerging technologies such as artificial intelligence and machine learning is highlighted.

Optimal control of bioproduction in the presence of population heterogeneity

Cell-to-cell variability, born of stochastic chemical kinetics, persists even in large isogenic populations. In the study of single-cell dynamics this is typically accounted for. However, on the population level this source of heterogeneity is often sidelined to avoid the inevitable complexity it introduces. The homogeneous models used instead are more tractable but risk disagreeing with their heterogeneous counterparts and may thus lead to severely suboptimal control of bioproduction. In this work, we introduce a comprehensive mathematical framework for solving bioproduction optimal control problems in the presence of heterogeneity. We study population-level models in which such heterogeneity is retained, and propose order-reduction approximation techniques. The reduced-order models take forms typical of homogeneous bioproduction models, making them a useful benchmark by which to study the importance of heterogeneity. Moreover, the derivation from the heterogeneous setting sheds light on parameter selection in ways a direct homogeneous outlook cannot, and reveals the source of approximation error. With view to optimally controlling bioproduction in microbial communities, we ask the question: when does optimising the reduced-order models produce strategies that work well in the presence of population heterogeneity? We show that, in some cases, homogeneous approximations provide remarkably accurate surrogate models. Nevertheless, we also demonstrate that this is not uniformly true: overlooking the heterogeneity can lead to significantly suboptimal control strategies. In these cases, the heterogeneous tools and perspective are crucial to optimise bioproduction.

Revisiting moment-closure methods with heterogeneous multiscale population models

Stochastic chemical kinetics at the single-cell level give rise to heterogeneous populations of cells even when all individuals are genetically identical. This heterogeneity can lead to nonuniform behaviour within populations, including different growth characteristics, cell-fate dynamics, and response to stimuli. Ultimately, these diverse behaviours lead to intricate population dynamics that are inherently multiscale: the population composition evolves based on population-level processes that interact with stochastically distributed single-cell states. Therefore, descriptions that account for this heterogeneity are essential to accurately model and control chemical processes. However, for real-world systems such models are computationally expensive to simulate, which can make optimisation problems, such as optimal control or parameter inference, prohibitively challenging. Here, we consider a class of multiscale population models that incorporate population-level mechanisms while remaining faithful to the underlying stochasticity at the single-cell level and the interplay between these two scales. To address the complexity, we study an order-reduction approximations based on the distribution moments. Since previous moment-closure work has focused on the single-cell kinetics, extending these techniques to populations models prompts us to revisit old observations as well as tackle new challenges. In this extended multiscale context, we encounter the previously established observation that the simplest closure techniques can lead to non-physical system trajectories. Despite their poor performance in some systems, we provide an example where these simple closures outperform more sophisticated closure methods in accurately, efficiently, and robustly solving the problem of optimal control of bioproduction in a microbial consortium model.

Biosurfactants and chemotaxis interplay in microbial consortium-based hydrocarbons degradation

Hydrocarbons are routinely detected at low concentrations, despite the degrading metabolic potential of ubiquitous microorganisms. The potential drivers of hydrocarbons persistence are lower bioavailability and mass transfer limitation. Recently, bioremediation strategies have developed rapidly, but still, the solution is not resilient. Biosurfactants, known to increase bioavailability and augment biodegradation, are tightly linked to bacterial surface motility and chemotaxis, while chemotaxis help bacteria to locate aromatic compounds and increase the mass transfer. Harassing the biosurfactant production and chemotaxis properties of degrading microorganisms could be a possible approach for the complete degradation of hydrocarbons. This review provides an overview of interplay between biosurfactants and chemotaxis in bioremediation. Besides, we discuss the chemical surfactants and biosurfactant-mediated biodegradation by microbial consortium.

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.

A light tunable differentiation system for the creation and control of consortia in yeast

Artificial microbial consortia seek to leverage division-of-labour to optimize function and possess immense potential for bioproduction. Co-culturing approaches, the preferred mode of generating a consortium, remain limited in their ability to give rise to stable consortia having finely tuned compositions. Here, we present an artificial differentiation system in budding yeast capable of generating stable microbial consortia with custom functionalities from a single strain at user-defined composition in space and in time based on optogenetically-driven genetic rewiring. Owing to fast, reproducible, and light-tunable dynamics, our system enables dynamic control of consortia composition in continuous cultures for extended periods. We further demonstrate that our system can be extended in a straightforward manner to give rise to consortia with multiple subpopulations. Our artificial differentiation strategy establishes a novel paradigm for the creation of complex microbial consortia that are simple to implement, precisely controllable, and versatile to use.

Nutrition and Cancer Risk from the Viewpoint of the Intestinal Microbiome

There are various important factors in reducing the risk of cancer development and progression; these factors may correct an unbalanced intake of nutrients to maintain the living body’s homeostasis, detoxify toxic materials, acting as an external factor, and maintain and strengthen the body’s immune function. In a normal cell environment, nutrients, such as carbohydrates, lipids, proteins, vitamins, and minerals, are properly digested and absorbed into the body, and, as a result, an environment in which cancer can develop and progress is prevented. It is necessary to prevent toxic materials from entering the body and to detoxify poisons in the body. If these processes occur correctly, cells work normally, and genes cannot be damaged. The most important factor in the fight against cancer and prevention of the development and progression of cancer is the immune system. This requires a nutritional state in which the immune system works well, allowing the intestinal microbiome to carry out all of its roles. In order to grow intestinal microbiota, the consumption of prebiotics, such as organic vegetables, fruits, and dietary fiber, and probiotics of effective intestinal microbiota, such as fermented foods and supplements, is required. Symbiosis, in which these organisms work together, is an effective means of reducing the risk of cancer. In addition, fecal microbiota transplantation (FMT) using ultrafine bubble water, produced specially by the Association for Clinical Research of Fecal Microbiota Transplantation Japan, is also useful for improving the nutritional condition and reducing the risk of cancer.

Exploiting interbacterial antagonism for microbiome engineering

Interbacterial antagonism can significantly impact microbiome assembly and stability and can potentially be exploited to modulate microbes and microbial communities in diverse environments, ranging from natural habitats to industrial bioreactors. Here we highlight key mechanisms of interspecies antagonism that rely on direct cell-to-cell contact or diffusion of secreted biomolecules, and discuss recent advances to provide altered function and specificities for microbiome engineering. We further outline the use of ecological design principles based on antagonistic interactions for bottom-up assembly of synthetic microbial communities. Manipulating microbial communities through these negative interactions will be critical for understanding complex microbiome processes and properties and developing new applications of microbiome engineering.