MiMiC: a bioinformatic approach for generation of synthetic communities from metagenomes

Designing function-specific minimal microbiomes from large microbial communities

Microorganisms exist in large communities of diverse species, exhibiting various functionalities. The mammalian gut microbiome, for instance, has the functionality of digesting dietary fibre and producing different short-chain fatty acids. Not all microbes present in a community contribute to a given functionality; it is possible to find a minimal microbiome, which is a subset of the large microbiome, that is capable of performing the functionality while maintaining other community properties such as growth rate and metabolite production. Such a minimal microbiome will also contain keystone species for SCFA production in that community. In this work, we present a systematic constraint-based approach to identify a minimal microbiome from a large community for a user-proposed function. We employ a top-down approach with sequential deletion followed by solving a mixed-integer linear programming problem with the objective of minimising the L1-norm of the membership vector. Notably, we consider quantitative measures of community growth rate and metabolite production rates. We demonstrate the utility of our algorithm by identifying the minimal microbiomes corresponding to three model communities of the gut, and discuss their validity based on the presence of the keystone species in the community. Our approach is generic, flexible and finds application in studying a variety of microbial communities. The algorithm is available from https://github.com/RamanLab/minMicrobiome .

Synthetic Communities of Gut Microbes for Basic Research and Translational Approaches in Animal Health and Nutrition

Microbes and animals have a symbiotic relationship that greatly influences nutrient uptake and animal health. This relationship can be studied using selections of microbes termed synthetic communities, or SynComs. SynComs are used in many different animal hosts, including agricultural animals, to investigate microbial interactions with nutrients and how these affect animal health. The most common host focuses for SynComs are currently mouse and human, from basic mechanistic research through to translational disease models and live biotherapeutic products (LBPs) as treatments. We discuss SynComs used in basic research models and findings that relate to human and animal health and nutrition. Translational use cases of SynComs are discussed, followed by LBPs, especially within the context of agriculture. SynComs still face challenges, such as standardization for reproducibility and contamination risks. However, the future of SynComs is hopeful, especially in the areas of genome-guided SynCom design and custom SynCom-based treatments.

Strategies for tailoring functional microbial synthetic communities

Natural ecosystems harbor a huge reservoir of taxonomically diverse microbes that are important for plant growth and health. The vast diversity of soil microorganisms and their complex interactions make it challenging to pinpoint the main players important for the life support functions microbes can provide to plants, including enhanced tolerance to (a)biotic stress factors. Designing simplified microbial synthetic communities (SynComs) helps reduce this complexity to unravel the molecular and chemical basis and interplay of specific microbiome functions. While SynComs have been successfully employed to dissect microbial interactions or reproduce microbiome-associated phenotypes, the assembly and reconstitution of these communities have often been based on generic abundance patterns or taxonomic identities and co-occurrences but have only rarely been informed by functional traits. Here, we review recent studies on designing functional SynComs to reveal common principles and discuss multidimensional approaches for community design. We propose a strategy for tailoring the design of functional SynComs based on integration of high-throughput experimental assays with microbial strains and computational genomic analyses of their functional capabilities.

Establishment of synthetic microbial consortia with Corynebacterium glutamicum and Pseudomonas putida: Design, construction, and application to production of γ-glutamylisopropylamide and l-theanine

Microbial synthetic consortia are a promising alternative to classical monoculture for biotechnological applications and fermentative processes. Their versatile use offers advantages in the degradation of complex substrates, the allocation of the metabolic burden between individual partners, or the division of labour in energy utilisation, substrate supply or product formation. Here, stable synthetic consortia between the two industrially relevant production hosts, Pseudomonas putida KT2440 and Corynebacterium glutamicum ATCC13032, were established for the first time. By applying arginine auxotrophy/overproduction and/or formamidase-based utilisation of the rare nitrogen source formamide, different types of interaction were realised, such as commensal relationships (+/0 and 0/+) and mutualistic cross-feeding (+/+). These consortia did not only show stable growth but could also be used for fermentative production of the γ-glutamylated amines theanine and γ-glutamyl-isopropylamide (GIPA). The consortia produced up to 2.8 g L-1 of GIPA and up to 2.6 g L-1 of theanine, a taste-enhancing constituent of green tea leaves. Thus, the advantageous approach of using synthetic microbial consortia for fermentative production of value-added compounds was successfully demonstrated.

Toward FAIR Representations of Microbial Interactions

Despite an ever-growing number of data sets that catalog and characterize interactions between microbes in different environments and conditions, many of these data are neither easily accessible nor intercompatible. These limitations present a major challenge to microbiome research by hindering the streamlined drawing of inferences across studies. Here, we propose guiding principles to make microbial interaction data more findable, accessible, interoperable, and reusable (FAIR). We outline specific use cases for interaction data that span the diverse space of microbiome research, and discuss the untapped potential for new insights that can be fulfilled through broader integration of microbial interaction data. These include, among others, the design of intercompatible synthetic communities for environmental, industrial, or medical applications, and the inference of novel interactions from disparate studies. Lastly, we envision potential trajectories for the deployment of FAIR microbial interaction data based on existing resources, reporting standards, and current momentum within the community.

Toward merging bottom-up and top-down model-based designing of synthetic microbial communities

The increasing interest of microbial communities as promising biocatalyst is leading an intense effort into the development of computational frameworks assisting the analysis and rational engineering of such complex ecosystems. Here, we critically review the recent computational and model-guided advances in the system-level engineering of microbiome, including both the rational bottom-up and the evolutionary top-down approaches. Furthermore, we highlight modeling and computational methods supporting both engineering paradigms. Finally, we discuss the advantages of combining both strategies into a hybrid top-down/bottom-up (middle-out) strategy to engineer synthetic microbial communities with improved performance and scope.

Microbiome-based interventions to modulate gut ecology and the immune system

The gut microbiome lies at the intersection between the environment and the host, with the ability to modify host responses to disease-relevant exposures and stimuli. This is evident in how enteric microbes interact with the immune system, e.g., supporting immune maturation in early life, affecting drug efficacy via modulation of immune responses, or influencing development of immune cell populations and their mediators. Many factors modulate gut ecosystem dynamics during daily life and we are just beginning to realise the therapeutic and prophylactic potential of microbiome-based interventions. These approaches vary in application, goal, and mechanisms of action. Some modify the entire community, such as nutritional approaches or faecal microbiota transplantation, while others, such as phage therapy, probiotics, and prebiotics, target specific taxa or strains. In this review, we assessed the experimental evidence for microbiome-based interventions, with a particular focus on their clinical relevance, ecological effects, and modulation of the immune system.