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Review
, 19 (8), 712-722

Metabolic Modeling of Microbial Community Interactions for Health, Environmental and Biotechnological Applications

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Review

Metabolic Modeling of Microbial Community Interactions for Health, Environmental and Biotechnological Applications

Kok Siong Ang et al. Curr Genomics.

Abstract

In nature, microbes do not exist in isolation but co-exist in a variety of ecological and biological environments and on various host organisms. Due to their close proximity, these microbes interact among themselves, and also with the hosts in both positive and negative manners. Moreover, these interactions may modulate dynamically upon external stimulus as well as internal community changes. This demands systematic techniques such as mathematical modeling to understand the intrinsic community behavior. Here, we reviewed various approaches for metabolic modeling of microbial communities. If detailed species-specific information is available, segregated models of individual organisms can be constructed and connected via metabolite exchanges; otherwise, the community may be represented as a lumped network of metabolic reactions. The constructed models can then be simulated to help fill knowledge gaps, and generate testable hypotheses for designing new experiments. More importantly, such community models have been developed to study microbial interactions in various niches such as host microbiome, biogeochemical and bioremediation, waste water treatment and synthetic consortia. As such, the metabolic modeling efforts have allowed us to gain new insights into the natural and synthetic microbial communities, and design interventions to achieve specific goals. Finally, potential directions for future development in metabolic modeling of microbial communities were also discussed.

Keywords: Community modeling; Flux balance analysis; Genome-scale metabolic models; Kinetic models; Metabolism; Microbial communities.

Figures

Fig. (1)
Fig. (1)
The approaches employed to model and study microbial communities can be divided into three major categories: compartmentalized and lumped. A) In a compartmentalized simulation model, each species or functional guild occupies its own distinct compartment. B) In a lumped reaction network simulation model, all reactions are included in a single network with no segregation into distinct subsets. C) The graph summarizes the number of published studies on modeling microbial communities (See supplementary materials for list of collected studies). There is a clear trend of an increasing number of studies published until 2 years ago, where the number of studies fell dramatically.
Fig. (2)
Fig. (2)
The published metabolic community modeling studies are divided into different areas of application: biogeochemical, bioremediation, gut microbiome, waste water treatment, and synthetic consortia.

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