Constraint-based stoichiometric modelling from single organisms to microbial communities

Abstract

Microbial communities are ubiquitously found in Nature and have direct implications for the environment, human health and biotechnology. The species composition and overall function of microbial communities are largely shaped by metabolic interactions such as competition for resources and cross-feeding. Although considerable scientific progress has been made towards mapping and modelling species-level metabolism, elucidating the metabolic exchanges between microorganisms and steering the community dynamics remain an enormous scientific challenge. In view of the complexity, computational models of microbial communities are essential to obtain systems-level understanding of ecosystem functioning. This review discusses the applications and limitations of constraint-based stoichiometric modelling tools, and in particular flux balance analysis (FBA). We explain this approach from first principles and identify the challenges one faces when extending it to communities, and discuss the approaches used in the field in view of these challenges. We distinguish between steady-state and dynamic FBA approaches extended to communities. We conclude that much progress has been made, but many of the challenges are still open.

Below‐ground connections underlying above‐ground food production: a framework for optimising ecological connections in the rhizosphere

“…In soil microbial networks, correlations between microbial taxa can result from a variety of interaction types (Box 1). To model process rates from data on interactions within microbial networks, and to predict functioning based on microbial network structure, we need to first elucidate the exact nature of dynamic microbemicrobe interactions (Gottstein et al 2016). Therefore, an important challenge is to identify interaction types between microbial groups or species and how these determine network structure.…”

Consistency, Inconsistency and Ambiguity of Metabolite Names in Biochemical Databases Used for Genome Scale Metabolic Modelling

“…Therefore, there is a need for models that can help combine both types of measurements. As a result, there are on-going efforts to define modelling frameworks, based on combining GEMs of individual organisms, to characterize the behaviour of the community [21,22,37,38]. Enabling unambiguous mapping will be required to take full advantage of these on-going developments.…”

Mathematical modelling of microbes: metabolism, gene expression and growth

“…It may seem somewhat paradoxical to exclude the major constituents of biomass from a model of microbial growth, but equation (3.6) can be replaced with a new definition of the growth rate, based on the rate of consumption of biomass precursor metabolites. To this end, similar to what was proposed in a recent review of FBA [79], we distinguish between free metabolites and the same metabolites incorporated into proteins and other macromolecules. The former, with concentration vector x M , are included in the model, whereas the latter, with mass vector C 0 M , are not, although they will be used in the derivation of the model ( figure 3).…”

“…One well-known example are so-called FBA approaches [79][80][81]. Below we summarize how flux balance models can be obtained from the general modelling framework of equations (5.4) -(5.7), by progressively introducing additional modelling assumptions.…”