Modelling approaches for studying the microbiome

Abstract

Advances in metagenome sequencing of the human microbiome have provided a plethora of new insights and revealed a close association of this complex ecosystem with a range of human diseases. However, there is little knowledge about how the different members of the microbial community interact with each other and with the host, and we lack basic mechanistic understanding of these interactions related to health and disease. Mathematical modelling has been demonstrated to be highly advantageous for gaining insights into the dynamics and interactions of complex systems and in recent years, several modelling approaches have been proposed to enhance our understanding of the microbiome. Here, we review the latest developments and current approaches, and highlight how different modelling strategies have been applied to unravel the highly dynamic nature of the human microbiome. Furthermore, we discuss present limitations of different modelling strategies and provide a perspective of how modelling can advance understanding and offer new treatment routes to impact human health.

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Fig. 1: Schematic illustration of ODE-based modelling accounting for phenotypic traits of microorganisms.
Fig. 2: Modelling strategies based on sequence-read abundance.
Fig. 3: Fundamentals of GEMs.
Fig. 4: Community-level analysis of gut microbiome based on GEMs.
Fig. 5: Applications of mathematical modelling in the systems-level analysis of human gut microbiome.

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Acknowledgements

We acknowledge financial support from Knut and Alice Wallenberg Foundation, the Novo Nordisk Foundation (grant no. NNF10CC1016517), Vetenskapsrådet, Bill & Melinda Gates Foundation (grant no. OPP1127499), MetaCardis (grant no. HEALTH-F4-2012-305312), FORMAS and the Swedish Foundation for Strategic Research.

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M.K., B.J. and J.N. collectively conceptualized the manuscript. M.K., B.J., K.Z. and J.N. wrote the manuscript.

Correspondence to Jens Nielsen.

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