Community‐scale models of microbiomes: Articulating metabolic modelling and metagenome sequencing

Author:

Cerk Klara12,Ugalde‐Salas Pablo3,Nedjad Chabname Ghassemi34,Lecomte Maxime35,Muller Coralie3,Sherman David J.3,Hildebrand Falk12,Labarthe Simon36,Frioux Clémence3ORCID

Affiliation:

1. Quadram Institute Bioscience Norwich UK

2. Earlham Institute Norwich UK

3. Inria, University of Bordeaux, INRAE Talence France

4. University of Bordeaux, CNRS, Bordeaux INP, LaBRI, UMR 5800 Talence France

5. INRAE STLO¸University of Rennes Rennes France

6. INRAE, University of Bordeaux, BIOGECO, UMR 1202 Cestas France

Abstract

AbstractBuilding models is essential for understanding the functions and dynamics of microbial communities. Metabolic models built on genome‐scale metabolic network reconstructions (GENREs) are especially relevant as a means to decipher the complex interactions occurring among species. Model reconstruction increasingly relies on metagenomics, which permits direct characterisation of naturally occurring communities that may contain organisms that cannot be isolated or cultured. In this review, we provide an overview of the field of metabolic modelling and its increasing reliance on and synergy with metagenomics and bioinformatics. We survey the means of assigning functions and reconstructing metabolic networks from (meta‐)genomes, and present the variety and mathematical fundamentals of metabolic models that foster the understanding of microbial dynamics. We emphasise the characterisation of interactions and the scaling of model construction to large communities, two important bottlenecks in the applicability of these models. We give an overview of the current state of the art in metagenome sequencing and bioinformatics analysis, focusing on the reconstruction of genomes in microbial communities. Metagenomics benefits tremendously from third‐generation sequencing, and we discuss the opportunities of long‐read sequencing, strain‐level characterisation and eukaryotic metagenomics. We aim at providing algorithmic and mathematical support, together with tool and application resources, that permit bridging the gap between metagenomics and metabolic modelling.

Funder

Biotechnology and Biological Sciences Research Council

Medical Research Council

Agence Nationale de la Recherche

Institut national de recherche en informatique et en automatique

H2020 European Research Council

Publisher

Wiley

Subject

Applied Microbiology and Biotechnology,Biochemistry,Bioengineering,Biotechnology

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