Next-generation sequencing generates data at metagenome levels, but requires advanced integrative bioinformatics and modeling to turn the data into physiological knowledge of the interacting species. In this project, we will develop workflows and software tools to integrate the data from the MICROWINE partners into models of the eco-level physiology of the communities under study.
Since (meta)genomic data form the majority of data, and many relevant interactions within - and functions of - the these consortia are metabolic, we will develop pipelines for automatic reconstruction of microbial metabolic networks and foodwebs. We will focus on quality control with respect to evidence and inference, standards and annotation of these networks and the constituent components (species, genes, proteins, metabolites). Thermodynamic constraints will be used combined with information on the environment (part of the program) to probe the potential interactions and fucntionalities. Constraint-based modeling of genome-scale metabolic models will be combined with (network-based) coarse-graining of the community-species’ behaviours and their interactions.