Intuitive Visualization and Analysis of Multi-Omics Dataand Application to Escherichia coli Carbon Metabolism

Combinations of ‘omics’ investigations (i.e, transcriptomic, proteomic, metabolomic and/or fluxomic) are increasingly applied toget comprehensive understanding of biological systems. Because the latter are organized as complex networks of molecular andfunctional interactions, the intuitive interpretation of multi-omics datasets is difficult. Here we describe a simple strategy tovisualize and analyze multi-omics data. Graphical representations of complex biological networks can be generated usingCytoscape where all molecular and functional components could be explicitly represented using a set of dedicated symbols. Thisrepresentation can be used i) to compile all biologically-relevant information regarding the network throughweb link association,and ii) to map the network components with multi-omics data. A Cytoscape plugin was developed to increase the possibilities ofbothmulti-omic data representation and interpretation. This plugin allowed different adjustable colour scales to be applied to thevarious omics data and performed the automatic extraction and visualization of the most significant changes in the datasets. Forillustration purpose, the approach was applied to the central carbon metabolism of Escherichia coli. The obtained networkcontained 774 components and 1232 interactions, highlighting the complexity of bacterialmulti-level regulations. The structuredrepresentation of this network represents a valuable resource for systemic studies of E. coli, as illustrated from the application tomulti-omics data. Some current issues in network representation are discussed on the basis of this work