The integration of multi-omics data is a major approach for the understanding of pathophysiological mechanisms and the discovery of biomarkers in health. However, few multi-omics data are publicly available to date.
In a study recently published in the open data reference journal Scientific Data1, the four French Infrastructures (INBS) in Mouse Phenogenomics (Phenomin-ICS; www.phenomin.fr), Proteomics (ProFI; www.profiproteomics.fr), Metabolomics and Fluxomics (MetaboHUB; www.metabohub.fr) and Bioinformatics (IFB; www.france-bioinformatique.fr) have joined forces to develop and make available the data and processing pipeline for the characterization of murine samples by combined proteomics and metabolomics approaches.
Nine raw datasets (1 preclinical, 2 proteomic and 6 metabolomic), corresponding to the study of the knock-out mice for the Lat (linker for activation of T cells) and Mx2 genes (MX dynamin-like GTPase 2), are available in the reference repositories (IMPC, PRIDE, and MetaboLights). In addition, the pre-processed data and the bioinformatics analysis pipeline are also available as an open access R package (github.com/IFB-ElixirFr/ProMetIS).
The ProMetIS pilot study thus represents a significant advance towards molecular phenotyping of cohorts. In particular, the data provide unique information on the functional characterization of the Lat and Mx2 genes. They will also become a reference for accessibility, reproducibility and interoperability (FAIR criteria) in the field of multi-omics studies. These data will be particularly valuable for developing new approaches for bioinformatic and biostatistic integration.
1Imbert, A., Rompais, M., Selloum, M., Castelli, F., Mouton-Barbosa, E., Brandolini-Bunlon, M., Chu-Van, E., Joly, C., Hirschler, A., Roger, P., Burger, T., Leblanc, S., Sorg, T., Ouzia, S., Vandenbrouck, Y., Médigue, C., Junot, C., Ferro, M., Pujos-Guillot, E., de Peredo, A. G., Fenaille, F., Carapito, C., Herault, Y., & Thévenot, E. A. (2021). ProMetIS, deep phenotyping of mouse models by combined proteomics and metabolomics analysis. Scientific Data, 8(1). https://doi.org/10.1038/s41597-021-01095-3