Metabolomics is the high-throughput quantitative analysis of the low molecular weight molecules in a biological system. Wrongly confused with chemometrics, as they use the same analytical set up, metabolomics is a multi-step biomolecular analysis aiming at providing a wide perspective of the metabolic physiology. Metabolism is the intertwined network of metabolic reaction pathways, which catabolize the carbon and energy resources of a system, to synthesize biomass for the system’s activity and growth and produce energy needed for all vital processes. Metabolomics quantifies the molecules that act as reactants and products in the metabolic reactions and as regulatory molecules of many proteins. It is thus the collective analysis of the measured abundances in the context of the role that these molecules play in the metabolic network in particular and in the overall biomolecular network at large, that can upgrade the information content of the metabolomic datasets. Molecular quantities being interconnected based on a certain stoichiometry, even subtle differences in one can carry significance if viewed in the context of the observed changes in the rest of the molecules. Moreover, one can explore disruptions in the network connectivity and dynamics to reveal molecular mechanisms of pathophysiologies and/or identify targets of systematic external intervention. Hence, metabolomics in systems biology can be a significant tool in many fields, from precision/translational medicine and personalized nutrition, to precision agriculture, ecology, functional genomics and synthetic biology.

In this seminar, I will use two recent collaborative studies of my group in quite distinct fields, translational psychiatry and ecophysiology, to support the power of metabolomics in systems biology to discriminate between physiologies with subtle differences when the conventionally applied tests and physiological measurements cannot, revealing characteristic multi-compound profiles that can form the basis for sensitive diagnostic tools, while providing clues for underlying molecular mechanisms and confounding factors that had been unknown so far. The importance of standardized experimental and computational protocols for designing and executing a reliable metabolomic study will also be discussed.