Molecular interactions provide the basis and structure of all life and living systems. Specifically, small molecules are principle mediators of essential processes across phyla, including signal transduction and metabolism, as well as interorganismal chemical attraction and defense. Therefore, the knowledge of the identity of these molecules and their biosynthetic and degradation pathways is central to understand living systems. In this thesis, a comparative metabolomics approach will be discussed which is heavily based on 2D-NMR Spectroscopy but often requires LC/MS validation. Using this technique, two main small-molecule metabolic pathways have been investigated in the purview of this thesis using the model organism C. elegans. The first one, the steroid biogenesis pathway, plays a central role in C. elegans metabolism by dictating its reproductive and developmental future and even its lifespan. Steroidal ligands have been proposed to bind to the Nuclear Hormone Receptor - DAF-12 and here using our approach we identify for the first time, the complete set of DAF-12 ligands in an unbiased and unambigious way. We then continue to investigate the biosynthetic pathway of these ligands and uncover components of the network that were previously unrecognized, thus fundamentally revising the current viewpoint on this subject for future researchers to explore. The second pathway, tryptophan degradation pathway, has increasingly become one of the most studied pathways in living organisms. In the context of this thesis we first identify anthranilic acids, metabolites of the tryptophan degradation pathway, as the fluorophore, that results in a striking blue fluorescence moments prior to the worm's death. This result is astounding since until now the origin of this fluorescence was considered to be something entirely different. Our findings reconfirm the importance of tryptophan catabolism across all organisms and provide us with a fantastic opportunity to explore and elucidate the roles of the non-small molecule components of a biosynthetic network, using metabolomics.