Extending Biochemical Databases by Metabolomic Surveys

Abstract

Metabolomics can map the large metabolic diversity in species, organs, or cell types. In addition to gains in enzyme specificity, many enzymes have retained substrate and reaction promiscuity. Enzyme promiscuity and the large number of enzymes with unknown enzyme function may explain the presence of a plethora of unidentified compounds in metabolomic studies. Cataloguing the identity and differential abundance of all detectable metabolites in metabolomic repositories may detail which compounds and pathways contribute to vital biological functions. The current status in metabolic databases is reviewed concomitant with tools to map and visualize the metabolome.Biological databases are indispensable for comparing genomes, proteins, and biological regulation. GenBank TM , Protein Data Bank (PDB), and Gene Expression Omnibus (GEO) are prime examples of how collecting biological information in a coherent manner enables novel insights into evolution and to derive testable hypotheses for gene function, yet biochemical databases on substrate-product relationships and organismspecific metabolic networks have lagged behind. Much of this lag is due to the inherent complexity of enzymology. Small changes in protein folding or in mutations in catalytic sites not only may change reaction kinetics but also have large impact on substrate specificity. Enzymes may have much broader substrate specificity than usually considered. Moreover, many enzymes exert reaction promiscuity (1), which is exploited in bioengineering but which also complicates the reconstruction of metabolic networks. Low-abundant enzymatic side reactions have likely not been reported in favor of the dominant and apparently biologically relevant functions and are consequently lacking in biochemical databases, yet such side reactions may become the major enzyme function through evolutionary pressure. Hence, the number of metabolites per species (or per cell type in multicellular organisms) is hard to predict except for the most conserved metabolic pathways.Accordingly, a surprisingly small fraction of detected metabolites can be readily identified by sensitive screening tools such as HPLC-or GC-coupled MS (Fig. 1). It appears that the metabolome is much larger than anticipated. Phenotypes of species need to be determined by their individual metabolic capacities, defined by the plasticity and flexibility of their metabolic networks. Metabolites can act as intracellular and extracellular signals at very low concentrations and enable communication between organs, as well as serve multiple and vital roles for species in their ecological niches, e.g. for defense or reproductive purposes.

N -lactoyl-amino acids are ubiquitous metabolites that originate from CNDP2-mediated reverse proteolysis of lactate and amino acids

“…Our results underline that large parts of the metabolome remain to be discovered, even in a well-defined in vitro cell system (4). Untargeted metabolomics provides an obvious method to address this gap in our knowledge.…”

“…These databases cover large parts of the metabolome, but significant gaps remain. Due to poorly characterized and promiscuous enzymes, the human metabolome is much larger than initially anticipated (4). State-of-the-art untargeted metabolomics studies still report up to 40% unidentified, but potentially important, metabolites that can be detected reproducibly (5)(6)(7)(8).…”

System Response of Metabolic Networks in Chlamydomonas reinhardtii to Total Available Ammonium

“…However, 22 metabolites were not mapped to any pathway map in KEGG database, including important lipids such as 1-and 2-monopalmitin. Therefore, we used a recently proposed visualization method (62,69) that combined biochemical similarity (via the KEGG Rpair database) with chemical similarity (via decomposing chemical structures into sets of substructures and subsequently calculating the Tanimoto similarity (60)). Using Cytoscape software (63), all identified metabolites were then mapped as nodes in network graphs to highlight the temporal dynamics of metabolic responses toward nitrogen limitation.…”

Plant Metabolic Modeling: Achieving New Insight into Metabolism and Metabolic Engineering

“…A "pathway mapping" tool developed for the KEGG database produces a graphical display of the location of various metabolites in the relevant metabolic network (Fiehn et al, 2011). The ever-expanding volume of omics data requires the elaboration of new databases and associated analytical tools to allow for the efficient archiving, access, and sharing of data (Gutiérrez et al, 2005).…”