Latest technological advances in accurate mass spectrometry and data analysis have revolutionized metabolomics experimentation. assignment of artificial and non-physiological functions. This review discusses state-of-the-art metabolomic approaches and highlights recent Masitinib examples of their use for enzyme annotation discovery of new metabolic pathways and gene assignment of orphan metabolic activities across diverse biological sources. sequence homology-based methods have been the driving force behind most genome annotation endeavours to date 2. Despite their strengths in Masitinib automation and sample throughput such techniques are unable to identify the functions of novel gene sequences that have little to no homology with pre-existing database entries or may lead to the misannotation of gene products that share very high homology but catalyse fundamentally different reactions. Gene misannotations in particular are a prevalent consequence of automated methods and the propagation of such misannotations is usually a serious and growing threat to the accuracy and reliability of genome and protein databases 3-5. Automated genome annotation remains the only viable option to efficiently process genetic sequences at their current rate of influx although a more comprehensive and experimentally decided understanding of the relationship between primary sequence and function is clearly required in order to improve annotation accuracy. A significant proportion of unannotated or misannotated genes encode enzymes the catalytic activity of which is usually fundamental to their physiological function. Techniques that can directly exploit or monitor the native activity of a candidate enzyme are therefore powerful tools in accurate functional assignment of unannotated gene products: several approaches that have historically been used to annotate enzyme function as well as newly developed techniques are described in Fig 1 and Table ?Table1.1. However many activity-based assays-for example those performed with purified enzyme preparations-require at least a prior basic knowledge of the type of reaction catalysed by or substrate specificity of the candidate enzyme and therefore lack broad applicability. Furthermore testing individual putative substrates on a case-by-case basis is usually time-consuming and expensive and relies on the native substrate being commercially available. Alternatively screens performed in the host organism are less biased as they evaluate enzyme activity within a physiologically relevant milieu. Forward and reverse genetic screens for example are fundamental tools in uncovering the function of unknown gene products but ultimately rely on the emergence of observable phenotypic traits for successful gene assignment which does not occur for many mutants 6 7 An activity-based proteomics approach (activity-based proteomic profiling; ABPP) has been recently used to identify class-specific enzymes within a complex mixture (including in cells) in an unbiased manner using covalent active-site-directed probes 8. Its potential as an enzyme function discovery tool has been illustrated by the successful assignment of mechanistic class and function to previously unannotated enzymes that lack sequence homology with canonical members of their enzyme class 9 10 Despite its dependence on unique synthetic chemistry tools and limited scope in native substrate identification this technique demonstrates the usefulness of physiologically relevant sequence- and phenotype-independent tools in modern functional genomics. Table 1 Strategies for enzyme function discovery Figure 1 Approaches used to uncover the function of orphan enzymes Masitinib Metabolites constitute the substrates and products of enzymatic reactions and the study of the total metabolite pool of a given organism or cell type is known as metabolomics. As metabolites represent the final outcome of gene expression and activity the metabolome can be perceived as the LRRC63 ultimate readout of the biochemical and physiological state Masitinib of a cell that is a direct link between mechanistic biochemistry and cellular phenotype 11. The concept of metabolomic profiling for assessing cellular or bodily function is not new 12; Masitinib however the analytical and computational technologies have only recently become sufficiently powerful and widely accessible to allow routine and unbiased investigations of cellular metabolite pools. With the latest improvements in mass.