Technology - Metabolomic

Computational prediction of human metabolic pathways from the complete human genome

Romero, P et al., 2004. Genome Biol. 6(1):R2-R18

Abstract

BACKGROUND:We present a computational pathway analysis of the human genome that assigns enzymes encoded therein to predicted metabolic pathways. Pathway assignments place genes in their larger biological context, and are a necessary first step toward quantitative modeling of metabolism. RESULTS:Our analysis assigns 2,709 human enzymes to 896 bioreactions; 622 of the enzymes are assigned roles in 135 predicted metabolic pathways. The predicted pathways closely match the known nutritional requirements of humans. This analysis identifies probable omissions in the human genome annotation in the form of 203 pathway holes (missing enzymes within the predicted pathways). We have identified putative genes to fill 25 of these holes. The predicted human metabolic map is described by a Pathway/Genome Database called HumanCyc, which is available at http://HumanCyc.org/. We describe the generation of HumanCyc, and present an analysis of the human metabolic map. For example, we compare the predicted human metabolic pathway complement to the pathways of Escherichia coli and Arabidopsis thaliana and identify 35 pathways that are shared among all three organisms. CONCLUSIONS:Our analysis elucidates a significant portion of the human metabolic map, and also indicates probable unidentified genes in the genome. HumanCyc provides a genome-based view of human nutrition that associates the essential dietary requirements of humans with a set of metabolic pathways whose existence is supported by the human genome. The database places many human genes in a pathway context, thereby facilitating analysis of gene expression, proteomics, and metabolomics datasets through a publicly available online tool called the Omics Viewer

Journal Link | PMID

Comment

This article illustrates how genomic and proteomic data can be used to computationally generate and fill-in metabolic pathways.  It includes tabulated lists of genes for important metabolic pathways with several corresponding illustrations of the pathways including those steps where the gene has not yet been identified.  As such, it is a good overview of the metabolomic approach.  Though it may be a bit more than a novice might want to try it is very useful for those teaching biochemistry and metabolism.  It contains multiple references to online databases and pathway websites.

Metabolic engineering in the -omics era: Elucidating and modulating regulatory networks

Vemuri, GN & Aristidou, AA, 2005. Microbiol. Molec. Biol. Rev. 69(2):197-216

Abstract

The importance of regulatory control in metabolic processes is widely acknowledged, and several enquiries (both local and global) are being made in understanding regulation at various levels of the metabolic hierarchy. The wealth of biological information has enabled identifying the individual components (genes, proteins, and metabolites) of a biological system, and we are now in a position to understand the interactions between these components. Since phenotype is the net result of these interactions, it is immensely important to elucidate them not only for an integrated understanding of physiology, but also for practical applications of using biological systems as cell factories. We present some of the recent "-omics" approaches that have expanded our understanding of regulation at the gene, protein, and metabolite level, followed by analysis of the impact of this progress on the advancement of metabolic engineering. Although this review is by no means exhaustive, we attempt to convey our ideology that combining global information from various levels of metabolic hierarchy is absolutely essential in understanding and subsequently predicting the relationship between changes in gene expression and the resulting phenotype. The ultimate aim of this review is to provide metabolic engineers with an overview of recent advances in complementary aspects of regulation at the gene, protein, and metabolite level and those involved in fundamental research with potential hurdles in the path to implementing their discoveries in practical applications.

Journal Link | PMID

Comment

A very well illustrated review of how to do metabolomics and how to use the information generated.  However, this review is a bit much for the novice since it assumes a significant understanding of molecular biology., But it is well worth the effort if one can get through it.