Post-Genomics Blog

Forging a connection between research and clinical applications.


The central achievement of the genomics revolution in biology arguably lies in the mapping and sequencing of the human genome and the generation of the fine haplotype maps that are being used to study human diversity. While this is an amazing accomplishment that will likely pay dividends for years, the genome’s sequence itself has taught us little that has immediate applicability in human health. This was clearly anticipated by some, who reflected that knowing the sequence of a 10 kB virus did little to immediately curb the AIDS epidemic, nor did identification of the gene for Huntington’s disease lead immediately to a cure for that disease. In both cases, however, great strides have been made, and these great strides have followed from the integration of genomics data with data from other areas, including studies of gene expression (mRNA and protein) and general biochemistry and cell biology studies.

Just as genomics is the -omics face of DNA sequence analysis, metabolomics is the -omics face of biochemistry and an important piece in an -omics approach to understanding cell and system level biology. One definition, which I believe originated with Oliver Fiehn, is that metabolomics is the measurement of changes in populations of low molecular weight metabolites under a given set of conditions. The field and its subfields have been known by many names, including metabolomics, metabonomics, metabolic fingerprinting, metabolite profiling, metanomics, metabolic profiling, metabolite target analysis, and metabolic footprinting. Today the most common usage, except perhaps within the NMR community, is metabolomics. NIH has placed metabolomics on the Roadmap (NIH’s plan for solving critical biomedical needs), and the FDA is also becoming active (Center for Metabolomics, Division of Systems Toxicology, NCTR, see also There is a journal devoted to the field (Metabolomics, Springer) and an international society (The Metabolomics Society, Standards for the field are actively being addressed (see society website if you wish to become involved).

Conceptually, the genome gives rise to the transcriptome, the transcriptome to the proteome, and the proteome acts on the endogenous and exogenous small molecule subset of the organism, the metabolome. Feedback interactions exist at all levels, and it is clear that all levels, including the metabolome, are both sensitive to environmental influences, including nutrition, toxicants, etc and reflect the physiological status of the organism.

Briefly, the workflow in a metabolomics study involves sample collection, high data density analytical instrumentation such as NMR, mass spectroscopy, or HPLC, data curation and a series of bioinformatics approaches. From the biochemical standpoint we measure metabolites (small molecules), pathways (eg, purine catabolites), interactive pathways (eg, amino acid metabolism), compound classes (eg, lipids), and conceptually linked systems (eg, antioxidants and damage products). From the conceptual standpoint, we measure biochemical constituents, excretion products, precursor-product relationship, balances (eg, redox systems), collection depots (eg, sera, urine), flux, snapshot views of biochemistry, integrated signal from genome and environment, short and long term status, temporal images, sub-threshold changes (eg, in toxicology and nutrition).

Metabolomics is being used to address questions across multiple broad areas of biology. It will eventually take its place with proteomics and transcriptomics as a central player in systems biology, especially as work within the computational biology field has already made inroads in this area. Other questions that will be addressed using metabolomics center about environmental influence, functional genomics, biomarkers and classification, mechanisms of disease, drug development and personalized medicine and nutrition.

Metabolomics offers advantages and disadvantages that complement those of the other omics level investigations. The advantages of metabolomics include its great sensitivity, the knowledge base that comes from years of biochemical research, the relatively small size of the number of endogenous molecules relative to the number of genes, mRNA species, or proteins. Another major advantage lies in metabolomics being the end product of the intersection of nature and nurture, at least theoretically offering an ability to gain that aforementioned snapshot and hope to encompass a broad picture. In addition, metabolomics is the fastest system to react to stimuli or to change, enabling the most current view possible of the organism. Of course, these advantages can also be disadvantages—the great sensitivity and responsiveness of the metabolome means that it is also the most subject to noise, complicating experimental design and interpretation. There are also practical issues, such as the comparatively high set-up costs and requirement for complex informatics and, in some cases, multiple analytical platforms.

Different analytical instrumentation platforms each have different strengths and weaknesses. For example, NMR offers high throughput, non-destructive analysis and the ability to look at intact tissue, but is relatively insensitive. Gas chromatography-mass spectroscopy offers high throughput and automated analysis of known compounds, but detection is limited to volatile compounds and the technique has medium sensitivity. An interesting system that we work with is HPLC separations coupled with coulometric electrode array detection (ESA, Inc, a company which, by way of disclosure, I collaborate and share intellectual property). The system offers high sensitivity and precision, but low throughput and less knowledge about biochemical identity. The system is particularly intriguing because it only sees redox active compounds, a strength in studying systems such as neurotransmitters and redox system, a limitation for systems such as the Krebs’ cycle in which the metabolites are relatively redox insensitive.

Metabolomics as a field has gone from one meeting a little as two years ago to at least eight this year. Several biotech companies have arisen to fill this niche, some, such as Metabolon (again, in interest of disclosure, a company I have financial interest in), focused on drug development and broad capture of the human and animal metabolome, to company specializing in specific areas, such as plants, lipids (Lipomics) or flux (SIDMAP), or in specific diseases, such as liver abnormalities.

In summary, metabolomics is a rapidly growing field with the potential to play major roles in helping to understand the complex issues in health and disease that are the focus in the post-genomics age.

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