Metabolomics analyzes and quantifies all metabolites in a given biological sample. Powerful instrumentation along with sophisticated chemometric software allows for comparison of changes in thousands of chemical entities.
Metabolomics is becoming sufficiently mature to complement other systems biology tools and to deliver medically relevant results.
According to some metabolomics researchers, continued development of metabolomics platforms and technologies will inevitably lead to development of rapid and comprehensive disease diagnostics. This and other ideas were discussed at OMICS group’s “Metabolomics and Systems Biology” conference last month.
“Interpretations of metabolomics signatures will make rapid bedside diagnostics possible,” agreed Chris Beecher, Ph.D., CSO, NextGen Metabolomics. “In 5–10 years this information will transform our diagnostic capabilities. The meaningful metabolome interpretation will be available to a physician within minutes for a fraction of the cost of today’s analyses.”
NextGen is contributing to this vision by perfecting Isotopic Ratio Outlier Analysis™ (IROA), a mass-spectrometry-based protocol that enables efficient identification of all biological metabolites in a sample and their relative concentration, said Dr. Beecher.
The technology has its roots in a physiochemical phenomenon of naturally occurring C13 atoms. C13 has an extra neutron producing a pattern of additional peaks for each metabolite in a sample. Because of their low natural abundance and the presence of other elemental isotopes, these additional peaks (called M+1, M+2, etc.) are very small and not very informative.
“We simply boosted the C13 concentration by growing cells in a culture media engineered with precise balances of C13-bearing components,” continued Dr. Beecher. “When you compare a culture grown with 5% C13 with culture grown in 95% C13, each metabolite will be represented by a symmetrical pattern of C12 and C13 peaks. The parameters of this pattern tell us how many carbons the molecule contains and its mass.”
The mirror symmetry of MS peaks in IROA experiments enables rapid classification of all peaks as real cell products (have mirror counterparts) or artifacts and contaminants (no enhanced M+1, M+2, etc.). NextGen computer algorithms look for the same symmetry to perform phenotyping experiments.
To identify metabolites in tissue biopsies, the tissue cells are analyzed together with “standard” cells that were isotopically labeled with IROA C13 media. The tissue-derived metabolites can be easily identified by their mass and position relative to the standard.
The company demonstrated a significant proof of principle for toxicology analysis of drug candidates. Dr. Beecher’s team used IROA to show the response of every metabolite in the cell to flucytosine, a well-characterized inhibitor of DNA synthesis. The data showed clear response in metabolic pathways related to nucleotide biosynthesis, but not in other pathways.
“We plan to perfect this technology to answer fundamental questions in drug development,” commented Dr. Beecher. “What toxicities should we expect? What is the biological reason for this toxicity?” NextGen plans to set up internal biomarker and toxicology discovery departments based on IROA technology.