Citation:

CHERNEY, D. P. AND T. W. COLLETTE. RAMAN SPECTROSCOPY-BASED METABOLOMICS: EVALUATION OF SAMPLE PREPARATION AND OPTICAL ACCESSORIES. Presented at Federation of Analytical Chemistry and Spectroscopy Societies Conference, Quebec City, QC, CANADA, October 09 - 13, 2005.

Impact/Purpose:

This task is divided into four major research areas: (1) Development of computational tools and databases for screening-level modeling of the environmental fate of organic chemicals; (2) Metabolism of xenobiotics: Enhancing the development of a metabolic simulator; (3) Metabonomics: The use of advanced analytical tools to identify toxicity pathways; and (4) Software infrastructure to support development and application of transformation/metabolic simulators.

For many chemicals, multiple transformation/metabolic pathways can exist. Consequently, transformation/metabolic simulators must utilize transformation rate data for prioritization of competing pathways. The prioritization process thus requires the integration of reliable rate data. When this data is absent, it is necessary to generate a database with metabolic and transformation rate constants based on: (1) experimentally measured values, including those requiring the use of advanced analytical techniques for measuring metabolic rate constants in vivo and in vitro; (2) rate constants derived from SPARC and mechanistic-based QSAR models; and (3) data mined from the literature and Program Office CBI. A long-term goal of this project is to build this database. This information will be used to enhance the predictive capabilities of the transformation/metabolic simulators. As indicated previously, exposure genomics, which provide early signs of chemical exposure based on changes in gene expression, will be used to guide chemical fate and metabolism studies. The incorporation of exposure genomics into fate studies will provide information concerning (1) the minimal concentrations at which biological events occur; and (2) the identification of biologically relevant chemicals(s) in mixtures.

The capability of categorizing chemicals and their metabolites based on toxicity pathway is imperative to the success of the CompTox Research Program. Metabonomics, which is the multi-parametric measurement of metabolites in living systems due to physiological stimuli and/or genetic modification, provides such a capability. The application of metabonomics to toxicity testing involves the elucidation of changes in metabolic patterns associated with chemical toxicity based on the measurement of component profiles in biofluids, and enables the generation of spectral profiles for a wide range of endogenous metabolites. Metabolic profiles can provide a measure of the real outcome of potential changes as the result of xenobiotic exposure.

Description:

The field of metabonomics/metabolomics involves observing endogenous metabolites from organisms that change in response to exposure to a stressor or chemical of interest. Methods are being developed for measuring the Raman spectra of low-concentration metabolites in urine. The goal of this study is to be able to both detect and quantify individual metabolites in urine. A list of 20 of the most concentrated metabolites in urine was compiled and standard solutions were prepared of both individual components and mixtures at physiologically relevant concentrations. Raman spectra of these were then compared with spectra of real urine samples. To prepare these samples for Raman spectroscopy, it was necessary to remove as many fluorescing molecules that reduce the S/N ratio of the non-fluorescing metabolites as possible. A variety of techniques were used to reduce fluorescence interference including charcoal filtration, ultrafiltration cells and photobleaching of samples. Two different excitation wavelengths (532 and 785nm) along with a cuvette and a waveguide (liquid core optical fiber) were employed to compare the S/N ratio of the metabolites found in urine. Lastly, the concentrations of the individual synthetic components were used to determine the concentration of those components in human urine samples via successive subtraction and with the use of PLS. Thus far, use the green wavelength (532 nm) with a waveguide and sample ultrafiltration has shown the most promise for quantification of metabolites. Subtraction of the individual component spectra shows that constructively interfering peaks may be individually quantified for some of the most concentrated samples.

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