An award is made to the University of North Carolina at Charlotte to develop a computational workflow that will create libraries of high-quality mass spectra for unknown metabolites that are observed repeatedly by mass spectrometers in metabolomics studies. Metabolomics is a rapidly developing field of ?omics? research concerned with the high-throughput identification and quantitation of small molecule metabolites in the metabolome. Since the metabolome constitutes a wide array of compound classes that are crucial for the normal functioning of a biological system, the metabolomics approach promises to offer new insights in many areas of biological investigation. Recent metabolomics research benefited greatly from advances in mass spectrometry and chromatography. These advances allow researchers to detect many metabolites that could not be detected previously. However, a sizable fraction of these compounds are unknown and a new computational infrastructure is required for processing the complex mass spectral data and identifying and characterizing these metabolites. This project addresses this need by developing a computational workflow that will create libraries of high-quality mass spectra for unknown compounds from many samples. These resulting libraries will enable the identification of many currently unidentified, but commonly observed components by their spectra. Equally important, the workflow will allow more precise quantitation of metabolites and subsequent differential analysis of metabolic profiles. The most biologically interesting unknown compounds in the library can then be subjected to further attempts at structure elucidation.
The project will contribute to the training of postdoctoral fellows and graduate students in bioinformatics methods. The PI will develop modules covering metabolomics bioinformatics methods for a graduate course. Materials developed for the class will also be made available online and presented at a bioinformatics workshop hosted at UNC-Charlotte.
