Metabolomics: Challenges and Success

Metabolomics is defined as the comprehensive analysis of all small-molecule compounds that can be found in biological samples, such as cells, tissues or biofluids (Fiehn, 2002). Interest in this research field stems from research goals of identifying biomarkers of disease, or quantifying biochemical phenotypes. Advances in mass spectrometry (MS) and variations of such compound separation technologies also spur the interest and growth. This presentation at NCCC170 serves as an introduction to a popular data analysis package, MetaboAnalyst (Xia & Wishart, 2011). The goal is to prepare fellow statistical consultants and collaborators with the process of this technique, and corresponding analyses options and interpretations. An experimental design and analysis will be presented. The experiment consists of a two-way balanced factorial treatment structure: (Salmonella challenge or Control) and (Prophylaxis treatment or Placebo), n=10 bovine per treatment group. The biological sample from each animal is blood serum, and metabolomics assay is gas chromatography/mass spectrometry (GC/MS). Raw spectral data processing steps is performed by a third-party contractor. MetaboAnalyst 3.0 web-based platform is utilized to perform data processing steps such as data normalization and transformation, as well as data analysis such as exploratory statistical analysis, ANOVA, and partial least squares/discriminant analysis (PLS/DA). The advantages and disadvantages of this pipeline and its results will be presented and discussed.