A Taguchi Design of Experiments Approach for Untargeted Metabolomics Sample Preparation Optimization

Metabolomics commonly uses analytical techniques such as nuclear magnetic resonance (NMR) and liquid chromatography coupled to mass spectrometry (LC-MS) to quantify and identify metabolites associated with biological variation. Metabolome coverage from untargeted LC-MS studies relies heavily on the pre-analytical protocols used (e.g., homogenization and extraction). Chosen protocols impact which metabolites are successfully measured, which in turn impacts biological conclusions. Furthermore, different homogenization and extraction parameters produce significant variability in metabolome coverage, sample reproducibility, and extraction efficiency. There is a need for an efficient and systematic approach to optimize matrix-specific sample preparation parameters. Herein we describe a Taguchi design of experiments (DOE) approach for matrix-specific sample preparation optimization using model organism Caenorhabditis elegans. To demonstrate this methodology we optimized: i) extraction solvent, ii) volume, iii) extraction time, and iv) LC reconstitution solvent for a sequential non-polar and polar extraction, and confirmed our optimized results using NMR spectroscopy. DOE is rarely used in metabolomics, yet it provides a systematic path forward for optimizing multiple sample preparation parameters while keeping the number of experiments, labor, and costs necessarily low. Altogether, the Taguchi DOE method is an adaptable and scalable method well-fit for the diversity of current and future hypotheses studied using untargeted metabolomics.