Protocol for quality control in metabolic profiling of biological fluids by U(H)PLC-MS

• Untargeted metabolomics often lack standardisation and quality control assessment.
• Data quality assessment should be thorough employing different statistical tools.
• A roadmap is proposed for the QC of LC-HRMS untargeted metabolomics data.
• The current protocol allows monitoring the analytical processes.
• Set up of analytical sequence, data collection, analysis and processing are studied.

The process of untargeted metabolic profiling/phenotyping of complex biological matrices, i.e., biological fluids such as blood plasma/serum, saliva, bile, and tissue extracts, provides the analyst with a wide range of challenges. Not the least of these challenges is demonstrating that the acquired data are of “good” quality and provide the basis for more detailed multivariate, and other, statistical analysis necessary to detect, and identify, potential biomarkers that might provide insight into the process under study. Here straightforward and pragmatic “quality control (QC)” procedures are described that allow investigators to monitor the analytical processes employed for global, untargeted, metabolic profiling. The use of this methodology is illustrated with an example from the analysis of human urine where an excel spreadsheet of the preprocessed LC–MS output is provided with embedded macros, calculations and visualization plots that can be used to explore the data. Whilst the use of these procedures is exemplified on human urine samples, this protocol is generally applicable to metabonomic/metabolomic profiling of biofluids, tissue and cell extracts from many sources.