“NoTaMe”: Workflow for non-targeted LC-MS

1 University of Eastern Finland, Department of Clinical Nutrition and Public Health, Kuopio 10 2 University of Eastern Finland, School of Pharmacy, Faculty of Health Sciences, Kuopio 11 3 University of Eastern Finland, Institute of Biomedicine 12 4 Centre for Integrative Metabolomics & Computational Biology, School of Science, Edith Cowan University, 13 Joondalup 6027, Australia; d.broadhurst@ecu.edu.au 14 5 Chalmers University of Technology, Department of Biology and Biological Engineering; 15 carl.brunius@chalmers.se 16 17 † Equal contribution 18 * Correspondence: marietta.kokla@uef.fi; anton.klavus@uef.fi; kati.hanhineva@uef.fi 19 20 Abstract 21 Metabolomics analysis generates vast arrays of data, necessitating comprehensive 22 workflows involving expertise in analytics, biochemistry and bioinformatics, in 23 order to provide coherent and high-quality data that enables discovery of robust and 24 biologically significant metabolic findings. In this protocol article, we introduce 25 NoTaMe, an analytical workflow for non-targeted metabolic profiling approaches 26 utilizing liquid chromatography–mass spectrometry analysis. We provide an 27 overview of lab protocols and statistical methods that we commonly practice for the 28 analysis of nutritional metabolomics data. The paper is divided into three main 29 sections: the first and second sections introducing the background and the study 30 designs available for metabolomics research, and the third section describing in 31 detail the steps of the main methods and protocols used to produce, preprocess and 32 statistically analyze metabolomics data, and finally to identify and interpret the 33 compounds that have emerged as interesting. 34