Personalized Metabolomics
The human metabolome is the cumulative product of ingested metabolites and those produced by the body and its microbiota. Together these metabolites can dynamically report on the health and disease state of an individual, as well as their response to drug
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Introduction Understanding health and disease requires the detailed analysis of both an individual’s genome and the molecular events that determine human physiology [1]. The advent of accessible genomic sequencing has revolutionized the diagnosis of monogenetic disorders and enabled the expanded clinical application of personalized disease risk [2] and drug response prediction [3]. However, despite these advances the static nature of the genome limits the prognostic power for many of the most common diseases with origins that are complex and strongly influenced by the environment. As such, significant efforts have focused on capturing the dynamic aspects of human health by integrating the measurement of the microbiome, transcriptome, proteome, and metabolome from clinical samples with patient genomes [4]. This approach has been used to study the health of individuals longitudinally [5, 6] and identify biomarkers in large disease cohorts [7]. It has also revealed opportunities to therapeutically target the microbiome to treat human disease [8].
Angelo D’Alessandro (ed.), High-Throughput Metabolomics: Methods and Protocols, Methods in Molecular Biology, vol. 1978, https://doi.org/10.1007/978-1-4939-9236-2_27, © Springer Science+Business Media, LLC, part of Springer Nature 2019
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David P. Marciano and Michael P. Snyder
The metabolome in particular has long been leveraged for its clinical utility, with dozens of metabolites routinely measured as FDA-approved diagnostics. The goal of modern clinical metabolomics is to expand these measurements to include thousands of molecules [9]. To this end, robust LC-MS-based methods have been developed that approach the coverage, throughput, and cost requirements of routine clinical application. These advances have enabled large-scale studies to identify common genetic polymorphism that influence metabolism [10] and are central to the widespread adoption of personalized metabolomics to stratify patients and inform medical decisions. In this chapter we describe the sample preparation, LC-MS methods, and data analysis workflow to enable the untargeted profiling of blood plasma and urine metabolites.
2 Materials All solutions should be prepared with >99% ultrapure HPLC-MS grade reagents in glass bottles to minimize background signal. Standard deionized water contains significant amounts of organic contaminants. Powder-free nitrile gloves should be worn during sample preparation. 2.1 Blood Plasma and Urine Preparation
1. EDTA-coated whole blood collection tube (e.g., BD Biosciences K2 EDTA #366643). 2. Sterile urine collection cup.
2.2 Metabolite Extraction
1. Plasma precipitation solvent: HPLC-MS grade acetone- acetonitrile-methanol (1:1:1, v/v) (see Note 1). 2. Urine precipitation solvent: HPLC-MS grade methanol. 3. 2 mL polypropylene microcentrifuge tubes (e.g., Eppendorf LoBind) (see Note 2). 4. Sample mixer (e.g., HulaMixer). 5. Nitrogen evaporator (e.g., Biotage TurboVap LV or equivalent). 6. LC compatible glass vials and low volume inserts (e.g., WAT094171D
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