BI86CH12-Rabinowitz ARI 17 May 2017 16:18 ANNUAL REVIEWS Further Click here to view this article's online features: • Download figures as PPT slides • Navigate linked references • Download citations Metabolite Measurement: • Explore related articles • Search keywords Pitfalls to Avoid and Practices to Follow Wenyun Lu,1 Xiaoyang Su,1 Matthias S. Klein,2 Ian A. Lewis,2 Oliver Fiehn,3,4 and Joshua D. Rabinowitz1 1Lewis Sigler Institute for Integrative Genomics and Department of Chemistry, Princeton University, Princeton, New Jersey 08544; email: [email protected] 2Department of Biological Science, University of Calgary, Calgary, Alberta T2N 1N4, Canada 3National Institutes of Health West Coast Metabolomics Center, University of California, Davis, California 95616 4Department of Biochemistry, King Abdulaziz University, Jeddah, Saudi Arabia Annu. Rev. Biochem. 2017. 86:277–304 Keywords The Annual Review of Biochemistry is online at metabolomics, metabonomics, metabolite extraction, stability, accuracy, biochem.annualreviews.org mass spectroscopy https://doi.org/10.1146/annurev-biochem- 061516-044952 Abstract Copyright c 2017 by Annual Reviews. Metabolites are the small biological molecules involved in energy conver- All rights reserved sion and biosynthesis. Studying metabolism is inherently challenging due to metabolites’ reactivity, structural diversity, and broad concentration range. Access provided by West Virginia University on 03/11/19. For personal use only. Annu. Rev. Biochem. 2017.86:277-304. Downloaded from www.annualreviews.org Herein, we review the common pitfalls encountered in metabolomics and provide concrete guidelines for obtaining accurate metabolite measure- ments, focusing on water-soluble primary metabolites. We show how seem- ingly straightforward sample preparation methods can introduce systematic errors (e.g., owing to interconversion among metabolites) and how proper selection of quenching solvent (e.g., acidic acetonitrile:methanol:water) can mitigate such problems. We discuss the specific strengths, pitfalls, and best practices for each common analytical platform: liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS), nuclear magnetic resonance (NMR), and enzyme assays. Together this in- formation provides a pragmatic knowledge base for carrying out biologically informative metabolite measurements. 277 BI86CH12-Rabinowitz ARI 17 May 2017 16:18 Contents 1. SCOPE OF THE CHALLENGE . 278 2.ABSOLUTEVERSUSRELATIVEQUANTITATION......................... 279 3.QUENCHING................................................................. 279 4.EXTRACTION................................................................ 280 4.1.ExtractionMethods........................................................ 281 4.2. Sample Degradation and Metabolite Interconversion After Extraction . 282 4.3.TakeHomeMessage....................................................... 283 5.LIQUIDCHROMATOGRAPHY-MASSSPECTROMETRY................... 284 5.1.MassSpectrometry......................................................... 284 5.2. Liquid Chromatography . 285 5.3.PeakMisidentification...................................................... 285 5.4. Quantitative Error in Liquid Chromatography-Mass Spectrometry . 289 6.GASCHROMATOGRAPHY-MASSSPECTROMETRY....................... 290 7. HIGH-THROUGHPUT MASS SPECTROMETRY. 292 8.NUCLEARMAGNETICRESONANCE....................................... 292 8.1. Practical Recommendations for Identifying and Quantifying Metabolites by NMR . 294 8.2.NMR-BasedMeasurementofIsotopeLabeling.............................. 294 8.3.InVivoNMR.............................................................. 294 9.ENZYMEASSAYS............................................................. 295 9.1.ATP....................................................................... 295 9.2. NADPH/NADP+ .......................................................... 295 9.3.Glutathione................................................................ 296 10.OUTLOOK................................................................... 297 1. SCOPE OF THE CHALLENGE In contrast to DNA, RNA, and proteins, which are made by genetically encoded polymerization of a small number of building blocks, metabolites do not follow a fixed structural template and accordingly have diverse physical properties. As a result, no single analytical tool can measure all metabolites. In addition, the complete scope of metabolic networks remains unknown, and this uncertainty complicates metabolite analysis because a definitive list of relevant analytes (analogous Access provided by West Virginia University on 03/11/19. For personal use only. Annu. Rev. Biochem. 2017.86:277-304. Downloaded from www.annualreviews.org to genes in the genome) is lacking. The Human Metabolome Database (HMDB) (1, 2) is a good illustration of this uncertainty: The HMDB has identified more than 40,000 putative human metabolites, but only 680 of the HMDB’s water-soluble compounds have been mapped to standard metabolic pathways in humans (3). The biological significance of many unmapped compounds remains unknown. Metabolites can be classified in both biological and chemical dimensions. Biologically, pri- mary metabolites are required for growth, development, and reproduction, whereas secondary metabolites are involved in communication, defense, or other life cycle–independent functions. Chemically, water-soluble versus insoluble compounds must be extracted in different solvents, and therefore, solubility plays a major role in real-world metabolomics studies. Primary water-soluble metabolites are key players in the conversion of nutrients into usable energy, provide the building blocks for biomass, turn over rapidly, and collectively carry the vast majority of metabolic flux. They are among the most evolutionarily conserved biomolecules. 278 Lu et al. BI86CH12-Rabinowitz ARI 17 May 2017 16:18 This review focuses on the practical challenges that are encountered in the analysis of water- soluble primary metabolites with particular attention to issues arising from their reactivity and fast cellular turnover. These issues are substantially different from those in analyzing lipids, whose measurements were discussed in a previous article (4). We begin by discussing quenching and extraction, steps that are nearly universal in metabolite measurement and critical to measurement accuracy. This is followed by in-depth discussion of liquid chromatography-mass spectrometry (LC-MS), an important and versatile metabolite measurement technology. Several general issues in metabolite quantitation are also illustrated within the context of LC-MS. We then discuss im- portant alternative measurement approaches, including gas chromatography-mass spectrometry (GC-MS), nuclear magnetic resonance (NMR), and enzyme assays. Throughout, we focus on both the strengths and weaknesses of each technology, with an eye on potential pitfalls and how they can be avoided. 2. ABSOLUTE VERSUS RELATIVE QUANTITATION In most cases, the absolute concentration of a metabolite cannot be determined based solely on the intensity of the associated instrument signal. For example, in LC-MS, different metabolites ionize with dramatically different efficiencies. Thus, depending on the metabolite, the same number of ion counts can reflect a millimolar or nanomolar concentration in the sample. A standard curve shows the relationship between signal intensity and analyte concentration. When a signal falls in the linear range of the standard curve, a relative signal change equals a fold concentration change. When the signals from different biological samples fall out of the linear range, fold changes can be either under- or overestimated. Absolute metabolite concentrations provide additional information. They determine enzyme binding-site occupancies, the thermodynamics of metabolic reactions, and the relevant concentra- tion range for biochemical experiments. There are two ways to determine absolute concentrations: by comparison to internal standards (for MS, this is accomplished by measuring intensity differ- ence between 13Cor15N labeled standards and unlabeled metabolites; for NMR, a single reference metabolite can frequently be used) or by external comparison to metabolite standards prepared at a range of concentrations. To account for matrix effects, external calibration curves are preferably made by adding standards into samples. To equate losses during extraction and handling between standards and endogenous analyte, standards should be added in the original extraction solvent, not to the final samples. Although isotopic internal standards are both convenient and reliable, they are not commer- cially available for many metabolites. Accordingly, it is sometimes more pragmatic to feed cells Access provided by West Virginia University on 03/11/19. For personal use only. Annu. Rev. Biochem. 2017.86:277-304. Downloaded from www.annualreviews.org 13 with a labeled nutrient (e.g., C6-glucose) and compare the levels of labeled intracellular metabo- lites with unlabeled standards. In such experiments, correction for incomplete cellular metabolite labeling is important. Detailed methods for this purpose are provided in Reference 5. Using this approach, we have measured absolute concentrations for ∼100 of the most important metabolites in Escherichia coli, yeast, and mammalian cells (6, 7). Once such absolute concentration measure- ments have been made, absolute concentration measurements in related specimens can be made by relative