Review pubs.acs.org/ac
NMR Spectroscopy for Metabolomics and Metabolic Profiling Cynthia K. Larive,*,† Gregory A. Barding, Jr.,‡ and Meredith M. Dinges† †
Department of Chemistry, University of California−Riverside, Riverside, California 92521, United States Chemistry and Biochemistry Department, California State Polytechnic University, Pomona, California 91768, United States
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CONTENTS
Applications of NMR Metabolomics Biofluids Cells and Tissues Plants Natural Products Environmental Interactions Food and Beverages Experimental Design Sample Storage and Preparation Extraction Development of New Methods and Experiments: 1H NMR Relaxation Effects New Pulse Sequences Fast and Ultrafast NMR Experiments Probe Developments High-Resolution Magic Angle Spinning (HR-MAS) Development of New Methods and Experiments: Nuclei Other than 1H Isotope Labeling Metabolic Flux Analysis Hyperpolarization and DNP Data Processing and Chemometrics Spectral Processing Resonance Assignments and Databases Quantitation Chemometrics Perspective Author Information Corresponding Author Notes Biographies Acknowledgments References
133 134 134 134 134 135 135 135 136 136 136 136 137 137 137 138 Figure 1. Growth in publications on NMR metabolomics/ metabonomics since 2000. These results were obtained from a topic search of all documents on the Web of Knowledge using the keywords “NMR and metabonomic*” and “NMR and metabolomics*”.
138 138 139 140 140 141 142 142 142 143 144 144 144 144 144 144
illustrates the rapid growth in publications on topics that include the keywords NMR and metabolomics/metabonomics since the year 2000. Due to space limitations, this Review covers only papers published between 2011 and the first half of 2014.
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APPLICATIONS OF NMR METABOLOMICS The omics revolution in systems biology has provided an unprecedented level of understanding of how organisms respond to environmental factors such as diet, aging, and disease. As the end products of transcription and translation, small molecule metabolites can be considered as the output of the biological system, in essence a molecular phenotype. Because metabolites can impact gene transcription through feedback loops, the flow of information from the genome through the transcriptome and proteome to the metabolome is bidirectional (Figure 2).1,2 Though a comprehensive review of NMR metabolomics applications is beyond the scope of this Review, the impact of this approach can be appreciated by a survey of recently published review articles. The section below provides an overview of recent reviews describing applications of NMR-based metabolomics. In addition, the review by
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pplications of NMR for metabolomics and metabolic profiling continue to grow rapidly as does the refinement of methods for the measurement, analysis, and interpretation of complex data sets. Metabolomics (metabonomics) is a set of global measurements performed on biological samples with the goal of quantifying as many metabolites as possible and evaluating changes in metabolite levels as a result of an applied stress. Metabolic profiling experiments follow a more limited set of metabolites often through specific pathways. NMR is also well suited for metabolite fingerprinting, which involves the comprehensive and simultaneous analysis of a wide variety of compounds. For the purpose of this Review, we do not distinguish between metabolomics and metabonomics and have elected to use the term metabolomics throughout. Figure 1 © 2014 American Chemical Society
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Figure 2. Complex interactions of functional levels (genome, transcriptome, proteome, and metabolome) in biological systems. Bidirectional flows of biological information are observed between the genome, transcriptome, proteome, and metabolome. The complex interaction of components from all the functional levels and the environment produces the phenotype, the output of the system measured in systems-level metabolomics and systems biology. Adapted from ref 1 with permission of The Royal Society of Chemistry, copyright 2011.
mixtures, was also demonstrated and validated as a rapid and nondestructive tool for forensic analysis.12 Cells and Tissues. In addition to the global metabolic view provided by blood and urine, sampling of intact tissues can provide a more specific, local response to disease. For example blood serum, bronchoalveolar lavage fluid, and excised lung tissue were used to identify metabolic biomarkers of sepsis in rats.13 Another recent review documents the progress made in the application of NMR and magnetic resonance spectroscopic imaging (MRSI) to detection, diagnosis, and characterization of human prostate cancer.14 NMR metabolomics was used to investigate the effects of environmental stressors associated with biofilm development by Staphlococcus epidermis, strongly implicating a central role for the TCA cycle.15 NMR studies on the effect, mode of action, delivery, and toxicity of therapeutic drugs has been recently reviewed.16 NMR metabolomics also has potential to provide a thorough assessment of the toxicity and mechanisms of action of new nanomaterial-based therapeutics.17 Plants. Plant metabolomics studies have been used to address the effects of genotype, ecotype, and environmental stressors such as drought and submergence18−20 and can provide a metabolic phenotype in chemical genomics studies in plants.21 The application of 1H NMR spectroscopy to plant metabolomics is in many ways more complicated than biofluid analysis and requires consideration of whether the whole plant, a portion of the plant (i.e., leaves, roots, or fruit), or a single cell type is most relevant to the question being explored.22 Most plant metabolomics studies are carried out on plant tissue extracts;18,22 however, the review by Serra et al. discusses the use of solid state NMR for the characterization of the insoluble protective biopolymers cutin and suberin.23 In addition to their primary metabolome, plants also produce an immense number of secondary metabolites (∼200 000) that allow them to interact with beneficial or harmful organisms. Leiss et al. provide an overview on the use of NMR metabolomics to identify compounds important for host plant resistance to western flower thrips (Frankliniella occidentalis).24 Natural Products. NMR metabolomics approaches are also finding use in discovery-oriented natural products chemistry.25 Comparison of high-resolution 2D NMR spectra of unfractionated sample extracts can facilitate the detection and
Bothwell and Griffin provides an excellent introduction to biological NMR.3 Biofluids. Biofluids are an attractive sample matrix for metabolomics studies because they can be obtained in a noninvasive (e.g., saliva, urine) or minimally invasive manner (e.g., blood plasma or serum, cerebrospinal fluid). NMR metabolomics studies using biofluids offer potential for a deeper understanding of disease pathogenesis and the identification of metabolic biomarkers useful for disease diagnosis or treatment monitoring.4−7 Because of the aberrant metabolism of cancer cells involving enhanced glucose uptake and glycolytic activity, a shift in the TCA cycle from oxidation to lipogenesis, increased glutaminolysis, and nucleotide biosynthesis, metabolic screening of biofluids has the potential to contribute to early cancer screening, improved diagnostic accuracy, and prediction of a patient’s response to treatment.8 For example, urine metabolic profiling shows excellent promise as a screening tool for bladder cancer.9 For a metabolic biomarker to be clinically useful, its level must clearly associate with disease risk or progression, should be insensitive to variables like ethnicity, diet, and location, and should not vary too much over the short-term within an individual. To assess the sources of variation among individuals, blood plasma and urine 1H NMR spectra were measured for samples obtained from 154 healthy Caucasian, postmenopausal female twins (identical and nonidentical).10 Thirty four of the identical twins provided two samples over the space of several months in this study. On the basis of these results, Nicholson et al. estimate that stable variation derived from familial and individual-environmental factors accounts for on average 60% of the biological variation in the 1H NMR spectra of plasma and 47% of the variation in the urine spectra. The authors postulate that clinically predictive metabolic variation potentially useful for biomarker discovery lies within this stable component. In an effort to catalog the metabolic components of urine, a comprehensive study of the human urine metabolome using NMR, GC/MS, ICPMS, and direct infusion- and LC-MS/MS reported the identification of 445 and quantification of 378 unique urine metabolites or metabolic species, with 179 metabolites detected using NMR.11 The potential of 1H NMR metabolic profiling to identify trace quantities of body fluids (blood, urine, saliva, and semen,) singly or in binary 134
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identification of novel compounds that might be lost during chromatographic fractionation because of their low abundance, chemical properties, or instability. Activity guided fractionation, a common approach in natural products research, also fails when several biogenic small molecules (BSMs) act synergistically. Through the statistical analysis of NMR spectra of complex mixtures of BSMs, unique spectral features can be identified and correlated to a phenotype or biological property of interest.26 Environmental Interactions. Environmental metabolomics addresses the effects of complex environmental stressors including abiotic factors (e.g., exposure to xenobiotic compounds and temperature shifts) and biotic factors (e.g., herbivory and competition) and can be used to elucidate their biochemical modes of action.27 As NMR metabolomics studies using samples derived from human patients can be a powerful tool for the discovery of disease biomarkers, metabolic shifts in terrestrial or aquatic organisms are potential early bioindicators of environmental stress. To integrate the results of genomic, transcriptomic, and metabolomics data, Ogata et al. introduced ECOMICS, a public domain web-based toolkit that allows for monitoring of biomass metabolism and facilitates understanding of relationships between molecular and microbial elements.28 Food and Beverages. Though applications of NMR metabolomics are most prevalent in studies using biofluids or samples derived from living organisms, this approach has also been used to address a diverse range of applications involving other types of complex samples. For example, NMR metabolomics has been used to assess the quality of plant herbal products and juices.29 For wines, NMR metabolomics measurements can reflect the grape variety and age of the vintage, as well as provide insights to the “terroir”, which can encompass the effects of geographic region, climate, soil, agricultural practices, and fermentation organisms, parameters well-known to impact the taste of wine as well as its metabolic profile.30 The application of NMR metabolomics using wine, juice, and milk samples has been described for student instruction in a variety of courses while also illustrating how students can use 1H NMR metabolic profiling to follow the utilization of glucose by yeast.31
Figure 3. Work flow for clinical metabolomics/metabolic NMR spectroscopy. Samples are collected in a uniform way to minimize variability and are analyzed by an NMR profile to collect data on all metabolites potentially present in the sample. Pattern recognition approaches (PRA) include principal component analysis, partial leastsquares discriminant analysis, orthogonal projections to latent structures, heat map, support vector machines, the random forests method, and other modes aiming to highlight underlying trends and visualization tools such as contribution. Trend and box plots are used to further evaluate these. Receiver operating characteristic (ROC) curves are generally considered the method of choice for evaluating the performance of potential biomarkers. The markers are eventually placed in a metabolic pathway to provide insight on the biochemical phenomena. Reprinted from ref 32 with permission from John Wiley & Sons Inc., copyright 2013.
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EXPERIMENTAL DESIGN A typical metabolomics workflow is summarized diagrammatically in Figure 3.32 The study begins with consideration of factors such as determining the number of subjects, establishing appropriate controls, the types of samples that will be provided, how frequently samples will be taken, and how the samples will be stored. The collected samples undergo preparation for NMR analysis, and the NMR spectra are recorded according to a standardized protocol selected by the investigator. The NMR data sets are then subjected to statistical analyses to identify variance between the test groups and those NMR resonances important for distinguishing the sample groupings. Once key metabolites are identified, a univariate analysis can be performed to establish trends in metabolite levels as a function of a perturbation (i.e., dose, time) or to quantify differences between control and treatment samples. After significance has been established, metabolic pathways are examined to understand the biochemical basis for the effect. Proper experimental design is critical to obtaining metabolomics data that addresses the experimental hypothesis and can be translated to other laboratories or situations. Keun and
Athersuch have reported typical experimental protocols for NMR metabolomics analyses of biofluids, tissues, cell extracts, and culture media.33 A comparison study of technical replicates of human urine samples at two universities using 5 mm and 3 mm probes revealed the importance of parameter standardization in producing reliable and reproducible quantitative NMR metabolomics data.34 An important finding of this study is that previously unrecognized parameters, especially those 135
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related to solvent suppression, can have a dramatic effect on the results. Though the metabolomics community has not yet arrived at a set of standardized methods, standardization of controlled vocabularies (or ontologies) and agreement on reporting standards for the experimental methods and biological data facilitate data exchange.1 An important step toward reducing interlaboratory variability, verifying method accuracy, and validation of new measurement methods is the availability of a standard reference material SRM 1950 “Metabolites in Human Plasma” by the National Institute of Standards and Technology (NIST).35 SRM 1950 is provided with comprehensive metabolomics characterization using GC/MS, LC-MS/MS, and NMR. Sample Storage and Preparation. As in almost any analysis, reproducible and effective methods of sample storage, preservation, and preparation are critical to the outcome of NMR metabolomics studies. Factors affecting the inter- and intrasubject variability in human urine samples, including storage conditions and diet, were investigated.36 Bacterial metabolites were minimized by storing the samples under refrigeration, and diet standardization attenuated the effects of diet culture and cohabitation, though gender-specific differences remained. The effects of sample handling and storage conditions on human plasma samples for NMR metabolomics studies have also been investigated.37 Due to the high protein content of blood plasma or serum samples, which obscures the resonances of small molecule metabolites, it is typically necessary to physically remove the proteins by precipitation or ultrafiltration or to attenuate the intensity of protein resonances in the 1H NMR spectrum based on their faster rates of T2 relaxation. Gowda and Raftery compared these approaches and found that precipitation of blood serum proteins using methanol gave the best performance, producing significantly higher levels of some metabolites than other approaches.38 An optimized method for attenuating intersample differences in the pH and dication concentrations in NMR spectra of rat, mouse, and human urine samples has also been reported.39 Extraction. Extraction is a critical component of sample preparation protocols for cell and tissue analysis,32 but it can also be slow and labor-intensive. Matheus et al. report a streamlined approach using sonication to disrupt cell membranes or tissue structures during the extraction step.40 A study exploring extraction protocols using solvents with varying polarities for NMR metabolomics of adherent mammalian cells demonstrated that a higher proportion of hydrophilic metabolites was obtained with a solvent of methanol/ chloroform/water.41 Compared with liquid−liquid extraction methods, solid phase extraction (SPE) can be useful for fractionating complex samples prior to measurement of NMR spectra and can be more amenable to automation. SPE-NMR was used to isolate 3 fractions from urine samples based on differences in polarity and improved the selectively of the NMR measurements. Figure 4 shows the 1H NMR spectra obtained for urine samples applied to hydrophilic−lipophilic balance (HLB) SPE cartridges and collected into three fractions which were analyzed separately: wash (load + 3 wash volumes of 0.5 mL of water), elute 1 (3 elutions with 0.5 mL of 10% methanol/90% water), and elute 2 (3 elutions of 0.5 mL of methanol).42 Mass-guided SPE-trapping of selected compounds for NMR measurements were used in conjunction with HPLCFTMS to elucidate the structures of 36 phenolic conjugates in human urine following a single bolus intake of black or green tea.43 Hyphenation of LC-MS-SPE-NMR has proven a useful
Figure 4. 1H NMR spectra of the “wash”, “elute 1”, and “elute 2” fractions compared with the reference (nonfractionated) profile from the same urine sample. The blue profile was reconstructed by adding the “wash”, “elute 1”, and “elute 2” subprofiles. The aromatic and aliphatic regions are shown in (a) and (b), respectively. Reprinted from ref 42 with kind permission from Springer Science and Business Media, copyright 2012.
strategy for structure elucidation and compound identification in metabolomics studies.43−45
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DEVELOPMENT OF NEW METHODS AND EXPERIMENTS: 1H NMR Because of its high sensitivity and natural abundance and its nearly ubiquitous presence in organic metabolites, many metabolomics studies rely on the measurement of 1H NMR spectra. In this section, efforts to improve the reproducibility, throughput, sensitivity, and selectivity of 1H NMR metabolomics measurements are summarized. Relaxation Effects. Most NMR metabolomics experiments, and especially those performed on biofluids, depend on effective suppression of the water resonance. One of the most popular methods of solvent suppression is the 1D-NOESY pulse sequence, because of its robustness and ease of implementation. 136
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Figure 5. Schematic diagram for MaxEnt. MaxEnt reconstruction begins with empirical data and a preliminary trial spectrum f (typically a blank spectrum). Spectrum f is inverted (DFT−1) to create “mock” data (m) that is compared with the empirical data (d). An update to the trial spectrum is computed by searching along the gradients of the entropy and the constraint (the agreement between the empirical and mock data). The algorithm converges to the unique MaxEnt solution when the gradient of the objective function Q = S − λC is zero and the gradients of S and C are antiparallel. Reprinted from ref 52. Copyright 2014 American Chemical Society.
dimension is limited. One way to overcome this limitation is through fast NMR experiments which use nonuniform sampling with maximum entropy (MaxEnt) reconstruction, a non-Fourier method of spectrum analysis, illustrated in Figure 5.52 Rai and Sinha report the use of nonlinear sampling, forward maximum entropy reconstruction, and the J-compensated heteronuclear single quantum coherence (HSQC) pulse sequence to achieve a 22-fold reduction in the data collection time for body fluid samples without any compromise in the quantitation of low abundance metabolites.53 Though maximum entropy reduces the time required for multidimensional NMR experiments by reducing the number of data points acquired, ultrafast NMR experiments which grew out of magnetic resonance imaging techniques, allow the acquisition of 2D NMR spectra in a single scan.54 These ultrafast 2D NMR experiments open the door to high resolution and high throughput 2D NMR-based metabolomics studies.55 An ultrafast heteronuclear 2D J-resolved spectroscopy pulse sequence has been reported.56 As an extension of this experiment, an ultrafast 3D UFJCOSY pulse sequence was described that produces COSY-type correlations with heteronuclear couplings displayed in the third dimension.57 This experiment allows direct measurement of the level of isotopic enrichments, which are critical for metabolic flux experiments.58 In addition to greatly reducing the acquisition time, these ultrafast experiments are also widely applicable for quantitative NMR measurements.59 Coupled with stable isotope labeling and polarization methods that enhance sensitivity, this breakthrough promises to revolutionize in vivo NMR spectroscopy. Probe Developments. The NMR probe contains the hardware elements necessary to apply radio frequency pulses to the sample and to detect the resultant signal prior to amplification and digitization. Therefore, probe design and optimization is an avenue frequently explored to improve
Parameter optimization and the mechanism of 1D NOESY for water suppression, which in part depends on differences in the T1 relaxation properties of water and the metabolites of interest, have been recently reviewed.46 In a different application of the NOESY experiment, Farooq et al. report the use of supercooled water in 1.4 mm capillaries to measure high quality 2D NOESY spectra of small molecule metabolites at −15 °C.47 At this temperature, the solvent viscosity is 3−4 times higher than water at room temperature affecting the rate of proton cross relaxation and producing strong NOESY correlations that can be used in concert with 2D experiments based on J-coupling for resonance assignment and metabolite identification. New Pulse Sequences. To overcome problems of resonance overlap in the 1H NMR spectra of complicated samples, Martin-Pastor described a one-dimensional singlet-filtered experiment that edits complex spectra to reveal only the peaks of singlet resonances and weakly coupled signals.48 Experimental schemes that produce high quality 2D J-resolved spectroscopy and spin−echo correlated spectroscopy (SECSY) spectra in inhomogeneous magnetic fields have also been reported and demonstrated to be useful for in vivo measurements.49,50 Longitudinal relaxation enhancements using selective excitation and refocusing pulses were demonstrated to increase the sensitivity of in vivo detection of mouse brain metabolites by magnetic resonance spectroscopy (MRS).51 Fast and Ultrafast NMR Experiments. Pulsed NMR experiments typically rely on the discrete Fourier transform (DFT) to convert digitized time domain free induction decays (FIDs) to frequency domain data. Multidimensional NMR spectra using DFT require uniform sampling intervals with sufficiently small time increments in the indirect dimension to satisfy the Nyquist condition and long evolution times for high resolution. As a result, multidimensional NMR spectra often require long acquisition times and resolution in the indirect 137
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than 1 Hz.69 This technology was used to obtain 1H NMR spectra at 18.8 and 23.5 T for two strains of C. elegans nematodes highlighting the potential of NMR microprobe technologies for metabolic screening of small model organisms.70 To minimize heating from eddy currents and reduce the centrifugal force felt by the worms, a spinning frequency of 350 Hz was used.
detection sensitivity or to enable new types of measurements. Renslow et al. describe a biofilm microreactor seated on a custom built NMR probe that allows for simultaneous electrochemical and NMR measurements at the microscale.60 Other advances in probe design include development of a 13 C-optimized probe with a 35 μL sample volume constructed from a high temperature superconducting oxide deposited on a sapphire substrate.61 To facilitate experiments involving heteronuclear hyperpolarization at low fields, a single input, doubletuned probe circuit has been developed that enables double resonance NMR to be performed with single channel consoles using PANORAMIC (Precession And Nutation for Observing Rotations At Multiple Intervals about the Carrier) waveforms.62 Compared with traditional 5 mm NMR probes, microcoil probes offer improved mass sensitivity. The application of microcoil NMR for metabolomics of urine and serum samples, including the effect of concentrating biofluid samples on metabolite quantification, has been investigated using a probe designed for flow injection analysis.63 A stripline NMR probe has been integrated into a microfluidic flow system allowing electrochemical generation of reactive products concentrated via SPE before measurement of the NMR spectrum in the 150 nL active volume.64 Though microfluidic chip-based flow probes are potentially attractive for high-throughput metabolomics measurements, obtaining high spectral resolution remains a challenge because mismatch in magnetic susceptibility of the sample and the chip material results in susceptibility broadening. An innovative strategy to overcome susceptibility broadening in chip-based NMR probes relies on the simulation of field maps to optimize the shape of air filled compensating structures that ensure a flat magnetic field distribution inside the sample detection region.65 High-Resolution Magic Angle Spinning (HR-MAS). HR-MAS experiments provide 1H NMR spectra of semisolid materials such as cells, tissues, biopsy samples, organs, and organisms. Spinning the sample about an axis at the magic angle (54°44′) reduces line broadening by averaging magnetic field gradients at compartment boundaries, the effects of residual homonuclear dipolar interactions, and chemical shift anisotropy.66 A complication in interpreting HR-MAS spectra is that metabolite chemical shifts can vary slightly according to the local microenvironment in tissues or cells (e.g., pH) hampering accurate quantitation of metabolite concentrations. Lazariev et al. describe an accurate method coupling quantum mechanical simulations and quantitation algorithms (QM-QUEST) that corrects mismatches producing corrected metabolite fingerprints.67 An exciting advance in HR-MAS is the reduction in sample size requirements using microcoil NMR probes. Wong et al. report the use of magic angle coil spinning (MACS) in which a 62 μm diameter copper wire was wound around a quartz capillary tube and soldered to a nonmagnetic capacitor producing a detection volume of 690 nL.68 The capillary and coil were fit inside a ceramic insert and placed in a standard 4 mm rotor. This setup allowed the measurement of 1H NMR spectra for a 500 ng sample of muscle tissue and produced a 7-fold gain in sensitivity compared with a spectrum measured for 16 mg of tissue packed into a 30 μL disposable insert, though the resonances in the MACS spectra were broader than desired for detailed metabolic phenotyping. Refinements of the initial MACS design were reported that minimize line broadening from temperature gradients and anisotropic magnetic susceptibility to produce resonance line widths less
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DEVELOPMENT OF NEW METHODS AND EXPERIMENTS: NUCLEI OTHER THAN 1H A fundamental advantage of using NMR to probe biological systems is the ability to measure a wide variety of spin 1/2 nuclei, including (but not limited to) the biologically relevant 1 H, 13C, 31P, and 15N in addition to the pharmaceutically relevant 19F. Of these, 1H, 19F, and 31P are found at high percentages of natural abundance. The lower natural abundance of 13C and 15N can be useful in measuring enrichment due to catabolism of labeled precursors as a function of specific biological processes or pathways. More specifically, NMR can easily be used to monitor the positional enrichment of a molecule for both 13C and 15N NMR to establish which pathways are being activated or inactivated. The sensitivity disadvantage of NMR compared to mass spectrometry-based techniques is somewhat overcome by the inherent capability of NMR to monitor isotopomer enrichment. The disadvantage of mass spectrometry for measuring isotopomer distribution is based on spectral interpretation; the investigator must deduce from fragmentation patterns the location of enrichment, reducing sensitivity and throughput. The fate of labeled precursors (especially 13C labeled glycolytic intermediates) has been tracked with NMR (or MRS) in vivo using hyperpolarization and DNP. To better appreciate the versatility of NMR for exploring biological processes, the application of NMR for metabolic flux measurements (including isotope tracing), isotope labeling, and DNP are discussed below. Isotope Labeling. Although NMR has inherent advantages for measuring in vivo isotopologue enrichment from 13C and 15N labeled substrates, it may still be difficult to identify and quantify enrichment. Many experiments permit the direct detection of 13C to determine isotopomer distribution;71−74 however, these experiments can still suffer from a lack of sensitivity for isotopomers that are only partially enriched. Although the enrichment of a given isotopomer may be minor, this change may still be important to understanding the biological mechanisms of the system or pathway. Alternatively, 1D 1H experiments can be used by taking advantage of the splitting in the 1H spectrum resulting from 13C enrichment, though 1H spectra at natural abundance can be convoluted even without the additional complication arising from the extra signals due to 13C couplings. To reduce the spectral complexity arising from 13C enrichment, Cahoreau et al. used 2D heteronuclear J-resolved spectroscopy (2D-JRES), which records the scalar couplings in the second dimension instead of chemical shifts, decreasing experiment time compared with other 2D experiments.75 Other 2D experiments (such as 1 H−13C HSQC) can also be used to monitor isotopomer enrichment by taking advantage of the dispersion of a second dimension and the enhanced detection sensitivity of the 1H nucleus coupled to 13C.76 A recent publication by Fan and Lane applied a variety of 2D and 2D-edited experiments on either [U−13C]-glucose or [U−13C, 15N]-glutamine enriched cancer cells.77 The 2D experiments described include 1H−1H TOCSY, 138
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Figure 6. Workflow implemented in IsoDesign to determine the optimal label input in a 13C-MFA experiment. Blue, orange, and green boxes detail steps performed by the calculation module, the visualization module, and a spreadsheet program, respectively. Reprinted from ref 92 with permission from John Wiley & Sons Inc., copyright 2014. 1
H−1H HCCH TOCSY, 1H−13C HSQC, 1H−15N HSQC HACACO (correlating carbonyl carbons with neighboring protons), 1H−13C HSQC-TOCSY, and 1H−31P HSQC TOCSY, and the authors discuss how the isotopomer distribution is determined from the spectra. Despite isotopic enrichment, traditional 2D experiments can still be time-consuming and less amenable to high-throughput isotope tracing than 1D experiments. The advent of ultrafast 2D NMR experiments, which allow the acquisition of a multidimensional NMR experiment in a single scan, has greatly reduced experiment times.78 Giraudeau and coworkers measured the 13C enrichment in a biological sample with a traditional TOCSY experiment, which had a run time of greater than 2 h, compared to an ultrafast TOCSY with an experiment time of 3 s on a 400 MHz spectrometer equipped with a room temperature probe.58 Continued development and applications of ultrafast 2D NMR experiments will significantly increase the throughput of isotope tracing by NMR. This section has predominantly discussed the use of isotope labeling for the use of in vivo isotope labeling for the analysis of biological pathways. Another interesting approach is to use isotope labeling ex vivo to improve NMR sensitivity for general metabolomics experiments. By incorporating an NMR active isotope onto a tag, specific chemical moieties, such carboxylic acid groups or amines, can be derivatized significantly increasing sensitivity and selectivity while decreasing spectral convolution.79,80 For example, Tayyari and co-workers designed a cholamine tag with a 15N label on the primary amine, allowing derivatization of carboxylic acid functional groups.81 The authors demonstrate the sensitivity of the tag using 1H−15N HSQC experiments by collecting only 1−4 scans over 128 increments. The tag also included a tertiary amine which provides a stable, permanent positive charge attached to all derivatized molecules, enhancing mass spectrometry sensitivity as well. Although not yet widely used, the use of derivatization to enhance NMR sensitivity and selectivity and decrease NMR resonance overlap while enhancing cross-platform utility has strong potential for improving NMR metabolite profiling experiments. Metabolic Flux Analysis. Metabolic flux analysis (MFA) is a popular and growing topic in analytical chemistry and
molecular biology and has recently been extensively reviewed.82,83 The ultimate goal of MFA is to establish the metabolic flux through a particular pathway using labeled reagents and to compare the flux under different stresses and in various tissue types including cancers,84−86 oysters,87 plants,88 and bacteria.89 These analyses are often limited to specific, welldefined biochemical pathways. Flux experiments measure timebased isotope enrichments and require that the activities of the enzymes involved in the pathway are known. For well-studied pathways, enzymatic activities can often be approximated; otherwise, parameters must be estimated to understand how the pathways may be affected. Regardless, computational methods are necessary to model the pathways and estimate the flux parameters. One such program reported by Hettling and co-workers estimated TCA fluxes with noisy NMR data in heart tissue using a computational model to estimate the flux parameters.90 In addition to data analysis, the actual design of a MFA study can be challenging, as one must consider what precursors and isotopic composition to use and the desired outcome (dependent on the biological question under investigation). Work by Millard et al. presents a novel software program for the design of 13C-MFA experiments, termed IsoDesign.91 As illustrated in Figure 6, the program allows the investigator to generate models using different label inputs, simulate the isotopic data, calculate the precision expected on each flux for each label input, and outputs these results in a visually interpreted sensitivity landscape. Isodesign can be used for comparison of isotopic data from MS (including MS/MS) and NMR (both 1H and 13C). Tools such as those provided by Hettling et al., Millard et al., and others are increasingly in need as more biological questions are being probed with substrates labeled specifically for the investigation of selected pathways.90−92 A major advantage of NMR over other popular MFA analytical platforms is that it is nondestructive which allows for in vivo NMR spectroscopy under specific conditions. A comprehensive review and guide for in vivo NMR by de Graaf and co-workers has recently been published and discusses topics such as substrate choice, metabolic model, and choice of NMR experiment (direct vs indirect detection).93 Although this 139
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transferred to organic molecules by reacting hyperpolarized hydrogen with precursor molecules in the presence of a transition metal catalyst. The use of PHIP for imaging, including the use of 13C or 15N labeled metabolite precursors, has been reviewed by Glöggler et al.99 An exciting development in hyperpolarization experiments for metabolic profiling is the rapidly expanding use of dynamic nuclear polarization (DNP), which has been accelerated by the introduction of commercial instruments that facilitate its implementation. An excellent overview of DNP in liquids has been recently authored by Günther.97 DNP takes advantage of the comparably larger polarization of electron spins, which can be nearly 100% at low temperatures. Saturation of the electron spin transfers this polarization from the unpaired electrons to nuclear spin via hyperfine and dipolar interactions. Though DNP experiments can be executed in a variety of experimental arrangements, the most useful configuration for metabolic profiling experiments is dissolution DNP, in which polarization is carried out at low temperatures (
NMR Spectroscopy for Metabolomics and Metabolic Profiling Cynthia K. Larive,*,† Gregory A. Barding, Jr.,‡ and Meredith M. Dinges† †
Department of Chemistry, University of California−Riverside, Riverside, California 92521, United States Chemistry and Biochemistry Department, California State Polytechnic University, Pomona, California 91768, United States
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CONTENTS
Applications of NMR Metabolomics Biofluids Cells and Tissues Plants Natural Products Environmental Interactions Food and Beverages Experimental Design Sample Storage and Preparation Extraction Development of New Methods and Experiments: 1H NMR Relaxation Effects New Pulse Sequences Fast and Ultrafast NMR Experiments Probe Developments High-Resolution Magic Angle Spinning (HR-MAS) Development of New Methods and Experiments: Nuclei Other than 1H Isotope Labeling Metabolic Flux Analysis Hyperpolarization and DNP Data Processing and Chemometrics Spectral Processing Resonance Assignments and Databases Quantitation Chemometrics Perspective Author Information Corresponding Author Notes Biographies Acknowledgments References
133 134 134 134 134 135 135 135 136 136 136 136 137 137 137 138 Figure 1. Growth in publications on NMR metabolomics/ metabonomics since 2000. These results were obtained from a topic search of all documents on the Web of Knowledge using the keywords “NMR and metabonomic*” and “NMR and metabolomics*”.
138 138 139 140 140 141 142 142 142 143 144 144 144 144 144 144
illustrates the rapid growth in publications on topics that include the keywords NMR and metabolomics/metabonomics since the year 2000. Due to space limitations, this Review covers only papers published between 2011 and the first half of 2014.
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APPLICATIONS OF NMR METABOLOMICS The omics revolution in systems biology has provided an unprecedented level of understanding of how organisms respond to environmental factors such as diet, aging, and disease. As the end products of transcription and translation, small molecule metabolites can be considered as the output of the biological system, in essence a molecular phenotype. Because metabolites can impact gene transcription through feedback loops, the flow of information from the genome through the transcriptome and proteome to the metabolome is bidirectional (Figure 2).1,2 Though a comprehensive review of NMR metabolomics applications is beyond the scope of this Review, the impact of this approach can be appreciated by a survey of recently published review articles. The section below provides an overview of recent reviews describing applications of NMR-based metabolomics. In addition, the review by
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pplications of NMR for metabolomics and metabolic profiling continue to grow rapidly as does the refinement of methods for the measurement, analysis, and interpretation of complex data sets. Metabolomics (metabonomics) is a set of global measurements performed on biological samples with the goal of quantifying as many metabolites as possible and evaluating changes in metabolite levels as a result of an applied stress. Metabolic profiling experiments follow a more limited set of metabolites often through specific pathways. NMR is also well suited for metabolite fingerprinting, which involves the comprehensive and simultaneous analysis of a wide variety of compounds. For the purpose of this Review, we do not distinguish between metabolomics and metabonomics and have elected to use the term metabolomics throughout. Figure 1 © 2014 American Chemical Society
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Figure 2. Complex interactions of functional levels (genome, transcriptome, proteome, and metabolome) in biological systems. Bidirectional flows of biological information are observed between the genome, transcriptome, proteome, and metabolome. The complex interaction of components from all the functional levels and the environment produces the phenotype, the output of the system measured in systems-level metabolomics and systems biology. Adapted from ref 1 with permission of The Royal Society of Chemistry, copyright 2011.
mixtures, was also demonstrated and validated as a rapid and nondestructive tool for forensic analysis.12 Cells and Tissues. In addition to the global metabolic view provided by blood and urine, sampling of intact tissues can provide a more specific, local response to disease. For example blood serum, bronchoalveolar lavage fluid, and excised lung tissue were used to identify metabolic biomarkers of sepsis in rats.13 Another recent review documents the progress made in the application of NMR and magnetic resonance spectroscopic imaging (MRSI) to detection, diagnosis, and characterization of human prostate cancer.14 NMR metabolomics was used to investigate the effects of environmental stressors associated with biofilm development by Staphlococcus epidermis, strongly implicating a central role for the TCA cycle.15 NMR studies on the effect, mode of action, delivery, and toxicity of therapeutic drugs has been recently reviewed.16 NMR metabolomics also has potential to provide a thorough assessment of the toxicity and mechanisms of action of new nanomaterial-based therapeutics.17 Plants. Plant metabolomics studies have been used to address the effects of genotype, ecotype, and environmental stressors such as drought and submergence18−20 and can provide a metabolic phenotype in chemical genomics studies in plants.21 The application of 1H NMR spectroscopy to plant metabolomics is in many ways more complicated than biofluid analysis and requires consideration of whether the whole plant, a portion of the plant (i.e., leaves, roots, or fruit), or a single cell type is most relevant to the question being explored.22 Most plant metabolomics studies are carried out on plant tissue extracts;18,22 however, the review by Serra et al. discusses the use of solid state NMR for the characterization of the insoluble protective biopolymers cutin and suberin.23 In addition to their primary metabolome, plants also produce an immense number of secondary metabolites (∼200 000) that allow them to interact with beneficial or harmful organisms. Leiss et al. provide an overview on the use of NMR metabolomics to identify compounds important for host plant resistance to western flower thrips (Frankliniella occidentalis).24 Natural Products. NMR metabolomics approaches are also finding use in discovery-oriented natural products chemistry.25 Comparison of high-resolution 2D NMR spectra of unfractionated sample extracts can facilitate the detection and
Bothwell and Griffin provides an excellent introduction to biological NMR.3 Biofluids. Biofluids are an attractive sample matrix for metabolomics studies because they can be obtained in a noninvasive (e.g., saliva, urine) or minimally invasive manner (e.g., blood plasma or serum, cerebrospinal fluid). NMR metabolomics studies using biofluids offer potential for a deeper understanding of disease pathogenesis and the identification of metabolic biomarkers useful for disease diagnosis or treatment monitoring.4−7 Because of the aberrant metabolism of cancer cells involving enhanced glucose uptake and glycolytic activity, a shift in the TCA cycle from oxidation to lipogenesis, increased glutaminolysis, and nucleotide biosynthesis, metabolic screening of biofluids has the potential to contribute to early cancer screening, improved diagnostic accuracy, and prediction of a patient’s response to treatment.8 For example, urine metabolic profiling shows excellent promise as a screening tool for bladder cancer.9 For a metabolic biomarker to be clinically useful, its level must clearly associate with disease risk or progression, should be insensitive to variables like ethnicity, diet, and location, and should not vary too much over the short-term within an individual. To assess the sources of variation among individuals, blood plasma and urine 1H NMR spectra were measured for samples obtained from 154 healthy Caucasian, postmenopausal female twins (identical and nonidentical).10 Thirty four of the identical twins provided two samples over the space of several months in this study. On the basis of these results, Nicholson et al. estimate that stable variation derived from familial and individual-environmental factors accounts for on average 60% of the biological variation in the 1H NMR spectra of plasma and 47% of the variation in the urine spectra. The authors postulate that clinically predictive metabolic variation potentially useful for biomarker discovery lies within this stable component. In an effort to catalog the metabolic components of urine, a comprehensive study of the human urine metabolome using NMR, GC/MS, ICPMS, and direct infusion- and LC-MS/MS reported the identification of 445 and quantification of 378 unique urine metabolites or metabolic species, with 179 metabolites detected using NMR.11 The potential of 1H NMR metabolic profiling to identify trace quantities of body fluids (blood, urine, saliva, and semen,) singly or in binary 134
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identification of novel compounds that might be lost during chromatographic fractionation because of their low abundance, chemical properties, or instability. Activity guided fractionation, a common approach in natural products research, also fails when several biogenic small molecules (BSMs) act synergistically. Through the statistical analysis of NMR spectra of complex mixtures of BSMs, unique spectral features can be identified and correlated to a phenotype or biological property of interest.26 Environmental Interactions. Environmental metabolomics addresses the effects of complex environmental stressors including abiotic factors (e.g., exposure to xenobiotic compounds and temperature shifts) and biotic factors (e.g., herbivory and competition) and can be used to elucidate their biochemical modes of action.27 As NMR metabolomics studies using samples derived from human patients can be a powerful tool for the discovery of disease biomarkers, metabolic shifts in terrestrial or aquatic organisms are potential early bioindicators of environmental stress. To integrate the results of genomic, transcriptomic, and metabolomics data, Ogata et al. introduced ECOMICS, a public domain web-based toolkit that allows for monitoring of biomass metabolism and facilitates understanding of relationships between molecular and microbial elements.28 Food and Beverages. Though applications of NMR metabolomics are most prevalent in studies using biofluids or samples derived from living organisms, this approach has also been used to address a diverse range of applications involving other types of complex samples. For example, NMR metabolomics has been used to assess the quality of plant herbal products and juices.29 For wines, NMR metabolomics measurements can reflect the grape variety and age of the vintage, as well as provide insights to the “terroir”, which can encompass the effects of geographic region, climate, soil, agricultural practices, and fermentation organisms, parameters well-known to impact the taste of wine as well as its metabolic profile.30 The application of NMR metabolomics using wine, juice, and milk samples has been described for student instruction in a variety of courses while also illustrating how students can use 1H NMR metabolic profiling to follow the utilization of glucose by yeast.31
Figure 3. Work flow for clinical metabolomics/metabolic NMR spectroscopy. Samples are collected in a uniform way to minimize variability and are analyzed by an NMR profile to collect data on all metabolites potentially present in the sample. Pattern recognition approaches (PRA) include principal component analysis, partial leastsquares discriminant analysis, orthogonal projections to latent structures, heat map, support vector machines, the random forests method, and other modes aiming to highlight underlying trends and visualization tools such as contribution. Trend and box plots are used to further evaluate these. Receiver operating characteristic (ROC) curves are generally considered the method of choice for evaluating the performance of potential biomarkers. The markers are eventually placed in a metabolic pathway to provide insight on the biochemical phenomena. Reprinted from ref 32 with permission from John Wiley & Sons Inc., copyright 2013.
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EXPERIMENTAL DESIGN A typical metabolomics workflow is summarized diagrammatically in Figure 3.32 The study begins with consideration of factors such as determining the number of subjects, establishing appropriate controls, the types of samples that will be provided, how frequently samples will be taken, and how the samples will be stored. The collected samples undergo preparation for NMR analysis, and the NMR spectra are recorded according to a standardized protocol selected by the investigator. The NMR data sets are then subjected to statistical analyses to identify variance between the test groups and those NMR resonances important for distinguishing the sample groupings. Once key metabolites are identified, a univariate analysis can be performed to establish trends in metabolite levels as a function of a perturbation (i.e., dose, time) or to quantify differences between control and treatment samples. After significance has been established, metabolic pathways are examined to understand the biochemical basis for the effect. Proper experimental design is critical to obtaining metabolomics data that addresses the experimental hypothesis and can be translated to other laboratories or situations. Keun and
Athersuch have reported typical experimental protocols for NMR metabolomics analyses of biofluids, tissues, cell extracts, and culture media.33 A comparison study of technical replicates of human urine samples at two universities using 5 mm and 3 mm probes revealed the importance of parameter standardization in producing reliable and reproducible quantitative NMR metabolomics data.34 An important finding of this study is that previously unrecognized parameters, especially those 135
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related to solvent suppression, can have a dramatic effect on the results. Though the metabolomics community has not yet arrived at a set of standardized methods, standardization of controlled vocabularies (or ontologies) and agreement on reporting standards for the experimental methods and biological data facilitate data exchange.1 An important step toward reducing interlaboratory variability, verifying method accuracy, and validation of new measurement methods is the availability of a standard reference material SRM 1950 “Metabolites in Human Plasma” by the National Institute of Standards and Technology (NIST).35 SRM 1950 is provided with comprehensive metabolomics characterization using GC/MS, LC-MS/MS, and NMR. Sample Storage and Preparation. As in almost any analysis, reproducible and effective methods of sample storage, preservation, and preparation are critical to the outcome of NMR metabolomics studies. Factors affecting the inter- and intrasubject variability in human urine samples, including storage conditions and diet, were investigated.36 Bacterial metabolites were minimized by storing the samples under refrigeration, and diet standardization attenuated the effects of diet culture and cohabitation, though gender-specific differences remained. The effects of sample handling and storage conditions on human plasma samples for NMR metabolomics studies have also been investigated.37 Due to the high protein content of blood plasma or serum samples, which obscures the resonances of small molecule metabolites, it is typically necessary to physically remove the proteins by precipitation or ultrafiltration or to attenuate the intensity of protein resonances in the 1H NMR spectrum based on their faster rates of T2 relaxation. Gowda and Raftery compared these approaches and found that precipitation of blood serum proteins using methanol gave the best performance, producing significantly higher levels of some metabolites than other approaches.38 An optimized method for attenuating intersample differences in the pH and dication concentrations in NMR spectra of rat, mouse, and human urine samples has also been reported.39 Extraction. Extraction is a critical component of sample preparation protocols for cell and tissue analysis,32 but it can also be slow and labor-intensive. Matheus et al. report a streamlined approach using sonication to disrupt cell membranes or tissue structures during the extraction step.40 A study exploring extraction protocols using solvents with varying polarities for NMR metabolomics of adherent mammalian cells demonstrated that a higher proportion of hydrophilic metabolites was obtained with a solvent of methanol/ chloroform/water.41 Compared with liquid−liquid extraction methods, solid phase extraction (SPE) can be useful for fractionating complex samples prior to measurement of NMR spectra and can be more amenable to automation. SPE-NMR was used to isolate 3 fractions from urine samples based on differences in polarity and improved the selectively of the NMR measurements. Figure 4 shows the 1H NMR spectra obtained for urine samples applied to hydrophilic−lipophilic balance (HLB) SPE cartridges and collected into three fractions which were analyzed separately: wash (load + 3 wash volumes of 0.5 mL of water), elute 1 (3 elutions with 0.5 mL of 10% methanol/90% water), and elute 2 (3 elutions of 0.5 mL of methanol).42 Mass-guided SPE-trapping of selected compounds for NMR measurements were used in conjunction with HPLCFTMS to elucidate the structures of 36 phenolic conjugates in human urine following a single bolus intake of black or green tea.43 Hyphenation of LC-MS-SPE-NMR has proven a useful
Figure 4. 1H NMR spectra of the “wash”, “elute 1”, and “elute 2” fractions compared with the reference (nonfractionated) profile from the same urine sample. The blue profile was reconstructed by adding the “wash”, “elute 1”, and “elute 2” subprofiles. The aromatic and aliphatic regions are shown in (a) and (b), respectively. Reprinted from ref 42 with kind permission from Springer Science and Business Media, copyright 2012.
strategy for structure elucidation and compound identification in metabolomics studies.43−45
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DEVELOPMENT OF NEW METHODS AND EXPERIMENTS: 1H NMR Because of its high sensitivity and natural abundance and its nearly ubiquitous presence in organic metabolites, many metabolomics studies rely on the measurement of 1H NMR spectra. In this section, efforts to improve the reproducibility, throughput, sensitivity, and selectivity of 1H NMR metabolomics measurements are summarized. Relaxation Effects. Most NMR metabolomics experiments, and especially those performed on biofluids, depend on effective suppression of the water resonance. One of the most popular methods of solvent suppression is the 1D-NOESY pulse sequence, because of its robustness and ease of implementation. 136
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Figure 5. Schematic diagram for MaxEnt. MaxEnt reconstruction begins with empirical data and a preliminary trial spectrum f (typically a blank spectrum). Spectrum f is inverted (DFT−1) to create “mock” data (m) that is compared with the empirical data (d). An update to the trial spectrum is computed by searching along the gradients of the entropy and the constraint (the agreement between the empirical and mock data). The algorithm converges to the unique MaxEnt solution when the gradient of the objective function Q = S − λC is zero and the gradients of S and C are antiparallel. Reprinted from ref 52. Copyright 2014 American Chemical Society.
dimension is limited. One way to overcome this limitation is through fast NMR experiments which use nonuniform sampling with maximum entropy (MaxEnt) reconstruction, a non-Fourier method of spectrum analysis, illustrated in Figure 5.52 Rai and Sinha report the use of nonlinear sampling, forward maximum entropy reconstruction, and the J-compensated heteronuclear single quantum coherence (HSQC) pulse sequence to achieve a 22-fold reduction in the data collection time for body fluid samples without any compromise in the quantitation of low abundance metabolites.53 Though maximum entropy reduces the time required for multidimensional NMR experiments by reducing the number of data points acquired, ultrafast NMR experiments which grew out of magnetic resonance imaging techniques, allow the acquisition of 2D NMR spectra in a single scan.54 These ultrafast 2D NMR experiments open the door to high resolution and high throughput 2D NMR-based metabolomics studies.55 An ultrafast heteronuclear 2D J-resolved spectroscopy pulse sequence has been reported.56 As an extension of this experiment, an ultrafast 3D UFJCOSY pulse sequence was described that produces COSY-type correlations with heteronuclear couplings displayed in the third dimension.57 This experiment allows direct measurement of the level of isotopic enrichments, which are critical for metabolic flux experiments.58 In addition to greatly reducing the acquisition time, these ultrafast experiments are also widely applicable for quantitative NMR measurements.59 Coupled with stable isotope labeling and polarization methods that enhance sensitivity, this breakthrough promises to revolutionize in vivo NMR spectroscopy. Probe Developments. The NMR probe contains the hardware elements necessary to apply radio frequency pulses to the sample and to detect the resultant signal prior to amplification and digitization. Therefore, probe design and optimization is an avenue frequently explored to improve
Parameter optimization and the mechanism of 1D NOESY for water suppression, which in part depends on differences in the T1 relaxation properties of water and the metabolites of interest, have been recently reviewed.46 In a different application of the NOESY experiment, Farooq et al. report the use of supercooled water in 1.4 mm capillaries to measure high quality 2D NOESY spectra of small molecule metabolites at −15 °C.47 At this temperature, the solvent viscosity is 3−4 times higher than water at room temperature affecting the rate of proton cross relaxation and producing strong NOESY correlations that can be used in concert with 2D experiments based on J-coupling for resonance assignment and metabolite identification. New Pulse Sequences. To overcome problems of resonance overlap in the 1H NMR spectra of complicated samples, Martin-Pastor described a one-dimensional singlet-filtered experiment that edits complex spectra to reveal only the peaks of singlet resonances and weakly coupled signals.48 Experimental schemes that produce high quality 2D J-resolved spectroscopy and spin−echo correlated spectroscopy (SECSY) spectra in inhomogeneous magnetic fields have also been reported and demonstrated to be useful for in vivo measurements.49,50 Longitudinal relaxation enhancements using selective excitation and refocusing pulses were demonstrated to increase the sensitivity of in vivo detection of mouse brain metabolites by magnetic resonance spectroscopy (MRS).51 Fast and Ultrafast NMR Experiments. Pulsed NMR experiments typically rely on the discrete Fourier transform (DFT) to convert digitized time domain free induction decays (FIDs) to frequency domain data. Multidimensional NMR spectra using DFT require uniform sampling intervals with sufficiently small time increments in the indirect dimension to satisfy the Nyquist condition and long evolution times for high resolution. As a result, multidimensional NMR spectra often require long acquisition times and resolution in the indirect 137
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than 1 Hz.69 This technology was used to obtain 1H NMR spectra at 18.8 and 23.5 T for two strains of C. elegans nematodes highlighting the potential of NMR microprobe technologies for metabolic screening of small model organisms.70 To minimize heating from eddy currents and reduce the centrifugal force felt by the worms, a spinning frequency of 350 Hz was used.
detection sensitivity or to enable new types of measurements. Renslow et al. describe a biofilm microreactor seated on a custom built NMR probe that allows for simultaneous electrochemical and NMR measurements at the microscale.60 Other advances in probe design include development of a 13 C-optimized probe with a 35 μL sample volume constructed from a high temperature superconducting oxide deposited on a sapphire substrate.61 To facilitate experiments involving heteronuclear hyperpolarization at low fields, a single input, doubletuned probe circuit has been developed that enables double resonance NMR to be performed with single channel consoles using PANORAMIC (Precession And Nutation for Observing Rotations At Multiple Intervals about the Carrier) waveforms.62 Compared with traditional 5 mm NMR probes, microcoil probes offer improved mass sensitivity. The application of microcoil NMR for metabolomics of urine and serum samples, including the effect of concentrating biofluid samples on metabolite quantification, has been investigated using a probe designed for flow injection analysis.63 A stripline NMR probe has been integrated into a microfluidic flow system allowing electrochemical generation of reactive products concentrated via SPE before measurement of the NMR spectrum in the 150 nL active volume.64 Though microfluidic chip-based flow probes are potentially attractive for high-throughput metabolomics measurements, obtaining high spectral resolution remains a challenge because mismatch in magnetic susceptibility of the sample and the chip material results in susceptibility broadening. An innovative strategy to overcome susceptibility broadening in chip-based NMR probes relies on the simulation of field maps to optimize the shape of air filled compensating structures that ensure a flat magnetic field distribution inside the sample detection region.65 High-Resolution Magic Angle Spinning (HR-MAS). HR-MAS experiments provide 1H NMR spectra of semisolid materials such as cells, tissues, biopsy samples, organs, and organisms. Spinning the sample about an axis at the magic angle (54°44′) reduces line broadening by averaging magnetic field gradients at compartment boundaries, the effects of residual homonuclear dipolar interactions, and chemical shift anisotropy.66 A complication in interpreting HR-MAS spectra is that metabolite chemical shifts can vary slightly according to the local microenvironment in tissues or cells (e.g., pH) hampering accurate quantitation of metabolite concentrations. Lazariev et al. describe an accurate method coupling quantum mechanical simulations and quantitation algorithms (QM-QUEST) that corrects mismatches producing corrected metabolite fingerprints.67 An exciting advance in HR-MAS is the reduction in sample size requirements using microcoil NMR probes. Wong et al. report the use of magic angle coil spinning (MACS) in which a 62 μm diameter copper wire was wound around a quartz capillary tube and soldered to a nonmagnetic capacitor producing a detection volume of 690 nL.68 The capillary and coil were fit inside a ceramic insert and placed in a standard 4 mm rotor. This setup allowed the measurement of 1H NMR spectra for a 500 ng sample of muscle tissue and produced a 7-fold gain in sensitivity compared with a spectrum measured for 16 mg of tissue packed into a 30 μL disposable insert, though the resonances in the MACS spectra were broader than desired for detailed metabolic phenotyping. Refinements of the initial MACS design were reported that minimize line broadening from temperature gradients and anisotropic magnetic susceptibility to produce resonance line widths less
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DEVELOPMENT OF NEW METHODS AND EXPERIMENTS: NUCLEI OTHER THAN 1H A fundamental advantage of using NMR to probe biological systems is the ability to measure a wide variety of spin 1/2 nuclei, including (but not limited to) the biologically relevant 1 H, 13C, 31P, and 15N in addition to the pharmaceutically relevant 19F. Of these, 1H, 19F, and 31P are found at high percentages of natural abundance. The lower natural abundance of 13C and 15N can be useful in measuring enrichment due to catabolism of labeled precursors as a function of specific biological processes or pathways. More specifically, NMR can easily be used to monitor the positional enrichment of a molecule for both 13C and 15N NMR to establish which pathways are being activated or inactivated. The sensitivity disadvantage of NMR compared to mass spectrometry-based techniques is somewhat overcome by the inherent capability of NMR to monitor isotopomer enrichment. The disadvantage of mass spectrometry for measuring isotopomer distribution is based on spectral interpretation; the investigator must deduce from fragmentation patterns the location of enrichment, reducing sensitivity and throughput. The fate of labeled precursors (especially 13C labeled glycolytic intermediates) has been tracked with NMR (or MRS) in vivo using hyperpolarization and DNP. To better appreciate the versatility of NMR for exploring biological processes, the application of NMR for metabolic flux measurements (including isotope tracing), isotope labeling, and DNP are discussed below. Isotope Labeling. Although NMR has inherent advantages for measuring in vivo isotopologue enrichment from 13C and 15N labeled substrates, it may still be difficult to identify and quantify enrichment. Many experiments permit the direct detection of 13C to determine isotopomer distribution;71−74 however, these experiments can still suffer from a lack of sensitivity for isotopomers that are only partially enriched. Although the enrichment of a given isotopomer may be minor, this change may still be important to understanding the biological mechanisms of the system or pathway. Alternatively, 1D 1H experiments can be used by taking advantage of the splitting in the 1H spectrum resulting from 13C enrichment, though 1H spectra at natural abundance can be convoluted even without the additional complication arising from the extra signals due to 13C couplings. To reduce the spectral complexity arising from 13C enrichment, Cahoreau et al. used 2D heteronuclear J-resolved spectroscopy (2D-JRES), which records the scalar couplings in the second dimension instead of chemical shifts, decreasing experiment time compared with other 2D experiments.75 Other 2D experiments (such as 1 H−13C HSQC) can also be used to monitor isotopomer enrichment by taking advantage of the dispersion of a second dimension and the enhanced detection sensitivity of the 1H nucleus coupled to 13C.76 A recent publication by Fan and Lane applied a variety of 2D and 2D-edited experiments on either [U−13C]-glucose or [U−13C, 15N]-glutamine enriched cancer cells.77 The 2D experiments described include 1H−1H TOCSY, 138
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Figure 6. Workflow implemented in IsoDesign to determine the optimal label input in a 13C-MFA experiment. Blue, orange, and green boxes detail steps performed by the calculation module, the visualization module, and a spreadsheet program, respectively. Reprinted from ref 92 with permission from John Wiley & Sons Inc., copyright 2014. 1
H−1H HCCH TOCSY, 1H−13C HSQC, 1H−15N HSQC HACACO (correlating carbonyl carbons with neighboring protons), 1H−13C HSQC-TOCSY, and 1H−31P HSQC TOCSY, and the authors discuss how the isotopomer distribution is determined from the spectra. Despite isotopic enrichment, traditional 2D experiments can still be time-consuming and less amenable to high-throughput isotope tracing than 1D experiments. The advent of ultrafast 2D NMR experiments, which allow the acquisition of a multidimensional NMR experiment in a single scan, has greatly reduced experiment times.78 Giraudeau and coworkers measured the 13C enrichment in a biological sample with a traditional TOCSY experiment, which had a run time of greater than 2 h, compared to an ultrafast TOCSY with an experiment time of 3 s on a 400 MHz spectrometer equipped with a room temperature probe.58 Continued development and applications of ultrafast 2D NMR experiments will significantly increase the throughput of isotope tracing by NMR. This section has predominantly discussed the use of isotope labeling for the use of in vivo isotope labeling for the analysis of biological pathways. Another interesting approach is to use isotope labeling ex vivo to improve NMR sensitivity for general metabolomics experiments. By incorporating an NMR active isotope onto a tag, specific chemical moieties, such carboxylic acid groups or amines, can be derivatized significantly increasing sensitivity and selectivity while decreasing spectral convolution.79,80 For example, Tayyari and co-workers designed a cholamine tag with a 15N label on the primary amine, allowing derivatization of carboxylic acid functional groups.81 The authors demonstrate the sensitivity of the tag using 1H−15N HSQC experiments by collecting only 1−4 scans over 128 increments. The tag also included a tertiary amine which provides a stable, permanent positive charge attached to all derivatized molecules, enhancing mass spectrometry sensitivity as well. Although not yet widely used, the use of derivatization to enhance NMR sensitivity and selectivity and decrease NMR resonance overlap while enhancing cross-platform utility has strong potential for improving NMR metabolite profiling experiments. Metabolic Flux Analysis. Metabolic flux analysis (MFA) is a popular and growing topic in analytical chemistry and
molecular biology and has recently been extensively reviewed.82,83 The ultimate goal of MFA is to establish the metabolic flux through a particular pathway using labeled reagents and to compare the flux under different stresses and in various tissue types including cancers,84−86 oysters,87 plants,88 and bacteria.89 These analyses are often limited to specific, welldefined biochemical pathways. Flux experiments measure timebased isotope enrichments and require that the activities of the enzymes involved in the pathway are known. For well-studied pathways, enzymatic activities can often be approximated; otherwise, parameters must be estimated to understand how the pathways may be affected. Regardless, computational methods are necessary to model the pathways and estimate the flux parameters. One such program reported by Hettling and co-workers estimated TCA fluxes with noisy NMR data in heart tissue using a computational model to estimate the flux parameters.90 In addition to data analysis, the actual design of a MFA study can be challenging, as one must consider what precursors and isotopic composition to use and the desired outcome (dependent on the biological question under investigation). Work by Millard et al. presents a novel software program for the design of 13C-MFA experiments, termed IsoDesign.91 As illustrated in Figure 6, the program allows the investigator to generate models using different label inputs, simulate the isotopic data, calculate the precision expected on each flux for each label input, and outputs these results in a visually interpreted sensitivity landscape. Isodesign can be used for comparison of isotopic data from MS (including MS/MS) and NMR (both 1H and 13C). Tools such as those provided by Hettling et al., Millard et al., and others are increasingly in need as more biological questions are being probed with substrates labeled specifically for the investigation of selected pathways.90−92 A major advantage of NMR over other popular MFA analytical platforms is that it is nondestructive which allows for in vivo NMR spectroscopy under specific conditions. A comprehensive review and guide for in vivo NMR by de Graaf and co-workers has recently been published and discusses topics such as substrate choice, metabolic model, and choice of NMR experiment (direct vs indirect detection).93 Although this 139
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transferred to organic molecules by reacting hyperpolarized hydrogen with precursor molecules in the presence of a transition metal catalyst. The use of PHIP for imaging, including the use of 13C or 15N labeled metabolite precursors, has been reviewed by Glöggler et al.99 An exciting development in hyperpolarization experiments for metabolic profiling is the rapidly expanding use of dynamic nuclear polarization (DNP), which has been accelerated by the introduction of commercial instruments that facilitate its implementation. An excellent overview of DNP in liquids has been recently authored by Günther.97 DNP takes advantage of the comparably larger polarization of electron spins, which can be nearly 100% at low temperatures. Saturation of the electron spin transfers this polarization from the unpaired electrons to nuclear spin via hyperfine and dipolar interactions. Though DNP experiments can be executed in a variety of experimental arrangements, the most useful configuration for metabolic profiling experiments is dissolution DNP, in which polarization is carried out at low temperatures (
