¹³C NMR metabolomics: applications at natural abundance

Novel selective TOCSY method enables NMR spectral elucidation of metabolomic mixtures

Complex mixture analysis is routinely encountered in NMR-based investigations. With the aim of component identification, spectral complexity may be addressed chromatographically or spectroscopically, the latter being favored to reduce sample handling requirements. An attractive experiment is selective total correlation spectroscopy (sel-TOCSY), which is capable of providing tremendous spectral simplification and thereby enhancing assignment capability. Unfortunately, isolating a well resolved resonance is increasingly difficult as the complexity of the mixture increases and the assumption of single spin system excitation is no longer robust. We present TOCSY optimized mixture elucidation (TOOMIXED), a technique capable of performing spectral assignment particularly in the case where the assumption of single spin system excitation is relaxed. Key to the technique is the collection of a series of 1D sel-TOCSY experiments as a function of the isotropic mixing time (τ_m), resulting in a series of resonance intensities indicative of the underlying molecular structure. By comparing these τ_m-dependent intensity patterns with a library of pre-determined component spectra, one is able to regain assignment capability. After consideration of the technique's robustness, we tested TOOMIXED firstly on a model mixture. As a benchmark we were able to assign a molecule with high confidence in the case of selectively exciting an isolated resonance. Assignment confidence was not compromised when performing TOOMIXED on a resonance known to contain multiple overlapping signals, and in the worst case the method suggested a follow-up sel-TOCSY experiment to confirm an ambiguous assignment. TOOMIXED was then demonstrated on two realistic samples (whisky and urine), where under our conditions an approximate limit of detection of 0.6mM was determined. Taking into account literature reports for the sel-TOCSY limit of detection, the technique should reach on the order of 10μM sensitivity. We anticipate this technique will be highly attractive to various analytical fields facing mixture analysis, including metabolomics, foodstuff analysis, pharmaceutical analysis, and forensics.

The future of NMR-based metabolomics

The two leading analytical approaches to metabolomics are mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. Although currently overshadowed by MS in terms of numbers of compounds resolved, NMR spectroscopy offers advantages both on its own and coupled with MS. NMR data are highly reproducible and quantitative over a wide dynamic range and are unmatched for determining structures of unknowns. NMR is adept at tracing metabolic pathways and fluxes using isotope labels. Moreover, NMR is non-destructive and can be utilized in vivo. NMR results have a proven track record of translating in vitro findings to in vivo clinical applications.

Highly Repeatable Dissolution Dynamic Nuclear Polarization for Heteronuclear NMR Metabolomics

At natural (13)C abundance, metabolomics based on heteronuclear NMR is limited by sensitivity. We have recently demonstrated how hyperpolarization by dissolution dynamic nuclear polarization (D-DNP) assisted by cross-polarization (CP) provides a reliable way of enhancing the sensitivity of heteronuclear NMR in dilute mixtures of metabolites. In this Technical Note, we evaluate the precision of this experimental approach, a critical point for applications to metabolomics. The higher the repeatability, the greater the likelihood that one can detect small biologically relevant differences between samples. The average repeatability of our state-of-the-art D-DNP NMR equipment for samples of metabolomic relevance (20 mg dry weight tomato extracts) is 3.6% for signals above the limit of quantification (LOQ) and 6.4% when all the signals above the limit of detection (LOD) are taken into account. This first report on the repeatability of D-DNP highlights the compatibility of the technique with the requirements of metabolomics and confirms its potential as an analytical tool for such applications.

Simultaneous Analysis of Major Coenzymes of Cellular Redox Reactions and Energy Using ex Vivo (1)H NMR Spectroscopy

Coenzymes of cellular redox reactions and cellular energy mediate biochemical reactions fundamental to the functioning of all living cells. Despite their immense interest, no simple method exists to gain insights into their cellular concentrations in a single step. We show that a simple (1)H NMR experiment can simultaneously measure oxidized and reduced forms of nicotinamide adenine dinucleotide (NAD(+) and NADH), oxidized and reduced forms of nicotinamide adenine dinucleotide phosphate (NADP(+) and NADPH), and adenosine triphosphate (ATP) and its precursors, adenosine diphosphate (ADP) and adenosine monophosphate (AMP), using mouse heart, kidney, brain, liver, and skeletal muscle tissue extracts as examples. Combining 1D/2D NMR experiments, chemical shift libraries, and authentic compound data, reliable peak identities for these coenzymes have been established. To assess this methodology, cardiac NADH and NAD(+) ratios/pool sizes were measured using mouse models with a cardiac-specific knockout of the mitochondrial Complex I Ndufs4 gene (cKO) and cardiac-specific overexpression of nicotinamide phosphoribosyltransferase (cNAMPT) as examples. Sensitivity of NAD(+) and NADH to cKO or cNAMPT was observed, as anticipated. Time-dependent investigations showed that the levels of NADH and NADPH diminish by up to ∼50% within 24 h; concomitantly, NAD(+) and NADP(+) increase proportionately; however, degassing the sample and flushing the sample tubes with helium gas halted such changes. The analysis protocol along with the annotated characteristic fingerprints for each coenzyme is provided for easy identification and absolute quantification using a single internal reference for routine use. The ability to visualize the ubiquitous coenzymes fundamental to cellular functions, simultaneously and reliably, offers a new avenue to interrogate the mechanistic details of cellular function in health and disease.

Isoprenoid generating systems in plants - A handy toolbox how to assess contribution of the mevalonate and methylerythritol phosphate pathways to the biosynthetic process

Isoprenoids comprise an astonishingly diverse group of metabolites with numerous potential and actual applications in medicine, agriculture and the chemical industry. Generation of efficient platforms producing isoprenoids is a target of numerous laboratories. Such efforts are generally enhanced if the native biosynthetic routes can be identified, and if the regulatory mechanisms responsible for the biosynthesis of the compound(s) of interest can be determined. In this review a critical summary of the techniques applied to establish the contribution of the two alternative routes of isoprenoid production operating in plant cells, the mevalonate and methylerythritol pathways, with a focus on their co-operation (cross-talk) is presented. Special attention has been paid to methodological aspects of the referred studies, in order to give the reader a deeper understanding for the nuances of these powerful techniques. This review has been designed as an organized toolbox, which might offer the researchers comments useful both for project design and for interpretation of results obtained.

Emerging new strategies for successful metabolite identification in metabolomics

This review discusses strategies for the identification of metabolites in complex biological mixtures, as encountered in metabolomics, which have emerged in the recent past. These include NMR database-assisted approaches for the identification of commonly known metabolites as well as novel combinations of NMR and MS analysis methods for the identification of unknown metabolites. The use of certain chemical additives to the NMR tube can permit identification of metabolites with specific physical chemical properties.

Applications of NMR spectroscopy to systems biochemistry

The past decades of advancements in NMR have made it a very powerful tool for metabolic research. Despite its limitations in sensitivity relative to mass spectrometric techniques, NMR has a number of unparalleled advantages for metabolic studies, most notably the rigor and versatility in structure elucidation, isotope-filtered selection of molecules, and analysis of positional isotopomer distributions in complex mixtures afforded by multinuclear and multidimensional experiments. In addition, NMR has the capacity for spatially selective in vivo imaging and dynamical analysis of metabolism in tissues of living organisms. In conjunction with the use of stable isotope tracers, NMR is a method of choice for exploring the dynamics and compartmentation of metabolic pathways and networks, for which our current understanding is grossly insufficient. In this review, we describe how various direct and isotope-edited 1D and 2D NMR methods can be employed to profile metabolites and their isotopomer distributions by stable isotope-resolved metabolomic (SIRM) analysis. We also highlight the importance of sample preparation methods including rapid cryoquenching, efficient extraction, and chemoselective derivatization to facilitate robust and reproducible NMR-based metabolomic analysis. We further illustrate how NMR has been applied in vitro, ex vivo, or in vivo in various stable isotope tracer-based metabolic studies, to gain systematic and novel metabolic insights in different biological systems, including human subjects. The pathway and network knowledge generated from NMR- and MS-based tracing of isotopically enriched substrates will be invaluable for directing functional analysis of other 'omics data to achieve understanding of regulation of biochemical systems, as demonstrated in a case study. Future developments in NMR technologies and reagents to enhance both detection sensitivity and resolution should further empower NMR in systems biochemical research.

SENSI: signal enhancement by spectral integration for the analysis of metabolic mixtures

The method provided here can overcome the low S/N problem in ¹³C NMR by the integration of plural spectra to increase the resolution based on non-bucketing analysis without measurements.

Can NMR solve some significant challenges in metabolomics?

The field of metabolomics continues to witness rapid growth driven by fundamental studies, methods development, and applications in a number of disciplines that include biomedical science, plant and nutrition sciences, drug development, energy and environmental sciences, toxicology, etc. NMR spectroscopy is one of the two most widely used analytical platforms in the metabolomics field, along with mass spectrometry (MS). NMR's excellent reproducibility and quantitative accuracy, its ability to identify structures of unknown metabolites, its capacity to generate metabolite profiles using intact bio-specimens with no need for separation, and its capabilities for tracing metabolic pathways using isotope labeled substrates offer unique strengths for metabolomics applications. However, NMR's limited sensitivity and resolution continue to pose a major challenge and have restricted both the number and the quantitative accuracy of metabolites analyzed by NMR. Further, the analysis of highly complex biological samples has increased the demand for new methods with improved detection, better unknown identification, and more accurate quantitation of larger numbers of metabolites. Recent efforts have contributed significant improvements in these areas, and have thereby enhanced the pool of routinely quantifiable metabolites. Additionally, efforts focused on combining NMR and MS promise opportunities to exploit the combined strength of the two analytical platforms for direct comparison of the metabolite data, unknown identification and reliable biomarker discovery that continue to challenge the metabolomics field. This article presents our perspectives on the emerging trends in NMR-based metabolomics and NMR's continuing role in the field with an emphasis on recent and ongoing research from our laboratory.

Internal Referencing for ¹³C Position-Specific Isotope Analysis Measured by NMR Spectrometry

The intramolecular (13)C composition of a molecule retains evidence relevant to its (bio)synthetic history and can provide valuable information in numerous fields ranging from biochemistry to environmental sciences. Isotope ratio monitoring by (13)C NMR spectrometry (irm-(13)C NMR) is a generic method that offers the potential to conduct (13)C position-specific isotope analysis with a precision better than 1‰. Until now, determining absolute values also required measurement of the global (or bulk) (13)C composition (δ(13)Cg) by mass spectrometry. In a radical new approach, it is shown that an internal isotopic chemical reference for irm-(13)C NMR can be used instead. The strategy uses (1)H NMR to quantify both the number of moles of the reference and of the studied compound present in the NMR tube. Thus, the sample preparation protocol is greatly simplified, bypassing the previous requirement for precise purity and mass determination. The key to accurate results is suppressing the effect of radiation damping in (1)H NMR which produces signal distortion and alters quantification. The methodology, applied to vanillin with dimethylsulfone as an internal standard, has an equivalent accuracy (<1‰) to that of the conventional approach. Hence, it was possible to clearly identify vanillin from different origins based on the (13)C isotopic profiles.

(13)C NMR Metabolomics: INADEQUATE Network Analysis

The many advantages of (13)C NMR are often overshadowed by its intrinsically low sensitivity. Given that carbon makes up the backbone of most biologically relevant molecules, (13)C NMR offers a straightforward measurement of these compounds. Two-dimensional (13)C-(13)C correlation experiments like INADEQUATE (incredible natural abundance double quantum transfer experiment) are ideal for the structural elucidation of natural products and have great but untapped potential for metabolomics analysis. We demonstrate a new and semiautomated approach called INETA (INADEQUATE network analysis) for the untargeted analysis of INADEQUATE data sets using an in silico INADEQUATE database. We demonstrate this approach using isotopically labeled Caenorhabditis elegans mixtures.

Hyperpolarized NMR of plant and cancer cell extracts at natural abundance

Natural abundance ¹³C 1D and 2D NMR spectra of biological extracts are recorded in a single scan for samples hyperpolarised by dissolution dynamic nuclear polarization combined with cross polarization.

An overview of methods using (13)C for improved compound identification in metabolomics and natural products

Compound identification is a major bottleneck in metabolomics studies. In nuclear magnetic resonance (NMR) investigations, resonance overlap often hinders unambiguous database matching or de novo compound identification. In liquid chromatography-mass spectrometry (LC-MS), discriminating between biological signals and background artifacts and reliable determination of molecular formulae are not always straightforward. We have designed and implemented several NMR and LC-MS approaches that utilize (13)C, either enriched or at natural abundance, in metabolomics applications. For LC-MS applications, we describe a technique called isotopic ratio outlier analysis (IROA), which utilizes samples that are isotopically labeled with 5% (test) and 95% (control) (13)C. This labeling strategy leads to characteristic isotopic patterns that allow the differentiation of biological signals from artifacts and yield the exact number of carbons, significantly reducing possible molecular formulae. The relative abundance between the test and control samples for every IROA feature can be determined simply by integrating the peaks that arise from the 5 and 95% channels. For NMR applications, we describe two (13)C-based approaches. For samples at natural abundance, we have developed a workflow to obtain (13)C-(13)C and (13)C-(1)H statistical correlations using 1D (13)C and (1)H NMR spectra. For samples that can be isotopically labeled, we describe another NMR approach to obtain direct (13)C-(13)C spectroscopic correlations. These methods both provide extensive information about the carbon framework of compounds in the mixture for either database matching or de novo compound identification. We also discuss strategies in which (13)C NMR can be used to identify unknown compounds from IROA experiments. By combining technologies with the same samples, we can identify important biomarkers and corresponding metabolites of interest.