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Canadian NMR Research - University of Calgary
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Get access to the full version of this article. View access options below. You previously purchased this article through ReadCube. Institutional Login. Log in to Wiley Online Library. Purchase Instant Access. View Preview. Learn more Check out. Volume 30 , Issue 11 November Pages Related Information. To get around this problem, Shanaiah et al. In particular, by adding 13 C-acetic anhydride to urine or serum samples, it is possible to selectively 13 C-tag certain classes of metabolites such as amino acids through the 13 C acetylation of amines.
This tagging enables rapid collection of 13 C NMR spectra while at the same time significantly simplifying the NMR spectra of complex biofluids such as urine through selective labeling. This chemo-selective tagging method was successfully used to identify and compare amino acids and related metabolites in urine collected from patients with inborn errors of metabolism [ 99 ]. We believe this simple and elegant approach for enhancing 13 C NMR signals could be extended to many other applications in human or mammalian metabolomics.
In particular, the use of cryoprobe technology, where the NMR probe and its electronics are cooled to near absolute zero as a way to reduce electronic noise, can lead to a two- to four-fold signal enhancement. For instance, Keun and colleagues employed a 13 C direct-detect cryoprobe to study drug toxicity in urine via 1D 13 C NMR [ , ].
The resulting 13 C spectra had much greater spectral dispersion than 1 H spectra which is critical in analyzing complex biofluids like urine while still providing sufficient signal-to-noise to enable analysis. Another approach that can be used to enhance 13 C NMR signals involves the use of hyperpolarization techniques, which are described in Section 5. It is important to note that 13 C NMR is particularly useful for isotope tracking or isotope tracing experiments [ 98 , , ].
These metabolic experiments allow the direct determination of the source of certain carbons in various biosynthetic pathways as well as further clarification of the precise chemistry involved in various biosynthetic steps. As a result, 13 C has become the most commonly observed nucleus in experiments involving NMR as well as MS-based fluxomics. Fluxomics is a branch of metabolomics that focuses on determining intracellular metabolic fluxes in living cells [ ].
The experiment consists of incorporating isotopically enriched 13 C molecules in living cells and then quantifying the metabolic activity i. However, the direct detection of 15 N is challenging because of its very poor sensitivity. In particular, its low natural abundance 0. As a remedy, isotopic enrichment combined with 1 H-mediated enhancement via indirect detection is often the only route to make 15 N NMR practical.
Indirectly detected 15 N NMR spectroscopy is widely used in structural elucidation of proteins [ , , ], RNA [ , , ], and DNA [ , , , ], but it has not been commonly applied in metabolomics studies. The Raftery group has pioneered the development of 15 N isotope-based indirect detection for NMR-based metabolomics.
Their ingenious concept is based on isotope tagging to expand the pool of quantifiable metabolites [ 46 ]. This approach, like the 13 C tagging approach described earlier, allows selective tagging of certain metabolite classes that provides further spectral simplification. Typically, this selective tagging approach generates a single peak for each tagged metabolite, effectively suppresses the signal from nontagged metabolites, and significantly adds to the sensitivity and peak dispersion.
This can enable the detection of over a hundred quantifiable metabolites from a single class of molecules i. Its utility in metabolomics studies is limited because most metabolites do not contain phosphorus atoms.
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One approach that potentially expands the utility of 31 P NMR for metabolomics was recently provided by the Raftery group [ ]. Like the 15 N tagging method described earlier, this approach uses isotope tagging to enable the detection of various hydrophobic compounds. More specifically, this method employs the 31 P reagent, 2-chloro-4,4,5,5-tetramethyldioxaphospholane CTMDP , to tag lipid metabolites containing hydroxyl, aldehyde, and carboxyl groups.
One-dimensional 31 P NMR then enables detection of the tagged metabolites with enhanced resolution. This method, which was applied to the detection of a number of metabolites in serum, was shown to be simple, reproducible, and highly quantitative. Two-dimensional NMR spectroscopy can be used for many applications including molecular identification, structural elucidation, and kinetic or energetic analysis [ , , ]. In the following sections we will describe some of the more popular 2D NMR experiments for metabolomics in more detail.
It provides information on homonuclear correlations between coupled nuclei 1 H- 1 H and has been widely used for molecular identification and for structural elucidation [ , , , ]. Fourier transformation in both the t 1 and t 2 dimensions yields a 2D spectrum, in which the cross peaks in the 2D spectrum indicate pairs of nuclei connected by through-bond 3JHH couplings.
The fact that the COSY experiment is relatively simple, fast often a few minutes , easy to perform, and easy to interpret makes it particularly useful for metabolomics research [ , , , , ].
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Moreover, COSY cross peaks, which represent through-bond coupling between coupled nuclei, provide important clues for the identification of unknown metabolites in complex biological mixtures. In other words, COSY experiments as well as other 2D NMR experiments enable the identification of both known and unknown metabolites, while 1D NMR experiments are largely limited to the identification of known metabolites. As a result, one must be careful in choosing the proper COSY variant by carefully considering which type and what physical aspects one wants to observe. For example, the magnitude mode acquisition COSY reduces the complexity of the experiment, but it loses much of the coupling information that other COSY versions allow.
It is also worth mentioning that, for very complex mixtures composed of many small molecules such as urine , the spectral complexity due to spectral overlap is often so great that one quickly loses the inherent advantages of the 2D COSY. TOCSY total correlation spectroscopy , also known as the homonuclear Hartmann—Hahn HOHAHA experiment, is an extension of the COSY experiment, wherein the chemical shift of a given nucleus is correlated with the chemical shift of other nuclei within the total or near total spin system of a given compound.
The 1D TOCSY is characterized by a spectrum in which only signals appear from those nuclei that are in the same spin system as the excited signal or signals. The 1D TOCSY experiment is particularly useful when there is considerable overlap in the NMR spectrum or when one wishes to quantify highly overlapped metabolite species The 1D TOCSY was first shown to be useful in a metabolomics setting with the analysis of low-concentration metabolites in honey samples where carbohydrate signals were extremely strong and dominated the NMR spectra [ 91 ].
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Selective excitation TOCSY experiments are another variant of the TOCSY experiment that can be used to resolve the spectral overlapping problem and to aid in metabolite identification [ 90 , , ]. It was initially introduced by Ernst et al. As with other 2D experiments, the J-Res experiment simplifies spectral assignments by increasing the peak dispersion compared with a conventional 1D NMR experiment [ ]. For example, J-Res NMR spectroscopy has been employed to resolve overlapped resonances of metabolites and for metabolite identification in human biofluids such as urine, blood plasma, and cerebral spinal fluid [ , , ].
It was reported that plasma J-Res NMR spectra were simpler and yet contained much more information than the corresponding 1D Hahn spin-echo spectra. J-Res NMR spectroscopy has also been shown to have similar advantages when employed with different types of biological samples such as hemolymph from tobacco hornworm larvae Manduca sexta [ ]. The basic methodology of 2D J-Res NMR spectroscopy, along with optimized spectral acquisition parameters and specific recommendations for optimal data processing in the context of metabolomics applications, has recently been reviewed [ ].
The extended experimental time is one of the main disadvantages of 2D NMR experiments, especially with metabolomic studies that involve a large number of samples. Several approaches have been developed to shorten the acquisition time of multidimensional NMR experiments, including the J-Res experiment [ 30 , , ].
For instance, Frydman et al. This has reduced the J-Res acquisition time to less than one minute [ ]. However, these experiments suffer from extremely low sensitivity and require very high metabolite concentrations that are not practical for most metabolomics studies. Bond correlation spectroscopy COSY and TOCSY-like spectroscopy is not limited to homonuclear correlations; therefore, it can also be used for measuring heteronuclear correlations. Furthermore, heteronuclear correlation experiments can be used to enhance the signal coming from a lower sensitivity nucleus by transferring the nuclear spin polarization from the more sensitive nucleus via J-coupling i.
Such nuclear spin polarization transfer from nuclei with large Boltzmann population differences mainly 1 H to nuclei with a low Boltzmann population difference e. Here, the magnetization from the more sensitive nucleus usually 1 H is transferred to the less sensitive nucleus, such as 13 C or 15 N, and then transferred back to 1 H for direct observation. The general feature of the INEPT-based HSQC experiment is the mapping of the chemical shift of one nucleus such as 1 H detected in the directly measured dimension and the chemical shift of the other nucleus, such as 13 C, recorded in the indirectly measured dimension.
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An 1 H, 13 C-HSQC spectrum maps the chemical shifts of proton and carbon atoms that are directly bonded, providing only one cross-peak for each H—C coupled pair. Likewise, an 1 H, 15 N-HSQC spectrum maps the chemical shifts of directly bonded proton and nitrogen atoms yielding one cross-peak for each H—N coupled pair see Figure 5.
HSQC is a very useful experiment for resolving and assigning overlapping proton signals, particularly for metabolite signals arising from complex biofluid mixtures. HSQC experiments are also among the most important and common experimental techniques in biomolecular NMR for the assignment of protein backbone and side-chain NH signals [ , , , ].
Furthermore, because of the large number of metabolites with a broad concentration range, 2D NMR spectra need to be collected with high-resolution settings. The greater the resolution required, the longer the experiments take. Fortunately, a number of novel pulse sequences have been developed to help address these problems for HSQC spectra.
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FMQ has been employed to identify and quantify 40 of the most abundant metabolites in biological samples, with accurate metabolite identification and concentration determination with spectra collected in as little as 12 min [ ] Figure 6. HMQC provides virtually the same type of correlation as in HSQC, but it uses a different approach to transfer magnetization from 1 H to the heteronucleus.
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