High field hyperpolarization-EXSY experiment for fast determination of dissociation rates in SABRE complexes.

SABRE (Signal Amplification By Reversible Exchange) is a nuclear spin hyperpolarization technique based on the reversible concurrent binding of small molecules and para-hydrogen (p-H2) to an iridium metal complex in solution. At low magnetic field, spontaneous conversion of p-H2 spin order to enhanced longitudinal magnetization of the nuclear spins of the other ligands occurs. Subsequent complex dissociation results in hyperpolarized substrate molecules in solution. The lifetime of this complex plays a crucial role in attained SABRE NMR signal enhancements. Depending on the ligands, vastly different dissociation rates have been previously measured using EXSY or selective inversion experiments. However, both these approaches are generally time-consuming due to the long recycle delays (up to 2min) necessary to reach thermal equilibrium for the nuclear spins of interest. In the cases of dilute solutions, signal averaging aggravates the problem, further extending the experimental time. Here, a new approach is proposed based on coherent hyperpolarization transfer to substrate protons in asymmetric complexes at high magnetic field. We have previously shown that such asymmetric complexes are important for application of SABRE to dilute substrates. Our results demonstrate that a series of high sensitivity EXSY spectra can be collected in a short experimental time thanks to the NMR signal enhancement and much shorter recycle delay.

Stable isotope labeling methods for DNA.

NMR is a powerful method for studying proteins and nucleic acids in solution. The study of nucleic acids by NMR is far more challenging than for proteins, which is mainly due to the limited number of building blocks and unfavorable spectral properties. For NMR studies of DNA molecules, (site specific) isotope enrichment is required to facilitate specific NMR experiments and applications. Here, we provide a comprehensive review of isotope-labeling strategies for obtaining stable isotope labeled DNA as well as specifically stable isotope labeled building blocks required for enzymatic DNA synthesis.

Determination of long-range scalar (1)H-(1)H coupling constants responsible for polarization transfer in SABRE.

SABRE (Signal Amplification By Reversible Exchange) nuclear spin hyperpolarization method can provide strongly enhanced NMR signals as a result of the reversible association of small molecules with para-hydrogen (p-H2) at an iridium metal complex. The conversion of p-H2 singlet order to enhanced substrate proton magnetization within such complex is driven by the scalar coupling interactions between the p-H2 derived hydrides and substrate nuclear spins. In the present study these long-range homonuclear couplings are experimentally determined for several SABRE substrates using an NMR pulse sequence for coherent hyperpolarization transfer at high magnetic field. Pyridine and pyrazine derivatives appear to have a similar ∼1.2 Hz (4)J coupling to p-H2 derived hydrides for their ortho protons, and a much lower (5)J coupling for their meta protons. Interestingly, the (4)J hydride-substrate coupling for five-membered N-heterocyclic substrates is well below 1 Hz.

NMR-Based Chemosensing via p-H2 Hyperpolarization: Application to Natural Extracts.

When dealing with trace analysis of complex mixtures, NMR suffers from both low sensitivity and signal overlap. NMR chemosensing, in which the association between an analyte and a receptor is "signaled" by an NMR response, has been proposed as a valuable analytical tool for biofluids and natural extracts. Such chemosensors offer the possibility to simultaneously detect and distinguish different analytes in solution, which makes them particularly suitable for analytical applications on complex mixtures. In this study, we have combined NMR chemosensing with nuclear spin hyperpolarization. This was realized using an iridium complex as a receptor in the presence of parahydrogen: association of the target analytes to the metal center results in approximately 1000-fold enhancement of the NMR response. This amplification allows the detection, identification, and quantification of analytes at low-micromolar concentrations, provided they can weakly associate to the iridium chemosensor. Here, our NMR chemosensing approach was applied to the quantitative determination of several flavor components in methanol extracts of ground coffee.

2D†NMR Trace Analysis by Continuous Hyperpolarization at High Magnetic Field.

Nuclear magnetic resonance is often the technique of choice in chemical analysis because of its sensitivity to molecular structure, quantitative character, and straightforward sample preparation. However, determination of trace analytes in complex mixtures is generally limited by low sensitivity and extensive signal overlap. Here, we present an approach for continuous hyperpolarization at high magnetic field that is based on signal amplification by reversible exchange (SABRE) and can be straightforwardly incorporated in multidimensional NMR experiments. This method was implemented in a 2D correlation experiment that allows detection and quantification of analytes at nanomolar concentration in complex solutions.

Production of Homogeneous Recombinant RNA Using a tRNA Scaffold and Hammerhead Ribozymes.

Bacterial overproduction of recombinant RNA using a tRNA scaffold yields large amounts of chimeric RNA. For structural and functional characterizations of the RNA it is often necessary to remove the scaffold. Here we describe an efficient and facile method to release the RNA of interest from the tRNA scaffold by selective cleavage using cis-acting hammerhead ribozymes. After cleavage, the RNA of interest is purified to homogeneity using standard chromatographic and electrophoretic methods. Up to 5 mg of highly pure end-product RNA can be obtained from a single liter of bacterial culture.

Magnetic susceptibility to measure total protein concentration from NMR metabolite spectra: Demonstration on blood plasma.

PURPOSE: Accurate metabolite and protein quantification in blood plasma and other body fluids from one single NMR measurement, allowing for improved quantitative metabolic profiling and better assessment of metabolite-protein interactions. THEORY AND METHODS: The total protein concentration is derived from the common chemical-shift changes-caused by protein-induced bulk magnetic susceptibility (BMS)-measured on well-accessible and exchange-free metabolite resonances. These BMS shifts are simply obtained by external referencing with respect to 3-(trimethylsilyl)propionic-2,2,3,3-d4 acid, sodium salt in a coaxial insert. RESULTS: Based on blood-plasma data from five volunteers, the estimated accuracy of the BMS method is ≤ 5% with respect and comparable to the 3.8% error of the standard colorimetric, Biuret, method. Valine, alanine, glucose, leucine, and lactate display no exchange-induced shift changes. Their well-accessible signals act as reliable probes for pure protein-induced BMS. The slopes and intercepts of their chemical-shift change versus protein concentration were derived from metabolite mixtures with (fatted) human and bovine albumin acting as blood-plasma mimics. CONCLUSION: The BMS method, demonstrated on blood plasma, can also be used on other samples containing sufficient protein (> 10 g/L). Also, it allows measurement of the presence and sign of exchange-induced chemical-shift changes.

Quantitative trace analysis of complex mixtures using SABRE hyperpolarization.

Signal amplification by reversible exchange (SABRE) is an emerging nuclear spin hyperpolarization technique that strongly enhances NMR signals of small molecules in solution. However, such signal enhancements have never been exploited for concentration determination, as the efficiency of SABRE can strongly vary between different substrates or even between nuclear spins in the same molecule. The first application of SABRE for the quantitative analysis of a complex mixture is now reported. Despite the inherent complexity of the system under investigation, which involves thousands of competing binding equilibria, analytes at concentrations in the low micromolar range could be quantified from single-scan SABRE spectra using a standard-addition approach.

How a low-fidelity DNA polymerase chooses non-Watson-Crick from Watson-Crick incorporation.

A dogma for DNA polymerase catalysis is that the enzyme binds DNA first, followed by MgdNTP. This mechanism contributes to the selection of correct dNTP by Watson-Crick base pairing, but it cannot explain how low-fidelity DNA polymerases overcome Watson-Crick base pairing to catalyze non-Watson-Crick dNTP incorporation. DNA polymerase X from the deadly African swine fever virus (Pol X) is a half-sized repair polymerase that catalyzes efficient dG:dGTP incorporation in addition to correct repair. Here we report the use of solution structures of Pol X in the free, binary (Pol X:MgdGTP), and ternary (Pol X:DNA:MgdGTP with dG:dGTP non-Watson-Crick pairing) forms, along with functional analyses, to show that Pol X uses multiple unprecedented strategies to achieve the mutagenic dG:dGTP incorporation. Unlike high fidelity polymerases, Pol X can prebind purine MgdNTP tightly and undergo a specific conformational change in the absence of DNA. The prebound MgdGTP assumes an unusual syn conformation stabilized by partial ring stacking with His115. Upon binding of a gapped DNA, also with a unique mechanism involving primarily helix αE, the prebound syn-dGTP forms a Hoogsteen base pair with the template anti-dG. Interestingly, while Pol X prebinds MgdCTP weakly, the correct dG:dCTP ternary complex is readily formed in the presence of DNA. H115A mutation disrupted MgdGTP binding and dG:dGTP ternary complex formation but not dG:dCTP ternary complex formation. The results demonstrate the first solution structural view of DNA polymerase catalysis, a unique DNA binding mode, and a novel mechanism for non-Watson-Crick incorporation by a low-fidelity DNA polymerase.

Toward nanomolar detection by NMR through SABRE hyperpolarization.

SABRE is a nuclear spin hyperpolarization technique based on the reversible association of a substrate molecule and para-hydrogen (p-H2) to a metal complex. During the lifetime of such a complex, generally fractions of a second, the spin order of p-H2 is transferred to the nuclear spins of the substrate molecule via a transient scalar coupling network, resulting in strongly enhanced NMR signals. This technique is generally applied at relatively high concentrations (mM), in large excess of substrate with respect to metal complex. Dilution of substrate ligands below stoichiometry results in progressive decrease of signal enhancement, which precludes the direct application of SABRE to the NMR analysis of low concentration (µM) solutions. Here, we show that the efficiency of SABRE at low substrate concentrations can be restored by addition of a suitable coordinating ligand to the solution. The proposed method allowed NMR detection below 1 µM in a single scan.

Structural and thermodynamic signatures that define pseudotriloop RNA hairpins.

Pseudotriloop (PTL) structures in RNAs have been recognized as essential elements in RNA folding and recognition of proteins. PTL structures are derived from hexaloops by formation of a cross-loop base pair leaving a triloop and 3' bulged out residue. Despite their common presence and functional importance, insufficient structural and thermodynamic data are available that can be used to predict formation of PTLs from sequence alone. Using NMR spectroscopy and UV-melting data we established factors that contribute to the formation and stability of PTL structures derived from hepatitis B virus and human foamy virus. The NMR data show that, besides the cross-loop base pair, also a 3' pyrimidine bulge and a G-C loop-closing base pair are primary determinants of PTL formation. By changing the G-C closing base pair into C-G, the PTL switches into a hexaloop. Comparison of these rules with regular triloop hairpins and PTLs from other sources is discussed as well as the conservation of a PTL in human foamy virus and other spumaretroviruses.

EC-SPE-stripline-NMR analysis of reactive products: a feasibility study.

Flow-through electrochemical conversion (EC) of drug-like molecules was hyphenated to miniaturized nuclear magnetic resonance spectroscopy (NMR) via on-line solid-phase extraction (SPE). After EC of the prominent p38α mitogen-activated protein kinase inhibitor BIRB796 into its reactive products, the SPE step provided preconcentration of the EC products and solvent exchange for NMR analysis. The acquisition of NMR spectra of the mass-limited samples was achieved in a stripline probe with a detection volume of 150 nL offering superior mass sensitivity. This hyphenated EC-SPE-stripline-NMR setup enabled the detection of the reactive products using only minute amounts of substrate. Furthermore, the integration of conversion and detection into one flow setup counteracts incorrect assessments caused by the degradation of reactive products. However, apparent interferences of the NMR magnetic field with the EC, leading to a low product yield, so far demanded relatively long signal averaging. A critical assessment of what is and what is not (yet) possible with this approach is presented, for example in terms of structure elucidation and the estimation of concentrations. Additionally, promising routes for further improvement of EC-SPE-stripline-NMR are discussed.

Fluorine detected 2D NMR experiments for the practical determination of size and sign of homonuclear F-F and heteronuclear C-F multiple bond J-coupling constants in multiple fluorinated compounds.

The use of fluorine in molecules obtained from chemical synthesis has become increasingly important within the pharmaceutical and agricultural industry. NMR characterization of these compounds is of great value with respect to their structure elucidation, their screening in metabolomics investigations and binding studies. The favorable NMR properties of the fluorine nucleus make NMR with fluorine detection of great value in this respect. A suite of NMR 2D F-F- and F-C-correlation experiments with fluorine detection was applied to the assignment of resonances, (n)J(CF)- and (n)J(FF)-couplings as well as the determination of their size and sign. The utilization of this experiment suite was exemplarily demonstrated for a highly fluorinated vinyl alkyl ether. Especially F-C HSQC and J-scaled F-C HMBC experiments allowed determining the size of the J-couplings of this compound. The relative sign of its homo- and heteronuclear couplings was achieved by different combinations of 2D NMR experiments, including non-selective and F2-selective F-C XLOC, F2-selective F-C HMQC, and F-F COSY. The F2-one/two-site selective F-C XLOC versions were found highly useful, as they led to simplifications of the common E.COSY patterns and resulted in a higher confidence level of the assignment by using selective excitation. The combination of F2-one/two-site selective F-C XLOC experiments with a F2-one-site selective F-C HMQC experiment provided the signs of all (n)J(CF)- and (n)J(FF)-couplings in the vinyl moiety of the test compound. Other combinations of experiments were found useful as well for special purposes when focusing for example on homonuclear couplings a combination of F-F COSY-10 with a F2-one-site selective F-C HMQC could be used. The E.COSY patterns in the spectra demonstrated were analyzed by use of the spin-selective displacement vectors, and in case of the XLOC also by use of the DQ- and ZQ-displacement vectors. The variety of experiments presented shall contribute to facilitate the interpretation of F-C correlations as well as to open alternative pathways for the determination of size and signs of homo- and heteronuclear couplings of multiply fluorinated small molecules.

Nucleic acid helix structure determination from NMR proton chemical shifts.

We present a method for de novo derivation of the three-dimensional helix structure of nucleic acids using non-exchangeable proton chemical shifts as sole source of experimental restraints. The method is called chemical shift de novo structure derivation protocol employing singular value decomposition (CHEOPS) and uses iterative singular value decomposition to optimize the structure in helix parameter space. The correct performance of CHEOPS and its range of application are established via an extensive set of structure derivations using either simulated or experimental chemical shifts as input. The simulated input data are used to assess in a defined manner the effect of errors or limitations in the input data on the derived structures. We find that the RNA helix parameters can be determined with high accuracy. We finally demonstrate via three deposited RNA structures that experimental proton chemical shifts suffice to derive RNA helix structures with high precision and accuracy. CHEOPS provides, subject to further development, new directions for high-resolution NMR structure determination of nucleic acids.

Interconverting conformations of slipped-DNA junctions formed by trinucleotide repeats affect repair outcome.

Expansions of (CTG)·(CAG) repeated DNAs are the mutagenic cause of 14 neurological diseases, likely arising through the formation and processing of slipped-strand DNAs. These transient intermediates of repeat length mutations are formed by out-of-register mispairing of repeat units on complementary strands. The three-way slipped-DNA junction, at which the excess repeats slip out from the duplex, is a poorly understood feature common to these mutagenic intermediates. Here, we reveal that slipped junctions can assume a surprising number of interconverting conformations where the strand opposite the slip-out either is fully base paired or has one or two unpaired nucleotides. These unpaired nucleotides can also arise opposite either of the nonslipped junction arms. Junction conformation can affect binding by various structure-specific DNA repair proteins and can also alter correct nick-directed repair levels. Junctions that have the potential to contain unpaired nucleotides are repaired with a significantly higher efficiency than constrained fully paired junctions. Surprisingly, certain junction conformations are aberrantly repaired to expansion mutations: misdirection of repair to the non-nicked strand opposite the slip-out leads to integration of the excess slipped-out repeats rather than their excision. Thus, slipped-junction structure can determine whether repair attempts lead to correction or expansion mutations.

NMR identification of endogenous metabolites interacting with fatted and non-fatted human serum albumin in blood plasma: Fatty acids influence the HSA-metabolite interaction.

Metabolites and their concentrations are direct reporters on body biochemistry. Thanks to technical developments metabolic profiling of body fluids, such as blood plasma, by for instance NMR has in the past decade become increasingly accurate enabling successful clinical diagnostics. Human Serum Albumin (HSA) is the main plasma protein (∼60% of all plasma protein) and responsible for the transport of endogenous (e.g. fatty acids) and exogenous metabolites, which it achieves thanks to its multiple binding sites and its flexibility. HSA has been extensively studied with regard to its binding of drugs (exogenous metabolites), but only to a lesser extent with regard to its binding of endogenous (non-fatty acid) metabolites. To obtain correct NMR measured metabolic profiles of blood plasma and/or potentially extract information on HSA and fatty acids content, it is necessary to characterize these endogenous metabolite/plasma protein interactions. Here, we investigate these metabolite-HSA interactions in blood plasma and blood plasma mimics. The latter contain the roughly twenty metabolites routinely detected by NMR (also most abundant) in normal relative concentrations with fatted or non-fatted HSA added or not. First, we find that chemical shift changes are small and seen only for a few of the metabolites. In contrast, a significant number of the metabolites display reduced resonance integrals and reduced free concentrations in the presence of HSA or fatted HSA. For slow-exchange (or strong) interactions, NMR resonance integrals report the free metabolite concentration, while for fast exchange (weak binding) the chemical shift reports on the binding. Hence, these metabolites bind strongly to HSA and/or fatted HSA, but to a limited degree because for most metabolites their concentration is smaller than the HSA concentration. Most interestingly, fatty acids decrease the metabolite-HSA binding quite significantly for most of the interacting metabolites. We further find that competition between the metabolites for binding is absent for most of these metabolites. These mappings in plasma mimics may thus open new opportunities for improved metabolic profiling of blood plasma. For instance, correct metabolite concentrations can be determined for the non-interacting metabolites and/or concentration corrections made for interacting metabolites. Secondly, the interacting metabolites could be used to act as reporters on HSA and fatty acid concentration in plasma, and thus potentially act as biomarker in diagnostic studies of trauma or cardiovascular diseases. Finally, we find in the blood plasma mimics that after ultrafiltration, commonly used to remove the protein from plasma, the measured concentration equals the total metabolite concentration, except for the strongest binding metabolite citrate.

NMR and pattern recognition methods in metabolomics: from data acquisition to biomarker discovery: a review.

Metabolomics is the discipline where endogenous and exogenous metabolites are assessed, identified and quantified in different biological samples. Metabolites are crucial components of biological system and highly informative about its functional state, due to their closeness to functional endpoints and to the organism's phenotypes. Nuclear Magnetic Resonance (NMR) spectroscopy, next to Mass Spectrometry (MS), is one of the main metabolomics analytical platforms. The technological developments in the field of NMR spectroscopy have enabled the identification and quantitative measurement of the many metabolites in a single sample of biofluids in a non-targeted and non-destructive manner. Combination of NMR spectra of biofluids and pattern recognition methods has driven forward the application of metabolomics in the field of biomarker discovery. The importance of metabolomics in diagnostics, e.g. in identifying biomarkers or defining pathological status, has been growing exponentially as evidenced by the number of published papers. In this review, we describe the developments in data acquisition and multivariate analysis of NMR-based metabolomics data, with particular emphasis on the metabolomics of Cerebrospinal Fluid (CSF) and biomarker discovery in Multiple Sclerosis (MScl).

Chemical shifts in nucleic acids studied by density functional theory calculations and comparison with experiment.

NMR chemical shifts are highly sensitive probes of local molecular conformation and environment and form an important source of structural information. In this study, the relationship between the NMR chemical shifts of nucleic acids and the glycosidic torsion angle, χ, has been investigated for the two commonly occurring sugar conformations. We have calculated by means of DFT the chemical shifts of all atoms in the eight DNA and RNA mono-nucleosides as a function of these two variables. From the DFT calculations, structures and potential energy surfaces were determined by using constrained geometry optimizations at the BP86/TZ2P level of theory. The NMR parameters were subsequently calculated by single-point calculations at the SAOP/TZ2P level of theory. Comparison of the (1)H and (13)C NMR shifts calculated for the mono-nucleosides with the shifts determined by NMR spectroscopy for nucleic acids demonstrates that the theoretical shifts are valuable for the characterization of nucleic acid conformation. For example, a clear distinction can be made between χ angles in the anti and syn domains. Furthermore, a quantitative determination of the χ angle in the syn domain is possible, in particular when (13)C and (1)H chemical shift data are combined. The approximate linear dependence of the C1' shift on the χ angle in the anti domain provides a good estimate of the angle in this region. It is also possible to derive the sugar conformation from the chemical shift information. The DFT calculations reported herein were performed on mono-nucleosides, but examples are also provided to estimate intramolecularly induced shifts as a result of hydrogen bonding, polarization effects, or ring-current effects.

Interpretation and visualization of non-linear data fusion in kernel space: study on metabolomic characterization of progression of multiple sclerosis.

BACKGROUND: In the last decade data fusion has become widespread in the field of metabolomics. Linear data fusion is performed most commonly. However, many data display non-linear parameter dependences. The linear methods are bound to fail in such situations. We used proton Nuclear Magnetic Resonance and Gas Chromatography-Mass Spectrometry, two well established techniques, to generate metabolic profiles of Cerebrospinal fluid of Multiple Sclerosis (MScl) individuals. These datasets represent non-linearly separable groups. Thus, to extract relevant information and to combine them a special framework for data fusion is required. METHODOLOGY: The main aim is to demonstrate a novel approach for data fusion for classification; the approach is applied to metabolomics datasets coming from patients suffering from MScl at a different stage of the disease. The approach involves data fusion in kernel space and consists of four main steps. The first one is to extract the significant information per data source using Support Vector Machine Recursive Feature Elimination. This method allows one to select a set of relevant variables. In the next step the optimized kernel matrices are merged by linear combination. In step 3 the merged datasets are analyzed with a classification technique, namely Kernel Partial Least Square Discriminant Analysis. In the final step, the variables in kernel space are visualized and their significance established. CONCLUSIONS: We find that fusion in kernel space allows for efficient and reliable discrimination of classes (MScl and early stage). This data fusion approach achieves better class prediction accuracy than analysis of individual datasets and the commonly used mid-level fusion. The prediction accuracy on an independent test set (8 samples) reaches 100%. Additionally, the classification model obtained on fused kernels is simpler in terms of complexity, i.e. just one latent variable was sufficient. Finally, visualization of variables importance in kernel space was achieved.

Simultaneous analysis of plasma and CSF by NMR and hierarchical models fusion.

Because cerebrospinal fluid (CSF) is the biofluid which interacts most closely with the central nervous system, it holds promise as a reporter of neurological disease, for example multiple sclerosis (MScl). To characterize the metabolomics profile of neuroinflammatory aspects of this disease we studied an animal model of MScl-experimental autoimmune/allergic encephalomyelitis (EAE). Because CSF also exchanges metabolites with blood via the blood-brain barrier, malfunctions occurring in the CNS may be reflected in the biochemical composition of blood plasma. The combination of blood plasma and CSF provides more complete information about the disease. Both biofluids can be studied by use of NMR spectroscopy. It is then necessary to perform combined analysis of the two different datasets. Mid-level data fusion was therefore applied to blood plasma and CSF datasets. First, relevant information was extracted from each biofluid dataset by use of linear support vector machine recursive feature elimination. The selected variables from each dataset were concatenated for joint analysis by partial least squares discriminant analysis (PLS-DA). The combined metabolomics information from plasma and CSF enables more efficient and reliable discrimination of the onset of EAE. Second, we introduced hierarchical models fusion, in which previously developed PLS-DA models are hierarchically combined. We show that this approach enables neuroinflamed rats (even on the day of onset) to be distinguished from either healthy or peripherally inflamed rats. Moreover, progression of EAE can be investigated because the model separates the onset and peak of the disease.