Predicting PSR filters by transverse relaxation enhancements

Filtering the NMR Spectra of Mixtures by Coordination to Paramagnetic Cu2

The paramagnetic spin relaxation (PSR) filter allows the selective NMR signal suppression of components in mixtures according to their complexation ability to a paramagnetic ion. It relies on the faster relaxation of nuclei in paramagnetic environments and thus is complementary to classical diffusion and relaxation filters. So far, the PSR filter has established Gd³⁺ as the sole PSR agent, restricting the paramagnetic filtering repertoire. Herein, we present Cu²⁺ as a robust PSR agent with characteristic filtering properties. While Gd³⁺ depends on unspecific ion-pair interactions with anionic components, Cu²⁺ stands out for filtering species via ordered coordination complexes. An evaluation of the paramagnetic effect of Cu²⁺ over more than 50 small molecules and polymers has unveiled different sensitivities to Cu²⁺ (especially high for pyridines, diamines, polyamines, and amino alcohols) and precise filtering conditions for mixtures (¹H, COSY, and HMQC) that were challenged with a test bed of commercial drugs. The advantage of integrating Cu²⁺ and Gd³⁺ for the stepwise PSR filtering of complex mixtures is also shown.

Parahydrogen induced hyperpolarization provides a tool for NMR metabolomics at nanomolar concentrations

Sensitivity enhancement by parahydrogen hyperpolarization allows NMR detection and quantification of hundreds of urinary metabolites at down to nanomolar concentrations.

Fast NMR Screening of Macromolecular Complexes by a Paramagnetic Spin Relaxation Filter

The paramagnetic spin relaxation filter is described for the rapid NMR screening of intermolecular interactions between ligands and macromolecular anionic receptors with large transverse relaxation enhancements (R 2p). The addition of micromolar concentrations of Gd3+ to the mixture produces the immediate broadening/suppression of the NMR signals of interacting species while leaving unaffected those of noncompetitive binders (one-dimensional and two-dimensional experiments). The method is highly sensitive, unveiling interactions that are too weak to generate changes in chemical shifts or relaxation times. It is operationally very simple and hence, it is amenable to ready implementation by nonspecialists. Examples of application such as detecting the formation of interpolymer complexes, cyclodextrin host-guest interactions, and the screening of DNA ligands are included that demonstrate the reliability and broad applicability of the method.

Differential Attenuation of NMR Signals by Complementary Ion-Exchange Resin Beads for De Novo Analysis of Complex Metabolomics Mixtures

A primary goal of metabolomics is the characterization of a potentially very large number of metabolites that are part of complex mixtures. Application to biofluids and tissue samples offers insights into biochemical metabolic pathways and their role in health and disease. 1D ¹ H and 2D ¹³ C-¹ H HSQC NMR spectra are most commonly used for this purpose. They yield quantitative information about each proton of the mixture, but do not tell which protons belong to the same molecule. Interpretation requires the use of NMR spectral databases, which naturally limits these investigations to known metabolites. Here, a new method is presented that uses complementary ion exchange resin beads to differentially attenuate 2D NMR cross-peaks that belong to different metabolites. Based on their characteristic attenuation patterns, cross-peaks could be clustered and assigned to individual molecules, including unknown metabolites with multiple spin systems, as demonstrated for a metabolite model mixture and E. coli cell lysate.

Knowns and unknowns in metabolomics identified by multidimensional NMR and hybrid MS/NMR methods

Metabolomics continues to make rapid progress through the development of new and better methods and their applications to gain insight into the metabolism of a wide range of different biological systems from a systems biology perspective. Customization of NMR databases and search tools allows the faster and more accurate identification of known metabolites, whereas the identification of unknowns, without a need for extensive purification, requires new strategies to integrate NMR with mass spectrometry, cheminformatics, and computational methods. For some applications, the use of covalent and non-covalent attachments in the form of labeled tags or nanoparticles can significantly reduce the complexity of these tasks.

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.

Use of Charged Nanoparticles in NMR-Based Metabolomics for Spectral Simplification and Improved Metabolite Identification

Metabolomics aims at a complete characterization of all metabolites in biological samples in terms of both their identities and concentrations. Because changes of metabolites and their concentrations are a direct reflection of cellular activity, it allows for a better understanding of cellular processes and function to be obtained. Although NMR spectroscopy is routinely applied to complex biological mixtures without purification, overlapping NMR peaks often pose a challenge for the comprehensive and accurate identification of the underlying metabolites. To address this problem, we present a novel nanoparticle-based strategy that differentiates between metabolites based on their electric charge. By adding electrically charged silica nanoparticles to the solution NMR sample, metabolites of opposite charge bind to the nanoparticles and their NMR signals are weakened or entirely suppressed due to peak broadening caused by the slow rotational tumbling of the nanometer-sized nanoparticles. Comparison of the edited with the original spectrum significantly facilitates analysis and reduces ambiguities in the identification of metabolites. This method makes NMR directly sensitive to the detection of molecular charges at constant pH, as demonstrated here both for model mixtures and human urine. The simplicity of the approach should make it useful for a wide range of metabolomics applications.