2D and 3D maximum-quantum NMR and diffusion spectroscopy for the characterization of enzymatic reaction mixtures.

1D 1H NMR spectroscopy has been widely used to monitor enzymatic activity by recording the evolution of the spectra of substrates and/or products, thanks to the linear response of NMR. For complex systems involving the coexistence of multiple compounds (substrate, final product and various intermediates), the identification and quantification can be a more arduous task. Here, we present a simple analytical method for the rapid characterization of reaction mixtures involving enzymatic complexes using Maximum Quantum (MaxQ) NMR, accelerated with the Non-Uniform Sampling (NUS) acquisition procedure. Specifically, this approach enables, in the first analytical step, the counting of the molecules present in the samples. We also show, using two different enzymatic systems, that the implementation of these pulse sequences implies precautions related to the short relaxation times due to the presence of metallo-enzymes or paramagnetic catalysts. Finally, the combination of MaxQ and diffusion experiments, which leads to a 3D chart, greatly improves the resolution and offers an extreme simplification of the spectra while giving valuable indications on the affinity of the enzymes to the different compounds present in the reaction mixture.

Evaluation of the Rotating-Frame Relaxation (T1ρ) Filter and Its Application in Metabolomics as an Alternative to the Transverse Relaxation (T2) Filter.

Nuclear magnetic resonance (NMR)-based metabolomic studies commonly involve the use of T2 filter pulse sequences to eliminate or attenuate the broad signals from large molecules and improve spectral resolution. In this paper, we demonstrate that the T1ρ filter-based pulse sequence represents an interesting alternative because it allows the stability and the reproducibility needed for statistical analysis. The integrity of the samples and the stability of the instruments were assessed for different filter durations and amplitudes. We showed that the T1ρ filter pulse sequence did not induce sample overheating for a filter duration of up to 500 ms. The reproducibility was evaluated and compared with the T2 filter in serum and liver samples. The implementation is relatively simple and provides the same statistical and analytical results as those obtained with the standard filters. Regarding tissues analysis, because the duration of the filter is the same as that of the spin-lock, the synchronization of the echo delays with the magic angle spinning (MAS) rate is no longer necessary as for T2 filter-based sequences. The results presented in this article aim at establishing a new protocol to improve metabolomic studies and pave the way for future developments on T1ρ alternative filters, in liquid and HR-MAS NMR experiments.

Challenges in the decomposition of 2D NMR spectra of mixtures of small molecules.

Analytical methods for mixtures of small molecules require specificity (is a certain molecule present in the mix?) and speciation capabilities. NMR spectroscopy has been a tool of choice for both of these issues since its early days, due to its quantitative (linear) response, sufficiently high resolving power and capabilities of inferring molecular structures from spectral features (even in the absence of a reference database). However, the analytical performances of NMR spectroscopy are being stretched by the increased complexity of the samples, the dynamic range of the components, and the need for a reasonable turnover time. One approach that has been actively pursued for disentangling the composition complexity is the use of 2D NMR spectroscopy. While any of the many experiments from this family will increase the spectral resolution, some are more apt for mixtures, as they are capable of unveiling signals belonging to whole molecules or fragments of it. Among the most popular ones, one can enumerate HSQC-TOCSY, DOSY and Maximum-Quantum (MaxQ) NMR spectroscopy. For multicomponent samples, the development of robust mathematical methods of signal decomposition would provide a clear edge towards identification. We have been pursuing, along these lines, Blind Source Separation (BSS). Here, the un-mixing of the spectra is achieved relying on correlations detected on a series of datasets. The series could be associated with samples of different relative composition or in a classically acquired 2D experiment by the mathematical laws underlying the construction of the indirect dimension, the one not recorded by the spectrometer. Many algorithms have been proposed for BSS in NMR spectroscopy since the seminal work of Nuzillard. In this paper, we use rather standard algorithms in BSS in order to disentangle NMR spectra. We show on simulated data (both 1D and 2D HSQC) that these approaches enable us to accurately disentangle multiple components, and provide good estimates for the concentrations of compounds. Furthermore, we show that after proper realignment of the signals, the same algorithms are able to disentangle real 1D NMR spectra. We obtain similar results on 2D HSQC spectra, where the BSS algorithms are able to successfully disentangle components, and provide even better estimates for concentrations.