Compressed NMR: Combining compressive sampling and pure shift NMR techniques

Fast Pure Shift NMR Spectroscopy Using Attention-Assisted Deep Neural Network

Pure shift NMR spectroscopy enables the robust probing on molecular structure and dynamics, benefiting from great resolution enhancements. Despite extensive application landscapes in various branches of chemistry, the long experimental times induced by the additional time dimension generally hinder its further developments and practical deployments, especially for multi-dimensional pure shift NMR. Herein, this study proposes and implements the fast, reliable, and robust reconstruction for accelerated pure shift NMR spectroscopy with lightweight attention-assisted deep neural network. This deep learning protocol allows one to regain high-resolution signals and suppress undersampling artifacts, as well as furnish high-fidelity signal intensities along with the accelerated pure shift acquisition, benefitting from the introduction of the attention mechanism to highlight the spectral feature and information of interest. Extensive results of simulated and experimental NMR data demonstrate that this attention-assisted deep learning protocol enables the effective recovery of weak signals that are almost drown in the serious undersampling artifacts, and the distinction and recognition of close chemical shifts even though using merely 5.4% data, highlighting its huge potentials on fast pure shift NMR spectroscopy. As a result, this study affords a promising paradigm for the AI-assisted NMR protocols toward broader applications in chemistry, biology, materials, and life sciences, and among others.

CTCOSY-JRES: A high-resolution three-dimensional NMR method for unveiling J-couplings

Two-dimensional (2D) J-resolved spectroscopy provides valuable information on J-coupling constants for molecular structure analysis by resolving one-dimensional (1D) spectra. However, it is challenging to decipher the J-coupling connectivity in 2D J-resolved spectra because the J-coupling connectivity cannot be directly provided. In addition, 2D homonuclear correlation spectroscopy (COSY) can directly elucidate molecular structures by tracking the J-coupling connectivity between protons. However, this method is limited by the problem of spectral peak crowding and is only suitable for simple sample systems. To fully understand the intuitive coupling relationship and coupling constant information, we propose a three-dimensional (3D) COSY method called CTCOSY-JRES (Constant-Time COrrelation SpectroscopY and J-REsolved Spectroscopy) in this paper. By combining the J-resolved spectrum with the constant-time COSY technique, a doubly decoupled COSY spectrum can be provided while preserving the J-coupling constant along an additional dimension, ensuring high-resolution analysis of J-coupling connectivity and J-coupling information. Moreover, compression sensing and fold-over correction techniques are introduced to accelerate experimental acquisition. The CTCOSY-JRES method has been successfully validated in a variety of sample systems, including industrial, agricultural, and biopharmaceutical samples, revealing complex coupling interactions and providing deeper insights into the resolution of molecular structures.

Pure-Shift-Based Proton Magnetic Resonance Spectroscopy for High-Resolution Studies of Biological Samples

Proton magnetic resonance spectroscopy (1H MRS) presents a powerful tool for revealing molecular-level metabolite information, complementary to the anatomical insight delivered by magnetic resonance imaging (MRI), thus playing a significant role in in vivo/in vitro biological studies. However, its further applications are generally confined by spectral congestion caused by numerous biological metabolites contained within the limited proton frequency range. Herein, we propose a pure-shift-based 1H localized MRS method as a proof of concept for high-resolution studies of biological samples. Benefitting from the spectral simplification from multiplets to singlet peaks, this method addresses the challenge of spectral congestion encountered in conventional MRS experiments and facilitates metabolite analysis from crowded NMR resonances. The performance of the proposed pure-shift 1H MRS method is demonstrated on different kinds of samples, including brain metabolite phantom and in vitro biological samples of intact pig brain tissue and grape tissue, using a 7.0 T animal MRI scanner. This proposed MRS method is readily implemented in common commercial NMR/MRI instruments because of its generally adopted pulse-sequence modules. Therefore, this study takes a meaningful step for MRS studies toward potential applications in metabolite analysis and disease diagnosis.

Non-uniform sampling of similar NMR spectra and its application to studies of the interaction between alpha-synuclein and liposomes

The accelerated acquisition of multidimensional NMR spectra using sparse non-uniform sampling (NUS) has been widely adopted in recent years. The key concept in NUS is that a major part of the data is omitted during measurement, and then reconstructed using, for example, compressed sensing (CS) methods. CS requires spectra to be compressible, that is, they should contain relatively few "significant" points. The more compressible the spectrum, the fewer experimental NUS points needed in order for it to be accurately reconstructed. In this paper we show that the CS processing of similar spectra can be enhanced by reconstructing only the differences between them. Accurate reconstruction can be obtained at lower sampling levels as the difference is sparser than the spectrum itself. In many situations this method is superior to "conventional" compressed sensing. We exemplify the concept of "difference CS" with one such case-the study of alpha-synuclein binding to liposomes and its dependence on temperature. To obtain information on temperature-dependent transitions between different states, we need to acquire several dozen spectra at various temperatures, with and without the presence of liposomes. Our detailed investigation reveals that changes in the binding modes of the alpha-synuclein ensemble are not only temperature-dependent but also show non-linear behavior in their transitions. Our proposed CS processing approach dramatically reduces the number of NUS points required and thus significantly shortens the experimental time.

Structural analysis of unstable norbixin isomers guided by pure shift nuclear magnetic resonance

We report the analysis of complex samples obtained during the microwave irradiation/heating of norbixin, which has been identified as a potential therapeutic target for age-related macular degeneration (AMD). In this context, identifying the different isomers that are obtained during its degradation is of primary importance. However, this characterization is challenging because, on the one hand, some of these isomers are unstable, and on the other hand, the ¹ H spectra of these isomeric mixtures are poorly resolved. We could successfully apply 1D pure shift experiments to obtain ultrahigh-resolution ¹ H nuclear magnetic resonance (NMR) spectra of the norbixin isomer samples and exploit their information content to analyze complementary 2D NMR data and describe accurately their isomeric composition.

Non-uniform sampling for NOESY? A case study on spiramycin

To date, most nuclear magnetic resonance (NMR)-based 3-D structure determinations of both small molecules and of biopolymers utilize the nuclear Overhauser effect (NOE) via NOESY spectra. The acquisition of high-quality NOESY spectra is a prerequisite for quantitative analysis providing accurate interatomic distances. As the acquisition of NOE build-ups is time-consuming, acceleration of the process by the use of non-uniform sampling (NUS) may seem beneficial; however, the quantitativity of NOESY spectra acquired with NUS has not yet been validated. Herein, NOESY spectra with various extents of NUS have been recorded, artificial NUS spectra with two different sampling schemes created, and by using two different NUS reconstruction algorithms the influence of NUS on the data quality was evaluated. Using statistical analyses, NUS is demonstrated to influence the accuracy of quantitative NOE experiments. The NOE-based distances show an increased error as the sampling density decreases. Weak NOE signals are affected more severely by NUS than more intense ones. The application of NUS with NOESY comes at two major costs: the interatomic distances are determined with lower accuracy and long-range correlations are lost.

Solution-state behaviour of algal mono-uronates evaluated by pure shift and compressive sampling NMR techniques

Sodium salts of the algal uronic-acids, d-mannuronic acid (HManA) and l-guluronic acid (HGulA) have been isolated and characterised in solution by nuclear magnetic resonance (NMR) spectroscopy. A suite of recently-described NMR experiments (including pure shift and compressive sampling techniques) were used to provide confident assignments of the pyranose forms of the two uronic acids at various pD values (from 7.5 to 1.4). The resulting high resolution spectra were used to determine several previously unknown parameters for the two acids, including their pK_a values, the position of their isomeric equilibria, and their propensity to form furanurono-6,3-lactones. For each of the three parameters, comparisons are drawn with the behaviour of the related D-glucuronic (HGlcA) and D-galacturonic acids (HGalA), which have been previously studied extensively. This paper demonstrates how these new NMR spectroscopic techniques can be applied to better understand the properties of polyuronides and uronide-rich macroalgal biomass.

Enhancing Compression Level for More Efficient Compressed Sensing and Other Lessons from NMR Spectroscopy

Modern nuclear magnetic resonance spectroscopy (NMR) is based on two- and higher-dimensional experiments that allow the solving of molecular structures, i.e., determine the relative positions of single atoms very precisely. However, rich chemical information comes at the price of long data acquisition times (up to several days). This problem can be alleviated by compressed sensing (CS)—a method that revolutionized many fields of technology. It is known that CS performs the most efficiently when measured objects feature a high level of compressibility, which in the case of NMR signal means that its frequency domain representation (spectrum) has a low number of significant points. However, many NMR spectroscopists are not aware of the fact that various well-known signal acquisition procedures enhance compressibility and thus should be used prior to CS reconstruction. In this study, we discuss such procedures and show to what extent they are complementary to CS approaches. We believe that the survey will be useful not only for NMR spectroscopists but also to inspire the broader signal processing community.

Coherence transfer delay optimisation in PSYCOSY experiments

PSYCOSY is an f1 broadband homonuclear decoupled version of the COSY nuclear magnetic resonance pulse sequence. Here, we investigate by a combination of experimental measurements, spatially distributed spin dynamics simulations, and analytical predictions the coherence evolution delay necessary in PSYCOSY experiments to ensure intensity discrimination in favour of the correlations typically arising from short range (ⁿ J, n ≤ 3) ¹ H-¹ H couplings and show that, in general, a coherence evolution delay of around 35 ms is optimum.