Progress Towards a Higher Sensitivity 13C-Optimized 1.5 mm HTS NMR Probe

Optimization of RF coil geometry for NMR/MRI applications using a genetic algorithm

A simulation method that employs a genetic algorithm (GA) for optimizing radio frequency (RF) coil geometry is developed to maximize signal intensity in nuclear magnetic resonance (NMR)/magnetic resonance imaging (MRI) applications. NMR/MRI has a wide range of applications, including medical imaging, and chemical and biological analysis to investigate the structure, dynamics, and interactions of molecules. However, NMR suffers from inherently low signal intensity, which depends on factors related to RF coil geometry. The investigation of coil geometry is crucial for improving signal intensity, leading to a reduction in the number of scans and a shorter total scan time. We have explored a better optimization method by modifying RF coil geometry to maximize signal intensity. The RF coil geometry comprises wire elements, each of which is a small vector representing the current flow, and GA chooses some of the prepared wire elements for optimization. The optimization of a substrate coil with a surface perpendicular to a static field was demonstrated for single-sided NMR system applications while considering various cylindrical sample diameters. A non-optimized and a GA-optimized substrate coil were compared through simulation and experiment to confirm the performance of the GA simulation. The maximum error between simulation and experiment was below 5%, with an average of less than 3%, confirming simulation reliability. The results indicated that the GA improved signal intensity by approximately 10% and reduced the necessary total scan time by around 20%. Finally, we explain the limitations and explore other potential applications of this GA-based simulation method.

New unifying metric for NMR/MRI probe evaluation based on optimized solenoid coil geometry

A three-dimensional numerical simulation of the magnetic field distribution and Bloch equations for arbitrary radio frequency (RF) coils is developed and compared against nuclear magnetic resonance (NMR) experimental results to evaluate the NMR signal intensity. Because NMR is inherently insensitive and its signal intensity is dependent on RF coil geometry, the investigation of RF coil geometry to maximize signal intensity for a given sample volume is important for improving the signal-to-noise ratio (SNR) and shortening the accumulation time. The developed simulation can optimize the RF coil geometry, specifically a single-layer solenoid coil with a constant winding pitch, and the result of the solenoid coil simulation serves as a new unifying metric for evaluating NMR/MRI probes. It is found that the most efficient sample aspect ratio (ratio of sample length to sample diameter) and pitch to wire diameter ratio for the highest signal intensity are around 2.2 and 1.65, respectively. Some discrepancies from the solenoid coil geometry ratios for higher signal intensity in previous studies can be explained by the difference in the gap between the inner diameter of the solenoid coil and the sample diameter. These results are confirmed through NMR signal intensity expressed in voltages with three approaches: 3D simulation, experiment, and estimation based on probe parameters. The simulated signal intensity shows a maximum error of approximately 5 % and an average error of 1 % when compared to the experimental results. This result suggests that the developed methods hold the potential for application in quantitative NMR (qNMR) without relying on standard reference materials. Finally, this study introduces a standardized geometry for the optimized solenoid coil for higher signal intensity and uses it to establish an evaluation metric called the signal-to-optimized-solenoid-signal ratio (3SR). The 3SR addresses the volume-dependence problem in conventional metrics like SNR and SNR per sample volume. It provides a standardized approach for the unified evaluation of all RF coils and probe designs, regardless of sample volume and measurement frequency. Therefore, 3SR can be utilized as a useful metric in the search for optimal coil geometry, while metrics such as SNR or SNR per sample volume are currently used for such purpose. This metric is expected to be useful for NMR/magnetic resonance imaging (MRI) users and developers.

13C NMR metabolomics: J-resolved STOCSY meets INADEQUATE

Robust annotation of metabolites is a challenging task in metabolomics. Among available applications, ¹³C NMR experiment INADEQUATE determines direct ¹³C-¹³C connectivity unambiguously, offering indispensable information on molecular structure. Despite its great utility, it is not always practical to collect INADEQUATE data on every sample in a large metabolomics study because of its relatively long experiment time. Here, we propose an alternative approach that maintains the quality of information but saves experiment time. In this approach, individual samples in a study are first screened by ¹³C homonuclear J-resolved experiment (JRES). Next, JRES data are processed by statistical total correlation spectroscopy (STOCSY) to extract peaks that behave similarly among samples. Finally, INADEQUATE is collected on one internal pooled sample to select STOCSY peaks that originate from the same compound. We tested this concept using the ¹³C-labeled endometabolome of a model marine diatom strain incubated under various settings, intending to cover a range of metabolites produced under different external conditions. This scheme was able to extract known diatom metabolites proline, 2,3-dihydroxypropane-1-sulfonate (DHPS), β-1,3-glucan, choline, and glutamate. This pipeline also detected unknown compounds with structural information, which is valuable in metabolomics where a priori knowledge of metabolites is not always available. The ability of this scheme was seen even in sugar regions, which are usually challenging in ¹H NMR due to severe peak overlap. JRES and INADEQUATE were highly complementary; INADEQUATE provided directly-bonded ¹³C networks, whereas JRES linked INADEQUATE networks within the same compound but broken by nitrogen or sulfur atoms, highlighting the advantage of this integrated approach.

Metabolomics in Cell Biology

Metabolomics has long been used in a biomedical context. The most typical samples are body fluids in which small molecules can be detected and quantified using technologies such as Nuclear Magnetic Resonance (NMR) and Mass Spectrometry (MS). Many studies, in particular in the wider field of cancer research, are based on cellular models. Different cancer cells can have vastly different ways of regulating metabolism and responses to drug treatments depend on specific metabolic mechanisms which are often cell type specific. This has led to a series of publications using metabolomics to study metabolic mechanisms. Cell-based metabolomics has specific requirements and allows for interesting approaches where metabolism is followed in real-time. Here applications of metabolomics in cell biology have been reviewed, providing insight into specific technologies used and showing exemplary case studies with an emphasis towards applications which help to understand drug mechanisms.

NMR methods for the analysis of mixtures

NMR spectroscopy is a powerful approach for the analysis of mixtures. Its usefulness arises in large part from the vast landscape of methods, and corresponding pulse sequences, that have been and are being designed to tackle the specific properties of mixtures of small molecules. This feature article describes a selection of methods that aim to address the complexity, the low concentrations, and the changing nature that mixtures can display. These notably include pure-shift and diffusion NMR methods, hyperpolarisation methods, and fast 2D NMR methods such as ultrafast 2D NMR and non-uniform sampling. Examples or applications are also described, in fields such as reaction monitoring and metabolomics, to illustrate the relevance and limitations of different methods.

Implementing High Q-Factor HTS Resonators to Enhance Probe Sensitivity in 13C NMR Spectroscopy

Nuclear magnetic resonance spectroscopy (NMR) probes using thin-film high temperature superconducting (HTS) resonators provide exceptional mass sensitivity in small-sample NMR experiments for natural products chemistry and metabolomics. We report improvements in sensitivity to our 1.5 mm 13C-optimized NMR probe based on HTS resonators. The probe has a sample volume of 35 microliters and operates in a 14.1 T magnet. The probe also features HTS resonators for 1H transmission and detection and the 2H lock. The probe utilizes a 13C resonator design that provides greater efficiency than our previous design. The quality factor of the new resonator in the 14.1 T background field was measured to be 4,300, which is over 3x the value of the previous design. To effectively implement the improved quality factor, we demonstrate the effect of adding a shorted transmission line stub to increase the bandwidth and reduce the rise/fall time of 13C irradiation pulses. Initial NMR measurements verify 13C NMR sensitivity is significantly improved while preserving detection bandwidth. The probe will be used for applications in metabolomics.

NMR and Metabolomics-A Roadmap for the Future

Metabolomics investigates global metabolic alterations associated with chemical, biological, physiological, or pathological processes. These metabolic changes are measured with various analytical platforms including liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS) and nuclear magnetic resonance spectroscopy (NMR). While LC-MS methods are becoming increasingly popular in the field of metabolomics (accounting for more than 70% of published metabolomics studies to date), there are considerable benefits and advantages to NMR-based methods for metabolomic studies. In fact, according to PubMed, more than 926 papers on NMR-based metabolomics were published in 2021-the most ever published in a given year. This suggests that NMR-based metabolomics continues to grow and has plenty to offer to the scientific community. This perspective outlines the growing applications of NMR in metabolomics, highlights several recent advances in NMR technologies for metabolomics, and provides a roadmap for future advancements.

Application of Counter-wound Multi-arm Spirals in HTS Resonator Design

Significant sensitivity improvements have been achieved by utilizing high temperature superconducting (HTS) resonators in nuclear magnetic resonance (NMR) probes. Many nuclei such as 13C benefit from strong excitation fields which cannot be produced by traditional HTS resonator designs. We investigate the use of double-sided, counter-wound multi-arm spiral HTS resonators with the aim of increasing the excitation field at the required nuclear Larmor frequency for 13C. When compared to double-sided, counter-wound spiral resonators with similar geometry, simulations indicate that the multi-arm spiral version develops a more uniform current distribution. Preliminary tests of a two-arm resonator indicate that it may produce a stronger excitation field.