A simple 1H (12C/13C) filtered experiment to quantify and trace isotope enrichment in complex environmental and biological samples.

Nuclear magnetic resonance (NMR) based 13C tracing has broad applications across medical and environmental research. As many biological and environmental samples are heterogeneous, they experience considerable spectral overlap and relatively low signal. Here a 1D 1H-12C/13C is introduced that uses "in-phase/opposite-phase" encoding to simultaneously detect and discriminate both protons attached to 12C and 13C at full 1H sensitivity in every scan. Unlike traditional approaches that focus on the 12C/13C satellite ratios in a 1H spectrum, this approach creates separate sub-spectra for the 12C and 13C bound protons. These spectra can be used for both quantitative and qualitative analysis of complex samples with significant spectral overlap. Due to the presence of the 13C dipole, faster relaxation of the 1H-13C pairs results in slight underestimation compared to the 1H-12C pairs. However, this is easily compensated for, by collecting an additional reference spectrum, from which the absolute percentage of 13C can be calculated by difference. When combined with the result, 12C and 13C percent enrichment in both 1H-12C and 1H-13C fractions are obtained. As the approach uses isotope filtered 1H NMR for detection, it retains nearly the same sensitivity as a standard 1H spectrum. Here, a proof-of-concept is performed using simple mixtures of 12C and 13C glucose, followed by suspended algal cells with varying 12C /13C ratios representing a complex mixture. The results consistently return 12C/13C ratios that deviate less than 1 % on average from the expected. Finally, the sequence was used to monitor and quantify 13C% enrichment in Daphnia magna neonates which were fed a 13C diet over 1 week. The approach helped reveal how the organisms utilized the 12C lipids they are born with vs. the 13C lipids they assimilate from their diet during growth. Given the experiments simplicity, versatility, and sensitivity, we anticipate it should find broad application in a wide range of tracer studies, such as fluxomics, with applications spanning various disciplines.

Brewing alcohol 101: An undergraduate experiment utilizing benchtop NMR for quantification and process monitoring.

In recent years there has been a renewed interest in benchtop NMR. Given their lower cost of ownership, smaller footprint, and ease of use, they are especially suited as an educational tool. Here, a new experiment targeted at upper-year undergraduates and first-year graduate students follows the conversion of D-glucose into ethanol at low-field. First, high and low-field data on D-glucose are compared and students learn both the Hz and ppm scales and how J-coupling is field-independent. The students then acquire their own quantitative NMR datasets and perform the quantification using an Electronic Reference To Access In Vivo Concentration (ERETIC) technique. To our knowledge ERETIC is not currently taught at the undergraduate level, but has an advantage in that internal standards are not required; ideal for following processes or with future use in flow-based benchtop monitoring. Using this quantitative data, students can relate a simple chemical process (fermentation) back to more complex topics such as reaction kinetics, bridging the gaps between analytical and physical chemistry. When asked to reflect on the experiment, students had an overwhelmingly positive experience, citing agreement with learning objectives, ease of understanding the protocol, and enjoyment. Each of the respondents recommended this experiment as a learning tool for others. This experiment has been outlined for other instructors to utilize in their own courses across institutions, with the hope that a continued expansion of low-field NMR will increase accessibility and learning opportunities at the undergraduate level.

Slice through the water-Exploring the fundamental challenge of water suppression for benchtop NMR systems.

Benchtop NMR provides improved accessibility in terms of cost, space, and technical expertise. In turn, this encourages new users into the field of NMR spectroscopy. Unfortunately, many interesting samples in education and research, from beer to whole blood, contain significant amounts of water that require suppression in 1H NMR in order to recover sample information. However, due to the significant reduction in chemical shift dispersion in benchtop NMR systems, the sample signals are much closer to the water resonance compared to those in a corresponding high-field NMR spectrum. Therefore, simply translating solvent suppression experiments intended for high-field NMR instruments to benchtop NMR systems without careful consideration can be problematic. In this study, the effectiveness of several popular water suppression schemes was evaluated for benchtop NMR applications. Emphasis is placed on pulse sequences with no, or few, adjustable parameters making them easy to implement. These fall into two main categories: (1) those based on Pre-SAT including Pre-SAT, PURGE, NOESY-PR, and g-NOESY-PR and (2) those based on binomial inversion including JRS and W5-WATERGATE. Among these schemes, solvent suppression sequences based on Pre-SAT offer a general approach for easy solvent suppression for samples with higher analyte concentrations (sucrose standard and Redbull™). However, for human urine, binomial-like sequences were required. In summary, it is demonstrated that highly efficient water suppression approaches can be implemented on benchtop NMR systems in a simple manner, despite the limited spectral dispersion, further illustrating the potential for widespread implementation of these approaches in education and research.

Low-field, not low quality: 1D simplification, selective detection, and heteronuclear 2D experiments for improving low-field NMR spectroscopy of environmental and biological samples.

Understanding environmental change is challenging and requires molecular-level tools to explain the physicochemical phenomena behind complex processes. Nuclear magnetic resonance (NMR) spectroscopy is a key tool that provides information on both molecular structures and interactions but is underutilized in environmental research because standard "high-field" NMR is financially and physically inaccessible for many and can be overwhelming to those outside of disciplines that routinely use NMR. "Low-field" NMR is an accessible alternative but has reduced sensitivity and increased spectral overlap, which is especially problematic for natural, heterogeneous samples. Therefore, the goal of this study is to investigate and apply innovative experiments that could minimize these challenges and improve low-field NMR analysis of environmental and biological samples. Spectral simplification (JRES, PSYCHE, singlet-only, multiple quantum filters), selective detection (GEMSTONE, DREAMTIME), and heteronuclear (reverse and CH3/CH2/CH-only HSQCs) NMR experiments are tested on samples of increasing complexity (amino acids, spruce resin, and intact water fleas) at-high field (500 MHz) and at low-field (80 MHz). A novel experiment called Doubly Selective HSQC is also introduced, wherein 1H signals are selectively detected based on the 1H and 13C chemical shifts of 1H-13C J-coupled pairs. The most promising approaches identified are the selective techniques (namely for monitoring), and the reverse and CH3-only HSQCs. Findings ultimately demonstrate that low-field NMR holds great potential for biological and environmental research. The multitude of NMR experiments available makes NMR tailorable to nearly any research need, and low-field NMR is therefore anticipated to become a valuable and widely used analytical tool moving forward.

Development of Low-Magnetic Susceptibility Microcoils via 5-Axis Machining for Analysis of Biological and Environmental Samples.

In environmental research, it is critical to understand how toxins impact invertebrate eggs and egg banks, which, due to their tiny size, are very challenging to study by conventional nuclear magnetic resonance (NMR) spectroscopy. Microcoil technology has been extensively utilized to enhance the mass-sensitivity of NMR. In a previous study, 5-axis computer numerical control (CNC) micromilling (shown to be a viable alternative to traditional microcoil production methods) was used to create a prototype copper slotted-tube resonator (STR). Despite the excellent limit of detection (LOD) of the resonator, the quality of the line shape was very poor due to the magnetic susceptibility of the copper resonator itself. This is best solved using magnetic susceptibility-matched materials. In this study, approaches are investigated that improve the susceptibility while retaining the versatility of coil milling. One method involves machining STRs from various copper/aluminum alloys, while the other involves machining ones from an aluminum 2011 alloy and electroplating them with copper. In all cases, combining copper and aluminum to produce resonators resulted in improved line shape and SNR compared to pure copper resonators due to their reduced magnetic susceptibility. However, the copper-plated aluminum resonators showed optimal performance from the devices tested. The enhanced LOD of these STRs allowed for the first 1H-13C heteronuclear multiple quantum coherence (HMQC) of a single intact 13C-labeled Daphnia magna egg (∼4 µg total biomass). This is a key step toward future screening programs that aim to elucidate the toxic processes in aquatic eggs.

Exploring the Potential of Broadband Complementary Metal Oxide Semiconductor Micro-Coil Nuclear Magnetic Resonance for Environmental Research.

With sensitivity being the Achilles' heel of nuclear magnetic resonance (NMR), the superior mass sensitivity offered by micro-coils can be an excellent choice for tiny, mass limited samples such as eggs and small organisms. Recently, complementary metal oxide semiconductor (CMOS)-based micro-coil transceivers have been reported and demonstrate excellent mass sensitivity. However, the ability of broadband CMOS micro-coils to study heteronuclei has yet to be investigated, and here their potential is explored within the lens of environmental research. Eleven nuclei including 7Li, 19F, 31P and, 205Tl were studied and detection limits in the low to mid picomole range were found for an extended experiment. Further, two environmentally relevant samples (a sprouting broccoli seed and a D. magna egg) were successfully studied using the CMOS micro-coil system. 13C NMR was used to help resolve broad signals in the 1H spectrum of the 13C enriched broccoli seed, and steady state free precession was used to improve the signal-to-noise ratio by a factor of six. 19F NMR was used to track fluorinated contaminants in a single D. magna egg, showing potential for studying egg-pollutant interactions. Overall, CMOS micro-coil NMR demonstrates significant promise in environmental research, especially when the future potential to scale to multiple coil arrays (greatly improving throughput) is considered.

Exploring Proton-Only NMR Experiments and Filters for Daphnia In Vivo: Potential and Limitations.

Environmental metabolomics provides insight into how anthropogenic activities have an impact on the health of an organism at the molecular level. Within this field, in vivo NMR stands out as a powerful tool for monitoring real-time changes in an organism's metabolome. Typically, these studies use 2D 13C-1H experiments on 13C-enriched organisms. Daphnia are the most studied species, given their widespread use in toxicity testing. However, with COVID-19 and other geopolitical factors, the cost of isotope enrichment increased ~6-7 fold over the last two years, making 13C-enriched cultures difficult to maintain. Thus, it is essential to revisit proton-only in vivo NMR and ask, "Can any metabolic information be obtained from Daphnia using proton-only experiments?". Two samples are considered here: living and whole reswollen organisms. A range of filters are tested, including relaxation, lipid suppression, multiple-quantum, J-coupling suppression, 2D 1H-1H experiments, selective experiments, and those exploiting intermolecular single-quantum coherence. While most filters improve the ex vivo spectra, only the most complex filters succeed in vivo. If non-enriched organisms must be used, then, DREAMTIME is recommended for targeted monitoring, while IP-iSQC was the only experiment that allowed non-targeted metabolite identification in vivo. This paper is critically important as it documents not just the experiments that succeed in vivo but also those that fail and demonstrates first-hand the difficulties associated with proton-only in vivo NMR.

Targeted Compound Selection with Increased Sensitivity in 13C-Enriched Biological and Environmental Samples Using 13C-DREAMTIME in Both High-Field and Low-Field NMR.

Chemical characterization of complex mixtures by Nuclear Magnetic Resonance (NMR) spectroscopy is challenging due to a high degree of spectral overlap and inherently low sensitivity. Therefore, NMR experiments that reduce overlap and increase signal intensity hold immense potential for the analysis of mixtures such as biological and environmental media. Here, we introduce a 13C version of DREAMTIME (Designed Refocused Excitation And Mixing for Targets In Vivo and Mixture Elucidation) NMR, which, when analyzing 13C-enriched materials, allows the user to selectively detect only the compound(s) of interest and remove all other peaks in a 13C spectrum. Selected peaks can additionally be "focused" into sharp "spikes" to increase sensitivity. 13C-DREAMTIME is first demonstrated at high field strength (500 MHz) with simultaneous selection of eight amino acids in a 13C-enriched cell free amino acid mixture and of six metabolites in an extract of 13C-enriched green algae and demonstrated at low field strength (80 MHz) with a standard solution of 13C-d-glucose and 13C-l-phenylalanine. 13C-DREAMTIME is then applied at high-field to analyze metabolic changes in 13C-enrichedDaphnia magna after exposure to polystyrene "microplastics," as well as at low-field to track fermentation of 13C-d-glucose using wine yeast. Ultimately, 13C-DREAMTIME reduces spectral overlap as only selected compounds are recorded, resulting in the detection of analyte peaks that may otherwise not have been discernable. In combination with focusing, up to a 6-fold increase in signal intensity can be obtained for a given peak. 13C-DREAMTIME is a promising experiment type for future reaction monitoring and for tracking metabolic processes with 13C-enriched compounds.

Personalised progression prediction in patients with monoclonal gammopathy of undetermined significance or smouldering multiple myeloma (PANGEA): a retrospective, multicohort study.

BACKGROUND: Patients with precursors to multiple myeloma are dichotomised as having monoclonal gammopathy of undetermined significance or smouldering multiple myeloma on the basis of monoclonal protein concentrations or bone marrow plasma cell percentage. Current risk stratifications use laboratory measurements at diagnosis and do not incorporate time-varying biomarkers. Our goal was to develop a monoclonal gammopathy of undetermined significance and smouldering multiple myeloma stratification algorithm that utilised accessible, time-varying biomarkers to model risk of progression to multiple myeloma. METHODS: In this retrospective, multicohort study, we included patients who were 18 years or older with monoclonal gammopathy of undetermined significance or smouldering multiple myeloma. We evaluated several modelling approaches for predicting disease progression to multiple myeloma using a training cohort (with patients at Dana-Farber Cancer Institute, Boston, MA, USA; annotated from Nov, 13, 2019, to April, 13, 2022). We created the PANGEA models, which used data on biomarkers (monoclonal protein concentration, free light chain ratio, age, creatinine concentration, and bone marrow plasma cell percentage) and haemoglobin trajectories from medical records to predict progression from precursor disease to multiple myeloma. The models were validated in two independent validation cohorts from National and Kapodistrian University of Athens (Athens, Greece; from Jan 26, 2020, to Feb 7, 2022; validation cohort 1), University College London (London, UK; from June 9, 2020, to April 10, 2022; validation cohort 1), and Registry of Monoclonal Gammopathies (Czech Republic, Czech Republic; Jan 5, 2004, to March 10, 2022; validation cohort 2). We compared the PANGEA models (with bone marrow [BM] data and without bone marrow [no BM] data) to current criteria (International Myeloma Working Group [IMWG] monoclonal gammopathy of undetermined significance and 20/2/20 smouldering multiple myeloma risk criteria). FINDINGS: We included 6441 patients, 4931 (77%) with monoclonal gammopathy of undetermined significance and 1510 (23%) with smouldering multiple myeloma. 3430 (53%) of 6441 participants were female. The PANGEA model (BM) improved prediction of progression from smouldering multiple myeloma to multiple myeloma compared with the 20/2/20 model, with a C-statistic increase from 0·533 (0·480-0·709) to 0·756 (0·629-0·785) at patient visit 1 to the clinic, 0·613 (0·504-0·704) to 0·720 (0·592-0·775) at visit 2, and 0·637 (0·386-0·841) to 0·756 (0·547-0·830) at visit three in validation cohort 1. The PANGEA model (no BM) improved prediction of smouldering multiple myeloma progression to multiple myeloma compared with the 20/2/20 model with a C-statistic increase from 0·534 (0·501-0·672) to 0·692 (0·614-0·736) at visit 1, 0·573 (0·518-0·647) to 0·693 (0·605-0·734) at visit 2, and 0·560 (0·497-0·645) to 0·692 (0·570-0·708) at visit 3 in validation cohort 1. The PANGEA models improved prediction of monoclonal gammopathy of undetermined significance progression to multiple myeloma compared with the IMWG rolling model at visit 1 in validation cohort 2, with C-statistics increases from 0·640 (0·518-0·718) to 0·729 (0·643-0·941) for the PANGEA model (BM) and 0·670 (0·523-0·729) to 0·879 (0·586-0·938) for the PANGEA model (no BM). INTERPRETATION: Use of the PANGEA models in clinical practice will allow patients with precursor disease to receive more accurate measures of their risk of progression to multiple myeloma, thus prompting for more appropriate treatment strategies. FUNDING: SU2C Dream Team and Cancer Research UK.

NMR spectroscopy of wastewater: A review, case study, and future potential.

NMR spectroscopy is arguably the most powerful tool for the study of molecular structures and interactions, and is increasingly being applied to environmental research, such as the study of wastewater. With over 97% of the planet's water being saltwater, and two thirds of freshwater being frozen in the ice caps and glaciers, there is a significant need to maintain and reuse the remaining 1%, which is a precious resource, critical to the sustainability of most life on Earth. Sanitation and reutilization of wastewater is an important method of water conservation, especially in arid regions, making the understanding of wastewater itself, and of its treatment processes, a highly relevant area of environmental research. Here, the benefits, challenges and subtleties of using NMR spectroscopy for the analysis of wastewater are considered. First, the techniques available to overcome the specific challenges arising from the nature of wastewater (which is a complex and dilute matrix), including an examination of sample preparation and NMR techniques (such as solvent suppression), in both the solid and solution states, are discussed. Then, the arsenal of available NMR techniques for both structure elucidation (e.g., heteronuclear, multidimensional NMR, homonuclear scalar coupling-based experiments) and the study of intermolecular interactions (e.g., diffusion, nuclear Overhauser and saturation transfer-based techniques) in wastewater are examined. Examples of wastewater NMR studies from the literature are reviewed and potential areas for future research are identified. Organized by nucleus, this review includes the common heteronuclei (13C, 15N, 19F, 31P, 29Si) as well as other environmentally relevant nuclei and metals such as 27Al, 51V, 207Pb and 113Cd, among others. Further, the potential of additional NMR methods such as comprehensive multiphase NMR, NMR microscopy and hyphenated techniques (for example, LC-SPE-NMR-MS) for advancing the current understanding of wastewater are discussed. In addition, a case study that combines natural abundance (i.e. non-concentrated), targeted and non-targeted NMR to characterize wastewater, along with in vivo based NMR to understand its toxicity, is included. The study demonstrates that, when applied comprehensively, NMR can provide unique insights into not just the structure, but also potential impacts, of wastewater and wastewater treatment processes. Finally, low-field NMR, which holds considerable future potential for on-site wastewater monitoring, is briefly discussed. In summary, NMR spectroscopy is one of the most versatile tools in modern science, with abilities to study all phases (gases, liquids, gels and solids), chemical structures, interactions, interfaces, toxicity and much more. The authors hope this review will inspire more scientists to embrace NMR, given its huge potential for both wastewater analysis in particular and environmental research in general.