In-Vivo NMR Spectroscopy: A Powerful and Complimentary Tool for Understanding Environmental Toxicity

Exploration of Materials for Three-Dimensional NMR Microcoil Production via CNC Micromilling and Laser Etching

The excellent versatility of 5-axis computer numerical control (CNC) micromilling has led to its application for prototyping NMR microcoils tailored to mass-limited samples (reducing development time and cost). However, vibrations during 5-axis milling can hinder the creation of complex 3D volume microcoils (i.e., solenoids and saddle coils). To address these limitations, a high-resolution NSCNC ELARA 4-axis milling machine was developed with the extra precision required for making complex 3D volume microcoils. Upon investigating the performance of resonators made with various copper-coated dielectrics, resonators with poly(methyl methacrylate) (PMMA) provided the best SNR/line shape. Thus, complex 1.7 mm microcoil designs were machined from Cu-coated PMMA. A milled 6.4 mm solenoid also provided 6.6× the total carbon signal for a 13C-labeled broccoli seed compared to a commercial inverse 5 mm NMR probe (demonstrating potential for larger coil designs). However, the manufacture of coils <1.7 mm with copper-coated PMMA rods was challenging as ∼0.5 mm of remaining PMMA was needed to retain their structural integrity. To manufacture smaller microcoils, both a solenoid and saddle coil (both with 1 mm O.D., 0.1 mm thick walls) were etched from Cu-coated glass capillaries using a UV picosecond laser that was mounted onto an NSCNC 5-axis MiRA7L. Both resonators showed excellent signal and identified a wide range of metabolites in a 13C-labeled algae extract, while the solenoid was further tested on two copepod egg sacs (∼4 μg of total sample). In summary, the flexibility to prototype complex microcoils in-house allows laboratories to tailor microcoils to specific mass-limited samples while avoiding the costs of cleanrooms.

Development of a Simple Cost Effective Oxygenation System for In Vivo Solution State NMR in 10 mm NMR Tubes

In vivo NMR is evolving into an important tool to understand biological processes and environmental responses. Current approaches use flow systems to sustain the organisms with oxygenated water and food (e.g., algae) inside the NMR. However, such systems have the potential to leak and clog (potentially damaging costly hardware), require large volumes of media, and multiple expensive HPLC pumps. The proposed "oxygenation system", uses a simple "double slit" adapter and a single air/oxygen flow line into the NMR. The design is especially suited to larger diameter probes given that standard flow systems would require higher flow rates thus amplifying the potential and impact of leaks/clogs. Traditionally, in vivo NMR of small organisms (e.g., Daphnia) have required 2D NMR in combination with 13C enrichment to overcome susceptibility distortions and provide information rich metabolic profiles. Here Daphnia magna, Eisenia fetida and Artemia franciscana are used to demonstrate the potential of the oxygenation system. Survivability tests and 1H time-resolved monitoring were first performed on D. magna, while E. fetida contained enough biomass to permit 1H-13C HSQC, 13C-1H HETCOR and 31P NMR without isotopic enrichment. Finally, STOCSY of 1D 13C NMR was used to follow the growth of A. franciscana (without 13C enrichment) for 48 h after birth, which helps visualize trends across a series of 1D in vivo data. In summary, application of the oxygenation system toward larger diameter probes allows the collection of NMR data without enrichment, offering a promising solution to better understand processes in vivo.

Effects of nasal allergens and environmental particulate matter on brainstem metabolites and the consequence of brain-spleen axis in allergic rhinitis

BACKGROUND

The growing consensus links exposure to fine particulate matter (PM2.5) with an increased risk of respiratory diseases. However, little is known about the additional effects of particulate matter on brainstem function in allergic rhinitis (AR). Furthermore, it is unknown to what extent the PM2.5-induced effects in the brainstem affect the inflammatory response in AR. This study aimed to determine the effects, mechanisms and consequences of brainstem neural activity altered by allergenic stimulation and PM2.5 exposure.

METHODS

Using an AR model of ovalbumin (OVA) elicitation and whole-body PM2.5 exposure, the metabolic profile of the brainstem post-allergen stimulation was characterized through in vivo proton magnetic resonance imaging (1H-MRS). Then, the transient receptor potential vanilloid-1 (TRPV1) neuronal expression and sensitivity in the trigeminal nerve in AR were investigated. The link between TRPV1 expression and brainstem differential metabolites was also determined. Finally, we evaluated the mediating effects of brainstem metabolites and the consequences in the brain-spleen axis in the inflammatory response of AR.

RESULTS

Exposure to allergens and PM2.5 led to changes in the metabolic profiles of the brainstem, particularly affecting levels of glutamine (Gln) and glutamate (Glu). This exposure also increased the expression and sensitivity of TRPV1+ neurons in the trigeminal nerve, with the levels of TRPV1 expression closely linked to the brainstem metabolism of Glu and Gln. Moreover, allergens increased the activity of p38, while PM2.5 led to the phosphorylation of p38 and ERK, resulting in the upregulation of TRPV1 expression. The brainstem metabolites Glu and Gln were found to partially mediate the impact of TRPV1 on AR inflammation, which was supported by the presence of pro-inflammatory changes in the brain-spleen axis.

CONCLUSION

Brainstem metabolites are altered under allergen stimulation and additional PM2.5 exposure in AR via sensitization of the trigeminal nerve, which exacerbates the inflammatory response via the brain-splenic axis.

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.

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.

SAND: Automated Time-Domain Modeling of NMR Spectra Applied to Metabolite Quantification

Developments in untargeted nuclear magnetic resonance (NMR) metabolomics enable the profiling of thousands of biological samples. The exploitation of this rich source of information requires a detailed quantification of spectral features. However, the development of a consistent and automatic workflow has been challenging because of extensive signal overlap. To address this challenge, we introduce the software Spectral Automated NMR Decomposition (SAND). SAND follows on from the previous success of time-domain modeling and automatically quantifies entire spectra without manual interaction. The SAND approach uses hybrid optimization with Markov chain Monte Carlo methods, employing subsampling in both time and frequency domains. In particular, SAND randomly divides the time-domain data into training and validation sets to help avoid overfitting. We demonstrate the accuracy of SAND, which provides a correlation of ∼0.9 with ground truth on cases including highly overlapped simulated data sets, a two-compound mixture, and a urine sample spiked with different amounts of a four-compound mixture. We further demonstrate an automated annotation using correlation networks derived from SAND decomposed peaks, and on average, 74% of peaks for each compound can be recovered in single clusters. SAND is available in NMRbox, the cloud computing environment for NMR software hosted by the Network for Advanced NMR (NAN). Since the SAND method uses time-domain subsampling (i.e., random subset of time-domain points), it has the potential to be extended to a higher dimensionality and nonuniformly sampled data.

Cutting without a Knife: A Slice-Selective 2D 1H-13C HSQC NMR Sequence for the Analysis of Inhomogeneous Samples

Nuclear magnetic resonance (NMR) is a powerful technique with applications ranging from small molecule structure elucidation to metabolomics studies of living organisms. Typically, solution-state NMR requires a homogeneous liquid, and the whole sample is analyzed as a single entity. While adequate for homogeneous samples, such an approach is limited if the composition varies as would be the case in samples that are naturally heterogeneous or layered. In complex samples such as living organisms, magnetic susceptibility distortions lead to broad 1H line shapes, and thus, the additional spectral dispersion afforded by 2D heteronuclear experiments is often required for metabolite discrimination. Here, a novel, slice-selective 2D, 1H-13C heteronuclear single quantum coherence (HSQC) sequence was developed that exclusively employs shaped pulses such that only spins in the desired volume are perturbed. In turn, this permits multiple volumes in the tube to be studied during a single relaxation delay, increasing sensitivity and throughput. The approach is first demonstrated on standards and then used to isolate specific sample/sensor elements from a microcoil array and finally study slices within a living earthworm, allowing metabolite changes to be discerned with feeding. Overall, slice-selective NMR is demonstrated to have significant potential for the study of layered and other inhomogeneous samples of varying complexity. In particular, its ability to select subelements is an important step toward developing microcoil receive-only arrays to study environmental toxicity in tiny eggs, cells, and neonates, whereas localization in larger living species could help better correlate toxin-induced biochemical responses to the physical localities or organs involved.

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 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.

Xanthine-derived reactive oxygen species exacerbates adipose tissue disorders in male db/db mice induced by real-ambient PM2.5 exposure

Epidemiological and experimental data have associated exposure to fine particulate matter (PM2.5) with various metabolic dysfunctions and diseases, including overweight and type 2 diabetes. Adipose tissue is an energy pool for storing lipids, a necessary regulator of glucose homeostasis, and an active endocrine organ, playing an essential role in developing various related diseases such as diabetes and obesity. However, the molecular mechanisms underlying PM2.5-impaired functions in adipose tissue have rarely been explored. In this work, metabolomics based on liquid chromatography-mass spectrometry was performed to study the adverse impacts of PM2.5 exposure on brown adipose tissue (BAT) and white adipose tissue (WAT) in the diabetic mouse model. We found the effects of PM2.5 exposure by comparing the different metabolites in both adipose tissues of male db/db mice using real-ambient PM2.5 exposure. The results showed that PM2.5 exposure changed the purine metabolism in mice, especially the dramatic increase of xanthine content in both WAT and BAT. These changes led to significant oxidative stress. Then the results from real-time quantitative polymerase chain reaction showed that PM2.5 exposure could cause the production of inflammatory factors in both adipose tissues. Moreover, the increased reactive oxygen species (ROS) promoted triglyceride accumulation in WAT and inhibited its decomposition, causing increased WAT content in db/db mice. In addition, PM2.5 exposure significantly suppressed thermogenesis and affected energy metabolism in the BAT of male db/db mice, which may deteriorate insulin sensitivity and blood glucose regulation. This research demonstrated the impact of PM2.5 on the adipose tissue of male db/db mice, which may be necessary for public health.

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.

In vivo singlet state filtered nuclear magnetic resonance: towards monitoring toxic responses inside living organisms

In line with recent paradigm shifts in toxicity testing, in vivo nuclear magnetic resonance (NMR) is a powerful tool for studying the biological impacts and perturbations caused by toxicants in living organisms. However, despite the excellent molecular insights that can be obtained through this technique, in vivo NMR applications are hampered by considerable experimental challenges such as poor line shape and spectral overlap. Here, we demonstrate the application of singlet-filtered NMR to target specific metabolites and facilitate the study of metabolite fluxes in living Daphnia magna, an aquatic keystone species and model organism. Informed by mathematical simulations and experiments on ex vivo organisms, singlet state NMR is used to monitor the flux of metabolites such as d-glucose and serine in living D. magna, during the environmentally relevant processes of anoxic stress and reduced food availability. Overall, singlet state NMR is shown to have significant future potential for studying metabolic processes in vivo.

Lenz Lenses in a Cryoprobe: Boosting NMR Sensitivity Toward Environmental Monitoring of Mass-Limited Samples

Nuclear magnetic resonance (NMR) spectroscopy is commonly employed in a wide range of metabolomic research. Unfortunately, due to its relatively low sensitivity, smaller samples become challenging to study by NMR. Cryoprobes can be used to increase sensitivity by cooling the coil and preamplifier, offering sensitivity improvements of ∼3 to 4x. Alternatively, microcoils can be used to increase mass sensitivity by improving sample filling and proximity, along with decreased electrical resistance. Unfortunately, combining the two approaches is not just technically challenging, but as the coil decreases, so does its thermal fingerprint, reducing the advantage of cryogenic cooling. Here, an alternative solution is proposed in the form of a Lenz lens inside a cryoprobe. Rather than replacing the detection coil, Lenz lenses allow the B₁ field from a larger coil to be refocused onto a much smaller sample area. In turn, the stronger B₁ field at the sample provides strong coupling to the cryocoil, improving the signal. By combining a 530 I.D. Lenz lens with a cryoprobe, sensitivity was further improved by 2.8x and 3.5x for ¹H and ¹³C, respectively, over the cryoprobe alone for small samples. Additionally, the broadband nature of the Lenz lenses allowed multiple nuclei to be studied and heteronuclear two-dimensional (2D) NMR approaches to be employed. The sensitivity improvements and 2D capabilities are demonstrated on 430 nL of hemolymph and eight eggs (∼350 μm O.D.) from the model organismDaphnia magna. In summary, combining Lenz lenses with cryoprobes offers a relatively simple approach to boost sensitivity for tiny samples while retaining cryoprobe advantages.

Metabolomics and modelling approaches for systems metabolic engineering

Metabolic engineering involves the manipulation of microbes to produce desirable compounds through genetic engineering or synthetic biology approaches. Metabolomics involves the quantitation of intracellular and extracellular metabolites, where mass spectrometry and nuclear magnetic resonance based analytical instrumentation are often used. Here, the experimental designs, sample preparations, metabolite quenching and extraction are essential to the quantitative metabolomics workflow. The resultant metabolomics data can then be used with computational modelling approaches, such as kinetic and constraint-based modelling, to better understand underlying mechanisms and bottlenecks in the synthesis of desired compounds, thereby accelerating research through systems metabolic engineering. Constraint-based models, such as genome scale models, have been used successfully to enhance the yield of desired compounds from engineered microbes, however, unlike kinetic or dynamic models, constraint-based models do not incorporate regulatory effects. Nevertheless, the lack of time-series metabolomic data generation has hindered the usefulness of dynamic models till today. In this review, we show that improvements in automation, dynamic real-time analysis and high throughput workflows can drive the generation of more quality data for dynamic models through time-series metabolomics data generation. Spatial metabolomics also has the potential to be used as a complementary approach to conventional metabolomics, as it provides information on the localization of metabolites. However, more effort must be undertaken to identify metabolites from spatial metabolomics data derived through imaging mass spectrometry, where machine learning approaches could prove useful. On the other hand, single-cell metabolomics has also seen rapid growth, where understanding cell-cell heterogeneity can provide more insights into efficient metabolic engineering of microbes. Moving forward, with potential improvements in automation, dynamic real-time analysis, high throughput workflows, and spatial metabolomics, more data can be produced and studied using machine learning algorithms, in conjunction with dynamic models, to generate qualitative and quantitative predictions to advance metabolic engineering efforts.

Exploring the Applications of Carbon-Detected NMR in Living and Dead Organisms Using a 13C-Optimized Comprehensive Multiphase NMR Probe

Comprehensive multiphase-nuclear magnetic resonance (CMP-NMR) is a non-invasive approach designed to observe all phases (solutions, gels, and solids) in intact samples using a single NMR probe. Studies of dead and living organisms are important to understand processes ranging from biological growth to environmental stress. Historically, such studies have utilized ¹H-based phase editing for the detection of soluble/swollen components and ¹H-detected 2D NMR for metabolite assignments/screening. However, living organisms require slow spinning rates (∼500 Hz) to increase survivability, but at such low speeds, complications from water sidebands and spectral overlap from the modest chemical shift window (∼0-10 ppm) make ¹H NMR challenging. Here, a novel ¹³C-optimized E-Free magic angle spinning CMP probe is applied to study all phases in ex vivo and in vivo samples. This probe consists of a two-coil design, with an inner single-tuned ¹³C coil providing a 113% increase in ¹³C sensitivity relative to a traditional multichannel single-CMP coil design. For organisms with a large biomass (∼0.1 g) like the Ganges River sprat (ex vivo), ¹³C-detected full spectral editing and ¹³C-detected heteronuclear correlation (HETCOR) can be performed at natural abundance. Unfortunately, for a single living shrimp (∼2 mg), ¹³C enrichment was still required, but ¹³C-detected HETCOR shows superior data relative to heteronuclear single-quantum coherence at low spinning speeds (due to complications from water sidebands in the latter). The probe is equipped with automatic-tuning-matching and is compatible with automated gradient shimming─a key step toward conducting multiphase screening of dead and living organisms under automation in the near future.

Inorganic phosphate in growing calcium carbonate abalone shell suggests a shared mineral ancestral precursor

The presence of phosphate from different origins (inorganic, bioorganic) is found more and more in calcium carbonate-based biominerals. Phosphate is often described as being responsible for the stabilization of the transient amorphous calcium carbonate phase. In order to specify the composition of the mineral phase deposited at the onset of carbonated shell formation, the present study investigates, down to the nanoscale, the growing shell from the European abalone Haliotis tuberculata, using a combination of solid state nuclear magnetic resonance, scanning transmission electron microscope and spatially-resolved electron energy loss spectroscopy techniques. We show the co-occurrence of inorganic phosphate with calcium and carbonate throughout the early stages of abalone shell formation. One possible hypothesis is that this first-formed mixed mineral phase represents the vestige of a shared ancestral mineral precursor that appeared early during Evolution. In addition, our findings strengthen the idea that the final crystalline phase (calcium carbonate or phosphate) depends strongly on the nature of the mineral-associated proteins in vivo.

Phosphate involvement in calcium carbonate biominerals raises questions on biomineralisation pathways. Here, the authors explore the presence of phosphate in the growing shell of the European abalone and suggest a shared mixed mineral ancestral precursor with final crystal phase being selected by mineral-associated proteins.

Marine Dissolved Organic Matter Shares Thousands of Molecular Formulae Yet Differs Structurally across Major Water Masses

Most oceanic dissolved organic matter (DOM) is still not fully molecularly characterized. We combined high-field nuclear magnetic resonance (NMR) and ultrahigh-resolution mass spectrometry (Fourier-transform ion cyclotron resonance mass spectrometry, FT-ICR-MS) for the structural and molecular formula-level characterization of solid-phase extracted (SPE) DOM from surface, mesopelagic, and bathypelagic Atlantic and Pacific Ocean samples. Using a MicroCryoProbe, unprecedented low amounts of SPE-DOM (∼1 mg carbon) were sufficient for two-dimensional NMR analysis. Low proportions of olefinic and aromatic relative to aliphatic and carboxylated structures (NMR) at the sea surface were likely related to photochemical transformations. This was consistent with lower molecular masses and higher degrees of saturation and oxygenation (FT-ICR-MS) compared to those of the deep sea. Carbohydrate structures in the mesopelagic North Pacific Ocean suggest export and release from sinking particles. In our sample set, the universal molecular DOM composition, as captured by FT-ICR-MS, appears to be structurally more diverse when analyzed by NMR, suggesting DOM variability across oceanic provinces to be more pronounced than previously assumed. As a proof of concept, our study takes advantage of new complementary approaches resolving thousands of structural and molecular DOM features while applying reasonable instrument times, allowing for the analysis of large oceanic data sets to increase our understanding of marine DOM biogeochemistry.

NMR spectroscopy of a single mammalian early stage embryo

The resolving power, chemical sensitivity and non-invasive nature of NMR have made it an established technique for in vivo studies of large organisms both for research and clinical applications. NMR would clearly be beneficial for analysis of entities at the microscopic scale of about 1 nL (the nanoliter scale), typical of early development of mammalian embryos, microtissues and organoids: the scale where the building blocks of complex organisms could be observed. However, the handling of such small samples (about 100 µm) and sensitivity issues have prevented a widespread adoption of NMR. In this article we show how these limitations can be overcome to obtain NMR spectra of a mammalian embryo in its early stage. To achieve this we employ ultra-compact micro-chip technologies in combination with 3D-printed micro-structures. Such device is packaged for use as plug & play sensor and it shows sufficient sensitivity to resolve NMR signals from individual bovine pre-implantation embryos. The embryos in this study are obtained through In Vitro Fertilization (IVF) techniques, transported cryopreserved to the NMR laboratory, and measured shortly after thawing. In less than 1 h these spherical samples of just 130-190 µm produce distinct spectral peaks, largely originating from lipids contained inside them. We further observe how the spectra vary from one sample to another despite their optical and morphological similarities, suggesting that the method can further develop into a non-invasive embryo assay for selection prior to embryo transfer.

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.

The exposome paradigm to predict environmental health in terms of systemic homeostasis and resource balance based on NMR data science

The environment, from microbial ecosystems to recycled resources, fluctuates dynamically due to many physical, chemical and biological factors, the profile of which reflects changes in overall state, such as environmental illness caused by a collapse of homeostasis. To evaluate and predict environmental health in terms of systemic homeostasis and resource balance, a comprehensive understanding of these factors requires an approach based on the "exposome paradigm", namely the totality of exposure to all substances. Furthermore, in considering sustainable development to meet global population growth, it is important to gain an understanding of both the circulation of biological resources and waste recycling in human society. From this perspective, natural environment, agriculture, aquaculture, wastewater treatment in industry, biomass degradation and biodegradable materials design are at the forefront of current research. In this respect, nuclear magnetic resonance (NMR) offers tremendous advantages in the analysis of samples of molecular complexity, such as crude bio-extracts, intact cells and tissues, fibres, foods, feeds, fertilizers and environmental samples. Here we outline examples to promote an understanding of recent applications of solution-state, solid-state, time-domain NMR and magnetic resonance imaging (MRI) to the complex evaluation of organisms, materials and the environment. We also describe useful databases and informatics tools, as well as machine learning techniques for NMR analysis, demonstrating that NMR data science can be used to evaluate the exposome in both the natural environment and human society towards a sustainable future.

Live monitoring of cellular metabolism and mitochondrial respiration in 3D cell culture system using NMR spectroscopy

Background: Because of the interplay between mitochondrial respiration and cellular metabolism, the simultaneous monitoring of both cellular processes provides important insights for the understanding of biological processes. NMR flow systems provide a unique window into the metabolome of cultured cells. Simplified bioreactor construction based on commercially available flow systems increase the practicability and reproducibility of bioreactor studies using standard NMR spectrometers. We therefore aim at establishing a reproducible NMR bioreactor system for metabolic ¹H-NMR investigations of small molecules and concurrent oxygenation determination by ¹⁹F-NMR, with in depth description and validation by accompanying measures. Methods: We demonstrate a detailed and standardized workflow for the preparation and transfer of collagen based 3D cell culture of high cell density for perfused investigation in a 5 mm NMR tube. Self-constructed gas mixing station enables 5% CO₂ atmosphere for physiological pH in carbon based medium and is perfused by HPLC pump. Results & Discussion: Implemented perfused bioreactor allows detection of perfusion rate dependent metabolite content. We show interleaved dynamic profiling of 26 metabolites and mitochondrial respiration. During constant perfusion, sequential injection of rotenone/oligomycin and 2-deoxy-glucose indicated immediate activation and deactivation of glycolytic rate and full inhibition of oxygen consumption. We show sensitivity to detect substrate degradation rates of major mitochondrial fuel pathways and were able to simultaneously measure cellular oxygen consumption.

We show sensitivity to detect substrate degradation rates of major mitochondrial fuel pathways and feasibility to simultaneously measure cellular oxygen consumption combining a commercially available flow tube system with a standard 5 mm NMR probe.

RTExtract: time-series NMR spectra quantification based on 3D surface ridge tracking

MOTIVATION

Time-series nuclear magnetic resonance (NMR) has advanced our knowledge about metabolic dynamics. Before analyzing compounds through modeling or statistical methods, chemical features need to be tracked and quantified. However, because of peak overlap and peak shifting, the available protocols are time consuming at best or even impossible for some regions in NMR spectra.

RESULTS

We introduce Ridge Tracking-based Extract (RTExtract), a computer vision-based algorithm, to quantify time-series NMR spectra. The NMR spectra of multiple time points were formulated as a 3D surface. Candidate points were first filtered using local curvature and optima, then connected into ridges by a greedy algorithm. Interactive steps were implemented to refine results. Among 173 simulated ridges, 115 can be tracked (RMSD < 0.001). For reproducing previous results, RTExtract took less than 2 h instead of ∼48 h, and two instead of seven parameters need tuning. Multiple regions with overlapping and changing chemical shifts are accurately tracked.

AVAILABILITY AND IMPLEMENTATION

Source code is freely available within Metabolomics toolbox GitHub repository (https://github.com/artedison/Edison_Lab_Shared_Metabolomics_UGA/tree/master/metabolomics_toolbox/code/ridge_tracking) and is implemented in MATLAB and R.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

5-Axis CNC Micromilling for Rapid, Cheap, and Background-Free NMR Microcoils

The superior mass sensitivity of microcoil technology in nuclear magnetic resonance (NMR) spectroscopy provides potential for the analysis of extremely small-mass-limited samples such as eggs, cells, and tiny organisms. For optimal performance and efficiency, the size of the microcoil should be tailored to the size of the mass-limited sample of interest, which can be costly as mass-limited samples come in many shapes and sizes. Therefore, rapid and economic microcoil production methods are needed. One method with great potential is 5-axis computer numerical control (CNC) micromilling, commonly used in the jewelry industry. Most CNC milling machines are designed to process larger objects and commonly have a precision of >25 μm (making the machining of common spiral microcoils, for example, impossible). Here, a 5-axis MiRA6 CNC milling machine, specifically designed for the jewelry industry, with a 0.3 μm precision was used to produce working planar microcoils, microstrips, and novel microsensor designs, with some tested on the NMR in less than 24 h after the start of the design process. Sample wells could be built into the microsensor and could be machined at the same time as the sensors themselves, in some cases leaving a sheet of Teflon as thin as 10 μm between the sample and the sensor. This provides the freedom to produce a wide array of designs and demonstrates 5-axis CNC micromilling as a versatile tool for the rapid prototyping of NMR microsensors. This approach allowed the experimental optimization of a prototype microstrip for the analysis of two intact adult Daphnia magna organisms. In addition, a 3D volume slotted-tube resonator was produced that allowed for 2D ¹H-¹³C NMR of D. magna neonates and exhibited ¹H sensitivity (nLOD_ω⁶⁰⁰ = 1.49 nmol s^1/2) close to that of double strip lines, which themselves offer the best compromise between concentration and mass sensitivity published to date.

Applications of microbial co-cultures in polyketides production

Polyketides are a large group of natural biomolecules that are normally produced by bacteria, fungi and plants. These molecules have clinical importance due to their anti-cancer, anti-microbial, anti-oxidant and anti-inflammatory properties. Polyketides are biosynthesized from units of acyl-CoA by different polyketide synthases (PKSs), which display wide diversity of functional domains and mechanisms of action between fungi and bacteria. Co-culture of different micro-organisms can produce novel products distinctive from those produced during single cultures. This study compared the new polyketides produced in such co-culture systems and discusses aspects of the cultivation systems, product structures and identification techniques. Current results indicate that the formation of new polyketides may be the result of activation of previously silent PKSs genes induced during co-culture. This review indicated a potential way to produce pure therapeutic polyketides by microbial fermentation and a potential way to develop functional foods and agricultural products using co-co-culture of different micro-organisms. It also pointed out a new perspective for studies on the process of functional foods, especially those involving multiple micro-organisms.

Nuclear Magnetic Resonance with Fast Field-Cycling Setup: A Valid Tool for Soil Quality Investigation

Nuclear magnetic resonance (NMR) techniques are largely employed in several fields. As an example, NMR spectroscopy is used to provide structural and conformational information on pure systems, while affording quantitative evaluation on the number of nuclei in a given chemical environment. When dealing with relaxation, NMR allows understanding of molecular dynamics, i.e., the time evolution of molecular motions. The analysis of relaxation times conducted on complex liquid–liquid and solid–liquid mixtures is directly related to the nature of the interactions among the components of the mixture. In the present review paper, the peculiarities of low resolution fast field-cycling (FFC) NMR relaxometry in soil science are reported. In particular, the general aspects of the typical FFC NMR relaxometry experiment are firstly provided. Afterwards, a discussion on the main mathematical models to be used to “read” and interpret experimental data on soils is given. Following this, an overview on the main results in soil science is supplied. Finally, new FFC NMR-based hypotheses on nutrient dynamics in soils are described

Ex vivo Comprehensive Multiphase NMR of whole organisms: A complementary tool to in vivo NMR

Nuclear Magnetic Resonance (NMR) spectroscopy is a non-invasive analytical technique which allows for the study of intact samples. Comprehensive Multiphase NMR (CMP-NMR) combines techniques and hardware from solution state and solid state NMR to allow for the holistic analysis of all phases (i.e. solutions, gels and solids) in unaltered samples. This study is the first to apply CMP-NMR to deceased, intact organisms and uses ¹³C enriched Daphnia magna (water fleas) as an example. D. magna are commonly used model organisms for environmental toxicology studies. As primary consumers, they are responsible for the transfer of nutrients across trophic levels, and a decline in their population can potentially impact the entire freshwater aquatic ecosystem. Though in vivo research is the ultimate tool to understand an organism’s most biologically relevant state, studies are limited by conditions (i.e. oxygen requirements, limited experiment time and reduced spinning speed) required to keep the organisms alive, which can negatively impact the quality of the data collected. In comparison, ex vivo CMP-NMR is beneficial in that; organisms do not need oxygen (eliminating air holes in rotor caps and subsequent evaporation); samples can be spun faster, leading to improved spectral resolution; more biomass per sample can be analyzed; and experiments can be run for longer. In turn, higher quality ex vivo NMR, can provide more comprehensive NMR assignments, which in many cases could be transferred to better understand less resolved in vivo signals. This manuscript is divided into three sections: 1) multiphase spectral editing techniques, 2) detailed metabolic assignments of 2D NMR of ¹³C enriched D. magna and 3) multiphase biological changes over different life stages, ages and generations of D. magna. In summary, ex vivo CMP-NMR proves to be a very powerful approach to study whole organisms in a comprehensive manner and should provide very complementary information to in vivo based research.

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Comprehensive Multiphase NMR detects all phases (solid/liquid/gel) in whole samples.

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Deceased organisms are not subjected to the limitations of in vivo NMR studies.

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2D ex vivo NMR offer increased spectral resolution, improving metabolite assignment.

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Holistic analysis shows biological changes in D. magna over different life stages.

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Ex vivo NMR can be a complementary tool for in vivo NMR metabolomic studies.

Metabolomics: A Tool for Cultivar Phenotyping and Investigation of Grain Crops

The quality of plants is often enhanced for diverse purposes such as improved resistance to environmental pressures, better taste, and higher yields. Considering the world’s dependence on plants (nutrition, medicine, or biofuel), developing new cultivars with superior characteristics is of great importance. As part of the ‘omics’ approaches, metabolomics has been employed to investigate the large number of metabolites present in plant systems under well-defined environmental conditions. Recent advances in the metabolomics field have greatly expanded our understanding of plant metabolism, largely driven by potential application to agricultural systems. The current review presents the workflow for plant metabolome analyses, current knowledge, and future directions of such research as determinants of cultivar phenotypes. Furthermore, the value of metabolome analyses in contemporary crop science is illustrated. Here, metabolomics has provided valuable information in research on grain crops and identified significant biomarkers under different conditions and/or stressors. Moreover, the value of metabolomics has been redefined from simple biomarker identification to a tool for discovering active drivers involved in biological processes. We illustrate and conclude that the rapid advances in metabolomics are driving an explosion of information that will advance modern breeding approaches for grain crops and address problems associated with crop productivity and sustainable agriculture.

Flow-based in vivo NMR spectroscopy of small aquatic organisms

NMR applied to living organisms is arguably the ultimate tool for understanding environmental stress responses and can provide desperately needed information on toxic mechanisms, synergistic effects, sublethal impacts, recovery, and biotransformation of xenobiotics. To perform in vivo NMR spectroscopy, a flow cell system is required to deliver oxygen and food to the organisms while maintaining optimal line shape for NMR spectroscopy. In this tutorial, two such flow cell systems and their constructions are discussed: (a) a single pump high-volume flow cell design is simple to build and ideal for organisms that do not require feeding (i.e., eggs) and (b) a more advanced low-volume double pump flow cell design that permits feeding, maintains optimal water height for water suppression, improves locking and shimming, and uses only a small recirculating volume, thus reducing the amount of xenobiotic required for testing. In addition, key experimental aspects including isotopic enrichment, water suppression, and 2D experiments for both ¹³ C enriched and natural abundance organisms are discussed.

In vivo comprehensive multiphase NMR

Traditionally, due to different hardware requirements, nuclear magnetic resonance (NMR) has developed as two separate fields: one dealing with solids, and one with solutions. Comprehensive multiphase (CMP) NMR combines all electronics and hardware (magic angle spinning [MAS], gradients, high power Radio Frequency (RF) handling, lock, susceptibility matching) into a universal probe that permits a comprehensive study of all phases (i.e., liquid, gel-like, semisolid, and solid), in intact samples. When applied in vivo, it provides unique insight into the wide array of bonds in a living system from the most mobile liquids (blood, fluids) through gels (muscle, tissues) to the most rigid (exoskeleton, shell). In this tutorial, the practical aspects of in vivo CMP NMR are discussed including: handling the organisms, rotor preparation, sample spinning, water suppression, editing experiments, and finishes with a brief look at the potential of other heteronuclei (² H, ¹⁵ N, ¹⁹ F, ³¹ P) for in vivo research. The tutorial is aimed as a general resource for researchers interested in developing and applying MAS-based approaches to living organisms. Although the focus here is CMP NMR, many of the approaches can be adapted (or directly applied) using conventional high-resolution magic angle spinning, and in some cases, even standard solid-state NMR probes.

Intact NMR spectroscopy: slow high-resolution magic angle spinning chemical shift imaging

High-Resolution Magic-Angle Spinning Chemical Shift Imaging (HR-MAS CSI) has recently been explored for nuclear magnetic resonance (NMR) metabolomics and shows considerable promise in organism research. This is due to its ability to offer a supplemental dimension - spatial metabolic distribution - for profiling. However, HR-MAS CSI suffers from the large centrifugal stress exerted on the sample, which inevitably hinders the metabolic assessment. Herein, a slow sample spinning strategy was implemented and evaluated. The results demonstrate its potential as a highly informative profiling approach for intact specimens, with high quality data and feasibility.

Selective Amino Acid-Only in Vivo NMR: A Powerful Tool To Follow Stress Processes

In vivo NMR of small 13C-enriched aquatic organisms is developing as a powerful tool to detect and explain toxic stress at the biochemical level. Amino acids are a very important category of metabolites for stress detection as they are involved in the vast majority of stress response pathways. As such, they are a useful proxy for stress detection in general, which could then be a trigger for more in-depth analysis of the metabolome. 1H-13C heteronuclear single quantum coherence (HSQC) is commonly used to provide additional spectral dispersion in vivo and permit metabolite assignment. While some amino acids can be assigned from HSQC, spectral overlap makes monitoring them in vivo challenging. Here, an experiment typically used to study protein structures is adapted for the selective detection of amino acids inside living Daphnia magna (water fleas). All 20 common amino acids can be selectively detected in both extracts and in vivo. By monitoring bisphenol-A exposure, the in vivo amino acid-only approach identified larger fluxes in a greater number of amino acids when compared to published works using extracts from whole organism homogenates. This suggests that amino acid-only NMR of living organisms may be a very sensitive tool in the detection of stress in vivo and is highly complementary to more traditional metabolomics-based methods. The ability of selective NMR experiments to help researchers to "look inside" living organisms and only detect specific molecules of interest is quite profound and paves the way for the future development of additional targeted experiments for in vivo research and monitoring.

Continuous in vivo Metabolism by NMR

Dense time-series metabolomics data are essential for unraveling the underlying dynamic properties of metabolism. Here we extend high-resolution-magic angle spinning (HR-MAS) to enable continuous in vivo monitoring of metabolism by NMR (CIVM-NMR) and provide analysis tools for these data. First, we reproduced a result in human chronic lymphoid leukemia cells by using isotope-edited CIVM-NMR to rapidly and unambiguously demonstrate unidirectional flux in branched-chain amino acid metabolism. We then collected untargeted CIVM-NMR datasets for Neurospora crassa, a classic multicellular model organism, and uncovered dynamics between central carbon metabolism, amino acid metabolism, energy storage molecules, and lipid and cell wall precursors. Virtually no sample preparation was required to yield a dynamic metabolic fingerprint over hours to days at ~4-min temporal resolution with little noise. CIVM-NMR is simple and readily adapted to different types of cells and microorganisms, offering an experimental complement to kinetic models of metabolism for diverse biological systems.

Assessing the potential of quantitative 2D HSQC NMR in 13C enriched living organisms

In vivo Nuclear Magnetic Resonance (NMR) spectroscopy has great potential to interpret the biochemical response of organisms to their environment, thus making it an essential tool in understanding toxic mechanisms. However, magnetic susceptibility distortions lead to 1D NMR spectra of living organisms with lines that are too broad to identify and quantify metabolites, necessitating the use of 2D ¹H-¹³C Heteronuclear Single Quantum Coherence (HSQC) as a primary tool. While quantitative 2D HSQC is well established, to our knowledge it has yet to be applied in vivo. This study represents a simple pilot study that compares two of the most popular quantitative 2D HSQC approaches to determine if quantitative results can be directly obtained in vivo in isotopically enriched Daphnia magna (water flea). The results show the perfect-HSQC experiment performs very well in vivo, but the decoupling scheme used is critical for accurate quantitation. An improved decoupling approach derived using optimal control theory is presented here that improves the accuracy of metabolite concentrations that can be extracted in vivo down to micromolar concentrations. When combined with 2D Electronic Reference To access In vivo Concentrations (ERETIC) protocols, the protocol allows for the direct extraction of in vivo metabolite concentrations without the use of internal standards that can be detrimental to living organisms. Extracting absolute metabolic concentrations in vivo is an important first step and should, for example, be important for the parameterization as well as the validation of metabolic flux models in the future.

Focusing on “the important” through targeted NMR experiments: an example of selective13C–12C bond detection in complex mixtures

Here, a targeted NMR experiment is introduced which selectively detects the formation of¹³C–¹²C bonds in mixtures.

Improvements in lipid suppression for 1 H NMR-based metabolomics: Applications to solution-state and HR-MAS NMR in natural and in vivo samples

Proton nuclear magnetic resonance (NMR) spectra of intact biological samples often show strong contributions from lipids, which overlap with signals of interest from small metabolites. Pioneering work by Diserens et al. demonstrated that the relative differences in diffusivity and relaxation of lipids versus small metabolites could be exploited to suppress lipid signals, in high-resolution magic angle spinning (HR-MAS) NMR spectroscopy. In solution-state NMR, suspended samples can exhibit very broad water signals, which are challenging to suppress. Here, improved water suppression is incorporated into the sequence, and the Carr-Purcell-Meiboom-Gill sequence (CPMG) train is replaced with a low-power adiabatic spinlock that reduces heating and spectral artefacts seen with longer CPMG filters. The result is a robust sequence that works well in both HR-MAS as well as static solution-state samples. Applications are also extended to include in vivo organisms. For solution-state NMR, samples containing significant amount of fats such as milk and hemp hearts seeds are used to demonstrate the technique. For HR-MAS, living earthworms (Eisenia fetida) and freshwater shrimp (Hyalella azteca) are used for in vivo applications. Lipid suppression techniques are essential for non-invasive NMR-based analysis of biological samples with a high-lipid content and adds to the suite of experiments advantageous for in vivo environmental metabolomics.