Whole Blood Metabolomics by 1H NMR Spectroscopy Provides a New Opportunity To Evaluate Coenzymes and Antioxidants

Basic accuracy of a 1D NOESY with presaturation method using standard solutions of amino and maleic acids

1D NOESY with presaturation (NOESY-presat) is the most popular water suppression method. When D2O solutions of L-phenylalanine or L-valine were measured using NOESY, the absolute concentration biases increased with longer mixing and evolution times, reaching a maximum of 54% with respect to the preparation values. At mixing and evolution times of 0 ms and 0 µs, respectively, the absolute concentration biases were reduced to less than 3%. The remaining biases were caused by the off-resonance effect, which was prevented by setting the frequency offset to an intermediate value between the analyte and internal standard 3-(trimethylsilyl)-1-propanesulfonic acid-d6 (DSS-d6) signals. Nevertheless, NOESY-presat gave maximum absolute biases of 26% and 11% for glycine and maleic acid concentrations, respectively, in three H2O/D2O (90/10 vol%) solutions. The proposed NOESY-dual-presat method reduced the absolute biases to below 4%. However, water suppression was insufficient but was improved by setting the frequency offset to the same as the presaturation offset with the H2O signal, although the absolute biases rose to 5 to 13%. Quantitative analyses using NOESY-presat and NOESY-dual-presat require careful consideration of the off-resonance effect.

Connecting the dots: investigating the link between environmental, genetic, and epigenetic influences in metabolomic alterations in oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) accounts for around 90% of all oral cancers and is the eighth most common cancer worldwide. Despite progress in managing OSCC, the overall prognosis remains poor, with a survival rate of around 50-60%, largely due to tumor size and recurrence. The challenges of late-stage diagnosis and limitations in current methods emphasize the urgent need for less invasive techniques to enable early detection and treatment, crucial for improving outcomes in this aggressive form of oral cancer. Research is currently aimed at unraveling tumor-specific metabolite profiles to identify candidate biomarkers as well as discover underlying pathways involved in the onset and progression of cancer that could be used as new targets for diagnostic and therapeutic purposes. Metabolomics is an advanced technological approach to identify metabolites in different sample types (biological fluids and tissues). Since OSCC promotes metabolic reprogramming influenced by a combination of genetic predisposition and environmental factors, including tobacco and alcohol consumption, and viral infections, the identification of distinct metabolites through screening may aid in the diagnosis of this condition. Moreover, studies have shown the use of metabolites during the catalysis of epigenetic modification, indicating a link between epigenetics and metabolism. In this review, we will focus on the link between environmental, genetic, and epigenetic influences in metabolomic alterations in OSCC. In addition, we will discuss therapeutic targets of tumor metabolism, which may prevent oral tumor growth, metastasis, and drug resistance.

Nuclear magnetic resonance spectroscopy reveals biomarkers of stroke recovery in a mouse model of obesity-associated type 2 diabetes

Obesity and Type 2 diabetes (T2D) are known to exacerbate cerebral injury caused by stroke. Metabolomics can provide signatures of metabolic disease, and now we explored whether the analysis of plasma metabolites carries biomarkers of how obesity and T2D impact post-stroke recovery. Male mice were fed a high-fat diet (HFD) for 10 months leading to development of obesity with T2D or a standard diet (non-diabetic mice). Then, mice were subjected to either transient middle cerebral artery occlusion (tMCAO) or sham surgery and allowed to recover on standard diet for 2 months before serum samples were collected. Nuclear magnetic resonance (NMR) spectroscopy of serum samples was used to investigate metabolite signals and metabolic pathways that were associated with tMCAO recovery in either T2D or non-diabetic mice. Overall, after post-stroke recovery there were different serum metabolite profiles in T2D and non-diabetic mice. In non-diabetic mice, which show full neurological recovery after stroke, we observed a reduction of isovalerate, and an increase of kynurenate, uridine monophosphate, gluconate and N6-acetyllysine in tMCAO relative to sham mice. In contrast, in mice with T2D, which show impaired stroke recovery, there was a reduction of N,N-dimethylglycine, succinate and proline, and an increase of 2-oxocaproate in serum of tMCAO versus sham mice. Given the inability of T2D mice to recover from stroke, in contrast with non-diabetic mice, we propose that these specific metabolite changes following tMCAO might be used as biomarkers of neurophysiological recovery after stroke in T2D.

Regulation of and challenges in targeting NAD+ metabolism

Nicotinamide adenine dinucleotide, in its oxidized (NAD+) and reduced (NADH) forms, is a reduction-oxidation (redox) co-factor and substrate for signalling enzymes that have essential roles in metabolism. The recognition that NAD+ levels fall in response to stress and can be readily replenished through supplementation has fostered great interest in the potential benefits of increasing or restoring NAD+ levels in humans to prevent or delay diseases and degenerative processes. However, much about the biology of NAD+ and related molecules remains poorly understood. In this Review, we discuss the current knowledge of NAD+ metabolism, including limitations of, assumptions about and unappreciated factors that might influence the success or contribute to risks of NAD+ supplementation. We highlight several ongoing controversies in the field, and discuss the role of the microbiome in modulating the availability of NAD+ precursors such as nicotinamide riboside (NR) and nicotinamide mononucleotide (NMN), the presence of multiple cellular compartments that have distinct pools of NAD+ and NADH, and non-canonical NAD+ and NADH degradation pathways. We conclude that a substantial investment in understanding the fundamental biology of NAD+, its detection and its metabolites in specific cells and cellular compartments is needed to support current translational efforts to safely boost NAD+ levels in humans.

Recent Advancement in NMR Based Plant Metabolomics: Techniques, Tools, and Analytical Approaches

Plant metabolomics, a rapidly advancing field within plant biology, is dedicated to comprehensively exploring the intricate array of small molecules in plant systems. This entails precisely gathering comprehensive chemical data, detecting numerous metabolites, and ensuring accurate molecular identification. Nuclear magnetic resonance (NMR) spectroscopy, with its detailed chemical insights, is crucial in obtaining metabolite profiles. Its widespread application spans various research disciplines, aiding in comprehending chemical reactions, kinetics, and molecule characterization. Biotechnological advancements have further expanded NMR's utility in metabolomics, particularly in identifying disease biomarkers across diverse fields such as agriculture, medicine, and pharmacology. This review covers the stages of NMR-based metabolomics, including historical aspects and limitations, with sample preparation, data acquisition, spectral processing, analysis, and their application parts.

In vivo biological validation of in silico analysis: A novel approach for predicting the effects of TLR4 exon 3 polymorphisms on brucellosis

The role of the Toll-like receptor 4 (TLR4) is of recognising intracellular and extracellular pathogens and of activating the immune response. This process can be compromised by single nucleotide polymorphisms (SNPs) which might affect the activity of several TLRs. The aim of this study is of ascertaining whether SNPs in the TLR4 of Bubalus bubalis infected by Brucella abortus, compromise the protein functionality. For this purpose, a computational analysis was performed. Next, computational predictions were confirmed by performing genotyping analysis. Finally, NMR-based metabolomics analysis was performed to identify potential biomarkers for brucellosis. The results indicate two SNPs (c. 672 A > C and c. 902 G > C) as risk factor for brucellosis in Bubalus bubalis, and three metabolites (lactate, 3-hydroxybutyrate and acetate) as biological markers for predicting the risk of developing the disease. These metabolites, together with TLR4 structural modifications in the MD2 interaction domain, are a clear signature of the immune system alteration during diverse Gram-negative bacterial infections. This suggests the possibility to extend this study to other pathogens, including Mycobacterium tuberculosis. In conclusion, this study combines multidisciplinary approaches to evaluate the biological and structural effects of SNPs on protein function.

Modeling blood metabolite homeostatic levels reduces sample heterogeneity across cohorts

Blood metabolite levels are affected by numerous factors, including preanalytical factors such as collection methods and geographical sites. These perturbations have caused deleterious consequences for many metabolomics studies and represent a major challenge in the metabolomics field. It is important to understand these factors and develop models to reduce their perturbations. However, to date, the lack of suitable mathematical models for blood metabolite levels under homeostasis has hindered progress. In this study, we develop quantitative models of blood metabolite levels in healthy adults based on multisite sample cohorts that mimic the current challenge. Five cohorts of samples obtained across four geographically distinct sites were investigated, focusing on approximately 50 metabolites that were quantified using 1H NMR spectroscopy. More than one-third of the variation in these metabolite profiles is due to cross-cohort variation. A dramatic reduction in the variation of metabolite levels (90%), especially their site-to-site variation (95%), was achieved by modeling each metabolite using demographic and clinical factors and especially other metabolites, as observed in the top principal components. The results also reveal that several metabolites contribute disproportionately to such variation, which could be explained by their association with biological pathways including biosynthesis and degradation. The study demonstrates an intriguing network effect of metabolites that can be utilized to better define homeostatic metabolite levels, which may have implications for improved health monitoring. As an example of the potential utility of the approach, we show that modeling gender-related metabolic differences retains the interesting variance while reducing unwanted (site-related) variance.

Multiplatform untargeted metabolomics

Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.

Multiplatform untargeted metabolomics

Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.

Labile Metabolite Profiling in Human Blood Using Phosphorus NMR Spectroscopy

Phosphorus metabolites occupy a unique place in cellular function as critical intermediates and products of cellular metabolism. Human blood is the most widely used biospecimen in the clinic and in the metabolomics field, and hence an ability to profile phosphorus metabolites in blood, quantitatively, would benefit a wide variety of investigations of cellular functions in health and diseases. Mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy are the two premier analytical platforms used in the metabolomics field. However, detection and quantitation of phosphorus metabolites by MS can be challenging due to their lability, high polarity, structural isomerism, and interaction with chromatographic columns. The conventionally used 1H NMR, on the other hand, suffers from poor resolution of these compounds. As a remedy, 31P NMR promises an important alternative to both MS and 1H NMR. However, numerous challenges including the instability of phosphorus metabolites, their chemical shift sensitivity to solvent composition, pH, salt, and temperature, and the lack of identified metabolites have so far restricted the scope of 31P NMR. In the current study, we describe a method to analyze nearly 25 phosphorus metabolites in blood using a simple one-dimensional (1D) NMR spectrum. Establishment of the identity of unknown metabolites involved a combination of (a) comprehensively analyzing an array of 1D and two-dimensional (2D) 1H/31P homonuclear and heteronuclear NMR spectra of blood; (b) mapping the central carbon metabolic pathway; (c) developing and using 1H and 31P spectral and chemical shift databases; and finally (d) confirming the putative metabolite peaks with spiking using authentic compounds. The resulting simple 1D 31P NMR-based method offers an ability to visualize and quantify the levels of intermediates and products of multiple metabolic pathways, including central carbon metabolism, in one step. Overall, the findings represent a new dimension for blood metabolite analysis and are anticipated to greatly impact the blood metabolomics field.

Whole-Blood Metabolomics of a Rat Model of Repetitive Concussion

Mild traumatic brain injury (mTBI) and repetitive mTBI (RmTBI) are silent epidemics, and so far, there is no objective diagnosis. The severity of the injury is solely based on the Glasgow Coma Score (GCS) scale. Most patients suffer from one or more behavioral abnormalities, such as headache, amnesia, cognitive decline, disturbed sleep pattern, anxiety, depression, and vision abnormalities. Additionally, most neuroimaging modalities are insensitive to capture structural and functional alterations in the brain, leading to inefficient patient management. Metabolomics is one of the established omics technologies to identify metabolic alterations, mostly in biofluids. NMR-based metabolomics provides quantitative metabolic information with non-destructive and minimal sample preparation. We employed whole-blood NMR analysis to identify metabolic markers using a high-field NMR spectrometer (800 MHz). Our approach involves chemical-free sample pretreatment and minimal sample preparation to obtain a robust whole-blood metabolic profile from a rat model of concussion. A single head injury was given to the mTBI group, and three head injuries to the RmTBI group. We found significant alterations in blood metabolites in both mTBI and RmTBI groups compared with the control, such as alanine, branched amino acid (BAA), adenosine diphosphate/adenosine try phosphate (ADP/ATP), creatine, glucose, pyruvate, and glycerphosphocholine (GPC). Choline was significantly altered only in the mTBI group and formate in the RmTBI group compared with the control. These metabolites corroborate previous findings in clinical and preclinical cohorts. Comprehensive whole-blood metabolomics can provide a robust metabolic marker for more accurate diagnosis and treatment intervention for a disease population.

Anomalous Dynamics of Labile Metabolites in Cold Human Blood Detected Using 1H NMR Spectroscopy

Recent efforts in our laboratory have enabled access to an unprecedented number (∼90) of quantifiable metabolites in human blood by a simple nuclear magnetic resonance (NMR) spectroscopy method, which includes energy coenzymes, redox coenzymes, and antioxidants that are fundamental to cellular functions [ J. Magn. Reson. Open 2022, 12-13, 100082]. The coenzymes and antioxidants, however, are notoriously labile and are extremely sensitive to specimen harvesting, extraction, and measurement conditions. This problem is largely underappreciated and carries the risk of grossly inaccurate measurements and incorrect study outcomes. As a part of addressing this challenge, in this study, human blood specimens were comprehensively and quantitatively investigated using 1H NMR spectroscopy. Freshly drawn human blood specimens were treated or not treated with methanol, ethanol, or a mixture of methanol and chloroform, and stored on ice or on bench, at room temperature for different time periods from 0 to 24 h, prior to storing at -80 °C. Interestingly, the labile metabolite levels were stable in blood treated with an organic solvent. However, their levels in blood in untreated samples increased or decreased by factors of up to 5 or more within 3 h. Further, surprisingly, and contrary to the current knowledge about metabolite stability, the variation of coenzyme levels was more dramatic in blood stored on ice than on bench, at room temperature. In addition, unlike the generally observed phenomenon of oxidation of redox coenzymes, reduction was observed in untreated blood. Such preanalytical dynamics of the labile metabolites potentially arises from the active cellular metabolism. From the metabolomics perspective, the massive variation of the labile metabolite levels even in blood stored on ice is alarming and stresses the critical need to immediately quench the cellular metabolism for reliable analyses. Overall, the results provide compelling evidence that warrants a paradigm shift in the sample collection protocol for blood metabolomics involving labile metabolites.

Metabolite Profiling in a Diet-Induced Obesity Mouse Model and Individuals with Diabetes: A Combined Mass Spectrometry and Proton Nuclear Magnetic Resonance Spectroscopy Study

Mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy techniques have been used extensively for metabolite profiling. Although combining these two analytical modalities has the potential of enhancing metabolite coverage, such studies are sparse. In this study we test the hypothesis that combining the metabolic information obtained using liquid chromatography (LC) MS and ¹H NMR spectroscopy improves the discrimination of metabolic disease development. We induced metabolic syndrome in male mice using a high-fat diet (HFD) exposure and performed LC-MS and NMR spectroscopy on plasma samples collected after 1 and 8 weeks of dietary intervention. In an orthogonal projection to latent structures (OPLS) analysis, we observed that combining MS and NMR was stronger than each analytical method alone at determining effects of both HFD feeding and time-on-diet. We then tested our metabolomics approach on plasma from 56 individuals from the Malmö Diet and Cancer Study (MDCS) cohort. All metabolic pathways impacted by HFD feeding in mice were confirmed to be affected by diabetes in the MDCS cohort, and most prominent HFD-induced metabolite concentration changes in mice were also associated with metabolic syndrome parameters in humans. The main drivers of metabolic disease discrimination emanating from the present study included plasma levels of xanthine, hippurate, 2-hydroxyisovalerate, S-adenosylhomocysteine and dimethylguanidino valeric acid. In conclusion, our combined NMR-MS approach provided a snapshot of metabolic imbalances in humans and a mouse model, which was improved over employment of each analytical method alone.

Fresh Dual Presaturation Method for Analyzing H2O-Rich Samples Using Quantitative 1H NMR

A fresh dual presaturation (pre-SAT) method was developed to quantify analytes accurately near the suppressed water signal in ¹H NMR spectra obtained from H₂O-rich samples. The method includes an extra dummy pre-SAT with a suitable offset for each analyte signal in addition to the water pre-SAT. The residual HOD signal at 4.66 ppm was observed using D₂O solutions containing l-phenylalanine (Phe) or l-valine (Val) and an internal standard of 3-(trimethylsilyl)-1-propanesulfonic acid-d₆ sodium salt (DSS-d₆). When the HOD signal was suppressed using the conventional single pre-SAT method, the measured concentration of Phe from the NCH signal at 3.89 ppm decreased by a maximum of 48%, whereas the dual pre-SAT method gave a reduction in the Phe concentration measured from the NCH signal of less than 3%. The proposed dual pre-SAT method achieved accurate quantification of glycine (Gly) and maleic acid (MA) in a 10 vol % D₂O/H₂O solution. The measured concentrations of Gly of 513.5 ± 8.9 mg kg^-1 and MA of 512.2 ± 10.3 mg kg^-1 corresponded to sample preparation values of Gly of 502.9 ± 1.7 mg kg^-1 and MA of 506.7 ± 2.9 mg kg^-1 (the number after "±" indicates the expanded uncertainty (k = 2)).

Whole Body Distribution of Labile Coenzymes and Antioxidants in a Mouse Model as Visualized Using 1H NMR Spectroscopy

Coenzyme A, acetyl coenzyme A, coenzymes of cellular energy, coenzymes of redox reactions, and antioxidants mediate biochemical reactions fundamental to the functioning of all living cells. There is an immense interest in measuring them routinely in biological specimens to gain insights into their roles in cellular functions and to help characterize the biological status. However, it is challenging to measure them ex vivo as they are sensitive to specimen harvesting, extraction, and measurement conditions. This challenge is largely underappreciated and carries the risk of grossly inaccurate measurements that lead to incorrect inferences. To date, several efforts have been focused on alleviating this challenge using NMR spectroscopy. However, a comprehensive solution for the measurement of the compounds in a wide variety of biological specimens is still lacking. As a part of addressing this challenge, we demonstrate here that the total pool of each group of unstable metabolites offers a starting place for the representation of labile metabolites in biological specimens. Based on this approach, in this proof-of-concept study, we determine the distribution of the labile compounds in different organs including heart, kidney, liver, brain, and skeletal muscle of a mouse model. The results were independently validated using different specimens and a different metabolite extraction protocol. Further, we show that both stable and unstable metabolites were distributed differentially in different organs, which signifies their differential functional roles, the knowledge of which is currently lacking for many metabolites. Intriguingly, the concentration of taurine, an amino sulfonic acid, in skeletal muscle is >30 mM, which is the highest for any metabolite in a mammalian tissue known to date. To the best of our knowledge, this is the first study to profile the whole body distribution of the labile and other high-concentration metabolites using NMR spectroscopy. The results may pave ways for gaining new insights into cellular functions in health and diseases.

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.

Quantitative NMR Methods in Metabolomics

Nuclear Magnetic Resonance (NMR) spectroscopy is one of the two major analytical platforms in the field of metabolomics, the other being mass spectrometry (MS). NMR is less sensitive than MS and hence it detects a relatively small number of metabolites. However, NMR exhibits numerous unique characteristics including its high reproducibility and non-destructive nature, its ability to identify unknown metabolites definitively, and its capabilities to obtain absolute concentrations of all detected metabolites, sometimes even without an internal standard. These characteristics outweigh the relatively low sensitivity and resolution of NMR in metabolomics applications. Since biological mixtures are highly complex, increased demand for new methods to improve detection, better identify unknown metabolites, and provide more accurate quantitation continues unabated. Technological and methodological advances to date have helped to improve the resolution and sensitivity and detection of a larger number of metabolite signals. Efforts focused on measuring unknown metabolite signals have resulted in the identification and quantitation of an expanded pool of metabolites including labile metabolites such as cellular redox coenzymes, energy coenzymes, and antioxidants. This chapter describes quantitative NMR methods in metabolomics with an emphasis on recent methodological developments, while highlighting the benefits and challenges of NMR-based metabolomics.

A new limit for blood metabolite analysis using 1H NMR spectroscopy

Human blood is the most widely used biospecimen in the clinic and the metabolomics field. While both mass spectrometry and NMR spectroscopy are the two premier analytical platforms in the metabolomics field, NMR exhibits several unsurpassed characteristics for blood metabolite analysis, the most important of which are its ability to identify unknown metabolites and its quantitative nature. However, the relatively small number of metabolites accessible by NMR has restricted the scope of its applications. Enhancing the limit of identified metabolites in blood will therefore greatly impact NMR-based metabolomics. Continuing our efforts to address this major issue, our current study describes the identification of 12 metabolites, which expands the number of quantifiable blood metabolites by ~15%. These results, in combination with our earlier efforts, now provide access to nearly 90 metabolites, which is the highest to date for a simple 1D 1H NMR experiment that is widely used in the metabolomics field. Metabolites were identified based on the comprehensive investigation of human blood and plasma using 1D/2D NMR techniques. The newly identified metabolites were validated based on chemical shift databases, spectra of authentic compounds obtained under conditions identical to blood/plasma, and, finally, spiking experiments using authentic compounds. Considering the high reproducibility of NMR and the sensitivity of chemical shifts to altered sample conditions, experimental protocols and peak annotations are provided for the newly identified metabolites, which serve as a template for identification of blood metabolites for routine applications. Separately, the identified metabolites were evaluated for their sensitivity to preanalytical conditions. The results reveal that among the newly identified metabolites, inosine monophosphate (IMP) and nicotinamide are associated with labile coenzymes and their levels are sensitive to preanalytical conditions. The study demonstrates the expansion of quantifiable blood metabolites using NMR to a new height and is expected to greatly impact blood metabolomics.

Cutting-edge strategies and critical advancements in characterization and quantification of metabolites concerning translational metabolomics

Despite remarkable progress in drug discovery strategies, significant challenges are still remaining in translating new insights into clinical applications. Scientists are devising creative approaches to bridge the gap between scientific and translational research. Metabolomics is a unique field among other omics techniques for identifying novel metabolites and biomarkers. Fortunately, characterization and quantification of metabolites are becoming faster due to the progress in the field of orthogonal analytical techniques. This review detailed the advancement in the progress of sample preparation, and data processing techniques including data mining tools, database, and their quality control (QC). Advances in data processing tools make it easier to acquire unbiased data that includes a diverse set of metabolites. In addition, novel breakthroughs including, miniaturization as well as their integration with other devices, metabolite array technology, and crystalline sponge-based method have led to faster, more efficient, cost-effective, and holistic metabolomic analysis. The use of cutting-edge techniques to identify the human metabolite, including biomarkers has proven to be advantageous in terms of early disease identification, tracking the progression of illness, and possibility of personalized treatments. This review addressed the constraints of current metabolomics research, which are impeding the facilitation of translation of research from bench to bedside. Nevertheless, the possible way out from such constraints and future direction of translational metabolomics has been conferred.

Systematic Review of NMR-Based Metabolomics Practices in Human Disease Research

Nuclear magnetic resonance (NMR) spectroscopy is one of the principal analytical techniques for metabolomics. It has the advantages of minimal sample preparation and high reproducibility, making it an ideal technique for generating large amounts of metabolomics data for biobanks and large-scale studies. Metabolomics is a popular “omics” technology and has established itself as a comprehensive exploratory biomarker tool; however, it has yet to reach its collaborative potential in data collation due to the lack of standardisation of the metabolomics workflow seen across small-scale studies. This systematic review compiles the different NMR metabolomics methods used for serum, plasma, and urine studies, from sample collection to data analysis, that were most popularly employed over a two-year period in 2019 and 2020. It also outlines how these methods influence the raw data and the downstream interpretations, and the importance of reporting for reproducibility and result validation. This review can act as a valuable summary of NMR metabolomic workflows that are actively used in human biofluid research and will help guide the workflow choice for future research.

Effects of Different Ratios of Carbohydrate-Fat in Enteral Nutrition on Metabolic Pattern and Organ Damage in Burned Rats

(1) Background: Nutritional support is one of the most important cornerstones in the management of patients with severe burns, but the carbohydrate-to-fat ratios in burn nutrition therapy remain highly controversial. In this study, we aimed to discuss the effects of different ratios of carbohydrate–fat through enteral nutrition on the metabolic changes and organ damage in burned rats. (2) Methods: Twenty-four burned rats were randomly divided into 5%, 10%, 20% and 30% fat nutritional groups. REE and body weight were measured individually for each rat daily. Then, 75% of REE was given in the first week after burns, and the full dose was given in the second week. Glucose tolerance of the rats was measured on days 1, 3, 7, 10 and 14. Blood biochemistry analysis and organ damage analysis were performed after 7 and 14 days of nutritional therapy, and nuclear magnetic resonance (NMR) and insulin content analysis were performed after 14 days. (3) Results: NMR spectra showed significant differences of glucose, lipid and amino acid metabolic pathways. The energy expenditure increased, and body weight decreased significantly after burn injury, with larger change in the 20%, 5% and 30% fat groups, and minimal change in the 10% fat group. The obvious changes in the level of plasma protein, glucose, lipids and insulin, as well as the organ damage, were in the 30%, 20% and 5% fat groups. In relative terms, the 10% fat group showed the least variation and was closest to normal group. (4) Conclusion: Lower fat intake is beneficial to maintaining metabolic stability and lessening organ damage after burns, but percentage of fat supply should not be less than 10% in burned rats.

Stability of Metabolomic Content during Sample Preparation: Blood and Brain Tissues

Thermal and enzymatic reactions can significantly change the tissue metabolomic content during the sample preparation. In this work, we evaluated the stability of metabolites in human whole blood, serum, and rat brain, as well as in metabolomic extracts from these tissues. We measured the concentrations of 63 metabolites in brain and 52 metabolites in blood. We have shown that metabolites in the extracts from biological tissues are stable within 24 h at 4 °C. Serum and whole blood metabolomes are also rather stable, changes in metabolomic content of the whole blood homogenate become apparent only after 1–2 h of incubation at 4 °C, and become strong after 24 h. The most significant changes correspond to energy metabolites: the concentrations of ATP and ADP decrease fivefold, and the concentrations of NAD, NADH, and NADPH decrease below the detectable level. A statistically significant increase was observed for AMP, IMP, hypoxanthine, and nicotinamide. The brain tissue is much more metabolically active than human blood, and significant metabolomic changes occur already within the first several minutes during the brain harvest and sample homogenization. At a longer timescale (hours), noticeable changes were observed for all classes of compounds, including amino acids, organic acids, alcohols, amines, sugars, nitrogenous bases, nucleotides, and nucleosides.

A Combination of Nicotinamide and D-Ribose (RiaGev) Is Safe and Effective to Increase NAD+ Metabolome in Healthy Middle-Aged Adults: A Randomized, Triple-Blind, Placebo-Controlled, Cross-Over Pilot Clinical Trial

Nicotinamide adenine dinucleotide (NAD⁺) is an essential cofactor required for proper functioning of all cells and its decline is correlated with advancing age and disease. This randomized, triple-blind, placebo-controlled, crossover pilot study assessed the efficacy and safety of a combination of nicotinamide with D-ribose (RiaGev) for NAD metabolome enhancement and related benefits in healthy middle-aged adults. Supplementing with 1520 mg RiaGev twice daily for 7 days significantly increased the NAD⁺ metabolome in blood, especially NADP⁺ by 27% compared to the placebo group (p = 0.033) and over the baseline (p = 0.007). Increases in glutathione and high energy phosphates were also observed in the blood. Seven-day supplementation with RiaGev significantly (p = 0.013) reduced overall blood glucose without significant changes in insulin secretion (p = 0.796), suggesting an improved insulin sensitivity and glucose tolerance. The waking salivary cortisol of the subjects steadily and significantly decreased (p = 0.026) in the RiaGev group in contrast to the placebo. Subjects in the RiaGev group showed less fatigue, improved mental concentration and motivation over the baseline (p = 0.015, 0.018, and 0.012, respectively) as observed through the Checklist Individual Strength (CIS) questionnaire. There were no clinically relevant adverse events, or alterations in hematology, electrolytes, liver, and kidney markers pre- and post-supplementation. RiaGev appears to be safe and efficacious in increasing NAD⁺ metabolome in healthy middle-aged adults, as shown by this study.

Efficient Assay and Marker Significance of NAD+ in Human Blood

Oxidized nicotinamide adenine dinucleotide (NAD+) is a biological molecule of systemic importance. Essential role of NAD+ in cellular metabolism relies on the substrate action in various redox reactions and cellular signaling. This work introduces an efficient enzymatic assay of NAD+ content in human blood using recombinant formate dehydrogenase (FDH, EC 1.2.1.2), and demonstrates its diagnostic potential, comparing NAD+ content in the whole blood of control subjects and patients with cardiac or neurological pathologies. In the control group (n = 22, 25–70 years old), our quantification of the blood concentration of NAD+ (18 μM, minimum 15, max 23) corresponds well to NAD+ quantifications reported in literature. In patients with demyelinating neurological diseases (n = 10, 18–55 years old), the NAD+ levels significantly (p < 0.0001) decrease (to 14 μM, min 13, max 16), compared to the control group. In cardiac patients with the heart failure of stage II and III according to the New York Heart Association (NYHA) functional classification (n = 24, 42–83 years old), the blood levels of NAD+ (13 μM, min 9, max 18) are lower than those in the control subjects (p < 0.0001) or neurological patients (p = 0.1). A better discrimination of the cardiac and neurological patients is achieved when the ratios of NAD+ to the blood creatinine levels, mean corpuscular volume or potassium ions are compared. The proposed NAD+ assay provides an easy and robust tool for clinical analyses of an important metabolic indicator in the human blood.

DREAMTIME NMR Spectroscopy: Targeted Multi-Compound Selection with Improved Detection Limits

NMR/MRI are critical tools for studying molecular structure and interactions but suffer from relatively low sensitivity and spectral overlap. Here, a Nuclear Magnetic Resonance (NMR) approach, termed DREAMTIME, is introduced that provides "a molecular window" inside complex systems, capable of showing only what the user desires, with complete molecular specificity. The user chooses a list of molecules of interest, and the approach detects only those targets while all other molecules are invisible. The approach is demonstrated in whole human blood and urine, small living aquatic organisms in 1D/2D NMR, and MRI. Finally, as proof-of-concept, once overlap is removed via DREAMTIME, a novel "multi-focusing" approach can be used to increase sensitivity. In human blood and urine, sensitivity increases of 7-12 fold over standard ¹ H NMR are observed. Applicable even to unknowns, DREAMTIME has widespread application, from monitoring product formation in organic chemistry to monitoring/identifying suites of molecular targets in complex media or in vivo.

Observable Metabolites and Metabolomic Sampling Protocols for Managed African Savanna Elephant (Loxodonta africana) Whole Blood Using H-NMR Spectroscopy

We used nuclear magnetic spectroscopy (NMR) to evaluate the metabolomics of heparinized whole blood drawn from six African savanna elephants (Loxodonta africana) maintained on a well characterized diet. Whole blood samples obtained under behavioral restraint, then quickly frozen in liquid nitrogen, were stored at −80 °C until analysis. Frozen samples were thawed under controlled conditions and extracted with methanol and chloroform to separate the polar and non-polar metabolites. We identified 18 polar metabolites and 14 non-polar lipids using one-dimensional (1D) and two-dimensional (2D) NMR spectra. Despite unexpected rouleaux formation in the thawed frozen samples, spectra were consistent among animals and did not vary dramatically with age or the sex of the animal.

Extending the Scope of 1H NMR-Based Blood Metabolomics for the Analysis of Labile Antioxidants: Reduced and Oxidized Glutathione

Glutathione is a ubiquitous cellular antioxidant, which is critically required to protect cells from oxidative damage and free radical injury. It is practically impossible to analyze glutathione in its native form after isolation from biological mixtures since the active form (reduced glutathione, GSH) spontaneously gets converted to the oxidized form (oxidized glutathione, GSSG). To address this challenge, numerous highly sensitive detection methods, including mass spectrometry, have been used in conjunction with derivatization to block the oxidation of GSH. Efforts so far to quantitate GSH and GSSG using the nuclear magnetic resonance (NMR) spectroscopy method have remained unsuccessful. With a focus on addressing this challenge, in this study, we describe an extension to our recent whole blood analysis method [ Anal. Chem. 2017, 89, 4620-4627] that includes the important antioxidants GSH and GSSG. Fresh and frozen human whole blood specimens as well as standard GSH and GSSG were comprehensively investigated using NMR without and with derivatization using N-ethylmaleimide (NEM). NMR experiments detect two diastereomers, distinctly, for the derivatized GSH and enable the analysis of both GSH and GSSG in human whole blood with an accuracy of >99%. Interestingly, the excess (unreacted) NEM used for blocking the GSH can be removed from the samples during a drying step after extraction, with no need for additional processing. This is an important characteristic that offers an added advantage for simultaneous analysis of the antioxidants (GSH and GSSG), redox coenzymes (oxidized nicotinamide adenine dinucleotide (NAD⁺), reduced nicotinamide adenine dinucleotide (NADH), oxidized nicotinamide adenine dinucleotide phosphate (NADP⁺), reduced nicotinamide adenine dinucleotide phosphate (NADPH)), energy coenzymes (adenosine 5'-triphosphate (ATP), adenosine 5'-diphosphate (ADP), adenosine 5'-monophosphate (AMP)), and a large number of other blood metabolites using the same one-dimensional (1D) NMR spectrum. The presented method broadens the scope of global metabolite profiling and adds a new dimension to NMR-based blood metabolomics. Further, the method demonstrated here for human blood can be extended to virtually any biological specimen.

A Method to Monitor the NAD+ Metabolome-From Mechanistic to Clinical Applications

Nicotinamide adenine dinucleotide (NAD+) and its reduced form (NADH) are coenzymes employed in hundreds of metabolic reactions. NAD+ also serves as a substrate for enzymes such as sirtuins, poly(ADP-ribose) polymerases (PARPs) and ADP-ribosyl cyclases. Given the pivotal role of NAD(H) in health and disease, studying NAD+ metabolism has become essential to monitor genetic- and/or drug-induced perturbations related to metabolic status and diseases (such as ageing, cancer or obesity), and its possible therapies. Here, we present a strategy based on liquid chromatography-tandem mass spectrometry (LC-MS/MS), for the analysis of the NAD+ metabolome in biological samples. In this method, hydrophilic interaction chromatography (HILIC) was used to separate a total of 18 metabolites belonging to pathways leading to NAD+ biosynthesis, including precursors, intermediates and catabolites. As redox cofactors are known for their instability, a sample preparation procedure was developed to handle a variety of biological matrices: cell models, rodent tissues and biofluids, as well as human biofluids (urine, plasma, serum, whole blood). For clinical applications, quantitative LC-MS/MS for a subset of metabolites was demonstrated for the analysis of the human whole blood of nine volunteers. Using this developed workflow, our methodology allows studying NAD+ biology from mechanistic to clinical applications.

Whole-blood metabolomics of dementia patients reveal classes of disease-linked metabolites

Dementia is a slowly progressing, chronic, and usually irreversible decline in cognitive function. Mechanistic causes and definitive treatments remain elusive. Using comprehensive metabolomics, we identified five groups of 33 metabolites (A to E), 13 of them previously reported, possibly useful for diagnosis and therapy of forms of dementia, such as Alzheimer’s disease. Seven A compounds may act as neurotoxins, whereas B to E compounds may protect the nervous system against oxidative stress, maintain energy reserves, supply nutrients and neuroprotective factors. Five metabolites, ergothioneine, S-methyl-ergothioneine, trimethyl-histidine, methionine, and tryptophan, overlap with those reported for frailty. Interventions for cognitive diseases involving these dementia metabolomic markers may be accomplished either by inhibiting A compounds or by supplementing B to E compounds in patients.

Dementia is caused by factors that damage neurons. We quantified small molecular markers in whole blood of dementia patients, using nontargeted liquid chromatography–mass spectroscopy (LC-MS). Thirty-three metabolites, classified into five groups (A to E), differed significantly in dementia patients, compared with healthy elderly subjects. Seven A metabolites present in plasma, including quinolinic acid, kynurenine, and indoxyl-sulfate, increased. Possibly they act as neurotoxins in the central nervous system (CNS). The remaining 26 compounds (B to E) decreased, possibly causing a loss of support or protection of the brain in dementia. Six B metabolites, normally enriched in red blood cells (RBCs), all contain trimethylated ammonium moieties. These metabolites include ergothioneine and structurally related compounds that have scarcely been investigated as dementia markers, validating the examination of RBC metabolites. Ergothioneine, a potent antioxidant, is significantly decreased in various cognition-related disorders, such as mild cognitive impairment and frailty. C compounds also include some oxidoreductants and are normally abundant in RBCs (NADP⁺, glutathione, adenosine triphosphate, pantothenate, S-adenosyl-methionine, and gluconate). Their decreased levels in dementia patients may also contribute to depressed brain function. Twelve D metabolites contains plasma compounds, such as amino acids, glycerophosphocholine, dodecanoyl-carnitine, and 2-hydroxybutyrate, which normally protect the brain, but their diminution in dementia may reduce that protection. Seven D compounds have been identified previously as dementia markers. B to E compounds may be critical to maintain the CNS by acting directly or indirectly. How RBC metabolites act in the CNS and why they diminish significantly in dementia remain to be determined.

Majid R, Ibraheem ZO, Mediani A, Ismail IS, Unyah NZ, Alhassan Abdullahi S, Nordin N, Nasiru Wana M, Basir R. Investigation of Andrographolide Effect on Non-Infected Red Blood Cells Using the 1H-NMR-Based Metabolomics Approach

Andrographolide (AG) has been shown to have several medicinal and pharmaceutical effects, such as antimicrobial, anti-inflammatory, antioxidant, anti-diabetic, and anti-malarial activities. Moreover, studies to assess the pharmacological effect of AG on the metabolic changes of uninfected red blood cells (uRBCs) have not yet been investigated. This study aims to evaluate the pharmacological effects of AG compared to chloroquine (CQ) on the metabolic variations of uRBCs in vitro using a proton nuclear magnetic resonance (¹H-NMR)-based metabolomics approach coupled with multivariate data analysis (MVDA). Forty-one metabolites were successfully identified by ¹H-NMR. The results of the unsupervised data analysis principal component analysis (PCA) showed ideal differentiation between AG and CQ. PC1 and PC2 accounted for 71.4% and 17.7% of the explained variation, respectively, with a total variance of 89.10%. Based on S-plot and VIP values, a total of 28 and 32 metabolites were identified as biomarkers in uRBCs-AG and uRBCs-CQ, respectively. In uRBCs treated with AG, ten metabolic pathways were determined to be disturbed, including riboflavin metabolism, d-glutamate and d-glutamine metabolism, phenylalanine metabolism, glutathione metabolism, proline and arginine metabolism, arginine biosynthesis, citrate cycle, glycolysis/gluconeogenesis, and pyruvate metabolism as well as alanine, aspartate, and glutamate metabolism. In contrast, in CQ-treated uRBCs, nine affected metabolic pathways were determined, which involved the same metabolic pathways for uRBCs-AG, except for glutathione metabolism. These findings suggest an evident relationship between AG and CQ associated with metabolic changes in intact RBCs after being exposed to the treatment. The metabolomics results could allow useful comprehensive insights into the underlying mechanism of the action of AG and CQ on red blood cells. Consequently, the ¹H-NMR-based metabolomics approach was successfully utilized to identify the pharmacological effects of AG and CQ on the metabolic variations of uRBCs.

Analytical considerations for reducing the matrix effect for the sphingolipidome quantification in whole blood

Aim: Plasma and serum are widely used blood-derived biofluids for metabolomics and lipidomics assays, but analytes that are present in high concentrations in blood cells cannot be evaluated in those samples and isolating serum or plasma could introduce additional variability in the data. Materials & methods: In this study, we provide a comprehensive method for quantification of the whole blood (WB) sphingolipidome, combining a single-phase extraction method with LC-high-resolution mass spectrometry. Results: We were able to quantify more than 150 sphingolipids, and when compared with paired plasma, WB contained higher concentration of most sphingolipids and individual variations were lower. These findings suggest that WB could be a better alternative to plasma, and potentially guide the evaluation of the sphingolipidome for biomarker discovery.

The Effect of Blood Contained in the Samples on the Metabolomic Profile of Mouse Brain Tissue: A Study by NMR Spectroscopy

(1) Recently, metabolic profiling of the tissue in the native state or extracts of its metabolites has become increasingly important in the field of metabolomics. An important factor, in this case, is the presence of blood in a tissue sample, which can potentially lead to a change in the concentration of tissue metabolites and, as a result, distortion of experimental data and their interpretation. (2) In this paper, the metabolomic profiling based on NMR spectroscopy was performed to determine the effect of blood contained in the studied samples of brain tissue on their metabolomic profile. We used 13 male laboratory CD-1^® IGS mice for this study. The animals were divided into two groups. The first group of animals (n = 7) was subjected to the perfusion procedure, and the second group of animals (n = 6) was not perfused. The brain tissues of the animals were homogenized, and the metabolite fraction was extracted with a water/methanol/chloroform solution. Samples were studied by high-frequency ¹H-NMR spectroscopy with subsequent statistical data analysis. The group comparison was performed with the use of the Student's test. We identified 36 metabolites in the brain tissue with the use of NMR spectroscopy. (3) For the major set of studied metabolites, no significant differences were found in the brain tissue metabolite concentrations in the native state and after the blood removal procedure. (4) Thus, it was shown that the presence of blood does not have a significant effect on the metabolomic profile of the brain in animals without pathologies.

Evaluation of Fumaric Acid and Maleic Acid as Internal Standards for NMR Analysis of Protein Precipitated Plasma, Serum, and Whole Blood

Significant advances have been made in unknown metabolite identification and expansion of the number of quantifiable metabolites in human plasma, serum, and whole blood using NMR spectroscopy. However, reliable quantitation of metabolites is still a challenge. A major bottleneck is the lack of a suitable internal standard that does not interact with the complex blood sample matrix and also does not overlap with metabolite peaks apart from exhibiting other favorable characteristics. With the goal of addressing this challenge, a comprehensive investigation of fumaric and maleic acids as potential internal standards was made along with a comparison with the conventional standards, TSP (trimethylsilylpropionic acid) and DSS (trimethylsilylpropanesulfonic acid). Both fumaric acid and maleic acid exhibited a surprisingly high performance with a quantitation error <1%, while the TSP and DSS caused an average error of up to 35% in plasma, serum, and whole blood. Further, the results indicate that while fumaric acid is a robust standard for all three biospecimens, maleic acid is suitable for only plasma and serum. Maleic acid is not suited for the analysis of whole blood due to its overlap with coenzyme peaks. These findings provide new opportunities for improved and accurate quantitation of metabolites in human plasma, serum, and whole blood using NMR spectroscopy. Moreover, the use of protein precipitation prior to NMR analysis mirrors the sample preparation commonly used for mass spectrometry based metabolomics, such that these findings further strengthen efforts to combine and compare NMR and MS based metabolite data of human plasma, serum, and whole blood for metabolomics based research.

NMR-Based Metabolomics

Nuclear magnetic resonance (NMR) spectroscopy is a major analytical method used in the growing field of metabolomics. Although NMR is relatively less sensitive than mass spectrometry, this analytical platform has numerous characteristics including its high reproducibility and quantitative abilities, its nonselective and noninvasive nature, and the ability to identify unknown metabolites in complex mixtures and trace the downstream products of isotope labeled substrates ex vivo, in vivo, or in vitro. Metabolomic analysis of highly complex biological mixtures has benefitted from the advances in both NMR data acquisition and analysis methods. Although metabolomics applications span a wide range of disciplines, a majority has focused on understanding, preventing, diagnosing, and managing human diseases. This chapter describes NMR-based methods relevant to the rapidly expanding metabolomics field.

Diagnosis of papillary thyroid carcinoma by 1H NMR spectroscopy-based metabolomic analysis of whole blood

The incidence rate of thyroid carcinoma, especially papillary thyroid carcinoma (PTC), has increased significantly over time. As a primary pathway for metastasis, the lymphatic system is an important prognostic factor for PTC patients. Although the metabolic changes in PTC patients have been investigated in extensive studies, few studies focused on the whole blood metabolic profiling of PTC patients. In this study, we investigated the ¹H NMR-based metabolic profiles of whole blood samples that were obtained from healthy individuals and PTC patients, with or without lymph node metastasis. The estimation of the predictive potential of metabolites was evaluated using multivariate statistical analyses, which revealed that the whole blood carries information that is sufficient for distinguishing between PTC patients and healthy individuals. However, PTC patients were not well classified as positive or negative according to the lymph nodes. We did not find a metabolite that could discriminate the presence of lymph node metastasis. Further studies with larger sample sizes are needed to elucidate significant metabolites to indicate the presence of lymph node metastasis in patients with PTC.

Metabolomics markers in Neurology: current knowledge and future perspectives for therapeutic targeting

INTRODUCTION

Metabolomics is an emerging approach providing new insights into the metabolic changes and underlying mechanisms involved in the pathogenesis of neurological disorders.

AREAS COVERED

Here, the authors present an overview of the current knowledge of metabolic profiling (metabolomics) to provide critical insight on the role of biochemical markers and metabolic alterations in neurological diseases.

EXPERT OPINION

Elucidation of characteristic metabolic alterations in neurological disorders is crucial for a better understanding of their pathogenesis, and for identifying potential biomarkers and drug targets. Nevertheless, discrepancies in diagnostic criteria, sample handling protocols, and analytical methods still affect the generalizability of current study results.

Psychopharmacological effects of riparin III from Aniba riparia (Nees) Mez. (Lauraceae) supported by metabolic approach and multivariate data analysis

Background

Currently there is a high prevalence of humor disorders such as anxiety and depression throughout the world, especially concerning advanced age patients. Aniba riparia (Nees) Mez. (Lauraceae), popular known as “louro”, can be found from the Amazon through Guianas until the Andes. Previous studies have already reported the isolation of alkamide-type alkaloids such as riparin III (O-methyl-N-2,6-dyhydroxy-benzoyl tyramine) which has demonstrated anxiolytic and antidepressant-like effects in high doses by intraperitoneal administration.

Methods

Experimental protocol was conducted in order to analyze the anxiolytic-like effect of riparin III at lower doses by intravenous administration to Wistar rats (Rattus norvegicus) (n = 5). The experimental approach was designed to last 15 days, divided in 3 distinct periods of five days: control, anxiogenic and treatment periods. The anxiolytic-like effect was evaluated by experimental behavior tests such as open field and elevated plus-maze test, combined with urine metabolic footprint analysis. The urine was collected daily and analyzed by ¹H NMR. Generated data were statistically treated by Principal Component Analysis in order to detect patterns among the distinct periods evaluated as well as biomarkers responsible for its distinction.

Results

It was observed on treatment group that cortisol, biomarker related to physiological stress was reduced, indicating anxiolytic-like effect of riparin III, probably through activation of 5-HT_2A receptors, which was corroborated by behavioral tests.

Conclusion

¹H NMR urine metabolic footprint combined with multivariate data analysis have demonstrated to be an important diagnostic tool to prove the anxiolytic-like effect of riparin III in a more efficient and pragmatic way.

Metabolic Changes in Synaptosomes in an Animal Model of Schizophrenia Revealed by 1H and 1H,13C NMR Spectroscopy

Synaptosomes are isolated nerve terminals that contain synaptic components, including neurotransmitters, metabolites, adhesion/fusion proteins, and nerve terminal receptors. The essential role of synaptosomes in neurotransmission has stimulated keen interest in understanding both their proteomic and metabolic composition. Mass spectrometric (MS) quantification of synaptosomes has illuminated their proteomic composition, but the determination of the metabolic composition by MS has been met with limited success. In this study, we report a proof-of-concept application of one- and two-dimensional nuclear magnetic resonance (NMR) spectroscopy for analyzing the metabolic composition of synaptosomes. We utilize this approach to compare the metabolic composition synaptosomes from a wild-type rat with that from a newly generated genetic rat model (Disc1 svΔ2), which qualitatively recapitulates clinically observed early DISC1 truncations associated with schizophrenia. This study demonstrates the feasibility of using NMR spectroscopy to identify and quantify metabolites within synaptosomal fractions.

Elevated levels of circulating betahydroxybutyrate in pituitary tumor patients may differentiate prolactinomas from other immunohistochemical subtypes

The diagnosis of various histological subtypes of pituitary tumors is made using serum based hormone panel test. However, certain subtypes secrete more than one hormone, making the diagnosis ambiguous. Here, we performed ¹H-NMR based metabolomic analysis of serum and whole-blood from luteinizing/follicle-stimulating (LH/FSH)-secreting (n = 24), prolactinomas (n = 14), and non-functional (NF) (n = 9) tumors. We found elevated levels of betahydroxybutyrate (BHB) in serum and whole-blood (WB) of prolactinomas (0.481 ± 0.211/0.329 ± 0.228 mM in serum/WB), but it was statistically significant (p ≤ 0.0033, Bonferroni correction) only in serum when compared with LH/FSH-secreting tumor patients (0.269 ± 0.139/0.167 ± 0.113 mM in serum/WB). Phenylalanine in NF tumors was found to be elevated in both serum and WB when compared with prolactinomas but it met the statistical significance criteria (p ≤ 0.0028) only in the serum. Alanine (p ≤ 0.011), tyrosine (p ≤ 0.014) and formate (p ≤ 0.011) were also elevated in NF tumors but none showed statistically significance when compared with prolactinomas. Quantification of BHB and the above amino acids in the circulation may aid in the development of blood-based in vitro diagnostic methods which can supplement the currently used serum hormone panel in the diagnosis of various subtypes of pituitary tumors.

Evaluation of sample preparation protocols for quantitative NMR-based metabolomics

INTRODUCTION

Quantification of metabolites in biological fluids and tissues by NMR spectroscopy is challenged by the presence of abundant macromolecules and lipoproteins in samples, which give broad signals in the NMR spectra. To improve the quality of NMR spectra the different protocols for protein and lipid removal from the sample are used.

OBJECTIVES

This work is aimed at the evaluation of the effectiveness of various methods of purification of blood serum from proteins and lipids for ¹H NMR metabolomic profiling.

METHODS

The advantages and limitations of different methods of the sample preparation for NMR-based quantitative metabolomics have been compared, including ultrafiltration, methanol and ethanol extractions with and without additional lipid removal, and methanol-chloroform extraction.

RESULTS

The concentrations of 30 abundant metabolites extracted from human blood serum have been measured. It is found that ultrafiltration provides the best lipid removal, but causes significant and inhomogeneous metabolite losses. Ethanol and methanol extractions demonstrate similar performance with the minimal metabolite losses, and are ideal for fluids and tissues with low lipid content. The additional purification of alcohol extracts from lipids allows for the significant improving of NMR spectra, but causes additional metabolite losses.

CONCLUSIONS

The methanol-chloroform extraction seems to be an optimal method for tissues with the high lipid content, providing a satisfactory lipid removal and low metabolite losses. The ultrafiltration leads to large losses of metabolites (up to 60%) and for this reason is not suitable for quantitative analysis.

Extractive Ratio Analysis NMR Spectroscopy for Metabolite Identification in Complex Biological Mixtures

The complexity of biological mixtures continues to challenge efforts aimed at unknown metabolite identification in the metabolomics field. To address this challenge, we provide a new method to identify related peaks from individual metabolites in complex NMR spectra. Extractive ratio analysis NMR spectroscopy (E-RANSY) builds on our previously described ratio analysis method [ Wei et al. Anal. Chem. 2011 , 83 , 7616 - 7623 ] and exploits the simplified NMR spectra provided by the extraction of metabolites under varied pH conditions. Under such conditions, metabolites from the same biological specimen are extracted differentially, and the resulting NMR spectra exhibit characteristics favorable for unraveling unknown metabolite peaks using ratio analysis. We demonstrate the utility of the E-RANSY method by extracting carboxylic acid containing metabolites from human urine, one of the highly complex biological mixtures encountered in the metabolomics field. E-RANSY performs better than STOCSY and the original RANSY method and offers new avenues to identify unknown metabolites in complex biological mixtures.

Metabolomic Insights into Human Arboviral Infections: Dengue, Chikungunya, and Zika Viruses

The global burden of arboviral diseases and the limited success in controlling them calls for innovative methods to understand arbovirus infections. Metabolomics has been applied to detect alterations in host physiology during infection. This approach relies on mass spectrometry or nuclear magnetic resonance spectroscopy to evaluate how perturbations in biological systems alter metabolic pathways, allowing for differentiation of closely related conditions. Because viruses heavily depend on host resources and pathways, they present unique challenges for characterizing metabolic changes. Here, we review the literature on metabolomics of arboviruses and focus on the interpretation of identified molecular features. Metabolomics has revealed biomarkers that differentiate disease states and outcomes, and has shown similarities in metabolic alterations caused by different viruses (e.g., lipid metabolism). Researchers investigating such metabolomic alterations aim to better understand host⁻virus dynamics, identify diagnostically useful molecular features, discern perturbed pathways for therapeutics, and guide further biochemical research. This review focuses on lessons derived from metabolomics studies on samples from arbovirus-infected humans.

Real-Time Pure Shift HSQC NMR for Untargeted Metabolomics

Sensitivity and resolution are key considerations for NMR applications in general and for metabolomics in particular, where complex mixtures containing hundreds of metabolites over a large range of concentrations are commonly encountered. There is a strong demand for advanced methods that can provide maximal information in the shortest possible time frame. Here, we present the optimization and application of the recently introduced 2D real-time BIRD 1H-13C HSQC experiment for NMR-based metabolomics of aqueous samples at 13C natural abundance. For mouse urine samples, it is demonstrated how this real-time pure shift sensitivity-improved heteronuclear single quantum correlation method provides broadband homonuclear decoupling along the proton detection dimension and thereby significantly improves spectral resolution in regions that are affected by spectral overlap. Moreover, the collapse of the scalar multiplet structure of cross-peaks leads to a sensitivity gain of about 40-50% over a traditional 2D HSQC-SI experiment. The experiment works well over a range of magnetic field strengths and is particularly useful when resonance overlap in crowded regions of the HSQC spectra hampers accurate metabolite identification and quantitation.

Extending the Scope of 1H NMR Spectroscopy for the Analysis of Cellular Coenzyme A and Acetyl Coenzyme A

Coenzyme A (CoA) and acetyl-coenzyme A (acetyl-CoA) are ubiquitous cellular molecules, which mediate hundreds of anabolic and catabolic reactions including energy metabolism. Highly sensitive methods including absorption spectroscopy and mass spectrometry enable their analysis, albeit with many limitations. To date, however, NMR spectroscopy has not been used to analyze these important molecules. Building on our recent efforts, which enabled simultaneous analysis of a large number of metabolites in tissue and blood including many coenzymes and antioxidants ( Anal. Chem. 2016, 88, 4817-24; ibid 2017, 89, 4620-4627), we describe here a new method for identification and quantitation of CoA and acetyl-CoA ex vivo in tissue. Using mouse heart, kidney, liver, brain, and skeletal tissue, we show that a simple ¹H NMR experiment can simultaneously measure these molecules. Identification of the two species involved a comprehensive analysis of the different tissue types using 1D and 2D NMR, in combination with spectral databases for standards, as well as spiking with authentic compounds. Time dependent studies showed that while the acetyl-CoA levels remain unaltered, CoA levels diminish by more than 50% within 24 h, which indicates that CoA is labile in solution; however, degassing the sample with helium gas halted its oxidation. Further, interestingly, we also identified endogenous coenzyme A glutathione disulfide (CoA-S-S-G) in tissue for the first time by NMR and show that CoA, when oxidized in tissue extract, also forms the same disulfide metabolite. The ability to simultaneously visualize absolute concentrations of CoA, acetyl-CoA, and endogenous CoA-S-S-G along with redox coenzymes (NAD⁺, NADH, NADP⁺, NADPH), energy coenzymes (ATP, ADP, AMP), antioxidants (GSH, GSSG), and a vast pool of other metabolites using a single 1D NMR spectrum offers a new avenue in the metabolomics field for investigation of cellular function in health and disease.

Analysis of Plasma, Serum, and Whole Blood Metabolites Using 1H NMR Spectroscopy

Blood is the most widely used biological specimen in the metabolomics field. With its unique characteristics of high reproducibility and excellent quantitation, NMR spectroscopy offers immense benefits for the analysis of blood metabolites. In the metabolomics field, intact blood serum and plasma have been widely used for many years. However, such analysis has met with challenges arising from the deleterious effects of the abundant proteins in serum and plasma. Recent advances have led to the development of improved NMR methods that involve removal of protein before analysis. In particular, protein removal by precipitation using methanol alone or using a mixture of methanol and chloroform was shown to be an optimal method for metabolite recovery and for producing highly resolved NMR spectra. This has led to the absolute quantitation of nearly 70 metabolites in serum and plasma and nearly 80 in whole blood. In this chapter, we describe protocols for the analysis of blood serum, blood plasma, and whole blood metabolites using 1D ¹H NMR spectroscopy methods.

Analysis of Coenzymes and Antioxidants in Tissue and Blood Using 1D 1H NMR Spectroscopy

Cellular coenzymes including coenzyme A (CoA), acetyl coenzyme A (acetyl-CoA), coenzymes of redox reactions and of energy, and antioxidants mediate biochemical reactions fundamental to the functioning of all living cells. The redox coenzymes include NAD⁺ (oxidized nicotinamide adenine dinucleotide), NADH (reduced nicotinamide adenine dinucleotide), NADP⁺ (oxidized nicotinamide adenine dinucleotide phosphate), and NADPH (reduced nicotinamide adenine dinucleotide phosphate); the energy coenzymes include ATP (adenosine triphosphate), ADP (adenosine diphosphate), and AMP (adenosine monophosphate); and the antioxidants include GSSG (oxidized glutathione) and GSH (reduced glutathione). Their measurement is important to better understand cellular metabolism. Recent advances have pushed the limit of metabolite quantitation using NMR methods to an unprecedented level, which offer a new avenue for analysis of the coenzymes and antioxidants. Unlike the conventional enzyme assays, which need separate protocols for analysis, a simple 1D ¹H NMR experiment enables analysis of all these molecular species in one step. In this chapter, we describe protocols for their identification and quantitation in tissue and whole blood using NMR spectroscopy.

A novel method of sample homogenization with the use of a microtome-cryostat apparatus

Quantitative metabolomics places high demands on sample preparation, including a high degree of metabolite extraction and controlled sample weight. In respect to elastic collagen-rich tissues, the existing methods of sample homogenization poorly fit these demands due to incomplete homogenization, sample material loss, or metabolite degradation. Herein, a novel method based on the use of a microtome-cryostat apparatus is proposed. The performance of the cryotome method is compared with the results obtained with the use of a vortex bead beating. NMR-based metabolomic analysis shows that the extraction efficiency and the data scattering for both methods of sample preparation are similar. However, the heat generation during the bead beating causes the destruction of thermally-unstable compounds; besides, it may cause protein hydrolysis, leading to an artificial increase in the amino acid level. The cryotome method of sample homogenization does not cause sample heating, and it seems to be ideal for elastic tissues.

A novel method of homogenization of elastic tissues does not cause sample heating and material losses.

Rapid, Reproducible, Quantifiable NMR Metabolomics: Methanol and Methanol: Chloroform Precipitation for Removal of Macromolecules in Serum and Whole Blood

Background: Though blood is an excellent biofluid for metabolomics, proteins and lipids present in blood can interfere with 1d-¹H NMR spectra and disrupt quantification of metabolites. Here, we present effective macromolecule removal strategies for serum and whole blood (WB) samples. Methods: A variety of macromolecule removal strategies were compared in both WB and serum, along with tests of ultrafiltration alone and in combination with precipitation methods. Results: In healthy human serum, methanol:chloroform:water extraction with ultrafiltration was compared to methanol precipitation with and without ultrafiltration. Methods were tested in healthy pooled human serum, and in serum from patients with sepsis. Effects of long-term storage at −80 °C were tested to explore the impact of macromolecule removal strategy on serum from different conditions. In WB a variety of extraction strategies were tested in two types of WB (from pigs and baboons) to examine the impact of macromolecule removal strategies on different samples. Conclusions: In healthy human serum methanol precipitation of serum with ultrafiltration was superior, but was similar in recovery and variance to methanol:chloroform:water extraction with ultrafiltration in pooled serum from patients with sepsis. In WB, high quality, quantifiable spectra were obtained with the use of a methanol: chloroform precipitation.