Low-Field, Benchtop NMR Spectroscopy as a Potential Tool for Point-of-Care Diagnostics of Metabolic Conditions: Validation, Protocols and Computational Models

Metabolomics for searching validated biomarkers in cancer studies: a decade in review

INTRODUCTION

In the dynamic landscape of modern healthcare, the ability to anticipate and diagnose diseases, particularly in cases where early treatment significantly impacts outcomes, is paramount. Cancer, a complex and heterogeneous disease, underscores the critical importance of early diagnosis for patient survival. The integration of metabolomics information has emerged as a crucial tool, complementing the genotype-phenotype landscape and providing insights into active metabolic mechanisms and disease-induced dysregulated pathways.

AREAS COVERED

This review explores a decade of developments in the search for biomarkers validated within the realm of cancer studies. By critically assessing a diverse array of research articles, clinical trials, and studies, this review aims to present an overview of the methodologies employed and the progress achieved in identifying and validating biomarkers in metabolomics results for various cancer types.

EXPERT OPINION

Through an exploration of more than 800 studies, this review has allowed to establish a general idea about state-of-art in the search of biomarkers in metabolomics studies involving cancer which include certain level of results validation. The potential for metabolites as diagnostic markers to reach the clinic and make a real difference in patient health is substantial, but challenges remain to be explored.

Automated nuclear magnetic resonance fingerprinting of mixtures

Nuclear magnetic resonance (NMR) spectroscopy is a powerful tool for qualitative and quantitative analysis. However, for complex mixtures, determining the speciation from NMR spectra can be tedious and sometimes even unfeasible. On the other hand, identifying and quantifying structural groups in a mixture from NMR spectra is much easier than doing the same for components. We call this group-based approach "NMR fingerprinting." In this work, we show that NMR fingerprinting can even be performed in an automated way, without expert knowledge, based only on standard NMR spectra, namely, 13C, 1H, and 13C DEPT NMR spectra. Our approach is based on the machine-learning method of support vector classification (SVC), which was trained here on thousands of labeled pure-component NMR spectra from open-source data banks. We demonstrate the applicability of the automated NMR fingerprinting using test mixtures, of which spectra were taken using a simple benchtop NMR spectrometer. The results from the NMR fingerprinting agree remarkably well with the ground truth, which was known from the gravimetric preparation of the samples. To facilitate the application of the method, we provide an interactive website (https://nmr-fingerprinting.de), where spectral information can be uploaded and which returns the NMR fingerprint. The NMR fingerprinting can be used in many ways, for example, for process monitoring or thermodynamic modeling using group-contribution methods-or simply as a first step in species analysis.

Mesenchymal stem cell-derived extracellular vesicles for metabolic syndrome therapy: Assessing efficacy with nuclear magnetic resonance spectroscopy

Metabolic syndrome (MetS) represents a cluster of metabolic abnormalities. The prevalence of MetS has surged, transforming it into a pressing public health concern that could potentially affect around 20%-25% of the global population. As MetS continues its ascent, diverse interventions, pharmacological, nonpharmacological and combined have been deployed. Yet, a comprehensive remedy that fully eradicates MetS symptoms remains elusive, compounded by the risks of polypharmacy's emergence. Acknowledging the imperative to grasp MetS's intricate pathologies, deeper insights for future research and therapy optimisation become paramount. Conventional treatments often target specific syndrome elements. However, a novel approach emerges in mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) therapy, promising a holistic shift. MSC-EVs, tiny membranous vesicles secreted by mesenchymal stem cells, have garnered immense attention for their multifaceted bioactivity and regenerative potential. Their ability to modulate inflammation, enhance tissue repair and regulate metabolic pathways has prompted researchers to explore their therapeutic application in MetS. This review primarily aims to provide an overview of how MSC-EVs therapy can improve metabolic parameters in subjects with MetS disease and also introduce the usefulness of NMR spectroscopy in assessing the efficacy of MSC-EVs therapy for treating MetS.

Low-field NMR with multilayer Halbach magnet and NMR selective excitation

This study introduces a low-field NMR spectrometer (LF-NMR) featuring a multilayer Halbach magnet supported by a combined mechanical and electrical shimming system. This setup offers improved field homogeneity and sensitivity compared to spectrometers relying on typical Halbach and dipole magnets. The multilayer Halbach magnet was designed and assembled using three nested cylindrical magnets, with an additional inner Halbach layer that can be rotated for mechanical shimming. The coils and shim-kernel of the electrical shimming system were constructed and coated with layers of zirconia, thermal epoxy, and silver-paste resin to facilitate passive heat dissipation and ensure mechanical and thermal stability. Furthermore, the 7-channel shim coils were divided into two parts connected in parallel, resulting in a reduction of joule heating temperatures from 96.2 to 32.6 °C. Without the shimming system, the Halbach magnet exhibits a field inhomogeneity of approximately 140 ppm over the sample volume. The probehead was designed to incorporate a solenoidal mini coil, integrated into a single planar board. This design choice aimed to enhance sensitivity, minimize [Formula: see text] inhomogeneity, and reduce impedance discrepancies, transmission loss, and signal reflections. Consequently, the resulting linewidth of water within a 3 mm length and 2.4 mm inner diameter sample volume was 4.5 Hz. To demonstrate the effectiveness of spectral editing in LF-NMR applications at 29.934 MHz, we selectively excited hydroxyl and/or methyl protons in neat acetic acid using optimal control pulses calculated through the Krotov algorithm.

Research of integrated shimming Halbach magnet for High strength, compact Benchtop NMR device

Due to production and assembly errors of magnets resulting in reduced magnetic field homogeneity, passive shimming (PS) is necessary when Halbach magnets are used in high-resolution Benchtop Nuclear Magnetic Resonance (BNMR) spectrometer. The conventional PS technique, which places independent PS devices inside the magnet aperture, is no longer applicable to small-aperture compact high-field-strength Halbach magnet studies. In this paper, based on spherical harmonic function expansion, we improve the magnetic field homogeneity by optimizing the moving step of the magnet moving arrays composed of Halbach magnets to generate the corresponding harmonic terms to compensate for the magnetic field. With this approach, the homogeneity of a 1 T Halbach magnet was improved from the original 3913 ppm to 8 ppm in a L10 mm × R2.5 mm of 0.64% copper sulfate doped water sample. This work explores the PS mechanism based on the movement of magnetic blocks, which can be applied in BNMR and other compact high-field strength high-homogeneity Halbach magnets application circumstances.

Successful combination of benchtop nuclear magnetic resonance spectroscopy and chemometric tools: A review

Low-field nuclear magnetic resonance (NMR) has three general modalities: spectroscopy, imaging, and relaxometry. In the last twelve years, the modality of spectroscopy, also known as benchtop NMR, compact NMR, or just low-field NMR, has undergone instrumental development due to new permanent magnetic materials and design. As a result, benchtop NMR has emerged as a powerful analytical tool for use in process analytical control (PAC). Nevertheless, the successful application of NMR devices as an analytical tool in several areas is intrinsically linked to its coupling with different chemometric methods. This review focuses on the evolution of benchtop NMR and chemometrics in chemical analysis, including applications in fuels, foods, pharmaceuticals, biochemicals, drugs, metabolomics, and polymers. The review also presents different low-resolution NMR methods for spectrum acquisition and chemometric techniques for calibration, classification, discrimination, data fusion, calibration transfer, multi-block and multi-way.

Practical Aspects of NMR-Based Metabolomics

While NMR-based metabolomics is only about 20 years old, NMR has been a key part of metabolic and metabolism studies for >40 years. Historically, metabolic researchers used NMR because of its high level of reproducibility, superb instrument stability, facile sample preparation protocols, inherently quantitative character, non-destructive nature, and amenability to automation. In this chapter, we provide a short history of NMR-based metabolomics. We then provide a detailed description of some of the practical aspects of performing NMR-based metabolomics studies including sample preparation, pulse sequence selection, and spectral acquisition and processing. The two different approaches to metabolomics data analysis, targeted vs. untargeted, are briefly outlined. We also describe several software packages to help users process NMR spectra obtained via these two different approaches. We then give several examples of useful or interesting applications of NMR-based metabolomics, ranging from applications to drug toxicology, to identifying inborn errors of metabolism to analyzing the contents of biofluids from dairy cattle. Throughout this chapter, we will highlight the strengths and limitations of NMR-based metabolomics. Additionally, we will conclude with descriptions of recent advances in NMR hardware, methodology, and software and speculate about where NMR-based metabolomics is going in the next 5-10 years.

Degradation of Xenobiotic Pollutants: An Environmentally Sustainable Approach

The ability of microorganisms to detoxify xenobiotic compounds allows them to thrive in a toxic environment using carbon, phosphorus, sulfur, and nitrogen from the available sources. Biotransformation is the most effective and useful metabolic process to degrade xenobiotic compounds. Microorganisms have an exceptional ability due to particular genes, enzymes, and degradative mechanisms. Microorganisms such as bacteria and fungi have unique properties that enable them to partially or completely metabolize the xenobiotic substances in various ecosystems.There are many cutting-edge approaches available to understand the molecular mechanism of degradative processes and pathways to decontaminate or change the core structure of xenobiotics in nature. These methods examine microorganisms, their metabolic machinery, novel proteins, and catabolic genes. This article addresses recent advances and current trends to characterize the catabolic genes, enzymes and the techniques involved in combating the threat of xenobiotic compounds using an eco-friendly approach.

A passive shimming method for Halbach magnet based on magnetic sheet arrays

Halbach magnet has great potential in nuclear magnetic resonance device, where the field homogeneity requirement puts heavy demands on high efficiencypassive shimming (PS) technique. Conventional PS involves a tedious iteration process of the magnetic block/sheet number and positions optimization. In this paper, we propose a PS method based on magnetic sheet arrays (MSAs) targeting at spherical harmonic basis up to the 3rd order including dedicated composition of Y(4Z2-X2-Y2), Z3 and X(4Z2-X2-Y2) (n = 3, m = -1,0,1) with cross terms to implement structural field compensation. With this approach, the homogeneity of a 0.5 T Halbach magnet was improved from the original 811 ppm to 4.7 ppm in a L15 mm × R2.5 mm water sample. Rough shimming in another 0.93 T Halbach magnet also improved the homogeneity from 1103 ppm to 125 ppm in R2.5 mm sphere. This work provides a flexible, convenient PS method based on MSAs for compact Halbach magnet, which can be applied in NMR spectrometers and other high homogeneity application circumstances.

Updates and Original Case Studies Focused on the NMR-Linked Metabolomics Analysis of Human Oral Fluids Part I: Emerging Platforms and Perspectives

1H NMR-based metabolomics analysis of human saliva, other oral fluids, and/or tissue biopsies serves as a valuable technique for the exploration of metabolic processes, and when associated with ’state-of-the-art’ multivariate (MV) statistical analysis strategies, provides a powerful means of examining the identification of characteristic metabolite patterns, which may serve to differentiate between patients with oral health conditions (e.g., periodontitis, dental caries, and oral cancers) and age-matched heathy controls. This approach may also be employed to explore such discriminatory signatures in the salivary 1H NMR profiles of patients with systemic diseases, and to date, these have included diabetes, Sjörgen’s syndrome, cancers, neurological conditions such as Alzheimer’s disease, and viral infections. However, such investigations are complicated in view of quite a large number of serious inconsistencies between the different studies performed by independent research groups globally; these include differing protocols and routes for saliva sample collection (e.g., stimulated versus unstimulated samples), their timings (particularly the oral activity abstention period involved, which may range from one to 12 h or more), and methods for sample transport, storage, and preparation for NMR analysis, not to mention a very wide variety of demographic variables that may influence salivary metabolite concentrations, notably the age, gender, ethnic origin, salivary flow-rate, lifestyles, diets, and smoking status of participant donors, together with their exposure to any other possible convoluting environmental factors. In view of the explosive increase in reported salivary metabolomics investigations, in this update, we critically review a wide range of critical considerations for the successful performance of such experiments. These include the nature, composite sources, and biomolecular status of human saliva samples; the merits of these samples as media for the screening of disease biomarkers, notably their facile, unsupervised collection; and the different classes of such metabolomics investigations possible. Also encompassed is an account of the history of NMR-based salivary metabolomics; our recommended regimens for the collection, transport, and storage of saliva samples, along with their preparation for NMR analysis; frequently employed pulse sequences for the NMR analysis of these samples; the supreme resonance assignment benefits offered by homo- and heteronuclear two-dimensional NMR techniques; deliberations regarding salivary biomolecule quantification approaches employed for such studies, including the preprocessing and bucketing of multianalyte salivary NMR spectra, and the normalization, transformation, and scaling of datasets therefrom; salivary phenotype analysis, featuring the segregation of a range of different metabolites into ‘pools’ grouped according to their potential physiological sources; and lastly, future prospects afforded by the applications of LF benchtop NMR spectrometers for direct evaluations of the oral or systemic health status of patients at clinical ‘point-of-contact’ sites, e.g., dental surgeries. This commentary is then concluded with appropriate recommendations for the conduct of future salivary metabolomics studies. Also included are two original case studies featuring investigations of (1) the 1H NMR resonance line-widths of selected biomolecules and their possible dependence on biomacromolecular binding equilibria, and (2) the combined univariate (UV) and MV analysis of saliva specimens collected from a large group of healthy control participants in order to potentially delineate the possible origins of biomolecules therein, particularly host- versus oral microbiome-derived sources. In a follow-up publication, Part II of this series, we conduct censorious reviews of reported observations acquired from a diversity of salivary metabolomics investigations performed to evaluate both localized oral and non-oral diseases. Perplexing problems encountered with these again include those arising from sample collection and preparation protocols, along with 1H NMR spectral misassignments.

Direct low field J-edited diffusional proton NMR spectroscopic measurement of COVID-19 inflammatory biomarkers in human serum

A JEDI NMR pulse experiment incorporating relaxation, diffusion and J-modulation peak editing was implemented at a low field (80 MHz) spectrometer system to quantify two recently discovered plasma markers of SARS-CoV-2 infection and general inflammation.

Preliminary demonstration of benchtop NMR metabolic profiling of feline urine: chronic kidney disease as a case study

Objective

The use of benchtop metabolic profiling technology based on nuclear magnetic resonance (NMR) was evaluated in a small cohort of cats with a view to applying this as a viable and rapid metabolic tool to support clinical decision making.

Results

Urinary metabolites were analysed from four subjects consisting of two healthy controls and two chronic kidney disease (CKD) IRIS stage 2 cases. The study identified 15 metabolites in cats with CKD that were different from the controls. Among them were acetate, creatinine, citrate, taurine, glycine, serine and threonine. Benchtop NMR technology is capable of distinguishing between chronic kidney disease case and control samples in a pilot feline cohort based on metabolic profile. We offer perspectives on the further development of this pilot work and the potential of the technology, when combined with sample databases and computational intelligence techniques to offer a clinical decision support tool not only for cases of renal disease but other metabolic conditions in the future.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13104-021-05888-y.

New Algorithm by Maximizing Mutual Information for Correction of Frequency Drifts Arising from One-Dimensional NMR Spectroscopic Data Acquisition

Benchtop nuclear magnetic resonance (NMR) instruments are getting popular these days. However, the obtained spectra sometimes suffer from significant frequency drifts, which cause difficulty in accumulating the raw data. In this paper, a new algorithm for correction of frequency drifts is proposed, which operates by maximizing mutual information between the obtained spectroscopic data. The algorithm worked well for both ¹H and ¹⁹F NMR spectroscopic data, even in the case of very noisy ones. In comparison with the previously reported algorithms, the present algorithm has an advantage that NMR spectra complicated by signal overlapping and spin coupling can be handled without difficulty. This makes the present algorithm particularly advantageous for application of benchtop NMR spectrometers in organic chemistry.

Benchtop nuclear magnetic resonance-based metabolomic approach for the diagnosis of bovine tuberculosis

Even though enormous efforts and control strategies have been implemented, bovine tuberculosis (TB) remains a significant source of health and socioeconomic concern. The standard method used in TB eradication programs for in vivo detection is the tuberculin skin test. However, the specificity of the tuberculin skin test is affected by infection with non-tuberculous mycobacteria or by vaccination. Thus, some animals are not correctly diagnosed. This study aimed first to identify a plasma metabolic TB profile by high-field (HF) nuclear magnetic resonance (NMR) spectroscopy and second measure this characteristic TB metabolic profile using low-field benchtop (LF) NMR as an affordable molecular technology for TB diagnosis. Plasma samples from cattle diagnosed with TB (derivation set, n = 11), diagnosed with paratuberculosis (PTB, n = 10), PTB-vaccinated healthy control (n = 10) and healthy PTB-unvaccinated control (n = 10) were analyzed by NMR. Unsupervised Principal Component Analysis (PCA) was used to identify metabolic differences between groups. We identified 14 metabolites significantly different between TB and control animals. The second group of TB animals was used to validate the results (validation set, n = 14). Predictive models based on metabolic fingerprint acquired by both HF and LF NMR spectroscopy successfully identified TB versus control subjects (Area under the curve of Receiver Operating Characteristic over 0.92, in both models; Confidence Interval 0.77-1). In summary, plasma fingerprinting using HF and LF-NMR differentiated TB subjects from uninfected animals, and PTB and PTB-vaccinated subjects who may provide a TB-false positive, highlighting the use of LF-NMR-based metabolomics as a complementary or alternative diagnostic tool to the current diagnostic methods.

Nuclear Magnetic Resonance Spectroscopy in Clinical Metabolomics and Personalized Medicine: Current Challenges and Perspectives

Personalized medicine is probably the most promising area being developed in modern medicine. This approach attempts to optimize the therapies and the patient care based on the individual patient characteristics. Its success highly depends on the way the characterization of the disease and its evolution, the patient’s classification, its follow-up and the treatment could be optimized. Thus, personalized medicine must combine innovative tools to measure, integrate and model data. Towards this goal, clinical metabolomics appears as ideally suited to obtain relevant information. Indeed, the metabolomics signature brings crucial insight to stratify patients according to their responses to a pathology and/or a treatment, to provide prognostic and diagnostic biomarkers, and to improve therapeutic outcomes. However, the translation of metabolomics from laboratory studies to clinical practice remains a subsequent challenge. Nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) are the two key platforms for the measurement of the metabolome. NMR has several advantages and features that are essential in clinical metabolomics. Indeed, NMR spectroscopy is inherently very robust, reproducible, unbiased, quantitative, informative at the structural molecular level, requires little sample preparation and reduced data processing. NMR is also well adapted to the measurement of large cohorts, to multi-sites and to longitudinal studies. This review focus on the potential of NMR in the context of clinical metabolomics and personalized medicine. Starting with the current status of NMR-based metabolomics at the clinical level and highlighting its strengths, weaknesses and challenges, this article also explores how, far from the initial “opposition” or “competition”, NMR and MS have been integrated and have demonstrated a great complementarity, in terms of sample classification and biomarker identification. Finally, a perspective discussion provides insight into the current methodological developments that could significantly raise NMR as a more resolutive, sensitive and accessible tool for clinical applications and point-of-care diagnosis. Thanks to these advances, NMR has a strong potential to join the other analytical tools currently used in clinical settings.

Alterations in Urine Metabolomics Following Sport-Related Concussion: A 1H NMR-Based Analysis

Objective: Millions of sport-related concussions (SRC) occur annually in North America, and current diagnosis of concussion is based largely on clinical evaluations. The objective of this study was to determine whether urinary metabolites are significantly altered post-SRC compared to pre-injury.

Setting: Outpatient sports medicine clinic.

Participants: Twenty-six male youth sport participants.

Methods: Urine was analyzed pre-injury and after SRC by ¹H NMR spectroscopy. Data were analyzed using multivariate statistics, pairwise t-test, and metabolic pathway analysis. Variable importance analysis based on random variable combination (VIAVC) was applied to the entire data set and resulted in a panel of 18 features. Partial least square discriminant analysis was performed exploring the separation between pre-injury and post-SRC groups. Pathway topography analysis was completed to identify biological pathway involvement. Spearman correlations provide support for the relationships between symptom burden and length of return to play and quantifiable metabolic changes in the human urinary metabolome.

Results: Phenylalanine and 3-indoxysulfate were upregulated, while citrate, propylene glycol, 1-methylhistidine, 3-methylhistidine, anserine, and carnosine were downregulated following SRC. A receiver operator curve (ROC) tool constructed using the 18-feature classifier had an area under the curve (AUC) of 0.887. A pairwise t-test found an additional 19 altered features, 7 of which overlapped with the VIAVC analysis. Pathway topology analysis indicated that aminoacyl-tRNA biosynthesis and beta-alanine metabolism were the two pathways most significantly changed. There was a significant positive correlation between post-SRC 2-hydroxybutyrate and the length of return to play (ρ = 0.482, p = 0.02) as well as the number of symptoms and post-SRC lactose (ρ = 0.422, p = 0.036).

Conclusion: We found that ¹H NMR metabolomic urinary analysis can identify a set of metabolites that can correctly classify SRC with an accuracy of 81.6%, suggesting potential for a more objective method of characterizing SRC. Correlations to both the number of symptoms and length of return to play indicated that 2-hydroxybutyrate and lactose may have potential applications as biomarkers for sport-related concussion.

Digesta and Plasma Metabolomics of Rainbow Trout Strains with Varied Tolerance of Plant-Based Diets Highlights Potential for Non-Lethal Assessments of Enteritis Development

The replacement of fishmeal in aquafeeds is essential to the sustainability of aquaculture. Besides the procurement of alternative protein sources, fish can also be selected for better performance on plant-based alternative diets. Rainbow trout (Oncorhynchus mykiss) is one such species in which the strain ARS-Sel has been selected for higher growth and enhanced utilization when fed soy-based diets. The aim of this study was to compare fish growth and plasma and digesta metabolomes between ARS-Sel and two commercial strains (CS-1 and CS-2), when fed plant-protein (PM) and fishmeal-based (FM) diets, and to correlate them with the onset of enteritis. An NMR-metabolomics approach was taken to assess plasma and digesta metabolite profiles. Diet and strain showed significant effects on fish growth, with the ARS-Sel fish receiving the PM diet reaching the highest final weight at sampling. Multivariate analysis revealed differences between plasma and digesta metabolite profiles of ARS-Sel and CS (CS-1 considered together with CS-2) PM-fed groups in the early stages of enteritis development, which was confirmed by intestinal histology. As reported in previous studies, the ARS-Sel strain performed better than the commercial strains when fed the PM diet. Our findings also suggest that metabolomic profiles of plasma and digesta, samples of which can be obtained through non-lethal methods, offer valuable insight in monitoring the occurrence of enteritis in carnivorous aquaculture species due to plant-based diets.

Recent Applications of Benchtop Nuclear Magnetic Resonance Spectroscopy

Benchtop nuclear magnetic resonance (NMR) spectroscopy uses small permanent magnets to generate magnetic fields and therefore offers the advantages of operational simplicity and reasonable cost, presenting a viable alternative to high-field NMR spectroscopy. In particular, the use of benchtop NMR spectroscopy for rapid in-field analysis, e.g., for quality control or forensic science purposes, has attracted considerable attention. As benchtop NMR spectrometers are sufficiently compact to be operated in a fume hood, they can be efficiently used for real-time reaction and process monitoring. This review introduces the recent applications of benchtop NMR spectroscopy in diverse fields, including food science, pharmaceuticals, process and reaction monitoring, metabolomics, and polymer materials.

The Role of Gut Microbiota and Its Produced Metabolites in Obesity, Dyslipidemia, Adipocyte Dysfunction, and Its Interventions

Obesity is becoming an increasing problem worldwide and is often, but not invariably, associated with dyslipidemia. The gut microbiota is increasingly linked to cardiovascular disease, nonalcoholic fatty liver disease, and type 2 diabetes mellitus. However, relatively little focus has been attributed to the role of gut-microbiota-derived metabolites in the development of dyslipidemia and alterations in lipid metabolism. In this review, we discuss current data involved in these processes and point out the therapeutic potentials. We cover the ability of gut microbiota metabolites to alter lipoprotein lipase action, VLDL secretion, and plasma triglyceride levels, and its effects on reverse cholesterol transport, adipocyte dysfunction, and adipose tissue inflammation. Finally, the current intervention strategies for treatment of obesity and dyslipidemia is addressed with emphasis on the role of gut microbiota metabolites and its ability to predict treatment efficacies.

Metabolomic Studies for the Evaluation of Toxicity Induced by Environmental Toxicants on Model Organisms

Environmental pollution causes significant toxicity to ecosystems. Thus, acquiring a deeper understanding of the concentration of environmental pollutants in ecosystems and, clarifying their potential toxicities is of great significance. Environmental metabolomics is a powerful technique in investigating the effects of pollutants on living organisms in the environment. In this review, we cover the different aspects of the environmental metabolomics approach, which allows the acquisition of reliable data. A step-by-step procedure from sample preparation to data interpretation is also discussed. Additionally, other factors, including model organisms and various types of emerging environmental toxicants are discussed. Moreover, we cover the considerations for successful environmental metabolomics as well as the identification of toxic effects based on data interpretation in combination with phenotype assays. Finally, the effects induced by various types of environmental toxicants in model organisms based on the application of environmental metabolomics are also discussed.

Chronic Kidney Disease Cohort Studies: A Guide to Metabolome Analyses

Kidney diseases still pose one of the biggest challenges for global health, and their heterogeneity and often high comorbidity load seriously hinders the unraveling of their underlying pathomechanisms and the delivery of optimal patient care. Metabolomics, the quantitative study of small organic compounds, called metabolites, in a biological specimen, is gaining more and more importance in nephrology research. Conducting a metabolomics study in human kidney disease cohorts, however, requires thorough knowledge about the key workflow steps: study planning, sample collection, metabolomics data acquisition and preprocessing, statistical/bioinformatics data analysis, and results interpretation within a biomedical context. This review provides a guide for future metabolomics studies in human kidney disease cohorts. We will offer an overview of important a priori considerations for metabolomics cohort studies, available analytical as well as statistical/bioinformatics data analysis techniques, and subsequent interpretation of metabolic findings. We will further point out potential research questions for metabolomics studies in the context of kidney diseases and summarize the main results and data availability of important studies already conducted in this field.

Urine NMR-based TB metabolic fingerprinting for the diagnosis of TB in children

Tuberculosis (TB) is a major cause of morbidity and mortality in children, and early diagnosis and treatment are crucial to reduce long-term morbidity and mortality. In this study, we explore whether urine nuclear magnetic resonance (NMR)-based metabolomics could be used to identify differences in the metabolic response of children with different diagnostic certainty of TB. We included 62 children with signs and symptoms of TB and 55 apparently healthy children. Six of the children with presumptive TB had bacteriologically confirmed TB, 52 children with unconfirmed TB, and 4 children with unlikely TB. Urine metabolic fingerprints were identified using high- and low-field proton NMR platforms and assessed with pattern recognition techniques such as principal components analysis and partial least squares discriminant analysis. We observed differences in the metabolic fingerprint of children with bacteriologically confirmed and unconfirmed TB compared to children with unlikely TB (p = 0.041 and p = 0.013, respectively). Moreover, children with unconfirmed TB with X-rays compatible with TB showed differences in the metabolic fingerprint compared to children with non-pathological X-rays (p = 0.009). Differences in the metabolic fingerprint in children with different diagnostic certainty of TB could contribute to a more accurate characterisation of TB in the paediatric population. The use of metabolomics could be useful to improve the prediction of TB progression and diagnosis in children.

Correlation of Metabolic Profiles of Plasma and Cerebrospinal Fluid of High-Grade Glioma Patients

This work compares the metabolic profiles of plasma and the cerebrospinal fluid (CSF) of the patients with high-grade (III and IV) gliomas and the conditionally healthy controls using the wide-range targeted screening of low molecular metabolites by HPLC-MS/MS. The obtained data were analyzed using robust linear regression with Huber’s M-estimates, and a number of metabolites with correlated content in plasma and CSF was identified. The statistical analysis shows a significant correlation of metabolite content in plasma and CSF samples for the majority of metabolites. Several metabolites were shown to have high correlation in the control samples, but not in the glioma patients. This can be due to the specific metabolic processes in the glioma patients or to the damaged integrity of blood-brain barrier. The results of our study may be useful for the understanding of molecular mechanisms underlying the development of gliomas, as well as for the search of potential biomarkers for the minimally invasive diagnostic procedures of gliomas.

CRAFT for NMR lipidomics: Targeting lipid metabolism in leucine-supplemented tumor-bearing mice

Lipid profiling by 1 H-NMR has gained increasing utility in many fields because of its intrinsically quantitative, nondestructive nature and the ability to differentiate small molecules based on their spectral location. Most nuclear magnetic resonance (NMR) techniques for metabolite quantification use frequency domain analysis that involves many user-dependent steps such as phase and baseline correction and quantification by either manual integration or peak fitting. Recently, Bayesian analysis of time-domain NMR data has been shown to reduce operator bias and increase automation in NMR spectroscopy. In this study, we demonstrate the use of CRAFT (complete reduction to amplitude-frequency table), a Bayesian-based approach to automate processing in NMR-based lipidomics using lipid standards and tissue samples of healthy and tumor-bearing mice supplemented with leucine. Complex mixtures of lipid standards were prepared and examined using CRAFT to validate it against conventional Fourier transform (FT)-NMR and derive a fingerprint to be used for analyzing lipid profiles of serum and liver samples. CRAFT and FT-NMR were comparable in accuracy, with CRAFT achieving higher correlation in quantifying several lipid species. Analysis of the serum lipidome of tumor-bearing mice revealed hyperlipidemia and no signs of hepatic triglyceride accumulation compared with that of the healthy group demonstrating that the tumor-bearing mice were in a state of precachexia. Leucine-supplementation was associated with minimal changes in the lipid profile in both tissues. In conclusion, our study demonstrates that the CRAFT method can accurately identify and quantify lipids in complex lipid mixtures and murine tissue samples and, hence, will increase automation and reproducibility in NMR-based lipidomics.

Low-field benchtop NMR spectroscopy as a potential non-stationary tool for point-of-care urinary metabolite tracking in diabetic conditions

We describe the advantages and diagnostic/prognostic significance of low-field, near-portable benchtop NMR spectrometers for the multicomponent metabolomics analysis of targeted and untargeted urinary biomarkers (≥15) in type 2 diabetes patients. Implementation of these facilities at 'point-of-care' clinical sites may yield valuable advantages for the sequential monitoring of diabetic and prediabetic individuals.

Discovery and validation of an NMR-based metabolomic profile in urine as TB biomarker

Despite efforts to improve tuberculosis (TB) detection, limitations in access, quality and timeliness of diagnostic services in low- and middle-income countries are challenging for current TB diagnostics. This study aimed to identify and characterise a metabolic profile of TB in urine by high-field nuclear magnetic resonance (NMR) spectrometry and assess whether the TB metabolic profile is also detected by a low-field benchtop NMR spectrometer. We included 189 patients with tuberculosis, 42 patients with pneumococcal pneumonia, 61 individuals infected with latent tuberculosis and 40 uninfected individuals. We acquired the urine spectra from high and low-field NMR. We characterised a TB metabolic fingerprint from the Principal Component Analysis. We developed a classification model from the Partial Least Squares-Discriminant Analysis and evaluated its performance. We identified a metabolic fingerprint of 31 chemical shift regions assigned to eight metabolites (aminoadipic acid, citrate, creatine, creatinine, glucose, mannitol, phenylalanine, and hippurate). The model developed using low-field NMR urine spectra correctly classified 87.32%, 85.21% and 100% of the TB patients compared to pneumococcal pneumonia patients, LTBI and uninfected individuals, respectively. The model validation correctly classified 84.10% of the TB patients. We have identified and characterised a metabolic profile of TB in urine from a high-field NMR spectrometer and have also detected it using a low-field benchtop NMR spectrometer. The models developed from the metabolic profile of TB identified by both NMR technologies were able to discriminate TB patients from the rest of the study groups and the results were not influenced by anti-TB treatment or TB location. This provides a new approach in the search for possible biomarkers for the diagnosis of TB.

Gradient-based pulse sequences for benchtop NMR spectroscopy

Benchtop NMR spectroscopy has been on the rise for the last decade, by bringing high-resolution NMR in environments that are not easily compatible with high-field NMR. Benchtop spectrometers are accessible, low cost and show an impressive performance in terms of sensitivity with respect to the relatively low associated magnetic field (40-100 MHz). However, their application is limited by the strong and ubiquitous peak overlaps arising from the complex mixtures which are often targeted, often characterized by a great diversity of concentrations and by strong signals from non-deuterated solvents. Such limitations can be addressed by pulse sequences making clever use of magnetic field gradient pulses, capable of performing efficient coherence selection or encoding chemical shift or diffusion information. Gradients pulses are well-known ingredients of high-field pulse sequence recipes, but were only recently made available on benchtop spectrometers, thanks to the introduction of gradient coils in 2015. This article reviews the recent methodological advances making use of gradient pulses on benchtop spectrometers and the applications stemming from these developments. Particular focus is made on solvent suppression schemes, diffusion-encoded, and spatially-encoded experiments, while discussing both methodological advances and subsequent applications. We eventually discuss the exciting development and application perspectives that result from such advances.

Feasibility of precise and reliable glucose quantification in human whole blood samples by 1 tesla benchtop NMR

The standard procedure for blood glucose measurements is enzymatic testing. This method is cheap, but requires small samples of open blood with direct contact to the test medium. In principle, NMR provides non-contact analysis of body fluids, but high-field spectrometers are expensive and cannot be easily utilized under clinical conditions. Low-field NMR systems with permanent magnets are becoming increasingly smaller and more affordable. The studies presented here aim at exploring the capabilities of low-field NMR for measuring glucose concentrations in whole blood. For this purpose, a modern 1 T benchtop NMR spectrometer was used. Challenges arise from broad spectral lines, the glucose peak locations close to the water signal, low SNR and the interference with signals from other blood components. Whole blood as a sample comprises even more boundary conditions: crucial for reliable results are avoiding the separation of plasma and cells by gravitation and reliable reference values. First, the accuracy of glucose levels measured by NMR was tested using aqueous glucose solutions and commercially available bovine plasma. Then, 117 blood samples from oral glucose tolerance testing were measured with minimal preparation by simple pulse-acquire NMR experiments. The analysis itself is the key to achieve high precision, so several approaches were investigated: peak integration, orthogonal projection to latent structure analysis and support vector machine regression. Correlations between results from the NMR spectra and the routine laboratory automated analyzer revealed an RMSE of 7.90 mg/dL for the best model. 91.5% of the model output lies within the limits of the German Medical Association guidelines, which require the glucose measurement to be within 11% of the reference method. It is concluded that spectral quantification of glucose in whole blood samples by high-quality NMR spectrometers operating at 1 T is feasible with sufficient accuracy.

Bacterial Vaginosis: Current Diagnostic Avenues and Future Opportunities

A healthy female genital tract harbors a microbiome dominated by lactic acid and hydrogen peroxide producing bacteria, which provide protection against infections by maintaining a low pH. Changes in the bacterial compositions of the vaginal microbiome can lead to bacterial vaginosis (BV), which is often associated with vaginal inflammation. Bacterial vaginosis increases the risk of acquiring sexually transmitted infections (STIs) like human immunodeficiency virus (HIV) and affects women's reproductive health negatively. In pregnant women, BV can lead to chorioamnionitis and adverse pregnancy outcomes, including preterm premature rupture of the membranes and preterm birth. In order to manage BV effectively, good diagnostic procedures are required. Traditionally clinical and microscopic methods have been used to diagnose BV; however, these methods require skilled staff and time and suffer from reduced sensitivity and specificity. New diagnostics, including highly sensitive and specific point-of-care (POC) tests, treatment modalities and vaccines can be developed based on the identification of biomarkers from the growing pool of vaginal microbiome and vaginal metabolome data. In this review the current and future diagnostic avenues will be discussed.

Benchtop Low-Frequency 60 MHz NMR Analysis of Urine: A Comparative Metabolomics Investigation

Metabolomics techniques are now applied in numerous fields, with the ability to provide information concerning a large number of metabolites from a single sample in a short timeframe. Although high-frequency (HF) nuclear magnetic resonance (NMR) analysis represents a common method of choice to perform such studies, few investigations employing low-frequency (LF) NMR spectrometers have yet been published. Herein, we apply and contrast LF and HF ¹H-NMR metabolomics approaches to the study of urine samples collected from type 2 diabetic patients (T2D), and apply a comparative investigation with healthy controls. Additionally, we explore the capabilities of LF ¹H-¹H 2D correlation spectroscopy (COSY) experiments regarding the determination of metabolites, their resolution and associated analyses in human urine samples. T2D samples were readily distinguishable from controls, with several metabolites, particularly glucose, being associated with this distinction. Comparable results were obtained with HF and LF spectrometers. Linear correlation analyses were performed to derive relationships between the intensities of 1D and 2D resonances of several metabolites, and R² values obtained were able to confirm these, an observation attesting to the validity of employing 2D LF experiments for future applications in metabolomics studies. Our data suggest that LF spectrometers may prove to be easy-to-use, compact and inexpensive tools to perform routine metabolomics analyses in laboratories and ‘point-of-care’ sites. Furthermore, the quality of 2D spectra obtained from these instruments in half an hour would broaden the horizon of their potential applications.

Chemical Constituents with GNMT-Promoter-Enhancing and NRF2-Reduction Activities from Taiwan Agarwood Excoecaria formosana

Hepatocellular carcinoma (HCC) is considered to be a silent killer, and was the fourth leading global cause of cancer deaths in 2018. For now, sorafenib is the only approved drug for advanced HCC treatment. The introduction of additional chemopreventive agents and/or adjuvant therapies may be helpful for the treatment of HCC. After screening 3000 methanolic extracts from the Formosan plant extract bank, Excoecaria formosana showed glycine N-methyltransferase (GNMT)-promoter-enhancing and nuclear factor erythroid 2-related factor 2 (NRF2)-suppressing activities. Further, the investigation of the whole plant of E. formosana led to the isolation of a new steroid, 7α-hydroperoxysitosterol-3-O-β-d-(6-O-palmitoyl)glucopyranoside (1); two new coumarinolignans, excoecoumarin A (2) and excoecoumarin B (3); a new diterpene, excoeterpenol A (4); and 40 known compounds (5-44). Among them, Compounds 38 and 40-44 at a 100 μM concentration showed a 2.97 ± 0.27-, 3.17 ± 1.03-, 2.73 ± 0.23-, 2.63 ± 0.14-, 6.57 ± 0.13-, and 2.62 ± 0.05-fold increase in GNMT promoter activity, respectively. In addition, Compounds 40 and 43 could reduce NRF2 activity, a transcription factor associated with drug resistance, in Huh7 cells with relative activity of 33.1 ± 0.2% and 45.2 ± 2.5%. These results provided the basis for the utilization of Taiwan agarwood for the development of anti-HCC agents.

Metabolomic Studies of Lipid Storage Disorders, with Special Reference to Niemann-Pick Type C Disease: A Critical Review with Future Perspectives

Lysosomal storage disorders (LSDs) are predominantly very rare recessive autosomal neurodegenerative diseases.Sphingolipidoses, a sub-group of LSDs, result from defects in lysosomal enzymes involved in sphingolipid catabolism, and feature disrupted storage systems which trigger complex pathogenic cascades with other organelles collaterally affected. This process leads to cell dysfunction and death, particularly in the central nervous system. One valuable approach to gaining insights into the global impact of lysosomal dysfunction is through metabolomics, which represents a discovery tool for investigating disease-induced modifications in the patterns of large numbers of simultaneously-analysed metabolites, which also features the identification of biomarkers Here, the scope and applications of metabolomics strategies to the investigation of sphingolipidoses is explored in order to facilitate our understanding of the biomolecular basis of these conditions. This review therefore surveys the benefits of applying ’state-of-the-art’ metabolomics strategies, both univariate and multivariate, to sphingolipidoses, particularly Niemann-Pick type C disease. Relevant limitations of these techniques are also discussed, along with the latest advances and developments. We conclude that metabolomics strategies are highly valuable, distinctive bioanalytical techniques for probing LSDs, most especially for the detection and validation of potential biomarkers. They also show much promise for monitoring disease progression and the evaluation of therapeutic strategies and targets.

Enhancing benchtop NMR spectroscopy by means of sample shifting

Benchtop NMR sensitivity enhancement by cyclic, mechanical shifting of a sample to preserve high nuclear spin polarization.

NMR-based metabolomics and fluxomics: developments and future prospects

Recent NMR developments are acting as game changers for metabolomics and fluxomics – a critical and perspective review.

Targeted Clinical Metabolite Profiling Platform for the Stratification of Diabetic Patients

Several small molecule biomarkers have been reported in the literature for prediction and diagnosis of (pre)diabetes, its co-morbidities, and complications. Here, we report the development and validation of a novel, quantitative method for the determination of a selected panel of 34 metabolite biomarkers from human plasma. We selected a panel of metabolites indicative of various clinically-relevant pathogenic stages of diabetes. We combined these candidate biomarkers into a single ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method and optimized it, prioritizing simplicity of sample preparation and time needed for analysis, enabling high-throughput analysis in clinical laboratory settings. We validated the method in terms of limits of detection (LOD) and quantitation (LOQ), linearity (R²), and intra- and inter-day repeatability of each metabolite. The method’s performance was demonstrated in the analysis of selected samples from a diabetes cohort study. Metabolite levels were associated with clinical measurements and kidney complications in type 1 diabetes (T1D) patients. Specifically, both amino acids and amino acid-related analytes, as well as specific bile acids, were associated with macro-albuminuria. Additionally, specific bile acids were associated with glycemic control, anti-hypertensive medication, statin medication, and clinical lipid measurements. The developed analytical method is suitable for robust determination of selected plasma metabolites in the diabetes clinic.

NMR metabolomics: A look ahead

NMR has been used to perform metabolic studies, metabolic profiling and metabolomics in biofluids and tissues for more than 40 years. This close connection between metabolic measurements and NMR has flourished because of NMR's many unique strengths for characterizing the chemical composition of complex mixtures. However, a number of other technologies, including mass spectrometry, have appeared in the past few years that are encroaching on NMR's dominance in metabolomics and metabolic studies. In this brief review, some of the current strengths and existing limitations of NMR-based metabolomics are highlighted. Additionally, a number of recent advances in NMR hardware, methodology and software are also described and these advancements are used to speculate about where NMR-based metabolomics is going, what needs to be done to make it more popular and how it will evolve in the next 5-10 years.

Low-field and benchtop NMR

NMR started at low field. Important discoveries like the first observation of NMR in condensed matter, the spin echo, NMR for chemical analysis, Fourier NMR spectroscopy, 2D NMR spectroscopy and magnetic resonance imaging happened at field strengths considered low today. With time the footprint of the NMR instruments at these field strengths shrunk from the laboratory floor to the tabletop. The first commercial tabletop NMR instruments were compact relaxometers for food analysis followed by mobile relaxometers for materials testing and oil-well exploration culminating in tabletop spectrometers for chemical analysis, capable of performing nearly the whole methodical portfolio of today's high-field instruments. The increasing sensitivity afforded by the lower noise of modern electronics and the unfolding richness of hyperpolarization scenarios along with detection schemes alternative to nuclear induction enable NMR at ultra-low field strengths down to zero applied field, where spin-spin couplings in local fields dominate the residual Zeeman interaction. Miniaturization and cost-reduction of NMR instruments outline current development goals along with the development of smart-phone-like apps to conduct standard NMR analyses.

Blueberry-Based Meals for Obese Patients with Metabolic Syndrome: A Multidisciplinary Metabolomic Pilot Study

A pilot study was carried out on five obese/overweight patients suffering from metabolic syndrome, with the aim to evaluate postprandial effects of high fat/high glycemic load meals enriched by blueberries. Postprandial urine samples were analyzed by ¹H-NMR spectroscopy after 2 and 4 h from ingestion to identify potential markers of blueberry intake. Significant decrease of methylamines, acetoacetate, acetone and succinate, known indicators of type 2 diabetes mellitus, were observed after the intake of meals enriched with blueberries. On the other hand, an accumulation of p-hydroxyphenyl-acetic acid and 3-(3’-hydroxyphenyl)-3-hydropropionic acid originating from gut microbial dehydrogenation of proanthocyanidins and procyanidins was detected. Real-time PCR-analysis of mRNAs obtained from mononuclear blood cells showed significant changes in cytokine gene expression levels after meals integrated with blueberries. In particular, the mRNAs expression of interleukin-6 (IL-6) and Transforming Growth Factor-β (TGF-β), pro and anti-inflammation cytokines, respectively, significantly decreased and increased after blueberry supplementation, indicating a positive impact of blueberry ingestion in the reduction of risk of inflammation. The combined analysis of the urine metabolome and clinical markers represents a promising approach in monitoring the metabolic impact of blueberries in persons with metabolic syndrome.

Progress in low-field benchtop NMR spectroscopy in chemical and biochemical analysis

The employment of spectroscopically-resolved NMR techniques as analytical probes have previously been both prohibitively expensive and logistically challenging in view of the large sizes of high-field facilities. However, with recent advances in the miniaturisation of magnetic resonance technology, low-field, cryogen-free "benchtop" NMR instruments are seeing wider use. Indeed, these miniaturised spectrometers are utilised in areas ranging from food and agricultural analyses, through to human biofluid assays and disease monitoring. Therefore, it is both intrinsically timely and important to highlight current applications of this analytical strategy, and also provide an outlook for the future, where this approach may be applied to a wider range of analytical problems, both qualitatively and quantitatively.