High-resolution magic-angle-spinning NMR spectroscopy for metabolic profiling of intact tissues

Navigating the challenges of engineering composite specialized metabolite pathways in plants

Plants are a valuable source of diverse specialized metabolites with numerous applications. However, these compounds are often produced in limited quantities, particularly under unfavorable ecological conditions. To achieve sufficient levels of target metabolites, alternative strategies such as pathway engineering in heterologous systems like microbes (e.g., bacteria and fungi) or cell-free systems can be employed. Another approach is plant engineering, which aims to either enhance the native production in the original plant or reconstruct the target pathway in a model plant system. Although increasing metabolite production in the native plant is a promising strategy, these source plants are often exotic and pose significant challenges for genetic manipulation. Effective pathway engineering requires comprehensive prior knowledge of the genes and enzymes involved, as well as the precursor, intermediate, branching, and final metabolites. Thus, a thorough elucidation of the biosynthetic pathway is closely linked to successful metabolic engineering in host or model systems. In this review, we highlight recent advances in strategies for biosynthetic pathway elucidation and metabolic engineering. We focus on efforts to engineer complex, multi-step pathways that require the expression of at least eight genes for transient and three genes for stable transformation. Reports on the engineering of complex pathways in stably transformed plants remain relatively scarce. We discuss the major hurdles in pathway elucidation and strategies for overcoming them, followed by an overview of achievements, challenges, and solutions in pathway reconstitution through metabolic engineering. Recent advances including computer-based predictions offer valuable platforms for the sustainable production of specialized metabolites in plants.

Development of an In Situ G Protein-Coupled Receptor Fragment Molecule Screening Approach with High-Resolution Magic Angle Spinning Nuclear Magnetic Resonance

Small molecules are essential for investigating the pharmacology of membrane proteins and remain the most common approach for therapeutically targeting them. However, most experimental small molecule screening methods require ligands containing radiolabels or fluorescent labels and often involve isolating proteins from their cellular environment. Additionally, most conventional screening methods are suited for identifying compounds with moderate to higher affinities (KD < 1 μM) and are less effective at detecting lower affinity compounds, such as weakly binding molecular fragments. To address these limitations, we demonstrated a proof-of-concept application of high-resolution magic angle spinning nuclear magnetic resonance (HRMAS NMR) spectroscopy with small molecules that bind the human A2A adenosine receptor (A2AAR), a class A G protein-coupled receptor. Our approach leverages a streamlined workflow to prepare NMR samples with only milligrams of unpurified cell membranes containing ∼1 μM of A2AAR. Utilizing saturation transfer difference NMR, we identified bound small molecules from spectra recorded within minutes and further derived information on ligand binding poses without the need for detailed structure determination. After establishing optimal criteria for which the HRMAS approach is most sensitive, we leveraged our HRMAS approach to identify and characterize molecular fragments not previously known to be ligands of A2AAR. In molecular docking and simulations, we observed novel binding poses for these fragments, which revealed the potential to grow them into more complex ligands and confirmed HRMAS NMR as a valuable tool for lead compound identification in the context of fragment-based drug discovery.

Metabolomics in the Diagnosis of Bacterial Infections

One of the essential factors in the appropriate treatment of infections is accurate and timely laboratory diagnosis. The correct diagnosis of infections plays a vital role in determining desirable therapy and controlling the spread of pathogens. Traditional methods of infection diagnosis are limited by several factors such as insufficient sensitivity and specificity, being time-consuming and laborious, having a low ability to distinguish infection from non-infectious inflammatory conditions and a low potential to predict treatment outcomes. Therefore, it is necessary to find innovative strategies for detecting specific biomarkers in order to diagnose infections. The rapid advancement of metabolomics makes it possible to determine the pattern of metabolite changes in the both of pathogen and the host during an infection. Metabolomics is a method used to assess the levels and type of metabolites in an organism. Metabolites are of low-molecular-weight compounds produced as a result of metabolic processes and pathways within cells. Metabolomics provides valuable data to detect accurate biomarkers of specific biochemical features directly related to certain phenotypes or conditions. This study aimed to review the applications and progress of metabolomics as a biomarker for the diagnosis of bacterial infections.

MYC-dependent upregulation of the de novo serine and glycine synthesis pathway is a targetable metabolic vulnerability in group 3 medulloblastoma

BACKGROUND

Group 3 medulloblastoma (MBGRP3) represents around 25% of medulloblastomas and is strongly associated with c-MYC (MYC) amplification, which confers significantly worse patient survival. Although elevated MYC expression is a significant molecular feature in MBGRP3, direct targeting of MYC remains elusive, and alternative strategies are needed. The metabolic landscape of MYC-driven MBGRP3 is largely unexplored and may offer novel opportunities for therapies.

METHODS

To study MYC-induced metabolic alterations in MBGRP3, we depleted MYC in isogenic cell-based model systems, followed by 1H high-resolution magic-angle spectroscopy (HRMAS) and stable isotope-resolved metabolomics, to assess changes in intracellular metabolites and pathway dynamics.

RESULTS

Steady-state metabolic profiling revealed consistent MYC-dependent alterations in metabolites involved in one-carbon metabolism such as glycine. 13C-glucose tracing further revealed a reduction in glucose-derived serine and glycine (de novo synthesis) following MYC knockdown, which coincided with lower expression and activity of phosphoglycerate dehydrogenase (PHGDH), the rate-limiting enzyme in this pathway. Furthermore, MYC-overexpressing MBGRP3 cells were more vulnerable to pharmacological inhibition of PHGDH compared to those with low expression. Using in vivo tumor-bearing genetically engineered and xenograft mouse models, pharmacological inhibition of PHGDH increased survival, implicating the de novo serine/glycine synthesis pathway as a pro-survival mechanism sustaining tumor progression. Critically, in primary human medulloblastomas, increased PHGDH expression correlated strongly with both MYC amplification and poorer clinical outcomes.

CONCLUSIONS

Our findings support a MYC-induced dependency on the serine/glycine pathway in MBGRP3 that represents a novel therapeutic treatment strategy for this poor prognosis disease group.

A metabolomic analysis on the toxicological effects of the universal solvent, dimethyl sulfoxide

Dimethyl sulfoxide (DMSO) is a solvent used to dissolve a variety of organic compounds. It is presumed to be non-toxic at concentrations below 1 % v/v, although several studies have demonstrated that low dose DMSO exposure can alter cellular biochemistry. This study evaluated the toxicity of DMSO at 0.0002 % v/v to the Sydney Rock oyster, Saccostrea glomerata, following 7d of exposure. Metabolites were chosen as the toxicity endpoints because they can be used as energy sources and counteract contaminant-induced stress. Relative to seawater controls, exposure to DMSO caused a 74 % significant change in metabolites in the female digestive gland, including decreases in most amino acids, carbohydrates, nicotinamides, and lipids. The female gonad showed a 43 % significant change in metabolites, with decreases in amino acids and carbohydrates, but increases in lipids. The male digestive gland showed a 29 % significant change in metabolites, with increases in lipids. The decline in metabolites in the female digestive gland, but not in the male digestive gland, may be due to their differential metabolic demands. Furthermore, pathway impact analysis revealed that DMSO exposure altered energy metabolism, disturbed osmotic balance, and induced oxidative stress in oysters. Because the effects of DMSO are not uniform across gender and tissue, use of DMSO as a solvent will confound metabolomic experimental results when comparisons among sexes and/or tissues are integral to the experimental design. There is a risk of incomplete dissolution of contaminants unless carrier solvents are used. Therefore, in practice, a solvent control along with a water control is recommended for experimentation.

Comparative lipidomic and metabolomic profiling of mdx and severe mdx-apolipoprotein e-null mice

Despite its notoriously mild phenotype, the dystrophin-deficient mdx mouse is the most common model of Duchenne muscular dystrophy (DMD). By mimicking a human DMD-associated metabolic comorbidity, hyperlipidemia, in mdx mice by inactivating the apolipoprotein E gene (mdx-ApoE) we previously reported severe myofiber damage exacerbation via histology with large fibro-fatty infiltrates and phenotype humanization with ambulation dysfunction when fed a cholesterol- and triglyceride-rich Western diet (mdx-ApoEW). Herein, we performed comparative lipidomic and metabolomic analyses of muscle, liver and serum samples from mdx and mdx-ApoEW mice using solution and high-resolution-magic angle spinning (HR-MAS) 1H-NMR spectroscopy. Compared to mdx and regular chow-fed mdx-ApoE mice, we observed an order of magnitude increase in lipid deposition in gastrocnemius muscle of mdx-ApoEW mice including 11-fold elevations in -CH3 and -CH2 lipids, along with pronounced elevations in serum cholesterol, fatty acid, triglyceride and phospholipids. Hepatic lipids were also elevated but did not correlate with the extent of muscle lipid infiltration or differences in serum lipids. This study provides the first lipometabolomic signature of severe mdx lesions exacerbated by high circulating lipids and lends credence to claims that the liver, the main regulator of whole-body lipoprotein metabolism, may play only a minor role in this process.

High-Resolution Magic Angle Spinning Nuclear Magnetic Resonance Spectroscopy of Paired Clinical Liver Tissue Samples from Hepatocellular Cancer and Surrounding Region

The global burden of liver cancer is increasing. Timely diagnosis is important for optimising the limited available treatment options. Understanding the metabolic consequences of hepatocellular carcinoma (HCC) may lead to more effective treatment options. We aimed to document metabolite differences between HCC and matched surrounding tissues of varying aetiology, obtained at the time of liver resection, and to interpret metabolite changes with clinical findings. High-resolution magic angle spinning nuclear magnetic resonance (HRMAS-NMR) spectroscopy analyses of N = 10 paired HCC and surrounding non-tumour liver tissue samples were undertaken. There were marked HRMAS-NMR differences in lipid levels in HCC tissue compared to matched surrounding tissue and more subtle changes in low-molecular-weight metabolites, particularly when adjusting for patient-specific variability. Differences in lipid-CH3, lipid-CH2, formate, and acetate levels were of particular interest. The obvious differences in lipid content highlight the intricate interplay between metabolic adaptations and cancer cell survival in the complex microenvironment of liver cancer. Differences in formate and acetate might relate to bacterial metabolites. Therefore, documentation of metabolites in HCC tissue according to histology findings in patients is of interest for personalised medicine approaches and for tailoring targeted treatment strategies.

Multivariate curve resolution-based data fusion approaches applied in 1H NMR metabolomic analysis of healthy cohorts

BACKGROUND

Metabolomics plays a critical role in deciphering metabolic alterations within individuals, demanding the use of sophisticated analytical methodologies to navigate its intricate complexity. While many studies focus on single biofluid types, simultaneous analysis of multiple matrices enhances understanding of complex biological mechanisms. Consequently, the development of data fusion methods enabling multiblock analysis becomes essential for comprehensive insights into metabolic dynamics.

RESULTS

This study introduces a novel guideline for jointly analyzing diverse metabolomic datasets (serum, urine, metadata) with a focus on metabolic differences between groups within a healthy cohort. The guideline presents two fusion strategies, 'Low-Level data fusion' (LLDF) and 'Mid-Level data fusion' (MLDF), employing a sequential application of Multivariate Curve Resolution with Alternating Least Squares (MCR-ALS), linking the outcomes of successive analyses. MCR-ALS is a versatile method for analyzing mixed data, adaptable at various stages of data processing-encompassing resonance integration, data compression, and exploratory analysis. The LLDF and MLDF strategies were applied to 1H NMR spectral data extracted from urine and serum samples, coupled with biochemical metadata sourced from 145 healthy volunteers.

SIGNIFICANCE

Both methodologies effectively integrated and analysed multiblock datasets, unveiling the inherent data structure and variables associated with discernible factors among healthy cohorts. While both approaches successfully detected sex-related differences, the MLDF strategy uniquely revealed components linked to age. By applying this analysis, we aim to enhance the interpretation of intricate biological mechanisms and uncover variations that may not be easily discernible through individual data analysis.

Integrated Metabolomics and Proteomics of Symptomatic and Early Presymptomatic States of Colitis

Colitis has a multifactorial pathogenesis with a strong cross-talk among microbiota, hypoxia, and tissue metabolism. Here, we aimed to characterize the molecular signature of the disease in symptomatic and presymptomatic stages of the inflammatory process at the tissue and fecal level. The study is based on two different murine models for colitis, and HR-MAS NMR on "intact" colon tissues and LC-MS/MS on colon tissue extracts were used to derive untargeted metabolomics and proteomics information, respectively. Solution NMR was used to derive metabolomic profiles of the fecal extracts. By combining metabolomic and proteomic analyses of the tissues, we found increased anaerobic glycolysis, accompanied by an altered citric acid cycle and oxidative phosphorylation in inflamed colons; these changes associate with inflammation-induced hypoxia taking place in colon tissues. Different colitis states were also characterized by significantly different metabolomic profiles of fecal extracts, attributable to both the dysbiosis characteristic of colitis as well as the dysregulated tissue metabolism. Strong and distinctive tissue and fecal metabolomic signatures can be detected before the onset of symptoms. Therefore, untargeted metabolomics of tissues and fecal extracts provides a comprehensive picture of the changes accompanying the disease onset already at preclinical stages, highlighting the diagnostic potential of global metabolomics for inflammatory diseases.

NMR spectroscopy for metabolomics in the living system: recent progress and future challenges

Metabolism is a fundamental process that underlies human health and diseases. Nuclear magnetic resonance (NMR) techniques offer a powerful approach to identify metabolic processes and track the flux of metabolites at the molecular level in living systems. An in vitro study through in-cell NMR tracks metabolites in real time and investigates protein structures and dynamics in a state close to their most natural environment. This technique characterizes metabolites and proteins involved in metabolic pathways in prokaryotic and eukaryotic cells. In vivo magnetic resonance spectroscopy (MRS) enables whole-organism metabolic monitoring by visualizing the spatial distribution of metabolites and targeted proteins. One limitation of these NMR techniques is the sensitivity, for which a possible improved approach is through isotopic enrichment or hyperpolarization methods, including dynamic nuclear polarization (DNP) and parahydrogen-induced polarization (PHIP). DNP involves the transfer of high polarization from electronic spins of radicals to surrounding nuclear spins for signal enhancements, allowing the detection of low-abundance metabolites and real-time monitoring of metabolic activities. PHIP enables the transfer of nuclear spin polarization from parahydrogen to other nuclei for signal enhancements, particularly in proton NMR, and has been applied in studies of enzymatic reactions and cell signaling. This review provides an overview of in-cell NMR, in vivo MRS, and hyperpolarization techniques, highlighting their applications in metabolic studies and discussing challenges and future perspectives.

Biodegradable Dual-Network Cellulosic Composite Bioplastic Metafilm for Plastic Substitute

With the escalating environmental and health concerns over petroleum-based plastics, sustainable and biodegradable cellulosic materials are a promising alternative to plastics, yet remain unsatisfied properties such as fragility, inflammability and water sensitivity for practical usage. Herein, we present a novel dual-network design strategy to address these limitations and fabricate a high-performance cellulosic composite bioplastic metafilm with the exceptional mechanical toughness (23.5 MJ m-3 ), flame retardance, and solvent resistance by in situ growth of cyclotriphosphazene-bridged organosilica network within bacterial cellulose matrix. The phosphorus, nitrogen-containing organosilica network, verified by the experimental and theoretical results, plays a triple action on significantly enhancing tensile strength, toughness, flame retardance and water resistance of composite bioplastic metafilm. Furthermore, cellulosic bioplastic composite metafilm demonstrates a higher maximum usage temperature (245 °C), lower thermal expansion coefficient (15.19 ppm °C-1 ), and better solvent resistance than traditional plastics, good biocompatibility and natural biodegradation. Moreover, the composite bioplastic metafilm have a good transparency of average 74 % and a high haze over 80 %, which can serve as an outstanding substrate substitute for commercial polyethylene terephthalate film to address the demand of flexible ITO films. This work paves a creative way to design and manufacture the competitive bioplastic composite to replace daily-used plastics.

Maternal exposure to polystyrene nanoplastics alters fetal brain metabolism in mice

INTRODUCTION

Plastics used in everyday materials accumulate as waste in the environment and degrade over time. The impacts of the resulting particulate micro- and nanoplastics on human health remain largely unknown. In pregnant mice, we recently demonstrated that exposure to nanoplastics throughout gestation and during lactation resulted in changes in brain structure detected on MRI. One possible explanation for this abnormal postnatal brain development is altered fetal brain metabolism.

OBJECTIVES

To determine the effect of maternal exposure to nanoplastics on fetal brain metabolism.

METHODS

Healthy pregnant CD-1 mice were exposed to 50 nm polystyrene nanoplastics at a concentration of 106 ng/L through drinking water during gestation. Fetal brain samples were collected at embryonic day 17.5 (n = 18-21 per group per sex) and snap-frozen in liquid nitrogen. Magic angle spinning nuclear magnetic resonance was used to determine metabolite profiles and their relative concentrations in the fetal brain.

RESULTS

The relative concentrations of gamma-aminobutyric acid (GABA), creatine and glucose were found to decrease by 40%, 21% and 30% respectively following maternal nanoplastic exposure when compared to the controls (p < 0.05). The change in relative concentration of asparagine with nanoplastic exposure was dependent on fetal sex (p < 0.005).

CONCLUSION

Maternal exposure to polystyrene nanoplastics caused abnormal fetal brain metabolism in mice. The present study demonstrates the potential impacts of nanoplastic exposure during fetal development and motivates further studies to evaluate the risk to human pregnancies.

HR-MAS DREAMTIME NMR for Slow Spinning ex Vivo and in Vivo Samples

HR-MAS NMR is a powerful tool, capable of monitoring molecular changes in intact heterogeneous samples. However, one of the biggest limitations of 1H NMR is its narrow spectral width which leads to considerable overlap in complex natural samples. DREAMTIME NMR is a highly selective technique that allows users to isolate suites of metabolites from congested spectra. This permits targeted metabolomics by NMR and is ideal for monitoring specific processes. To date, DREAMTIME has only been employed in solution-state NMR, here it is adapted for HR-MAS applications. At high spinning speeds (>5 kHz), DREAMTIME works with minimal modifications. However, spinning over 3-4 kHz leads to cell lysis, and if maintaining sample integrity is necessary, slower spinning (<2.5 kHz) is required. Very slow spinning (≤500 Hz) is advantageous for in vivo analysis to increase organism survival; however, sidebands from water pose a problem. To address this, a version of DREAMTIME, termed DREAMTIME-SLOWMAS, is introduced. Both techniques are compared at 2500, 500, and 50 Hz, using ex vivo worm tissue. Following this, DREAMTIME-SLOWMAS is applied to monitor key metabolites of anoxic stress in living shrimp at 500 Hz. Thus, standard DREAMTIME works well under MAS conditions and is recommended for samples reswollen in D2O or spun >2500 Hz. For slow spinning in vivo or intact tissue samples, DREAMTIME-SLOWMAS provides an excellent way to target process-specific metabolites while maintaining sample integrity. Overall, DREAMTIME should find widespread application wherever targeted molecular information is required from complex samples with a high degree of spectral overlap.

Identifying placental metabolic biomarkers of preterm birth using nuclear magnetic resonance of intact tissue samples

INTRODUCTION

Our understanding of the etiology of preterm birth (PTB) is incomplete; however, recent evidence has found a strong association between placental dysfunction and PTB. Altered placental metabolism may precede placental dysfunction and therefore the study of placental metabolic profiles could identify early biomarkers of PTB. In this study, we evaluated the placental metabolome in PTB in intact tissue samples using nuclear magnetic resonance (NMR) and spectral editing.

METHODS

Placental tissue samples were collected from nine term pregnancies and nine preterm pregnancies (<37 weeks' gestation). 1H NMR experiments on unprocessed tissue samples were performed using a high field magnet (500 MHz spectrometer) and a comprehensive multiphase NMR probe. The relative concentrations of 23 metabolites were corrected for gestational age and compared between groups.

RESULTS

The relative concentration of valine, glutamate and creatine were significantly decreased while alanine, choline and glucose were elevated in placentas from PTB pregnancies compared to controls (p < 0.05). Multivariate analysis using principal component analysis showed the PTB and control groups were significantly separated (p < 0.0001) and pathway analysis identified perturbations in the glycine, serine and threonine metabolism, aminoacyl-tRNA biosynthesis and valine, leucine and isoleucine biosynthesis pathways.

CONCLUSION

PTB is associated with significant alterations in placental metabolism. This study helps improve our understanding of the etiology of PTB. It also highlights the potential for small molecule metabolites to serve as placental metabolic biomarkers to aid in the prediction and diagnosis of PTB. The results can be translated to clinical use via in utero magnetic resonance spectroscopy.

1H HR-MAS NMR chemical profile and chemometric analysis as a tool for quality control of different cultivars of green tea (Camellia sinensis)

Green tea is a product obtained from the processing of fresh leaves of Camellia sinensis (L.) O. Kuntze species. In this study, the influence of climatic parameters on the chemical composition of green tea cultivars ('Yabukita' and 'Yutakamidori') over the harvest was evaluated using HR-MAS NMR. 'Yabukita' showed higher concentrations of epicatechin while higher amounts of theanine and caffeine were found in 'Yutakamidori'. The decline of theanine was associated with high average maximum temperature and solar radiation index, this latter also seemed to be responsible for relevant changes in epicatechin concentrations. It was not possible to associate any trend between climatic parameters and caffeine concentration. Fluctuations in linolenic acid concentration were monitored during the harvest period and were associated with the plant's defense mechanism. Monitoring of green tea over seasons and correlating the fluctuations of compounds to climatic parameters might become an efficient strategy for establishing quality standards for green teas.

A roadmap to high-resolution standard microcoil MAS NMR spectroscopy for metabolomics

Current microcoil probe technology has emerged as a significant advancement in NMR applications to biofluids research. It has continued to excel as a hyphenated tool with other prominent microdevices, opening many new possibilities in multiple omics fields. However, this does not hold for biological samples such as intact tissue or organisms, due to the considerable challenges of incorporating the microcoil in a magic-angle spinning (MAS) probe without relinquishing the high-resolution spectral data. Not until 2012 did a microcoil MAS probe show promise in profiling the metabolome in a submilligram tissue biopsy with spectral resolution on par with conventional high-resolution MAS (HR-MAS) NMR. This result subsequently triggered a great interest in the possibility of NMR analysis with microgram tissues and striving toward the probe development of "high-resolution" capable microcoil MAS NMR spectroscopy. This review gives an overview of the issues and challenges in the probe development and summarizes the advancements toward metabolomics.

To metabolomics and beyond: a technological portfolio to investigate cancer metabolism

Tumour cells have exquisite flexibility in reprogramming their metabolism in order to support tumour initiation, progression, metastasis and resistance to therapies. These reprogrammed activities include a complete rewiring of the bioenergetic, biosynthetic and redox status to sustain the increased energetic demand of the cells. Over the last decades, the cancer metabolism field has seen an explosion of new biochemical technologies giving more tools than ever before to navigate this complexity. Within a cell or a tissue, the metabolites constitute the direct signature of the molecular phenotype and thus their profiling has concrete clinical applications in oncology. Metabolomics and fluxomics, are key technological approaches that mainly revolutionized the field enabling researchers to have both a qualitative and mechanistic model of the biochemical activities in cancer. Furthermore, the upgrade from bulk to single-cell analysis technologies provided unprecedented opportunity to investigate cancer biology at cellular resolution allowing an in depth quantitative analysis of complex and heterogenous diseases. More recently, the advent of functional genomic screening allowed the identification of molecular pathways, cellular processes, biomarkers and novel therapeutic targets that in concert with other technologies allow patient stratification and identification of new treatment regimens. This review is intended to be a guide for researchers to cancer metabolism, highlighting current and emerging technologies, emphasizing advantages, disadvantages and applications with the potential of leading the development of innovative anti-cancer therapies.

Maternal exposure to polystyrene microplastics alters placental metabolism in mice

INTRODUCTION

The rapid growth in the worldwide use of plastics has resulted in a vast accumulation of microplastics in the air, soil and water. The impact of these microplastics on pregnancy and fetal development remains largely unknown. In pregnant mice, we recently demonstrated that exposure to micro- and nanoplastics throughout gestation resulted in significant fetal growth restriction. One possible explanation for reduced fetal growth is abnormal placental metabolism.

OBJECTIVES

To evaluate the effect of maternal exposure to microplastics on placental metabolism.

METHODS

In the present study, CD-1 pregnant mice were exposed to 5 μm polystyrene microplastics in filtered drinking water at one of four concentrations (0 ng/L (controls), 10² ng/L, 10⁴ ng/L, 10⁶ ng/L) throughout gestation (n = 7-11/group). At embryonic day 17.5, placental tissue samples were collected (n = 28-44/group). Metabolite profiles were determined using ¹ H high-resolution magic angle spinning magnetic resonance spectroscopy.

RESULTS

The relative concentration of lysine (p = 0.003) and glucose (p < 0.0001) in the placenta were found to decrease with increasing microplastic concentrations, with a significant reduction at the highest exposure concentration. Multivariate analysis identified shifts in the metabolic profile with MP exposure and pathway analysis identified perturbations in the biotin metabolism, lysine degradation, and glycolysis/gluconeogenesis pathways.

CONCLUSION

Maternal exposure to microplastics resulted in significant alterations in placental metabolism. This study highlights the potential impact of microplastic exposure on pregnancy outcomes and that efforts should be made to minimize exposure to plastics, particularly during pregnancy.

How to employ metabolomic analysis to research on functions of prebiotics and probiotics in poultry gut health?

Gut health can be considered one of the major, manageable constituents of the animal immunity and performance. The fast spread of intestinal diseases, and increase of antimicrobial resistance have been observed, therefore the intestinal health has become not only economically relevant, but also highly important subject addressing the interest of public health. It is expected, that the strategies to control infections should be based on development of natural immunity in animals and producing resilient flocks using natural solutions, whilst eliminating antibiotics and veterinary medicinal products from action. Probiotics and prebiotics have been favored, because they have potential to directly or indirectly optimize intestinal health by manipulating the metabolism of the intestinal tract, including the microbiota. Studying the metabolome of probiotics and gut environment, both in vivo, or using the in vitro models, is required to attain the scientific understanding about the functions of bioactive compounds in development of gut health and life lasting immunity. There is a practical need to identify new metabolites being the key bioactive agents regulating biochemical pathways of systems associated with gut (gut-associated axes). Technological advancement in metabolomics studies, and increasing access to the powerful analytical platforms have paved a way to implement metabolomics in exploration of the effects of prebiotics and probiotics on the intestinal health of poultry. In this article, the basic principles of metabolomics in research involving probiotics and probiotics are introduced, together with the overview of existing strategies and suggestions of their use to study metabolome in poultry.

In-cell NMR: Why and how?

NMR spectroscopy has been applied to cells and tissues analysis since its beginnings, as early as 1950. We have attempted to gather here in a didactic fashion the broad diversity of data and ideas that emerged from NMR investigations on living cells. Covering a large proportion of the periodic table, NMR spectroscopy permits scrutiny of a great variety of atomic nuclei in all living organisms non-invasively. It has thus provided quantitative information on cellular atoms and their chemical environment, dynamics, or interactions. We will show that NMR studies have generated valuable knowledge on a vast array of cellular molecules and events, from water, salts, metabolites, cell walls, proteins, nucleic acids, drugs and drug targets, to pH, redox equilibria and chemical reactions. The characterization of such a multitude of objects at the atomic scale has thus shaped our mental representation of cellular life at multiple levels, together with major techniques like mass-spectrometry or microscopies. NMR studies on cells has accompanied the developments of MRI and metabolomics, and various subfields have flourished, coined with appealing names: fluxomics, foodomics, MRI and MRS (i.e. imaging and localized spectroscopy of living tissues, respectively), whole-cell NMR, on-cell ligand-based NMR, systems NMR, cellular structural biology, in-cell NMR… All these have not grown separately, but rather by reinforcing each other like a braided trunk. Hence, we try here to provide an analytical account of a large ensemble of intricately linked approaches, whose integration has been and will be key to their success. We present extensive overviews, firstly on the various types of information provided by NMR in a cellular environment (the "why", oriented towards a broad readership), and secondly on the employed NMR techniques and setups (the "how", where we discuss the past, current and future methods). Each subsection is constructed as a historical anthology, showing how the intrinsic properties of NMR spectroscopy and its developments structured the accessible knowledge on cellular phenomena. Using this systematic approach, we sought i) to make this review accessible to the broadest audience and ii) to highlight some early techniques that may find renewed interest. Finally, we present a brief discussion on what may be potential and desirable developments in the context of integrative studies in biology.

The Potential Role of Metabolomics in Drug-Induced Liver Injury (DILI) Assessment

Drug-induced liver injury (DILI) is one of the most frequent adverse clinical reactions and a relevant cause of morbidity and mortality. Hepatotoxicity is among the major reasons for drug withdrawal during post-market and late development stages, representing a major concern to the pharmaceutical industry. The current biochemical parameters for the detection of DILI are based on enzymes (alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transpeptidase (GGT), alkaline phosphatase (ALP)) and bilirubin serum levels that are not specific of DILI and therefore there is an increasing interest on novel, specific, DILI biomarkers discovery. Metabolomics has emerged as a tool with a great potential for biomarker discovery, especially in disease diagnosis, and assessment of drug toxicity or efficacy. This review summarizes the multistep approaches in DILI biomarker research and discovery based on metabolomics and the principal outcomes from the research performed in this field. For that purpose, we have reviewed the recent scientific literature from PubMed, Web of Science, EMBASE, and PubTator using the terms “metabolomics”, “DILI”, and “humans”. Despite the undoubted contribution of metabolomics to our understanding of the underlying mechanisms of DILI and the identification of promising novel metabolite biomarkers, there are still some inconsistencies and limitations that hinder the translation of these research findings into general clinical practice, probably due to the variability of the methods used as well to the different mechanisms elicited by the DILI causing agent.

Plant metabolomics: a new strategy and tool for quality evaluation of Chinese medicinal materials

The present quality control method of Chinese medicinal materials (CMM) has obvious deficiency, which cannot be compatible with the multi-target and multi-component characteristics and production process of CMM. Plant metabolomics with a huge impetus to comprehensively characterize the metabolites and clarify the complexity and integrity of CMM, has been widely used in the research of CMM. This article comprehensively reviewed the application of plant metabolomics in the quality control of CMM. It introduced the concept, technique, and application examples, discussed the prospects, limitations, improvements of plant metabolomics. MS and NMR, as important techniques for plant metabolomics, are mainly highlighted in the case references. The purpose of this article is to clarify the advantage of plants metabolomics for promoting the optimization of the CMM quality control system and proposing a system approach to realize the overall quality control of CMM based on plant metabolomics combined with multidisciplinary method.

Metabolic Profiling of Thymic Epithelial Tumors Hints to a Strong Warburg Effect, Glutaminolysis and Precarious Redox Homeostasis as Potential Therapeutic Targets

Simple Summary

Thymomas and thymic carcinomas (TCs) are malignant thymic epithelial tumors (TETs) with poor outcome, if non-resectable. Metabolic signatures of TETs have not yet been studied and may offer new therapeutic options. This is the first metabolomics investigation on thymic epithelial tumors employing nuclear magnetic resonance spectroscopy of tissue samples. We could detect and quantify up to 37 metabolites in the major tumor subtypes, including acetylcholine that was not previously detected in other non-endocrine cancers. A metabolite-based cluster analysis distinguished three clinically relevant tumor subgroups, namely indolent and aggressive thymomas, as well as TCs. A metabolite-based metabolic pathway analysis also gave hints to activated metabolic pathways shared between aggressive thymomas and TCs. This finding was largely backed by enrichment of these pathways at the transcriptomic level in a large, publicly available, independent TET dataset. Due to the differential expression of metabolites in thymic epithelial tumors versus normal thymus, pathways related to proline, cysteine, glutathione, lactate and glutamine appear as promising therapeutic targets. From these findings, inhibitors of glutaminolysis and of the downstream TCA cycle are anticipated to be rational therapeutic strategies. If our results can be confirmed in future, sufficiently powered studies, metabolic signatures may contribute to the identification of new therapeutic options for aggressive thymomas and TCs.

Abstract

Thymomas and thymic carcinomas (TC) are malignant thymic epithelial tumors (TETs) with poor outcome, if non-resectable. Metabolic signatures of TETs have not yet been studied and may offer new therapeutic options. Metabolic profiles of snap-frozen thymomas (WHO types A, AB, B1, B2, B3, n = 12) and TCs (n = 3) were determined by high resolution magic angle spinning 1H nuclear magnetic resonance (HRMAS 1H-NMR) spectroscopy. Metabolite-based prediction of active KEGG metabolic pathways was achieved with MetPA. In relation to metabolite-based metabolic pathways, gene expression signatures of TETs (n = 115) were investigated in the public “The Cancer Genome Atlas” (TCGA) dataset using gene set enrichment analysis. Overall, thirty-seven metabolites were quantified in TETs, including acetylcholine that was not previously detected in other non-endocrine cancers. Metabolite-based cluster analysis distinguished clinically indolent (A, AB, B1) and aggressive TETs (B2, B3, TCs). Using MetPA, six KEGG metabolic pathways were predicted to be activated, including proline/arginine, glycolysis and glutathione pathways. The activated pathways as predicted by metabolite-profiling were generally enriched transcriptionally in the independent TCGA dataset. Shared high lactic acid and glutamine levels, together with associated gene expression signatures suggested a strong “Warburg effect”, glutaminolysis and redox homeostasis as potential vulnerabilities that need validation in a large, independent cohort of aggressive TETs. If confirmed, targeting metabolic pathways may eventually prove as adjunct therapeutic options in TETs, since the metabolic features identified here are known to confer resistance to cisplatin-based chemotherapy, kinase inhibitors and immune checkpoint blockers, i.e., currently used therapies for non-resectable TETs.

Diagnostic Value of 1H NMR-Based Metabolomics in Acute Lymphoblastic Leukemia, Acute Myeloid Leukemia, and Breast Cancer

Cancer refers to a massive number of diseases distinguished by the development of abnormal cells that divide uncontrollably and have the capability of infiltration and destroying the normal body tissue. It is critical to detect biomarkers that are early detectable and noninvasive to save millions of lives. The aim of the present work is to use NMR as a noninvasive diagnostic tool for cancer diseases. This study included 30 plasma and 21 urine samples of patients diagnosed with acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML), 25 plasma and 17 urine samples of patients diagnosed with breast cancer (BC), and 9 plasma and urine samples obtained from healthy individuals as controls. They were prepared for NMR measurements; then, the metabolites were identified and the data were analyzed using multivariate statistical procedures. The OPLS-DA score plots clearly discriminated ALL, AML, and BC from healthy controls. Plots of the PLS-DA loadings and S-line plots showed that all metabolites in plasma were greater in BC than in the healthy controls, whereas lactate, O-acetylcarnitine, pyruvate, trimethylamine-N-oxide (TMAO), and glucose were higher in healthy controls than in ALL and AML. On the other hand, urine samples showed lower amounts of lactate, melatonin, pyruvate, and succinate in all of the studied types of cancer when compared to those of healthy controls. 1H NMR can be a successful and noninvasive tool for the diagnosis of different types of cancer.

Rodent models and metabolomics in non-alcoholic fatty liver disease: What can we learn?

Non-alcoholic fatty liver disease (NAFLD) prevalence has increased drastically in recent decades, affecting up to 25% of the world’s population. NAFLD is a spectrum of different diseases that starts with asymptomatic steatosis and continues with development of an inflammatory response called steatohepatitis, which can progress to fibrosis. Several molecular and metabolic changes are required for the hepatocyte to finally vary its function; hence a “multiple hit” hypothesis seems a more accurate proposal. Previous studies and current knowledge suggest that in most cases, NAFLD initiates and progresses through most of nine hallmarks of the disease, although the triggers and mechanisms for these can vary widely. The use of animal models remains crucial for understanding the disease and for developing tools based on biological knowledge. Among certain requirements to be met, a good model must imitate certain aspects of the human NAFLD disorder, be reliable and reproducible, have low mortality, and be compatible with a simple and feasible method. Metabolism studies in these models provides a direct reflection of the workings of the cell and may be a useful approach to better understand the initiation and progression of the disease. Metabolomics seems a valid tool for studying metabolic pathways and crosstalk between organs affected in animal models of NAFLD and for the discovery and validation of relevant biomarkers with biological understanding. In this review, we provide a brief introduction to NAFLD hallmarks, the five groups of animal models available for studying NAFLD and the potential role of metabolomics in the study of experimental NAFLD.

The Potential of Metabolomics in Biomedical Applications

The metabolome offers a dynamic, comprehensive, and precise picture of the phenotype. Current high-throughput technologies have allowed the discovery of relevant metabolites that characterize a wide variety of human phenotypes with respect to health, disease, drug monitoring, and even aging. Metabolomics, parallel to genomics, has led to the discovery of biomarkers and has aided in the understanding of a diversity of molecular mechanisms, highlighting its application in precision medicine. This review focuses on the metabolomics that can be applied to improve human health, as well as its trends and impacts in metabolic and neurodegenerative diseases, cancer, longevity, the exposome, liquid biopsy development, and pharmacometabolomics. The identification of distinct metabolomic profiles will help in the discovery and improvement of clinical strategies to treat human disease. In the years to come, metabolomics will become a tool routinely applied to diagnose and monitor health and disease, aging, or drug development. Biomedical applications of metabolomics can already be foreseen to monitor the progression of metabolic diseases, such as obesity and diabetes, using branched-chain amino acids, acylcarnitines, certain phospholipids, and genomics; these can assess disease severity and predict a potential treatment. Future endeavors should focus on determining the applicability and clinical utility of metabolomic-derived markers and their appropriate implementation in large-scale clinical settings.

Placental metabolite profiles in late gestation for healthy mice

INTRODUCTION

During pregnancy, appropriate placental metabolism is essential for fetuses to reach their growth potential. However, metabolic mechanisms during pregnancy remain poorly understood. Determination of the levels of placental metabolites in healthy pregnancy and how they change throughout gestation is critical for understanding placental function.

OBJECTIVE

To determine the effects of gestational age on placental metabolites using healthy pregnant mice.

METHODS

In the present study, we collected placental tissue samples from healthy pregnant mice at three timepoints in late gestation (n = 16 placentas per gestational age). Metabolite profiles were determined using ¹H high-resolution magic angle spinning magnetic resonance spectroscopy (HRMAS MRS).

RESULTS

Using HRMAS MRS, we identified 14 metabolites in murine placental tissue samples. The relative concentration of 12 of the 14 metabolites remains unchanged throughout late gestation. Lysine was found to decrease significantly (p = 0.04) and glucose showed an inverted U-shape relationship (p = 0.03) with gestational age.

CONCLUSION

This study demonstrated the feasibility of HRMAS MRS to determine relative metabolite concentrations in murine placental tissue. These findings establish baseline levels of placental tissue metabolite profiles and will serve as reference ranges for future studies using mouse models of fetal distress.

Polydextrose with and without Bifidobacterium animalis ssp. lactis 420 drives the prevalence of Akkermansia and improves liver health in a multi-compartmental obesogenic mice study

The past two decades of research have raised gut microbiota composition as a contributing factor to the development of obesity, and higher abundance of certain bacterial species has been linked to the lean phenotype, such as Akkermansia muciniphila. The ability of pre- and probiotics to affect metabolic health could be via microbial community alterations and subsequently changes in metabolite profiles, modulating for example host energy balance via complex signaling pathways. The aim of this mice study was to determine how administration of a prebiotic fiber, polydextrose (PDX) and a probiotic Bifidobacterium animalis ssp. lactis 420 (B420), during high fat diet (HFD; 60 kcal% fat) affects microbiota composition in the gastrointestinal tract and adipose tissue, and metabolite levels in gut and liver. In this study C57Bl/6J mice (N = 200) were split in five treatments and daily gavaged: 1) Normal control (NC); 2) HFD; 3) HFD + PDX; 4) HFD + B420 or 5) HFD + PDX + B420 (HFD+S). At six weeks of treatment intraperitoneal glucose-tolerance test (IPGTT) was performed, and feces were collected at weeks 0, 3, 6 and 9. At end of the intervention, ileum and colon mucosa, adipose tissue and liver samples were collected. The microbiota composition in fecal, ileum, colon and adipose tissue was analyzed using 16S rDNA sequencing, fecal and liver metabolomics were performed by nuclear magnetic resonance (NMR) spectroscopy. It was found that HFD+PDX intervention reduced body weight gain and hepatic fat compared to HFD. Sequencing the mice adipose tissue (MAT) identified Akkermansia and its prevalence was increased in HFD+S group. Furthermore, by the inclusion of PDX, fecal, lleum and colon levels of Akkermansia were increased and liver health was improved as the detoxification capacity and levels of methyl-donors were increased. These new results demonstrate how PDX and B420 can affect the interactions between gut, liver and adipose tissue.

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

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

Statistical analysis in metabolic phenotyping

Metabolic phenotyping is an important tool in translational biomedical research. The advanced analytical technologies commonly used for phenotyping, including mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy, generate complex data requiring tailored statistical analysis methods. Detailed protocols have been published for data acquisition by liquid NMR, solid-state NMR, ultra-performance liquid chromatography (LC-)MS and gas chromatography (GC-)MS on biofluids or tissues and their preprocessing. Here we propose an efficient protocol (guidelines and software) for statistical analysis of metabolic data generated by these methods. Code for all steps is provided, and no prior coding skill is necessary. We offer efficient solutions for the different steps required within the complete phenotyping data analytics workflow: scaling, normalization, outlier detection, multivariate analysis to explore and model study-related effects, selection of candidate biomarkers, validation, multiple testing correction and performance evaluation of statistical models. We also provide a statistical power calculation algorithm and safeguards to ensure robust and meaningful experimental designs that deliver reliable results. We exemplify the protocol with a two-group classification study and data from an epidemiological cohort; however, the protocol can be easily modified to cover a wider range of experimental designs or incorporate different modeling approaches. This protocol describes a minimal set of analyses needed to rigorously investigate typical datasets encountered in metabolic phenotyping.

Complementary Nuclear Magnetic Resonance-Based Metabolomics Approaches for Glioma Biomarker Identification in a Drosophila melanogaster Model

Human malignant gliomas are the most common type of primary brain tumor. Composed of glial cells and their precursors, they are aggressive and highly invasive, leading to a poor prognosis. Due to the difficulty of surgically removing tumors and their resistance to treatments, novel therapeutic approaches are needed to improve patient life expectancy and comfort. Drosophila melanogaster is a compelling genetic model to better understanding human neurological diseases owing to its high conservation in signaling pathways and cellular content of the brain. Here, glioma has been induced in Drosophila by co-activating the epidermal growth factor receptor and the phosphatidyl-inositol-3 kinase signaling pathways. Complementary nuclear magnetic resonance (NMR) techniques were used to obtain metabolic profiles in the third instar larvae brains. Fresh organs were directly studied by ¹H high resolution-magic angle spinning (HR-MAS) NMR, and brain extracts were analyzed by solution-state ¹H-NMR. Statistical analyses revealed differential metabolic signatures, impacted metabolic pathways, and glioma biomarkers. Each method was efficient to determine biomarkers. The highlighted metabolites including glucose, myo-inositol, sarcosine, glycine, alanine, and pyruvate for solution-state NMR and proline, myo-inositol, acetate, and glucose for HR-MAS show very good performances in discriminating samples according to their nature with data mining based on receiver operating characteristic curves. Combining results allows for a more complete view of induced disturbances and opens the possibility of deciphering the biochemical mechanisms of these tumors. The identified biomarkers provide a means to rebalance specific pathways through targeted metabolic therapy and to study the effects of pharmacological treatments using Drosophila as a model organism.

Covalent modification of franckeite with maleimides: connecting molecules and van der Waals heterostructures

The building of van der Waals heterostructures and the decoration of 2D materials with organic molecules share a common goal: to obtain ultrathin materials with tailored properties. Performing controlled chemistry on van der Waals heterostructures would add an extra level of complexity, providing a pathway towards 2D-2D-0D mixed-dimensional heterostructures. Here we show that thiol-ene-like "click" chemistry can be used to decorate franckeite, a naturally occurring van der Waals heterostructure with maleimide reagents. ATR-IR and NMR analyses corroborate the Michael addition mechanism via the formation of a S-C covalent bond, while Raman and HR-TEM show that the SnS2-PbS alternating structure of franckeite is preserved, and suggest that SnS2 reacts preferentially, which is confirmed through XPS. We illustrate how this methodology can be used to add functional molecular moieties by decorating franckeite with porphyrins. UV-vis-NIR spectroscopy confirms that the chromophore ground state remains operative, showing negligible ground-state interactions with the franckeite. Excited-state interactions across the hybrid interface are revealed. Time-resolved photoluminescence confirms the presence of excited-state deactivation in the linked porphyrin ascribed to energy transfer to the franckeite.

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.

The metabolic reprogramming in acute myeloid leukemia patients depends on their genotype and is a prognostic marker

Leukemic cells display some alterations in metabolic pathways, which play a role in leukemogenesis and in patients' prognosis. To evaluate the characteristics and the impact of this metabolic reprogramming, we explore the bone marrow samples from 54 de novo acute myeloid leukemia (AML) patients, using an untargeted metabolomics approach based on proton high-resolution magic angle spinning-nuclear magnetic resonance. The spectra obtained were subjected to multivariate statistical analysis to find specific metabolome alterations and biomarkers correlated to clinical features. We found that patients display a large diversity of metabolic profiles, according to the different AML cytologic subtypes and molecular statuses. The link between metabolism and molecular status was particularly strong for the oncometabolite 2-hydroxyglutarate (2-HG), whose intracellular production is directly linked to the presence of isocitrate dehydrogenase mutations. Moreover, patients' prognosis was strongly impacted by several metabolites, such as 2-HG that appeared as a good prognostic biomarker in our cohort. Conversely, deregulations in phospholipid metabolism had a negative impact on prognosis through 2 main metabolites (phosphocholine and phosphoethanolamine), which could be potential aggressiveness biomarkers. Finally, we highlighted an overexpression of glutathione and alanine in chemoresistant patients. Overall, our results demonstrate that different metabolic pathways could be activated in leukemic cells according to their phenotype and maturation levels. This confirms that metabolic reprogramming strongly influences prognosis of patients and underscores a particular role of certain metabolites and associated pathways in AML prognosis, suggesting common mechanisms developed by leukemic cells to maintain their aggressiveness even after well-conducted induction chemotherapy.

NMR-Based Metabolomics in Cancer Research

Nuclear magnetic resonance (NMR) spectroscopy offers reproducible quantitative analysis and structural identification of metabolites in various complex biological samples, such as biofluids (plasma, serum, and urine), cells, tissue extracts, and even intact organs. Therefore, NMR-based metabolomics, a mainstream metabolomic platform, has been extensively applied in many research fields, including pharmacology, toxicology, pathophysiology, nutritional intervention, disease diagnosis/prognosis, and microbiology. In particular, NMR-based metabolomics has been successfully used for cancer research to investigate cancer metabolism and identify biomarker and therapeutic targets. This chapter highlights the innovations and challenges of NMR-based metabolomics platform and its applications in cancer research.

Metabolomic-based clinical studies and murine models for acute pancreatitis disease: A review

Acute pancreatitis (AP) is one of the most common gastroenterological disorders requiring hospitalization and is associated with substantial morbidity and mortality. Metabolomics nowadays not only help us to understand cellular metabolism to a degree that was not previously obtainable, but also to reveal the importance of the metabolites in physiological control, disease onset and development. An in-depth understanding of metabolic phenotyping would be therefore crucial for accurate diagnosis, prognosis and precise treatment of AP. In this review, we summarized and addressed the metabolomics design and workflow in AP studies, as well as the results and analysis of the in-depth of research. Based on the metabolic profiling work in both clinical populations and experimental AP models, we described the metabolites with potential utility as biomarkers and the correlation between the altered metabolites and AP status. Moreover, the disturbed metabolic pathways correlated with biological function were discussed in the end. A practical understanding of current and emerging metabolomic approaches applicable to AP and use of the metabolite information presented will aid in designing robust metabolomics and biological experiments that result in identification of unique biomarkers and mechanisms, and ultimately enhanced clinical decision-making.

HR-MAS NMR Applications in Plant Metabolomics

Metabolomics is used to reduce the complexity of plants and to understand the underlying pathways of the plant phenotype. The metabolic profile of plants can be obtained by mass spectrometry or liquid-state NMR. The extraction of metabolites from the sample is necessary for both techniques to obtain the metabolic profile. This extraction step can be eliminated by making use of high-resolution magic angle spinning (HR-MAS) NMR. In this review, an HR-MAS NMR-based workflow is described in more detail, including used pulse sequences in metabolomics. The pre-processing steps of one-dimensional HR-MAS NMR spectra are presented, including spectral alignment, baseline correction, bucketing, normalisation and scaling procedures. We also highlight some of the models which can be used to perform multivariate analysis on the HR-MAS NMR spectra. Finally, applications of HR-MAS NMR in plant metabolomics are described and show that HR-MAS NMR is a powerful tool for plant metabolomics studies.

Mitochondrial Regulation Assessment by 13C-NMR Isotopomer Analysis

Mitochondria play a central role in metabolic reprograming that occurs in numerous disease conditions. A precise evaluation of the extent of mitochondrial involvement in the metabolic alterations is essential for a better definition of metabolically based therapeutic strategies. In this chapter, some simple protocols are presented, using carbon 13 tracers and nuclear magnetic resonance isotopomer analysis, for the evaluation of mitochondrial contributions to intermediary metabolism and the metabolic effects of the implementation of some mitochondrial regulatory mechanisms.

Quantitative Analysis of Oncometabolite 2-Hydroxyglutarate

Gain-of-function mutations of isocitrate dehydrogenase 1 and 2 (IDH1/2) were demonstrated to induce the production and accumulation of oncometabolite 2-hydroxyglutarate (2HG). 2HG is a potent competitor of α-ketoglutarate (α-KG) and can inhibit multiple α-KG-dependent dioxygenases that are critical for regulating the metabolic and epigenetic state of cells. The accumulation of 2HG contributes to elevated risk of malignant tumors. 2HG carries an asymmetric carbon atom in its carbon backbone and therefore occurs in two enantiomers, D-2-hydroxyglutarate (D-2HG) and L-2-hydroxyglutarate (L-2HG). Each enantiomer is produced and metabolized in independent biochemical pathway and catalyzed by different enzymes. The accurate diagnosis of 2HG-related diseases relies on determining the configuration of the two enantiomers. Quantitative methods for analysis of D-2HG and L-2HG have been well developed. These analytical strategies mainly include the use of chiral chromatography medium to facilitate chromatographic separation of enantiomers prior to spectroscopy or mass spectrometry analysis and the use of chiral derivatization reagents to convert the enantiomers to diastereomers with differential physical and chemical properties that can improve their chromatographic separation. Here, we summarize and discuss these established methods for analysis of total 2HG as well as the determination of the enantiomers of D-2HG and L-2HG.

Sample Preparation and Data Analysis for NMR-Based Metabolomics

NMR spectroscopy has become one of the preferred analytical techniques for metabolomics studies due to its inherent nondestructive nature, ability to identify and quantify metabolites simultaneously in a complex mixture, minimal sample preparation requirement, and high degree of experimental reproducibility. NMR-based metabolomics studies involve the measurement and multivariate statistical analysis of metabolites present in biological samples such as biofluids, stool/feces, intestinal content, tissue, and cell extracts by high-resolution NMR spectroscopy-the goal then is to identify and quantify metabolites and evaluate changes of metabolite concentrations in response to some perturbation. Here we describe methodologies for NMR sample preparation of biofluids (serum, saliva, and urine) and stool/feces, intestinal content, and tissues for NMR experiments including extraction of polar metabolites and application of NMR in metabolomics studies. One dimensional (1D) ¹H NMR experiments with different variations such as pre-saturation, relaxation-edited, and diffusion-edited are routinely acquired for profiling and metabolite identification and quantification. 2D homonuclear ¹H-¹H TOCSY and COSY, 2D J-resolved, and heteronuclear ¹H-¹³C HSQC and HMBC are also performed to assist with metabolite identification and quantification. The NMR data are then subjected to targeted and/or untargeted multivariate statistical analysis for biomarker discovery, clinical diagnosis, toxicological studies, molecular phenotyping, and functional genomics.

Functional Metabolomics and Chemoproteomics Approaches Reveal Novel Metabolic Targets for Anticancer Therapy

Cancer cells exhibit different metabolic patterns compared to their normal counterparts. Although the reprogrammed metabolism has been indicated as strong biomarkers of cancer initiation and progression, increasing evidences suggest that metabolic alteration tuned by oncogenic drivers contributes to the occurrence and development of cancers rather than just being a hallmark of cancer. With this notion, targeting cancer metabolism holds promise as a novel anticancer strategy and is embracing its renaissance during the past two decades. Herein we have summarized the most recent developments in omics technology, including both metabolomics and proteomics, and how the combined use of these analytical tools significantly impacts this field by comprehensively and systematically recording the metabolic changes in cancer and hence reveals potential therapeutic targets that function by modulating the disrupted metabolic pathways.

1H NMR metabolic phenotyping of Dipterocarpus alatus as a novel tool for age and growth determination

Dipterocarpus alatus belongs to Family Dipterocarpaceae that can be commonly found in Southeast Asian countries. It is a perennial plant with oval-shaped leaves and oleoresin-rich wood. It has been considered as a multipurpose plant since all parts can be practically utilized. One of the major problems for utilizing Dipterocarpus alatus is the difficulty knowing the exact age as this kind of plant is ready for multipurpose use after 20 years of age. At present, the most commonly used method for determining age of Dipterocarpus alatus is the annual ring estimation. However, this conventional method is unable to provide the high precision and accuracy of age determination due to its limitation including blurry annual rings caused by enriched oleoresin in the wood. The current study aimed to investigate the differences of 1H -NMR spectroscopy-based metabolic profiles from bark and leaf of Dipterocarpus alatus at different ages including 2, 7, 15 and 25 years. Our findings demonstrated that there is a total of 56 metabolites shared between bark and leaf. It is noticeable that bark at different ages exhibited the strongest variation and sugar or sugar derivatives that were found in higher concentrations in bark compared with those in leaf. We found that decreasing levels of certain metabolites including tagatose, 1'kestose and 2'-fucosyllactose exhibited the promising patterns. In conclusion, panel metabolites involved in the sucrose biosynthesis can precisely determine the age and growth of Dipterocarpus alatus.

In vivo γ-aminobutyric acid increase as a biomarker of the epileptogenic zone: An unbiased metabolomics approach

OBJECTIVE

Following surgery, focal seizures relapse in 20% to 50% of cases due to the difficulty of delimiting the epileptogenic zone (EZ) by current imaging or electrophysiological techniques. Here, we evaluate an unbiased metabolomics approach based on ex vivo and in vivo nuclear magnetic resonance spectroscopy (MRS) methods to discriminate the EZ in a mouse model of mesiotemporal lobe epilepsy (MTLE).

METHODS

Four weeks after unilateral injection of kainic acid (KA) into the dorsal hippocampus of mice (KA-MTLE model), we analyzed hippocampal and cortical samples with high-resolution magic angle spinning (HRMAS) magnetic resonance spectroscopy (MRS). Using advanced multivariate statistics, we identified the metabolites that best discriminate the injected dorsal hippocampus (EZ) and developed an in vivo MEGAPRESS MRS method to focus on the detection of these metabolites in the same mouse model.

RESULTS

Multivariate analysis of HRMAS data provided evidence that γ-aminobutyric acid (GABA) is largely increased in the EZ of KA-MTLE mice and is the metabolite that best discriminates the EZ when compared to sham and, more importantly, when compared to adjacent brain regions. These results were confirmed by capillary electrophoresis analysis and were not reversed by a chronic exposition to an antiepileptic drug (carbamazepine). Then, using in vivo noninvasive GABA-edited MRS, we confirmed that a high GABA increase is specific to the injected hippocampus of KA-MTLE mice.

SIGNIFICANCE

Our strategy using ex vivo MRS-based untargeted metabolomics to select the most discriminant metabolite(s), followed by in vivo MRS-based targeted metabolomics, is an unbiased approach to accurately define the EZ in a mouse model of focal epilepsy. Results suggest that GABA is a specific biomarker of the EZ in MTLE.

Quantitative NMR-Based Biomedical Metabolomics: Current Status and Applications

Nuclear Magnetic Resonance (NMR) spectroscopy is a quantitative analytical tool commonly utilized for metabolomics analysis. Quantitative NMR (qNMR) is a field of NMR spectroscopy dedicated to the measurement of analytes through signal intensity and its linear relationship with analyte concentration. Metabolomics-based NMR exploits this quantitative relationship to identify and measure biomarkers within complex biological samples such as serum, plasma, and urine. In this review of quantitative NMR-based metabolomics, the advancements and limitations of current techniques for metabolite quantification will be evaluated as well as the applications of qNMR in biomedical metabolomics. While qNMR is limited by sensitivity and dynamic range, the simple method development, minimal sample derivatization, and the simultaneous qualitative and quantitative information provide a unique landscape for biomedical metabolomics, which is not available to other techniques. Furthermore, the non-destructive nature of NMR-based metabolomics allows for multidimensional analysis of biomarkers that facilitates unambiguous assignment and quantification of metabolites in complex biofluids.

1H NMR-Based Metabolic Signatures in the Liver and Brain in a Rat Model of Hepatic Encephalopathy

Hepatic encephalopathy (HE) is a debilitating neuropsychiatric complication associated with acute and chronic liver failure. It is characterized by diverse symptoms with variable severity that includes cognitive and motor deficits. The aim of the study is to assess metabolic alterations in the brain and liver using nuclear magnetic resonance (NMR) spectroscopy and subsequent multivariate analyses to characterize metabolic signatures associated with HE. HE was developed by bile duct ligation (BDL) that resulted in hepatic dysfunctions and cirrhosis as shown by liver function tests. Metabolic profiles from control and BDL rats indicated increased levels of lactate, branched-chain amino acids (BCAAs), glutamate, and choline in the liver, whereas levels of glucose, phenylalanine, and pyridoxine were decreased. In brain, the levels of lactate, acetate, succinate, citrate, and malate were increased, while glucose, creatine, isoleucine, leucine, and proline levels were decreased. Furthermore, neurotransmitters such as glutamate and GABA were increased, whereas choline and myo-inositol were decreased. The alterations in neurotransmitter levels resulted in cognitive and motor defects in BDL rats. A significant correlation was found among alterations in NAA/choline, choline/creatine, and NAA/creatine with behavioral deficits. Thus, the data suggests impairment in metabolic pathways such as the tricarboxylic acid (TCA) cycle, glycolysis, and ketogenesis in the liver and brain of animals with HE. The study highlights that metabolic signatures could be potential markers to monitor HE progression and to assess therapeutic interventions.

Improved Spatial Resolution of Metabolites in Tissue Biopsies Using High-Resolution Magic-Angle-Spinning Slice Localization NMR Spectroscopy

High-resolution magic-angle-spinning ¹H NMR spectroscopy (HR-MAS NMR) is a well-established technique for assessing the biochemical composition of intact tissue samples. In this study, we utilized a method based on HR-MAS NMR spectroscopy with slice localization (SLS) to achieve spatial resolution of metabolites. The obtained 7 slice spectra from each of the model samples (i.e., chicken thigh muscle with skin and murine renal biopsy including medulla (M) and cortex (C)) showed distinct metabolite compositions. Furthermore, we analyzed previously acquired ¹H HR-MAS NMR spectra of separated cortex and medulla samples using multivariate statistical methods. Concentrations of glycerophosphocholine (GPC) were found to be significantly higher in the renal medulla compared to the cortex. Using GPC as a biomarker, we identified the tissue slices that were predominantly the cortex or medulla. This study demonstrates that HR-MAS SLS combined with multivariate statistics has the potential for identifying tissue heterogeneity and detailed biochemical characterization of complex tissue samples.

High-precision measurement of pH in the full toothpaste using NMR chemical shift

The pH of toothpaste is a critical factor for product stability and customer acceptance. However, no reliable and consistent method is currently available to precisely quantify pH in toothpaste as it is. In this study, a new method to directly determine pH value in the full toothpaste contained sodium bicarbonate (NaHCO₃) was developed. Briefly, we utilized the ¹³C NMR chemical shift of a small molecule that has been formulated in the toothpaste as a sensitive probe to consistently respond to the pH value of the full toothpaste. The ideal pH probe molecule has the following characteristics: (1) its NMR chemical shift is sensitive to pH within a certain range, and (2) the chemical shift only responses to pH value, not to other factors, such as molecular interaction. NaHCO₃ is a common ingredient in many toothpaste products used as a mild abrasive and an effective pH adjustment compound. Its chemical shift is very sensitive to pH; therefore, it was used as a candidate molecule to test this concept. This technique was demonstrated on select toothpaste formula contained arginine and sodium bicarbonate with different abrasive bases. The result shows that the pH value of full toothpaste is significantly higher than the pH of the toothpaste slurry. Arginine is a key active ingredient in these toothpastes, and it does not interfere with the chemical shift of sodium bicarbonate. The traditional method to determine the pH of toothpaste using pH electrode in toothpaste slurry typically has a larger measuring error, ranging from 0.1 to 0.3. This new method greatly reduced the measuring error, providing a consistent way to reliably determine pH in the full toothpaste, and enabling the stability test of toothpaste with smaller variations. This newly developed method can be further extended to other low-water gel or paste products at a different pH range by using different probe molecules.

Magnetic resonance spectroscopy and its application in colorectal cancer diagnosis and screening: A narrative review

There are several slightly invasive methods to detect colorectal carcinoma (CRC) including colonoscopy and sigmoidoscopy; but there is no noninvasive, accurate screening test. It is recommended to initiate screening at the age of 50 for non-familial CRC. Laboratory tests are routinely suggested if internal observation and imaging are recommended for further evaluation. Spectroscopic-based imaging, such as magnetic resonance spectroscopy (MRS) is an interesting and promising tool with the potential to be an alternative to some minimally invasive procedures, such as biopsy. Accordingly, MRS might be a suitable substitution for invasive methods, such as colonoscopy. This article aimed to review the studies that have evaluated the MRS technique as a screening tool in CRC.