pH optimization for a reliable quantification of brain tumor cell and tissue extracts with (1)H NMR: focus on choline-containing compounds and taurine

Comparisons of Glutamate in the Brains of Alzheimer’s Disease Mice Under Chemical Exchange Saturation Transfer Imaging Based on Machine Learning Analysis

Chemical exchange saturation transfer (CEST) is one of the molecular magnetic resonance imaging (MRI) techniques that indirectly measures low-concentration metabolite or free protein signals that are difficult to detect by conventional MRI techniques. We applied CEST to Alzheimer’s disease (AD) and analyzed both region of interest (ROI) and pixel dimensions. Through the analysis of the ROI dimension, we found that the content of glutamate in the brains of AD mice was higher than that of normal mice of the same age. In the pixel-dimensional analysis, we obtained a map of the distribution of glutamate in the mouse brain. According to the experimental data of this study, we designed an algorithm framework based on data migration and used Resnet neural network to classify the glutamate distribution images of AD mice, with an accuracy rate of 75.6%. We evaluate the possibility of glutamate imaging as a biomarker for AD detection for the first time, with important implications for the detection and treatment of AD.

Radiation Induced Metabolic Alterations Associate With Tumor Aggressiveness and Poor Outcome in Glioblastoma

Glioblastoma (GBM) is uniformly fatal with a 1-year median survival, despite best available treatment, including radiotherapy (RT). Impacts of prior RT on tumor recurrence are poorly understood but may increase tumor aggressiveness. Metabolic changes have been investigated in radiation-induced brain injury; however, the tumor-promoting effect following prior radiation is lacking. Since RT is vital to GBM management, we quantified tumor-promoting effects of prior RT on patient-derived intracranial GBM xenografts and characterized metabolic alterations associated with the protumorigenic microenvironment. Human xenografts (GBM143) were implanted into nude mice 24 hrs following 20 Gy cranial radiation vs. sham animals. Tumors in pre-radiated mice were more proliferative and more infiltrative, yielding faster mortality (p < 0.0001). Histologic evaluation of tumor associated macrophage/microglia (TAMs) revealed cells with a more fully activated ameboid morphology in pre-radiated animals. Microdialyzates from radiated brain at the margin of tumor infiltration contralateral to the site of implantation were analyzed by unsupervised liquid chromatography-mass spectrometry (LC-MS). In pre-radiated animals, metabolites known to be associated with tumor progression (i.e., modified nucleotides and polyols) were identified. Whole-tissue metabolomic analysis of pre-radiated brain microenvironment for metabolic alterations in a separate cohort of nude mice using ¹H-NMR revealed a significant decrease in levels of antioxidants (glutathione (GSH) and ascorbate (ASC)), NAD⁺, Tricarboxylic acid cycle (TCA) intermediates, and rise in energy carriers (ATP, GTP). GSH and ASC showed highest Variable Importance on Projection prediction (VIPpred) (1.65) in Orthogonal Partial least square Discriminant Analysis (OPLS-DA); Ascorbate catabolism was identified by GC-MS. To assess longevity of radiation effects, we compared survival with implantation occurring 2 months vs. 24 hrs following radiation, finding worse survival in animals implanted at 2 months. These radiation-induced alterations are consistent with a chronic disease-like microenvironment characterized by reduced levels of antioxidants and NAD⁺, and elevated extracellular ATP and GTP serving as chemoattractants, promoting cell motility and vesicular secretion with decreased levels of GSH and ASC exacerbating oxidative stress. Taken together, these data suggest IR induces tumor-permissive changes in the microenvironment with metabolomic alterations that may facilitate tumor aggressiveness with important implications for recurrent glioblastoma. Harnessing these metabolomic insights may provide opportunities to attenuate RT-associated aggressiveness of recurrent GBM.

Carbohydrate Background Removal in Metabolomics Samples

NMR-based metabolomics is a powerful tool to comprehensively monitor chemical processes in biological systems. Key to its success is the accurate and complete metabolite identification and quantification. Due to the inherent complexity of most metabolic mixtures, NMR peak overlap can make data analysis of 1D or even 2D NMR spectra challenging, especially for the ¹H spectral region from 3.2-4.5 ppm that is dominated by carbohydrates and their derivatives. To address this problem, we present an effective method for carbohydrate signal removal in complex metabolomics samples by oxidation via the addition of sodium periodate (NaIO₄). In an optional step, reaction products can be removed with hydrazide beads. The treated samples show substantially simplified 1D and 2D NMR spectra with their carbohydrate peaks removed, whereas noncarbohydrate peaks remain mostly unaffected. This allows the unrestricted detection of those metabolites that are otherwise obscured by carbohydrate signals. The method was first tested for metabolite model mixtures and then applied to urine and serum samples. It revealed a significant number of noncarbohydrates that were made unambiguously observable and identifiable by this method. The proposed protocol is simple and it is suitable for high-throughput sample treatment for the comprehensive metabolite identification in a broad range of samples.

Balancing metabolome coverage and reproducibility for untargeted NMR-based metabolic profiling in tissue samples through mixture design methods

Untargeted metabolomics attempts to acquire a comprehensive and reproducible set of small-molecule metabolites in biological systems. However, metabolite extraction method significantly affects the quality of metabolomics data. In the present study, we calculated the number of peaks (NP) and coefficient of variation (CV) to reflect metabolome coverage and reproducibility in untargeted NMR-based metabolic profiling of tissue samples in rats under different methanol/chloroform/water (MCW) extraction conditions. Different MCW extractions expectedly generated diverse characteristics of metabolome. Moreover, the classic MCW method revealed tissue-specific differences in the NP and CV values. To obtain high-quality metabolomics data, therefore, we used mixture design methods to optimize the MCW extraction strategy by maximizing the NP value and minimizing the CV value in each tissue sample. Results show that the optimal formulations of MCW extraction were 2:2:8 (ml/mg tissue) for brain sample, 2:4:6 (ml/mg tissue) for heart sample, 1.3:2:8.7 (ml/mg tissue) for liver sample, 4:2:6 (ml/mg tissue) for kidney sample, 2:3:7 (ml/mg tissue) for muscle sample, and 2:4:6 (ml/mg tissue) for pancreas sample. Therefore, these findings demonstrate that different tissue samples need a specific optimal extraction condition for balancing metabolome coverage and reproducibility in the untargeted metabolomics study. Mixture design method is an effective tool to optimize metabolite extraction strategy for tissue samples. Graphical abstract ᅟ.

Consequences of blunting the mevalonate pathway in cancer identified by a pluri-omics approach

We have previously shown that the combination of statins and taxanes was a powerful trigger of HGT-1 human gastric cancer cells’ apoptosis¹. Importantly, several genes involved in the “Central carbon metabolism pathway in cancer”, as reported in the Kyoto Encyclopedia of Genes and Genomes, were either up- (ACLY, ERBB2, GCK, MYC, PGM, PKFB2, SLC1A5, SLC7A5, SLC16A3,) or down- (IDH, MDH1, OGDH, P53, PDK) regulated in response to the drug association. In the present study, we conducted non-targeted metabolomics and lipidomics analyses by complementary methods and cross-platform initiatives, namely mass spectrometry (GC-MS, LC-MS) and nuclear magnetic resonance (NMR), to analyze the changes resulting from these treatments. We identified several altered biochemical pathways involved in the anabolism and disposition of amino acids, sugars, and lipids. Using the Cytoscape environment with, as an input, the identified biochemical marker changes, we distinguished the functional links between pathways. Finally, looking at the overlap between metabolomics/lipidomics and transcriptome changes, we identified correlations between gene expression modifications and changes in metabolites/lipids. Among the metabolites commonly detected by all types of platforms, glutamine was the most induced (6–7-fold), pointing to an important metabolic adaptation of cancer cells. Taken together, our results demonstrated that combining robust biochemical and molecular approaches was efficient to identify both altered metabolic pathways and overlapping gene expression alterations in human gastric cancer cells engaging into apoptosis following blunting the cholesterol synthesis pathway.

Sex- and age-specific modulation of brain GABA levels in a mouse model of Alzheimer's disease

Age and sex are risk factors of Alzheimer's disease (AD). Among the neurotransmitter systems, gamma-aminobutyric acid (GABA) has been implicated in AD pathogenesis but the relevance of sex-specific GABAergic dysfunction during AD progression remains unknown. In the present study, we utilized state-of-the-art high-resolution magic angle spinning nuclear magnetic resonance to systematically monitor the brain region-, age-, and sex-specific modulation of GABA levels in wild-type and Tg2576 mice with amyloid pathology. In addition, we followed the possible role of reactive astrocytes in sex-specific GABA modulation. In female Tg2576 mice, hippocampal GABA levels were significantly elevated, along with higher number of reactive astrocytes and amyloid deposition. The elevated GABA was found to be produced via the monoamine oxidase-B route from putrescine in reactive astrocytes, more substantially in female than male mice, thus suggesting a role of astrocytes in memory impairment and sex-related differences in AD. Our results paint a coherent model of memory impairment in AD and signify that dynamic changes in regional GABA may be at the root of marked sex disparities observed in AD.

Identification of altered brain metabolites associated with TNAP activity in a mouse model of hypophosphatasia using untargeted NMR-based metabolomics analysis

Tissue non-specific alkaline phosphatase (TNAP) is a key player of bone mineralization and TNAP gene (ALPL) mutations in human are responsible for hypophosphatasia (HPP), a rare heritable disease affecting the mineralization of bones and teeth. Moreover, TNAP is also expressed by brain cells and the severe forms of HPP are associated with neurological disorders, including epilepsy and brain morphological anomalies. However, TNAP's role in the nervous system remains poorly understood. To investigate its neuronal functions, we aimed to identify without any a priori the metabolites regulated by TNAP in the nervous tissue. For this purpose we used ¹ H- and ³¹ P NMR to analyze the brain metabolome of Alpl (Akp2) mice null for TNAP function, a well-described model of infantile HPP. Among 39 metabolites identified in brain extracts of 1-week-old animals, eight displayed significantly different concentration in Akp2^-/- compared to Akp2^+/+ and Akp2^+/- mice: cystathionine, adenosine, GABA, methionine, histidine, 3-methylhistidine, N-acetylaspartate (NAA), and N-acetyl-aspartyl-glutamate, with cystathionine and adenosine levels displaying the strongest alteration. These metabolites identify several biochemical processes that directly or indirectly involve TNAP function, in particular through the regulation of ecto-nucleotide levels and of pyridoxal phosphate-dependent enzymes. Some of these metabolites are involved in neurotransmission (GABA, adenosine), in myelin synthesis (NAA, NAAG), and in the methionine cycle and transsulfuration pathway (cystathionine, methionine). Their disturbances may contribute to the neurodevelopmental and neurological phenotype of HPP.

Turmeric enhancing anti-tumor effect of Rhizoma paridis saponins by influencing their metabolic profiling in tumors of H22 hepatocarcinoma mice

Rhizoma Paridis saponins combined with turmeric (RT) showed well anti-hepatocarcinoma activities in our previous research. The aim of this study was to investigate the progression of the biochemical response to RT and capture metabolic variations during intragastric administration of their compatibility. In the experiment, histopathological examination and (1)H NMR method were developed and validated for the metabolic profiling of RT intervention in H22 tumor growth. Data were analyzed with principal components analysis (PCA) and partial least-squares discrimination analysis (PLS-DA). As a result, Rhizoma paridis saponins (RPS) or RT induced inflammatory cell infiltration in tumors. RT also mediated the tumor microenvironment to promote anti-tumor immunity of mice. RT significantly inhibited tumor growth rate through suppressing levels of amino acids containing alanine, asparagine, glutamine, putrescine, and sarcosine, lipid compounds, and carbohydrates like myo-inositol and arabinose in the tumor tissues. In conclusion, these results uncovered unexpectedly poor nutritional conditions in the RT-treated tumor tissues whose effect was stronger than RPS's. Therefore, RT could be a novel anticancer agent that targets on cancer metabolism through starving tumors reducing viability of cancer cells.

Characterization of heroin samples by 1H NMR and 2D DOSY 1H NMR

Twenty-four samples of heroin from different illicit drug seizures were analyzed using proton Nuclear Magnetic Resonance ((1)H NMR) and two-dimensional diffusion-ordered spectroscopy (2D DOSY) (1)H NMR. A careful assignment and quantification of (1)H signals enabled a comprehensive characterization of the substances present in the samples investigated: heroin, its main related impurities (6-acetylmorphine, acetylcodeine, morphine, noscapine and papaverine) and cutting agents (caffeine and acetaminophen in nearly all samples as well as lactose, lidocaine, mannitol, piracetam in one sample only), and hence to establish their spectral signatures. The good agreement between the amounts of heroin, noscapine, caffeine and acetaminophen determined by (1)H NMR and gas chromatography, the reference method in forensic laboratories, demonstrates the validity of the (1)H NMR technique. In this paper, 2D DOSY (1)H NMR offers a new approach for a whole characterization of the various components of these complex mixtures.

Use of 1H and 31P HRMAS to evaluate the relationship between quantitative alterations in metabolite concentrations and tissue features in human brain tumour biopsies

Quantitative multinuclear high-resolution magic angle spinning was performed in order to determine the tissue pH values of and the absolute metabolite concentrations in 33 samples of human brain tumour tissue. Metabolite concentrations were quantified by 1D (1)H and (31)P HRMAS using the electronic reference to in vivo concentrations (ERETIC) synthetic signal. (1)H-(1)H homonuclear and (1)H-(31)P heteronuclear correlation experiments enabled the direct assessment of the (1)H-(31)P spin systems for signals that suffered from overlapping in the 1D (1)H spectra, and linked the information present in the 1D (1)H and (31)P spectra. Afterwards, the main histological features were determined, and high heterogeneity in the tumour content, necrotic content and nonaffected tissue content was observed. The metabolite profiles obtained by HRMAS showed characteristics typical of tumour tissues: rather low levels of energetic molecules and increased concentrations of protective metabolites. Nevertheless, these characteristics were more strongly correlated with the total amount of living tissue than with the tumour cell contents of the samples alone, which could indicate that the sampling conditions make a significant contribution aside from the effect of tumour development in vivo. The use of methylene diphosphonic acid as a chemical shift and concentration reference for the (31)P HRMAS spectra of tissues presented important drawbacks due to its interaction with the tissue. Moreover, the pH data obtained from (31)P HRMAS enabled us to establish a correlation between the pH and the distance between the N(CH(3))(3) signals of phosphocholine and choline in (1)H spectra of the tissue in these tumour samples.