A Pilot Study on the 1H-NMR Serum Metabolic Profile of Takotsubo Patients Reveals Systemic Response to Oxidative Stress

Takotsubo syndrome (TTS) presents as an acute coronary syndrome characterized by severe left ventricular (LV) dysfunction and non-obstructive coronary artery disease that typically shows spontaneous recovery within days or weeks. The mechanisms behind TTS are mainly related to beta-adrenergic overstimulation and acute endogenous catecholamine surge, both of which could increase oxidative status that may induce further deterioration of cardiac function. Although several studies reported evidence of inflammation and oxidative stress overload in myocardial tissue of TTS models, systemic biochemical evidence of augmented oxidant activity in patients with TTS is lacking. In this study, serum samples of ten TTS patients and ten controls have been analyzed using 1H-NMR spectroscopy. The results of this pilot study show a marked alteration in the systemic metabolic profile of TTS patients, mainly characterized by significant elevation of ketone bodies, 2-hydroxybutyrate, acetyl-L-carnitine, and glutamate levels, in contrast with a decrease of several amino acid levels. The overall metabolic fingerprint reflects a systemic response to oxidative stress caused by the stressor that triggered the syndrome’s onset.

Effects of the Combined Treatment with a G-Quadruplex-Stabilizing Ligand and Photon Beams on Glioblastoma Stem-like Cells: A Magnetic Resonance Study

Glioblastoma multiforme is a malignant primary brain tumor with a poor prognosis and high rates of chemo-radiotherapy failure, mainly due to a small cell fraction with stem-like properties (GSCs). The mechanisms underlying GSC response to radiation need to be elucidated to enhance sensitivity to treatments and to develop new therapeutic strategies. In a previous study, two GSC lines, named line #1 and line #83, responded differently to carbon ions and photon beams, with the differences likely attributable to their own different metabolic fingerprint rather than to radiation type. Data from the literature showed the capability of RHPS4, a G-quadruplex stabilizing ligand, to sensitize the glioblastoma radioresistant U251MG cells to X-rays. The combined metabolic effect of ligand #190, a new RHPS4-derivative showing reduced cardiotoxicity, and a photon beam has been monitored by magnetic resonance (MR) spectroscopy for the two GSC lines, #1 and #83, to reveal whether a synergistic response occurs. MR spectra from both lines were affected by single and combined treatments, but the variations of the analysed metabolites were statistically significant mainly in line #1, without synergistic effects due to combination. The multivariate analysis of ten metabolites shows a separation between control and treated samples in line #1 regardless of treatment type, while separation was not detected in line #83.

Authentication of Zingiber Species Based on Analysis of Metabolite Profiles

Zingiber corallinum and Zingiber montanum, which belong to the Zingiberaceae family, are traditional Chinese folk medicinal herbs in Guizhou and Yunnan Province of China. They share great similarities in morphology, chemical constituent, and DNA barcoding sequence. The taxonomy of the two Zingiber species is controversial and discrimination of traditional Chinese medicines directly affects the pharmacological and clinical effects. In the present study, we performed a systemic analysis of “super-barcode” and untargeted metabolomics between Z. corallinum and Z. montanum using chloroplast (cp) genome sequencing and gas chromatography-mass spectrometry (GC-MS) analysis. Comparison and phylogenetic analysis of cp genomes of the two Zingiber species showed that the cp genome could not guarantee the accuracy of identification. An untargeted metabolomics strategy combining GC-MS with chemometric methods was proposed to distinguish the Zingiber samples of known variety. A total of 51 volatile compounds extracted from Z. corallinum and Z. montanum were identified, and nine compounds were selected as candidate metabolic markers to reveal the significant difference between Z. corallinum and Z. montanum. The performance of the untargeted metabolomic approach was verified with unknown Zingiber samples. Although the cp genomes could not be used to identify Zingiber species in this study, it will still provide a valuable genomics resource for population studies in the Zingiberaceae family, and the GC-MS based metabolic fingerprint is more promising for species identification and safe application of Z. corallinum and Z. montanum.

The Echocardiographic Parameters of Systolic Function Are Associated with Specific Metabolomic Fingerprints in Obstructive and Non-Obstructive Hypertrophic Cardiomyopathy

The purpose of this study was to assess whether metabolomics, associated with echocardiography, was able to highlight pathophysiological differences between obstructive (OHCM) or non-obstructive (NOHCM) hypertrophic cardiomyopathy. Thirty-one HCM patients underwent standard and advanced echocardiography; a plasma sample was collected for metabolomic analysis. Results. Patients with OHCM compared with subjects with NOHCM had higher values of 2DLVEF (66.5 ± 3.3% vs. 60.6 ± 1.8%, p < 0.01), S wave (7.6 ± 1.1 vs. 6.3 ± 0.7 cm/s, p < 0.01) and 3D global longitudinal strain (17.2 ± 4.2%, vs. 13.4 ± 1.3%, p < 0.05). A 2-group PLS-Discriminant Analysis was performed to verify whether the two HCM groups differed also based on the metabolic fingerprint. A clear clustering was shown (ANOVA p = 0.014). The most discriminating metabolites resulted as follows: in the NOHCM Group, there were higher levels of threitol, aminomalonic acid, and sucrose, while the OHCM Group presented higher levels of amino acids, in particular those branched chains, of intermediates of glycolysis (lactate) and the Krebs cycle (fumarate, succinate, citrate), of fatty acids (arachidonic acid, palmitoleic acid), of ketone bodies (2-OH-butyrate). Our data point out a different systolic function related to a specific metabolic activity in the two HCM phenotypic forms, with specific metabolites associated with better contractility in OHCM.

Metabolic Profiling of Type 2 Diabetes Patients after Bariatric Surgery by Raman Spectroscopy

Background: Bariatric surgery (BS) is an important procedure used for the treatment of morbid obesity and has been proven to improve, or even cure, type 2 diabetes mellitus (T2DM). However, of the patients with T2DM who initially go into remission, a proportion experience a relapse during the follow-up. In this context, Raman spectroscopy (RS) could be a promising technique for monitoring the metabolic profile of patients after surgical treatment with the aim of improving their postsurgical management. Methods: Fourteen obese patients with T2DM were recruited. Clinical parameters, adipokines, ghrelin, Fibroblast growth factor 19 (FGF-19) values, and Raman spectra were collected and analyzed before and after surgery. RS results were compared with profiles obtained from 23 healthy subjects (HC), to observe whether the metabolic fingerprint of bariatric patients normalized during the surgical follow-up. Results: The reduction in anthropometric measures and improved glycemic control and lipid profile after surgical treatment highlighted the benefits of BS. Consequently, adipokines, ghrelin and FGF-19 concentration returned to normal values after surgery. However, RS data highlighted an altered metabolic profile even after BS. Conclusion: RS suggests that BS does not fully restore the metabolic profile of patients in the immediate follow-up after the surgery.

Dissecting fine-flavor cocoa bean fermentation through metabolomics analysis to break down the current metabolic paradigm

Cocoa fermentation plays a crucial role in producing flavor and bioactive compounds of high demand for food and nutraceutical industries. Such fermentations are frequently described as a succession of three main groups of microorganisms (i.e., yeast, lactic acid, and acetic acid bacteria), each producing a relevant metabolite (i.e., ethanol, lactic acid, and acetic acid). Nevertheless, this view of fermentation overlooks two critical observations: the role of minor groups of microorganisms to produce valuable compounds and the influence of environmental factors (other than oxygen availability) on their biosynthesis. Dissecting the metabolome during spontaneous cocoa fermentation is a current challenge for the rational design of controlled fermentations. This study evaluates variations in the metabolic fingerprint during spontaneous fermentation of fine flavor cocoa through a multiplatform metabolomics approach. Our data suggested the presence of two phases of differential metabolic activity that correlate with the observed variations on temperature over fermentations: an exothermic and an isothermic phase. We observed a continuous increase in temperature from day 0 to day 4 of fermentation and a significant variation in flavonoids and peptides between phases. While the second phase, from day four on, was characterized for lower metabolic activity, concomitant with small upward and downward fluctuations in temperature. Our work is the first to reveal two phases of metabolic activity concomitant with two temperature phases during spontaneous cocoa fermentation. Here, we proposed a new paradigm of cocoa fermentation that considers the changes in the global metabolic activity over fermentation, thus changing the current paradigm based only on three main groups of microorganism and their primary metabolic products.

Metabolomic Fingerprint of Mecp2-Deficient Mouse Cortex: Evidence for a Pronounced Multi-Facetted Metabolic Component in Rett Syndrome

Using unsupervised metabolomics, we defined the complex metabolic conditions in the cortex of a mouse model of Rett syndrome (RTT). RTT, which represents a cause of mental and cognitive disabilities in females, results in profound cognitive impairment with autistic features, motor disabilities, seizures, gastrointestinal problems, and cardiorespiratory irregularities. Typical RTT originates from mutations in the X-chromosomal methyl-CpG-binding-protein-2 (Mecp2) gene, which encodes a transcriptional modulator. It then causes a deregulation of several target genes and metabolic alterations in the nervous system and peripheral organs. We identified 101 significantly deregulated metabolites in the Mecp2-deficient cortex of adult male mice; 68 were increased and 33 were decreased compared to wildtypes. Pathway analysis identified 31 mostly upregulated metabolic pathways, in particular carbohydrate and amino acid metabolism, key metabolic mitochondrial/extramitochondrial pathways, and lipid metabolism. In contrast, neurotransmitter-signaling is dampened. This metabolic fingerprint of the Mecp2-deficient cortex of severely symptomatic mice provides further mechanistic insights into the complex RTT pathogenesis. The deregulated pathways that were identified—in particular the markedly affected amino acid and carbohydrate metabolism—confirm a complex and multifaceted metabolic component in RTT, which in turn signifies putative therapeutic targets. Furthermore, the deregulated key metabolites provide a choice of potential biomarkers for a more detailed rating of disease severity and disease progression.

Lipid Metabolite Biomarkers in Cardiovascular Disease: Discovery and Biomechanism Translation from Human Studies

Lipids represent a valuable target for metabolomic studies since altered lipid metabolism is known to drive the pathological changes in cardiovascular disease (CVD). Metabolomic technologies give us the ability to measure thousands of metabolites providing us with a metabolic fingerprint of individual patients. Metabolomic studies in humans have supported previous findings into the pathomechanisms of CVD, namely atherosclerosis, apoptosis, inflammation, oxidative stress, and insulin resistance. The most widely studied classes of lipid metabolite biomarkers in CVD are phospholipids, sphingolipids/ceramides, glycolipids, cholesterol esters, fatty acids, and acylcarnitines. Technological advancements have enabled novel strategies to discover individual biomarkers or panels that may aid in the diagnosis and prognosis of CVD, with sphingolipids/ceramides as the most promising class of biomarkers thus far. In this review, application of metabolomic profiling for biomarker discovery to aid in the diagnosis and prognosis of CVD as well as metabolic abnormalities in CVD will be discussed with particular emphasis on lipid metabolites.