Metabolomics deals with the whole ensemble of metabolites (the metabolome). As one of the -omic sciences, it relates to biology, physiology, pathology and medicine; but metabolites are chemical entities, small organic molecules or inorganic ions. Therefore, their proper identification and quantitation in complex biological matrices requires a solid chemical ground. With respect to for example, DNA, metabolites are much more prone to oxidation or enzymatic degradation: we can reconstruct large parts of a mammoth's genome from a small specimen, but we are unable to do the same with its metabolome, which was probably largely degraded a few hours after the animal's death. Thus, we need standard operating procedures, good chemical skills in sample preparation for storage and subsequent analysis, accurate analytical procedures, a broad knowledge of chemometrics and advanced statistical tools, and a good knowledge of at least one of the two metabolomic techniques, MS or NMR. All these skills are traditionally cultivated by chemists. Here we focus on metabolomics from the chemical standpoint and restrict ourselves to NMR. From the analytical point of view, NMR has pros and cons but does provide a peculiar holistic perspective that may speak for its future adoption as a population-wide health screening technique.

Monoacylglycerol lipase (MAGL) is the enzyme degrading the endocannabinoid 2arachidonoylglycerol and it is involved in several physiological and pathological processes. The therapeutic potential of MAGL is linked to several diseases, including cancer. The development of MAGL inhibitors has been greatly limited by the side effects associated with the prolonged MAGL inactivation. Importantly, it could be preferable to use reversible MAGL inhibitors in vivo, but nowadays only few reversible compounds have been developed. In the present study, structural optimization of a previously developed class of MAGL inhibitors led to the identification of compound 23, which proved to be a very potent reversible MAGL inhibitor (IC50 = 80 nM), selective for MAGL over the other main components of the endocannabinoid system, endowed of a promising antiproliferative activity in a series of cancer cell lines and able to block MAGL both in cell-based as well as in vivo assays.

Erdem Gulersoy (2020) Nuclear magnetic resonance (NMR)-based metabolome profile evaluation in dairy cows with and without displaced abomasum, Veterinary Quarterly, 40:1, 1-15, ABSTRACT Background: Displaced abomasum (DA) is a condition of dairy cows that severely impacts animal welfare and causes huge economic losses. Objective: To assess the metabolic status of the disease using metabolomics in serum, urine and liver samples aimed at both water soluble and lipid soluble fractions. Methods: Fifty Holstein multiparous cows with DA (42 left, 8 right) and 20 clinically healthy Holstein multiparous cows were used. Left DA was associated with concomitant ketosis in 19 animals and right in two. NMR-based metabolomics approach and hematological and biochemical analyses were performed. Statistical analysis was carried out on 1 H-NMR data after they have been normalized using PQN method. Results: Contrary to generated PCA score plots the OPLS-supervised method revealed differences between healthy animals and diseased ones based on serum water-soluble samples. While water and lipid soluble metabolites decreased in serum samples, fatty acid fractions and cholesterol were increased in liver samples in DA affected cows. The metabolomic and chemical profiles clearly revealed that cows with DA (especially with LDA) were at risk of ketosis and fatty liver. Serum hippuric acid concentration was significantly higher in healthy cows in comparison with LDA, whereas serum glycine concentration was reported higher for healthy when compared to RDA affected animals. Conclusion: A biochemical network and pathway mapping revealed 'valine, leucine and isoleucine biosynthesis' and 'phenylalanine, tyrosine and tryptophan biosynthesis' as the most probable altered metabolic pathway in DA condition. Serum was advocated as the optimal biological matrix for the 1 H-NMR analysis. ARTICLE HISTORY

Advanced age represents one of the major risk factors for Parkinson’s Disease. Recent biomedical studies posit a role for microRNAs, also known to be remodelled during ageing. However, the relationship between microRNA remodelling and ageing in Parkinson’s Disease, has not been fully elucidated. Therefore, the aim of the present study is to unravel the relevance of microRNAs as biomarkers of Parkinson’s Disease within the ageing framework. We employed Next Generation Sequencing to profile serum microRNAs from samples informative for Parkinson’s Disease (recently diagnosed, drug-naïve) and healthy ageing (centenarians) plus healthy controls, age-matched with Parkinson’s Disease patients. Potential microRNA candidates markers, emerging from the combination of differential expression and network analyses, were further validated in an independent cohort including both drug-naïve and advanced Parkinson’s Disease patients, and healthy siblings of Parkinson’s Disease patients at higher genetic risk for developing the disease. While we did not find evidences of microRNAs co-regulated in Parkinson’s Disease and ageing, we report that hsa-miR-144-3p is consistently down-regulated in early Parkinson’s Disease patients. Moreover, interestingly, functional analysis revealed that hsa-miR-144-3p is involved in the regulation of coagulation, a process known to be altered in Parkinson’s Disease. Our results consistently show the down-regulation of hsa-mir144-3p in early Parkinson’s Disease, robustly confirmed across a variety of analytical and experimental analyses. These promising results ask for further research to unveil the functional details of the involvement of hsa-mir144-3p in Parkinson’s Disease.

Background Men with African ancestry are more likely to develop aggressive prostate cancer (PCa) and to die from this disease. The study of PCa in the South African population represents an opportunity for biomedical research due to the high prevalence of aggressive PCa. While inflammation is known to play a significant role in PCa progression, its association with tumor stage in populations of African descent has not been explored in detail. Identification of new metabolic biomarkers of inflammation may improve diagnosis of patients with aggressive PCa. Methods Plasma samples were profiled from 41 South African men with PCa using nuclear magnetic resonance (NMR) spectroscopy. A total of 41 features, including metabolites, lipid classes, total protein, and the inflammatory NMR markers, GlycA, and GlycB, were quantified from each NMR spectrum. The Bruker’s B.I.-LISA protocols were used to characterize 114 parameters related to the lipoproteins. The unsupervised KODAMA method was used to stratify the patients of our cohort based on their metabolic profile. Results We found that the plasma of patients with very high risk, aggressive PCa and high level of C-reactive protein have a peculiar metabolic phenotype (metabotype) characterized by extremely high levels of GlycA and GlycB. The inflammatory processes linked to the higher level of GlycA and GlycB are characterized by a deep change of the plasma metabolome that may be used to improve the stratification of patients with PCa. We also identified a not previously known relationship between high values of VLDL and low level of GlycB in a different metabotype of patients characterized by lower-risk PCa. Conclusions For the first time, a portrait of the metabolic changes in African men with PCa has been delineated indicating a strong association between inflammation and metabolic profiles. Our findings indicate how the metabolic profile could be used to identify those patients with high level of inflammation, characterized by aggressive PCa and short life expectancy. Integrating a metabolomic analysis as a tool for patient stratification could be important for opening the door to the development of new therapies. Further investigations are needed to understand the prevalence of an inflammatory metabotype in patients with aggressive PCa.

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Metabolomik befasst sich mit der Gesamtheit aller Metabolite, dem Metabolom. Als eine der “Omics”‐Wissenschaften hat sie Querbeziehungen zur Biologie, Physiologie, Pathologie und Medizin; andererseits sind Metabolite chemische Verbindungen, kleine organische Moleküle oder anorganische Ionen. Ihre korrekte Identifizierung und Quantifizierung in komplexen biologischen Matrizen erfordert daher eine solide chemische Grundlage. Im Vergleich beispielsweise zu DNA unterliegen Metabolite sehr viel stärker der Oxidation oder dem enzymatischen Abbau: Wir können große Teile eines Mammut‐Genoms aus einer kleinen Probe rekonstruieren, sind aber nicht in der Lage, dasselbe mit seinem Metabolom zu tun, das innerhalb weniger Stunden nach dem Tod des Tieres wahrscheinlich weitgehend abgebaut war. Erforderlich sind daher Standardverfahren, gute chemische Fertigkeiten der Probenvorbereitung für die Lagerung und anschließende Analyse, genaue analytische Protokolle, eine umfangreiche Kenntnis der Chemometrie, erweiterte statistische Verfahren und fundiertes Wissen über mindestens eine der beiden Metabolomik‐typischen Verfahren, MS oder NMR. All diese Fertigkeiten besitzen traditionell die Chemiker. Entsprechend betrachten wir die Metabolomik aus chemischer Perspektive und beschränken uns auf NMR. Der Analytiker findet Argumente für und gegen NMR, jedoch bietet das Verfahren eine besondere ganzheitliche Perspektive, die für künftige Anwendungen als eine bevölkerungsweite Screeningtechnik für Reihenuntersuchungen sprechen.

Here, we present an integrated multivariate, univariate, network reconstruction and differential analysis of metabolite–metabolite and metabolite–lipid association networks built from an array of 18 serum metabolites and 110 lipids identified and quantified through nuclear magnetic resonance spectroscopy in a cohort of 248 patients, of which 22 died and 82 developed a poor functional outcome within 3 months from acute ischemic stroke (AIS) treated with intravenous recombinant tissue plasminogen activator. We explored differences in metabolite and lipid connectivity of patients who did not develop a poor outcome and who survived the ischemic stroke from the related opposite conditions. We report statistically significant differences in the connectivity patterns of both low- and high-molecular-weight metabolites, implying underlying variations in the metabolic pathway involving leucine, glycine, glutamine, tyrosine, phenylalanine, citric, lactic, and acetic acids, ketone bodies, and different lipids, thus characterizing patients’ outcomes. Our results evidence the promising and powerful role of the metabolite–metabolite and metabolite–lipid association networks in investigating molecular mechanisms underlying AIS patient’s outcome.