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Background: Metabolic syndrome (MetS), a cluster of factors associated with risks of developing cardiovascular diseases, is a public health concern because of its growing prevalence. Considering the combination of concomitant components, their development and severity, MetS phenotypes are largely heterogeneous, inducing disparity in diagnosis., Methods: A case/control study was designed within the NuAge longitudinal cohort on aging. From a 3-year follow-up of 123 stable individuals, we present a deep phenotyping approach based on a multiplatform metabolomics and lipidomics untargeted strategy to better characterize metabolic perturbations in MetS and define a comprehensive MetS signature stable over time in older men., Findings: We characterize significant changes associated with MetS, involving modulations of 476 metabolites and lipids, and representing 16% of the detected serum metabolome/lipidome. These results revealed a systemic alteration of metabolism, involving various metabolic pathways (urea cycle, amino-acid, sphingo- and glycerophospholipid, and sugar metabolisms…) not only intrinsically interrelated, but also reflecting environmental factors (nutrition, microbiota, physical activity…)., Interpretation: These findings allowed identifying a comprehensive MetS signature, reduced to 26 metabolites for future translation into clinical applications for better diagnosing MetS., Funding: The NuAge Study was supported by a research grant from the Canadian Institutes of Health Research (CIHR; MOP-62842). The actual NuAge Database and Biobank, containing data and biologic samples of 1,753 NuAge participants (from the initial 1,793 participants), are supported by the Fonds de recherche du Québec (FRQ; 2020-VICO-279753), the Quebec Network for Research on Aging, a thematic network funded by the Fonds de Recherche du Québec - Santé (FRQS) and by the Merck-Frost Chair funded by La Fondation de l'Université de Sherbrooke. All metabolomics and lipidomics analyses were funded and performed within the metaboHUB French infrastructure (ANR-INBS-0010). All authors had full access to the full data in the study and accept responsibility to submit for publication., Competing Interests: Declaration of Competing Interest All authors declare they have no conflict of interest., (Copyright © 2021 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background & Aims: Systemic inflammation and organ failure(s) are the hallmarks of acute-on-chronic liver failure (ACLF), yet their pathogenesis remains uncertain. Herein, we aimed to assess the role of amino acids in these processes in patients with ACLF., Methods: The blood metabolomic database of the CANONIC study (comprising 137 metabolites, with 43% related to amino acids) - obtained in 181 patients with ACLF and 650 with acute decompensation without ACLF (AD) - was reanalyzed with a focus on amino acids, in particular 9 modules of co-regulated metabolites. We also compared blood metabolite levels between ACLF and AD., Results: The main findings in ACLF were: i) Metabolite modules were increased in parallel with increased levels of markers of systemic inflammation and oxidative stress. ii) Seventy percent of proteinogenic amino acids were present and most were increased. iii) A metabolic network, comprising the amino acids aspartate, glutamate, the serine-glycine one-carbon metabolism (folate cycle), and methionine cycle, was activated, suggesting increased purine and pyrimidine nucleotide synthesis. iv) Cystathionine, L-cystine, glutamate and pyroglutamate, which are involved in the transsulfuration pathway (a methionine cycle branch) were increased, consistent with increased synthesis of the antioxidant glutathione. v) Intermediates of the catabolism of 5 out of the 6 ketogenic amino acids were increased. vi) The levels of spermidine (a polyamine inducer of autophagy with anti-inflammatory effects) were decreased., Conclusions: In ACLF, blood amino acids fueled protein and nucleotide synthesis required for the intense systemic inflammatory response. Ketogenic amino acids were extensively catabolized to produce energy substrates in peripheral organs, an effect that was insufficient because organs failed. Finally, the decrease in spermidine levels may cause a defect in autophagy contributing to the proinflammatory phenotype in ACLF., Lay Summary: Systemic inflammation and organ failures are hallmarks of acute-on-chronic liver failure (ACLF). Herein, we aimed to characterize the role of amino acids in these processes. The blood metabolome of patients with acutely decompensated cirrhosis, and particularly those with ACLF, reveals evidence of intense skeletal muscle catabolism. Importantly, amino acids (along with glucose), are used for intense anabolic, energy-consuming metabolism in patients with ACLF, presumably to support de novo nucleotide and protein synthesis in the activated innate immune system., Competing Interests: Conflicts of interest Dr. Jalan has research collaborations with Yaqrit and Takeda. Dr. Jalan is the inventor of OPA, which has been patented by UCL and licensed to Mallinckrodt Pharma. He is also the founder of Yaqrit limited, a spin out company from University College London and Thoeris Ltd. Dr. Bernardi is part of the speakers’ bureau for Grifols SA, Octapharma AG, Shire/Takeda, CLS Behring GmbH, and PPTA, and is a consultant for Grifols SA, CLS Behring GmbH, Martin Pharmaceuticals and Shire/Takeda. The remaining authors disclose no conflicts. Please refer to the accompanying ICMJE disclosure forms for further details., (Copyright © 2020 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.)

Background & Aims: Acute-on-chronic liver failure (ACLF), which develops in patients with cirrhosis, is characterized by intense systemic inflammation and organ failure(s). Because systemic inflammation is energetically expensive, its metabolic costs may result in organ dysfunction/failure. Therefore, we aimed to analyze the blood metabolome in patients with cirrhosis, with and without ACLF., Methods: We performed untargeted metabolomics using liquid chromatography coupled to high-resolution mass spectrometry in serum from 650 patients with AD (acute decompensation of cirrhosis, without ACLF), 181 with ACLF, 43 with compensated cirrhosis, and 29 healthy individuals., Results: Of the 137 annotated metabolites identified, 100 were increased in patients with ACLF of any grade, relative to those with AD, and 38 comprised a distinctive blood metabolite fingerprint for ACLF. Among patients with ACLF, the intensity of the fingerprint increased across ACLF grades, and was similar in patients with kidney failure and in those without, indicating that the fingerprint reflected not only decreased kidney excretion but also altered cell metabolism. The higher the ACLF-associated fingerprint intensity, the higher the plasma levels of inflammatory markers, tumor necrosis factor α, soluble CD206, and soluble CD163. ACLF was characterized by intense proteolysis and lipolysis; amino acid catabolism; extra-mitochondrial glucose metabolism through glycolysis, pentose phosphate, and D-glucuronate pathways; depressed mitochondrial ATP-producing fatty acid β-oxidation; and extra-mitochondrial amino acid metabolism giving rise to metabotoxins., Conclusions: In ACLF, intense systemic inflammation is associated with blood metabolite accumulation and profound alterations in major metabolic pathways, in particular inhibition of mitochondrial energy production, which may contribute to the development of organ failures., Lay Summary: Acute-on-chronic liver failure (ACLF), which develops in patients with cirrhosis, is characterized by intense systemic inflammation and organ failure(s). Because systemic inflammation is energetically expensive, its metabolic costs may result in organ dysfunction/failure. We identified a 38-metabolite blood fingerprint specific for ACLF that revealed mitochondrial dysfunction in peripheral organs. This may contribute to organ failures., (Copyright © 2019 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.)

Staphylococcus aureus is a major human pathogen that can readily acquire antibiotic resistance. For instance, methicillin-resistant S. aureus represents a major cause of hospital- and community-acquired bacterial infections. In this chapter, we first provide a detailed protocol for obtaining unbiased and reproducible S. aureus metabolic profiles. The resulting intracellular metabolome is then analyzed in an untargeted manner by using both hydrophilic interaction liquid chromatography and pentafluorophenyl-propyl columns coupled to high-resolution mass spectrometry. Such analyses are done in conjunction with our in-house spectral database to identify with high confidence as many meaningful S. aureus metabolites as possible. Under these conditions, we can routinely monitor more than 200 annotated S. aureus metabolites. We also indicate how this protocol can be used to investigate the metabolic differences between methicillin-resistant and susceptible strains.

Staphylococcus aureus can cause a variety of severe disease patterns and can readily acquire antibiotic resistance; however, the mechanisms by which this commensal becomes a pathogen or develops antibiotic resistance are still poorly understood. Here we asked whether metabolomics can be used to distinguish bacterial strains with different antibiotic susceptibilities. Thus, an efficient and robust method was first thoroughly implemented to measure the intracellular metabolites of S. aureus in an unbiased and reproducible manner. We also placed special emphasis on metabolome coverage and annotation and used both hydrophilic interaction liquid chromatography and pentafluorophenyl-propyl columns coupled to high-resolution mass spectrometry in conjunction with our spectral database developed in-house to identify with high confidence as many meaningful S. aureus metabolites as possible. Overall, we were able to characterize up to 210 metabolites in S. aureus, which represents a substantial ∼50% improvement over previously published data. We then preliminarily compared the metabolic profiles of 10 clinically relevant methicillin-resistant and susceptible strains harvested at different time points during the exponential growth phase (without any antibiotic exposure). Interestingly, the resulting data revealed a distinct behavior of "slow-growing" resistant strains, which show modified levels of several precursors of peptidoglycan and capsular polysaccharide biosynthesis.

Urine metabolomics is widely used for biomarker research in the fields of medicine and toxicology. As a consequence, characterization of the variations of the urine metabolome under basal conditions becomes critical in order to avoid confounding effects in cohort studies. Such physiological information is however very scarce in the literature and in metabolomics databases so far. Here we studied the influence of age, body mass index (BMI), and gender on metabolite concentrations in a large cohort of 183 adults by using liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS). We implemented a comprehensive statistical workflow for univariate hypothesis testing and modeling by orthogonal partial least-squares (OPLS), which we made available to the metabolomics community within the online Workflow4Metabolomics.org resource. We found 108 urine metabolites displaying concentration variations with either age, BMI, or gender, by integrating the results from univariate p-values and multivariate variable importance in projection (VIP). Several metabolite clusters were further evidenced by correlation analysis, and they allowed stratification of the cohort. In conclusion, our study highlights the impact of gender and age on the urinary metabolome, and thus it indicates that these factors should be taken into account for the design of metabolomics studies.

The metabolome is the set of small molecular mass compounds found in biological media, and metabolomics, which refers to as the analysis of metabolome in a given biological condition, deals with the large scale detection and quantification of metabolites in biological media. It is a data driven and multidisciplinary approach combining analytical chemistry for data acquisition, and biostatistics, informatics and biochemistry for mining and interpretation of these data. Since the middle of the 2000s, high resolution mass spectrometry is widely used in metabolomics, mainly because the detection and identification of metabolites are improved compared to low resolution instruments. As the field of HRMS is quickly and permanently evolving, the aim of this work is to review its use in different aspects of metabolomics, including data acquisition, metabolite annotation, identification and quantification. At last, we would like to show that, thanks to their versatility, HRMS instruments are the most appropriate to achieve optimal metabolome coverage, at the border of other omics fields such as lipidomics and glycomics., (© 2013 Wiley Periodicals, Inc.)

This work aims at evaluating the relevance and versatility of liquid chromatography coupled to high resolution mass spectrometry (LC/HRMS) for performing a qualitative and comprehensive study of the human serum metabolome. To this end, three different chromatographic systems based on a reversed phase (RP), hydrophilic interaction chromatography (HILIC) and a pentafluorophenylpropyl (PFPP) stationary phase were used, with detection in both positive and negative electrospray modes. LC/HRMS platforms were first assessed for their ability to detect, retain and separate 657 metabolite standards representative of the chemical families occurring in biological fluids. More than 75% were efficiently retained in either one LC-condition and less than 5% were exclusively retained by the RP column. These three LC/HRMS systems were then evaluated for their coverage of serum metabolome. The combination of RP, HILIC and PFPP based LC/HRMS methods resulted in the annotation of about 1328 features in the negative ionization mode, and 1358 in the positive ionization mode on the basis of their accurate mass and precise retention time in at least one chromatographic condition. Less than 12% of these annotations were shared by the three LC systems, which highlights their complementarity. HILIC column ensured the greatest metabolome coverage in the negative ionization mode, whereas PFPP column was the most effective in the positive ionization mode. Altogether, 192 annotations were confirmed using our spectral database and 74 others by performing MS/MS experiments. This resulted in the formal or putative identification of 266 metabolites, among which 59 are reported for the first time in human serum., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Metabolic profiles of biofluids obtained by atmospheric pressure ionization mass spectrometry-based technologies contain hundreds to thousands of features, most of them remaining unknown or at least not characterized in analytical systems. We report here on the annotation of the human adult urinary metabolome and metabolite identification from electrospray ionization mass spectrometry (ESI-MS)-based metabolomics data sets. Features of biological interest were first of all annotated using the ESI-MS database of the laboratory. They were also grouped, thanks to software tools, and annotated using public databases. Metabolite identification was achieved using two complementary approaches: (i) formal identification by matching chromatographic retention times, mass spectra, and also product ion spectra (if required) of metabolites to be characterized in biological data sets to those of reference compounds and (ii) putative identification from biological data thanks to MS/MS experiments for metabolites not available in our chemical library. By these means, 384 metabolites corresponding to 1484 annotated features (659 in negative ion mode and 825 in positive ion mode) were characterized in human urine samples. Of these metabolites, 192 and 66 were formally and putatively identified, respectively, and 54 are reported in human urine for the first time. These lists of features could be used by other laboratories to annotate their ESI-MS metabolomics data sets.

Overhydrated hereditary stomatocytosis, clinically characterized by hemolytic anemia, is a rare disorder of the erythrocyte membrane permeability to monovalent cations, associated with mutations in the Rh-associated glycoprotein gene. We assessed the red blood cell metabolome of 4 patients with this disorder and showed recurrent metabolic abnormalities associated with this disease but not due to the diminished half-life of their erythrocytes. Glycolysis is exhausted with accumulation of ADP, pyruvate, lactate, and malate. Ascorbate metabolic pathway is altered probably due to a limited entry of dehydroascorbate. Although no major oxydative stress has been reported in patients with overhydrated hereditary stomatocytosis, we found decreased amounts of oxydized glutathione, creatine and ergothioneine, suggesting transporter abnormalities and/or uncharacterized oxydative stress. These results pinpoint major metabolic defects of overhydrated hereditary stomatocytosis erythrocytes and emphasize the relevance of red blood cell metabolomics for a better understanding of the pathophysiological bases of hemolytic anemia associated with erythrocyte abnormalities.

Emerging metabolomic tools can now be used to establish metabolic signatures of specialized circulating hematopoietic cells in physiologic or pathologic conditions and in human hematologic diseases. To determine metabolomes of normal and sickle cell erythrocytes, we used an extraction method of erythrocytes metabolites coupled with a liquid chromatography-mass spectrometry-based metabolite profiling method. Comparison of these 2 metabolomes identified major changes in metabolites produced by (1) endogenous glycolysis characterized by accumulation of many glycolytic intermediates; (2) endogenous glutathione and ascorbate metabolisms characterized by accumulation of ascorbate metabolism intermediates, such as diketogulonic acid and decreased levels of both glutathione and glutathione disulfide; (3) membrane turnover, such as carnitine, or membrane transport characteristics, such as amino acids; and (4) exogenous arginine and NO metabolisms, such as spermine, spermidine, or citrulline. Finally, metabolomic analysis of young and old normal red blood cells indicates metabolites whose levels are directly related to sickle cell disease. These results show the relevance of metabolic profiling for the follow-up of sickle cell patients or other red blood cell diseases and pinpoint the importance of metabolomics to further depict the pathophysiology of human hematologic diseases.

The metabolome is characterized by a large number of molecules exhibiting a high diversity of chemical structures and abundances, requiring complementary analytical platforms for extensive coverage. Of these analytical platforms, atmospheric pressure ionization Fourier transform mass spectrometry (FT/MS) instruments are popular because they provide accurate mass measurements with ppm and even sub-ppm errors, and also high and ultra-high resolving power. In this article, we evaluate the improvements provided for metabolomics by different types of FT/MS instruments, together with the ability of these platforms to cover the various analytical requirements: global metabolite profiling, absolute quantification and also structural characterization, of metabolomics. The specificities of FT/MS in terms of data pre-processing and the input of accurate mass measurements for biological interpretation and for highlighting metabolic networks are also addressed.

Abstract: Metabolic signatures of specialized circulating hematopoietic cells in physiological or human hematological diseases start to be described. We use a simple and highly reproductive extraction method of erythrocytes metabolites coupled with a liquid chromatography-mass spectrometry based metabolites profiling method to determine metabolomes of normal and sickle cell erythrocytes. Sickle cell erythrocytes and normal erythrocytes metabolomes display major differences in glycolysis, in glutathione, in ascorbate metabolisms and in metabolites associated to membranes turnover. In addition, the amounts of metabolites derived from urea cycle and NO metabolism that partly take place within erythrocyte were different between normal and sickle cell erythrocytes. These results show that metabolic profiling of red blood cell diseases can now be determined and might indicate new biomarkers that can be used for the follow-up of sickle cell patients. [ABSTRACT FROM AUTHOR]