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Abstract Primary Hyperparathyroidism (PHPT) is characterized by excessive parathormone (PTH) secretion and disrupted calcium homeostasis. Untargeted metabolomics offers a valuable approach to understanding the complex metabolic alterations associated with different diseases, including PHPT. Plasma untargeted metabolomics was applied to investigate the metabolic profiles of PHPT patients compared to a control group. Two complementary liquid-phase separation techniques were employed to comprehensively explore the metabolic landscape in this retrospective, single-center study. The study comprised 28 female patients diagnosed following the current guidelines of PHPT diagnosis and a group of 30 healthy females as a control group. To evaluate their association with PHPT, we identified changes in plasma metabolic profiles in patients with PHPT compared to the control group. The primary outcome measure included detecting plasma metabolites and discriminating PHPT patients from controls. The study unveiled specific metabolic imbalances that may link l-amino acids with peptic ulcer disease, gamma-glutamyls with oxidative stress, and asymmetric dimethylarginine (ADMA) with cardiovascular complications. Several metabolites, such as gamma-glutamyls, caffeine, sex hormones, carnitine, sphingosine-1-phosphate (S-1-P), and steroids, were connected with reduced bone mineral density (BMD). Metabolic profiling identified distinct metabolic patterns between patients with PHPT and healthy controls. These findings provided valuable insights into the pathophysiology of PHPT.

IntroductionGestational diabetes mellitus (GDM) is a global health concern with significant short and long-term complications for both mother and baby. Early prediction of GDM, particularly late-onset, is crucial for implementing timely interventions to mitigate adverse outcomes. In this study, we conducted a comprehensive metabolomic analysis to explore potential biomarkers for early GDM prediction.MethodsPlasma samples were collected during the first trimester from 60 women: 20 with early-onset GDM, 20 with late-onset GDM, and 20 with normal glucose tolerance. Using advanced analytical techniques, including liquid chromatography-tandem mass spectrometry (LC-MS/MS) and gas chromatography-mass spectrometry (GC-MS), we profiled over 150 lipid species and central carbon metabolism intermediates.ResultsSignificant metabolic alterations were observed in both early- and late-onset GDM groups compared to healthy controls, with a specific focus on glycerolipids, fatty acids, and glucose metabolism. Key findings revealed a 4.0-fold increase in TG(44:0), TG(46:0), TG(46:1) with p-values

Type 2 diabetes mellitus (T2DM) is one of the most common worldwide metabolic disorders, characterized by insulin resistance (IR) and defective insulin secretion by pancreatic β-cells which leads to multiple complications such as bone fragility. This complication might be influenced by other factors such as gender and cardiovascular disease (CVD). However, it is unclear why a certain T2DM group develops bone fragility, and what the molecular mechanism is. Metabolomics is a powerful approach to the study of human metabolism, especially in complex diseases such as T2DM. Thus, this study aimed to identify significant metabolites associated with bone fragility in T2DM patients. To achieve this, 81 individuals were enrolled and classified as T2DM patients (D, n=28), T2DM with bone fragility (D-Frag, n=25), or age-matched non-diabetic subjects (ND, n=28) as the control group. Serum samples were collected and analyzed using liquid chromatography and gas chromatography, both coupled to mass spectrometry (LC-MS and GC-MS, respectively). Samples were compared within four different scenarios: 1) the classical comparison of D vs ND to corroborate previous studies; 2) D-Frag vs D to explore the metabolites mainly associated with bone fragility; 3) the same comparison using male data (MD-Frag vs MD) to study as a more homogeneous model of bone fragility as in women, bone fragility could be mainly associated with hormonal stage and pregnancy; and 4) MD-Frag-CVD vs MD-CVD to explore the influence of bone fragility in the male-based model with CVD considering that most of the T2DM patients suffer from CVD. After analysis of these scenarios, our results suggest that acylcarnitines and glycerophospholipids, among other metabolites, are involved in the development of bone fragility in T2DM.

Liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS)-based methods have become the gold standard methodology for the comprehensive profiling of the human plasma lipidome. However, both the complexity of lipid chemistry and LC-HRMS-associated data pose challenges to the characterization of this biological matrix. In accordance with the current consensus of quality requirements for LC-HRMS lipidomics data, we aimed to characterize the NIST® Standard Reference Material for Human Plasma (SRM 1950) using an LC-ESI(+/−)-MS method compatible with high-throughput lipidome profiling. We generated a highly curated lipid database with increased coverage, quality, and consistency, including additional quality assurance procedures involving adduct formation, within-method m/z evaluation, retention behavior of species within lipid chain isomers, and expert-driven resolution of isomeric and isobaric interferences. As a proof-of-concept, we showed the utility of our in-house LC-MS lipidomic database —consisting of 592 lipid entries— for the fast, comprehensive, and reliable lipidomic profiling of the human plasma from healthy human volunteers. We are confident that the implementation of this robust resource and methodology will have a significant impact by reducing data redundancy and the current delays and bottlenecks in untargeted plasma lipidomic studies.

Background: Altered bacterial translocation is associated with changes in hepatic function and the progression from compensated to decompensated cirrhosis. Child-Turcotte-Pugh (CTP) score is an essential indicator of liver severity. Thus, we aimed to study differences in the blood microbiome together with metabolome profile between HCV-infected patients with CTP class B (CTP-B, significant functional compromise) and patients with CTP class A (CTP-A, well-compensated cirrhosis). Methods: We conducted a cross-sectional study in patients with advanced HCV-related cirrhosis (n = 88) stratified by CTP-B and CTP-A. Bacterial 16S rRNA sequencing was sequenced by MiSeq Illumina technology and non-targeted metabolomics was performed by GC-MS and LC-MS ESI+ and ESI- to complement the analysis. Results: Patients with CTP-B had lower levels of richness (Chao1), and alpha diversity (Shannon and Simpson indexes) at phylum level than patients with CTP-A. Likewise, we observed significant differences in beta diversity between groups at phylum, class, and order levels, showing lower diversity in patients with CTP-B. Higher relative abundance of Proteobacteria (p = 0.012), Alphaproteobacteria (p = 0.005), Sphingomonadales (p = 0.012) and Sphingomonadaceae (p = 0.016) were significantly associated with CTP-B. The phylum Proteobacteria was positively correlated with ethanolamine and oleic acid (p = 0.005 and p = 0.004, respectively) and negatively with p-cresol (p = 0.006). In addition, the order Sphingomonadales and the family Sphingomonadaceae was also negatively correlated with p-cresol (p = 0.001 and p = 0.001). Conclusions: Blood microbial diversity was significantly decreased in patients with CTP-B, who presented an enrichment of Proteobacteria, Alphaproteobacteria, Sphingomonadales and Sphingomonadaceae compared to patients with CTP-A.

Abstract The human gut microbiome establishes and matures during infancy, and dysregulation at this stage may lead to pathologies later in life. We conducted a multi-omics study comprising three generations of family members to investigate the early development of the gut microbiota. Fecal samples from 200 individuals, including infants (0-12 months old; 55% females, 45% males) and their respective mothers and grandmothers, were analyzed using two independent metabolomics platforms and metagenomics. For metabolomics, gas chromatography and capillary electrophoresis coupled to mass spectrometry were applied. For metagenomics, both 16S rRNA gene and shotgun sequencing were performed. Here we show that infants greatly vary from their elders in fecal microbiota populations, function, and metabolome. Infants have a less diverse microbiota than adults and present differences in several metabolite classes, such as short- and branched-chain fatty acids, which are associated with shifts in bacterial populations. These findings provide innovative biochemical insights into the shaping of the gut microbiome within the same generational line that could be beneficial in improving childhood health outcomes.

Abstract Heart failure (HF) studies typically focus on ischemic and idiopathic heart diseases. Chronic chagasic cardiomyopathy (CCC) is a progressive degenerative inflammatory condition highly prevalent in Latin America that leads to a disturbance of cardiac conduction system. Despite its clinical and epidemiological importance, CCC molecular pathogenesis is poorly understood. Here we characterize and discriminate the plasma metabolomic profile of 15 patients with advanced HF referred for heart transplantation – 8 patients with CCC and 7 with idiopathic dilated cardiomyopathy (IDC) – using gas chromatography/quadrupole time-of-flight mass spectrometry. Compared to the 12 heart donor individuals, also included to represent the control (CTRL) scenario, patients with advanced HF exhibited a metabolic imbalance with 21 discriminating metabolites, mostly indicative of accumulation of fatty acids, amino acids and important components of the tricarboxylic acid (TCA) cycle. CCC vs. IDC analyses revealed a metabolic disparity between conditions, with 12 CCC distinctive metabolites vs. 11 IDC representative metabolites. Disturbances were mainly related to amino acid metabolism profile. Although mitochondrial dysfunction and loss of metabolic flexibility may be a central mechanistic event in advanced HF, metabolic imbalance differs between CCC and IDC populations, possibly explaining the dissimilar clinical course of Chagas’ patients.

Abstract Accurate lipid annotation is crucial for understanding the role of lipids in health and disease and identifying therapeutic targets. However, annotating the wide variety of lipid species in biological samples remains challenging in untargeted lipidomic studies. In this work, we present a lipid annotation workflow based on LC-MS and MS/MS strategies, the combination of four bioinformatic tools, and a decision tree to support the accurate annotation and semi-quantification of the lipid species present in lung tissue from control mice. The proposed workflow allowed us to generate a lipid lung-based ATLAS (LiLA), which was then employed to unveil the lipidomic signatures of the Mycobacterium tuberculosis infection at two different time points for a deeper understanding of the disease progression. This workflow, combined with manual inspection strategies of MS/MS data, can enhance the annotation process for lipidomic studies and guide the generation of sample-specific lipidome maps. LiLA serves as a freely available data resource that can be employed in future studies to address lipidomic alterations in mice lung tissue.

Abstract The mechanisms driving SARS-CoV-2 susceptibility remain poorly understood, especially the factors determining why unvaccinated individuals remain uninfected despite high-risk exposures. To understand lipid and metabolite profiles related with COVID-19 susceptibility and disease progression. We collected samples from an exceptional group of unvaccinated healthcare workers heavily exposed to SARS-CoV-2 but not infected (‘non-susceptible’) and subjects who became infected during the follow-up (‘susceptible’), including non-hospitalized and hospitalized patients with different disease severity providing samples at early disease stages. Then, we analyzed their plasma metabolomic profiles using mass spectrometry coupled with liquid and gas chromatography. We show specific lipids profiles and metabolites that could explain SARS-CoV-2 susceptibility and COVID-19 severity. More importantly, non-susceptible individuals show a unique lipidomic pattern characterized by the upregulation of most lipids, especially ceramides and sphingomyelin, which could be interpreted as markers of low susceptibility to SARS-CoV-2 infection. This study strengthens the findings of other researchers about the importance of studying lipid profiles as relevant markers of SARS-CoV-2 pathogenesis.

BackgroundCombination antiretroviral therapy (ART) has transformed human immunodeficiency virus (HIV) infection in people with HIV (PWH). However, a chronic state of immune activation and inflammation is maintained despite achieving HIV suppression and satisfactory immunological recovery. We aimed to determine whether the plasma metabolomic profile of PWH on long-term suppressive ART and immunologically recovered approximates the normality by comparison with healthy controls with similar age and gender.MethodsWe carried out a cross-sectional study in 17 PWH on long-term ART (HIV-RNA

Abstract ATPase Inhibitory Factor 1 (IF1) regulates the activity of mitochondrial ATP synthase. The expression of IF1 in differentiated human and mouse cells is highly variable. In intestinal cells, the overexpression of IF1 protects against colon inflammation. Herein, we have developed a conditional IF1-knockout mouse model in intestinal epithelium to investigate the role of IF1 in mitochondrial function and tissue homeostasis. The results show that IF1-ablated mice have increased ATP synthase/hydrolase activities, leading to profound mitochondrial dysfunction and a pro-inflammatory phenotype that impairs the permeability of the intestinal barrier compromising mouse survival upon inflammation. Deletion of IF1 prevents the formation of oligomeric assemblies of ATP synthase and alters cristae structure and the electron transport chain. Moreover, lack of IF1 promotes an intramitochondrial Ca2+ overload in vivo, minimizing the threshold to Ca2+-induced permeability transition (mPT). Removal of IF1 in cell lines also prevents the formation of oligomeric assemblies of ATP synthase, minimizing the threshold to Ca2+-induced mPT. Metabolomic analyses of mice serum and colon tissue highlight that IF1 ablation promotes the activation of de novo purine and salvage pathways. Mechanistically, lack of IF1 in cell lines increases ATP synthase/hydrolase activities and installs futile ATP hydrolysis in mitochondria, resulting in the activation of purine metabolism and in the accumulation of adenosine, both in culture medium and in mice serum. Adenosine, through ADORA2B receptors, promotes an autoimmune phenotype in mice, stressing the role of the IF1/ATP synthase axis in tissue immune responses. Overall, the results highlight that IF1 is required for ATP synthase oligomerization and that it acts as a brake to prevent ATP hydrolysis under in vivo phosphorylating conditions in intestinal cells.

Exhaled breath analysis, with particular emphasis on volatile organic compounds, represents a growing area of clinical research due to its obvious advantages over other diagnostic tests. Numerous pathologies have been extensively investigated for the identification of specific biomarkers in exhalates through metabolomics. However, the transference of breath tests to clinics remains limited, mainly due to deficiency in methodological standardization. Critical steps include the selection of breath sample types, collection devices, and enrichment techniques. GC-MS is the reference analytical technique for the analysis of volatile organic compounds in exhalates, especially during the biomarker discovery phase in metabolomics. This review comprehensively examines and compares metabolomic studies focusing on cancer, lung diseases, and infectious diseases. In addition to delving into the experimental designs reported, it also provides a critical discussion of the methodological aspects, ranging from the experimental design and sample collection to the identification of potential pathology-specific biomarkers.

Introduction: Lung cancer is one of the most frequently studied types of cancer and represents the most common and lethal neoplasm. Our previous research on non-small cell lung cancer (NSCLC) has revealed deep lipid profile reprogramming and redox status disruption in cancer patients. Lung cell membranes are rich in phospholipids that are susceptible to oxidation, leading to the formation of bioactive oxidized phosphatidylcholines (oxPCs). Persistent and elevated levels of oxPCs have been shown to induce chronic inflammation, leading to detrimental effects. However, recent reports suggest that certain oxPCs possess anti-inflammatory, pro-survival, and endothelial barrier-protective properties. Thus, we aimed to measure the levels of oxPCs in NSCLC patients and investigate their potential role in lung cancer.Methods: To explore the oxPCs profiles in lung cancer, we performed in-depth, multi-level metabolomic analyses of nearly 350 plasma and lung tissue samples from 200 patients with NSCLC, including adenocarcinoma (ADC) and squamous cell carcinoma (SCC), the two most prevalent NSCLC subtypes and COPD patients as a control group. First, we performed oxPC profiling of plasma samples. Second, we analyzed tumor and non-cancerous lung tissues collected during the surgical removal of NSCLC tumors. Because of tumor tissue heterogeneity, subsequent analyses covered the surrounding healthy tissue and peripheral and central tumors. To assess whether the observed phenotypic changes in the patients were associated with measured oxPC levels, metabolomics data were augmented with data from medical records.Results: We observed a predominance of long-chain oxPCs in plasma samples and of short-chain oxPCs in tissue samples from patients with NSCLC. The highest concentration of oxPCs was observed in the central tumor region. ADC patients showed higher levels of oxPCs compared to the control group, than patients with SCC.Conclusion: The detrimental effects associated with the accumulation of short-chain oxPCs suggest that these molecules may have greater therapeutic utility than diagnostic value, especially given that elevated oxPC levels are a hallmark of multiple types of cancer.

Introduction: Obesity results from an interplay between genetic predisposition and environmental factors such as diet, physical activity, culture, and socioeconomic status. Personalized treatments for obesity would be optimal, thus necessitating the identification of individual characteristics to improve the effectiveness of therapies. For example, genetic impairment of the leptin-melanocortin pathway can result in rare cases of severe early-onset obesity. Metabolomics has the potential to distinguish between a healthy and obese status; however, differentiating subsets of individuals within the obesity spectrum remains challenging. Factor analysis can integrate patient features from diverse sources, allowing an accurate subclassification of individuals.Methods: This study presents a workflow to identify metabotypes, particularly when routine clinical studies fail in patient categorization. 110 children with obesity (BMI > +2 SDS) genotyped for nine genes involved in the leptin-melanocortin pathway (CPE, MC3R, MC4R, MRAP2, NCOA1, PCSK1, POMC, SH2B1, and SIM1) and two glutamate receptor genes (GRM7 and GRIK1) were studied; 55 harboring heterozygous rare sequence variants and 55 with no variants. Anthropometric and routine clinical laboratory data were collected, and serum samples processed for untargeted metabolomic analysis using GC-q-MS and CE-TOF-MS and reversed-phase U(H)PLC-QTOF-MS/MS in positive and negative ionization modes. Following signal processing and multialignment, multivariate and univariate statistical analyses were applied to evaluate the genetic trait association with metabolomics data and clinical and routine laboratory features.Results and Discussion: Neither the presence of a heterozygous rare sequence variant nor clinical/routine laboratory features determined subgroups in the metabolomics data. To identify metabolomic subtypes, we applied Factor Analysis, by constructing a composite matrix from the five analytical platforms. Six factors were discovered and three different metabotypes. Subtle but neat differences in the circulating lipids, as well as in insulin sensitivity could be established, which opens the possibility to personalize the treatment according to the patients categorization into such obesity subtypes. Metabotyping in clinical contexts poses challenges due to the influence of various uncontrolled variables on metabolic phenotypes. However, this strategy reveals the potential to identify subsets of patients with similar clinical diagnoses but different metabolic conditions. This approach underscores the broader applicability of Factor Analysis in metabotyping across diverse clinical scenarios.

Abstract Evidence is mounting that the nature of the lipid bound to the endothelial cell protein C receptor (EPCR) has an impact on its biological roles, as observed in anticoagulation and more recently, in autoimmune disease. Phosphatidylethanolamine and phosphatidylcholine species dominate the EPCR lipid cargo, yet, the extent of diversity in the EPCR-associated lipid repertoire is still unknown and remains to be uncovered. We undertook mass spectrometry analyses to decipher the EPCR lipidome, and identified species not yet described as EPCR ligands, such as phosphatidylinositols and phosphatidylserines. Remarkably, we found further, more structurally divergent lipids classes, represented by ceramides and sphingomyelins, both in less abundant quantities. In support of our mass spectrometry results and previous studies, high-resolution crystal structures of EPCR in three different space groups point to a prevalent diacyl phospholipid moiety in EPCR’s pocket but a mobile and ambiguous lipid polar head group. In sum, these studies indicate that EPCR can associate with varied lipid classes, which might impact its properties in anticoagulation and the onset of autoimmune disease.

IntroductionMacrophages are a heterogeneous population of innate immune cells that support tissue homeostasis through their involvement in tissue development and repair, and pathogen defense. Emerging data reveal that metabolism may control macrophage polarization and function and, conversely, phenotypic polarization may drive metabolic reprogramming.MethodsHere we use biochemical analysis, correlative cryogenic fluorescence microscopy and cryo-focused ion-beam scanning electron microscopy.ResultsWe demonstrate that growth hormone (GH) reprograms inflammatory GM-CSF-primed monocyte-derived macrophages (GM-MØ) by functioning as a metabolic modulator. We found that exogenous treatment of GM-MØ with recombinant human GH reduced glycolysis and lactate production to levels similar to those found in anti-inflammatory M-MØ. Moreover, GH treatment of GM-MØ augmented mitochondrial volume and altered mitochondrial dynamics, including the remodeling of the inner membrane to increase the density of cristae.ConclusionsOur data demonstrate that GH likely serves a modulatory role in the metabolism of inflammatory macrophages and suggest that metabolic reprogramming of macrophages should be considered as a new target to intervene in inflammatory diseases.

Background: Chronic kidney disease (CKD) is characterized by the progressive and irreversible deterioration of kidney function and structure with the appearance of renal fibrosis. A significant decrease in mitochondrial metabolism, specifically a reduction in fatty acid oxidation (FAO) in tubular cells, is observed in tubulointerstitial fibrosis, whereas FAO enhancement provides protection. Untargeted metabolomics offers the potential to provide a comprehensive analysis of the renal metabolome in the context of kidney injury.Methodology: Renal tissue from a carnitine palmitoyl transferase 1a (Cpt1a) overexpressing mouse model, which displays enhanced FAO in the renal tubule, subjected to folic acid nephropathy (FAN) was studied through a multiplatform untargeted metabolomics approach based on LC-MS, CE-MS and GC-MS analysis to achieve the highest coverage of the metabolome and lipidome affected by fibrosis. The expression of genes related to the biochemical routes showing significant changes was also evaluated.Results: By combining different tools for signal processing, statistical analysis and feature annotation, we were able to identify variations in 194 metabolites and lipids involved in many metabolic routes: TCA cycle, polyamines, one-carbon metabolism, amino acid metabolism, purine metabolism, FAO, glycerolipids and glycerophospholipids synthesis and degradation, glycosphingolipids interconversion, and sterol metabolism. We found several metabolites strongly altered by FAN, with no reversion induced by Cpt1a overexpression (v.g. citric acid), whereas other metabolites were influenced by CPT1A-induced FAO (v.g. glycine-betaine).Conclusion: It was implemented a successful multiplatform metabolomics approach for renal tissue analysis. Profound metabolic changes accompany CKD-associated fibrosis, some associated with tubular FAO failure. These results highlight the importance of addressing the crosstalk between metabolism and fibrosis when undertaking studies attempting to elucidate the mechanism of CKD progression.

Rhizobium leguminosarum bv. viciae (Rlv) UPM791 effectively nodulates pea and lentil, but bacteroids contain a number of proteins differentially expressed depending on the host. One of these host-dependent proteins (C189) is similar to a diaminobutyrate-2-oxoglutarate aminotransferase (DABA-AT). DABA-AT activity was demonstrated with cell extracts and with purified protein, so C189 was renamed as Dat. The dat gene was strongly induced in the central, active area of pea nodules, but not in lentil. Mutants defective in dat were impaired in symbiotic performance with pea plants, exhibiting reduced shoot dry weight, smaller nodules, and a lower competitiveness for nodulation. In contrast, there were no significant differences between mutant and wild-type in symbiosis with lentil plants. A comparative metabolomic approach using cell-free extracts from bacteroids induced in pea and lentil showed significant differences among the strains in pea bacteroids whereas no significant differences were found in lentil. Targeted metabolomic analysis revealed that the dat mutation abolished the presence of 2,4-diaminobutyrate (DABA) in pea nodules, indicating that DABA-AT reaction is oriented toward the production of DABA from L-aspartate semialdehyde. This analysis also showed the presence of L-homoserine, a likely source of aspartate semialdehyde, in pea bacteroids but not in those induced in lentil. The dat mutant showed impaired growth when cells were grown with L-homoserine as nitrogen source. Inclusion of DABA or L-homoserine as N source suppressed pantothenate auxotropy in Rlv UPM791, suggesting DABA as source of the pantothenate precursor β-alanine. These data indicate that Rlv UPM791 Dat enzyme is part of an adaptation mechanism of this bacterium to a homoserine-rich environment such as pea nodule and rhizosphere.

Abstract Retention time information is used for metabolite annotation in metabolomic experiments. But its usefulness is hindered by the availability of experimental retention time data in metabolomic databases, and by the lack of reproducibility between different chromatographic methods. Accurate prediction of retention time for a given chromatographic method would be a valuable support for metabolite annotation. We have trained state-of-the-art machine learning regressors using the 80, 038 experimental retention times from the METLIN Small Molecule Retention Tim (SMRT) dataset. The models included deep neural networks, deep kernel learning, several gradient boosting models, and a blending approach. 5, 666 molecular descriptors and 2, 214 fingerprints (MACCS166, Extended Connectivity, and Path Fingerprints fingerprints) were generated with the alvaDesc software. The models were trained using only the descriptors, only the fingerprints, and both types of features simultaneously. Bayesian hyperparameter search was used for parameter tuning. To avoid data-leakage when reporting the performance metrics, nested cross-validation was employed. The best results were obtained by a heavily regularized deep neural network trained with cosine annealing warm restarts and stochastic weight averaging, achieving a mean and median absolute errors of $$39.2 \pm 1.2\; s$$ 39.2 ± 1.2 s and $$17.2 \pm 0.9\;s$$ 17.2 ± 0.9 s , respectively. To the best of our knowledge, these are the most accurate predictions published up to date over the SMRT dataset. To project retention times between chromatographic methods, a novel Bayesian meta-learning approach that can learn from just a few molecules is proposed. By applying this projection between the deep neural network retention time predictions and a given chromatographic method, our approach can be integrated into a metabolite annotation workflow to obtain z-scores for the candidate annotations. To this end, it is enough that just as few as 10 molecules of a given experiment have been identified (probably by using pure metabolite standards). The use of z-scores permits considering the uncertainty in the projection when ranking candidates, and not only the accuracy. In this scenario, our results show that in 68% of the cases the correct molecule was among the top three candidates filtered by mass and ranked according to z-scores. This shows the usefulness of this information to support metabolite annotation. Python code is available on GitHub at https://github.com/constantino-garcia/cmmrt.

Abstract Background Cholangiocarcinoma (CCA) is still a deadly tumour. Histological and molecular aspects of thioacetamide (TAA)-induced intrahepatic CCA (iCCA) in rats mimic those of human iCCA. Carcinogenic changes and therapeutic vulnerabilities in CCA may be captured by molecular investigations in bile, where we performed bile proteomic and metabolomic analyses that help discovery yet unknown pathways relevant to human iCCA. Methods Cholangiocarcinogenesis was induced in rats (TAA) and mice (Jnk Δhepa + CCl4 + DEN model). We performed proteomic and metabolomic analyses in bile from control and CCA-bearing rats. Differential expression was validated in rat and human CCAs. Mechanisms were addressed in human CCA cells, including Huh28-KRASG12D cells. Cell signaling, growth, gene regulation and [U-13C]-D-glucose-serine fluxomics analyses were performed. In vivo studies were performed in the clinically-relevant iCCA mouse model. Results Pathways related to inflammation, oxidative stress and glucose metabolism were identified by proteomic analysis. Oxidative stress and high amounts of the oncogenesis-supporting amino acids serine and glycine were discovered by metabolomic studies. Most relevant hits were confirmed in rat and human CCAs (TCGA). Activation of interleukin-6 (IL6) and epidermal growth factor receptor (EGFR) pathways, and key genes in cancer-related glucose metabolic reprogramming, were validated in TAA-CCAs. In TAA-CCAs, G9a, an epigenetic pro-tumorigenic writer, was also increased. We show that EGFR signaling and mutant KRASG12D can both activate IL6 production in CCA cells. Furthermore, phosphoglycerate dehydrogenase (PHGDH), the rate-limiting enzyme in serine-glycine pathway, was upregulated in human iCCA correlating with G9a expression. In a G9a activity-dependent manner, KRASG12D promoted PHGDH expression, glucose flow towards serine synthesis, and increased CCA cell viability. KRASG12D CAA cells were more sensitive to PHGDH and G9a inhibition than controls. In mouse iCCA, G9a pharmacological targeting reduced PHGDH expression. Conclusions In CCA, we identified new pro-tumorigenic mechanisms: Activation of EGFR signaling or KRAS mutation drives IL6 expression in tumour cells; Glucose metabolism reprogramming in iCCA includes activation of the serine-glycine pathway; Mutant KRAS drives PHGDH expression in a G9a-dependent manner; PHGDH and G9a emerge as therapeutic targets in iCCA.

Abstract Pleiotrophin (PTN) is a cytokine involved in nerve tissue repair processes, neuroinflammation and neuronal survival. PTN expression levels are upregulated in the nigrostriatal pathway of Parkinson’s Disease (PD) patients. We aimed to characterize the dopaminergic injury and glial responses in the nigrostriatal pathway of mice with transgenic Ptn overexpression in the brain (Ptn-Tg) after intrastriatal injection of the catecholaminergic toxic 6-hydroxydopamine (6-OHDA) at a low dose (5 µg). Ten days after surgery, the injection of 6-OHDA induced a significant decrease of the number of tyrosine hydroxylase (TH)-positive neurons in the substantia nigra and of the striatal TH contents in Wild type (Wt) mice. In contrast, these effects of 6-OHDA were absent in Ptn-Tg mice. When the striatal Iba1 and GFAP immunoreactivity was studied, no statistical differences were found between vehicle-injected Wt and Ptn-Tg mice. Furthermore, 6-OHDA did not cause robust glial responses neither on Wt or Ptn-Tg mice 10 days after injections. In metabolomics studies, we detected interesting metabolites that significantly discriminate the more injured 6-OHDA-injected Wt striatum and the more protected 6-OHDA-injected Ptn-Tg striatum. Particularly, we detected groups of metabolites, mostly corresponding to phospholipids, whose trends were opposite in both groups. In summary, the data confirm lower 6-OHDA-induced decreases of TH contents in the nigrostriatal pathway of Ptn-Tg mice, suggesting a neuroprotective effect of brain PTN overexpression in this mouse model of PD. New lipid-related PD drug candidates emerge from this study and the data presented here support the increasingly recognized “lipid cascade” in PD.

Abstract Metabolic reprogramming contributes to oncogenesis, tumor growth, and treatment resistance in pancreatic ductal adenocarcinoma (PDAC). Here we report the effects of (R,S′)-4′-methoxy-1-naphthylfenoterol (MNF), a GPR55 antagonist and biased β2-adrenergic receptor (β2-AR) agonist on cellular signaling implicated in proliferation and metabolism in PDAC cells. The relative contribution of GPR55 and β2-AR in (R,S′)-MNF signaling was explored further in PANC-1 cells. Moreover, the effect of (R,S′)-MNF on tumor growth was determined in a PANC-1 mouse xenograft model. PANC-1 cells treated with (R,S′)-MNF showed marked attenuation in GPR55 signal transduction and function combined with increased β2-AR/Gαs/adenylyl cyclase/PKA signaling, both of which contributing to lower MEK/ERK, PI3K/AKT and YAP/TAZ signaling. (R,S′)-MNF administration significantly reduced PANC-1 tumor growth and circulating l-lactate concentrations. Global metabolic profiling of (R,S′)-MNF-treated tumor tissues revealed decreased glycolytic metabolism, with a shift towards normoxic processes, attenuated glutamate metabolism, and increased levels of ophthalmic acid and its precursor, 2-aminobutyric acid, indicative of elevated oxidative stress. Transcriptomics and immunoblot analyses indicated the downregulation of gene and protein expression of HIF-1α and c-Myc, key initiators of metabolic reprogramming in PDAC. (R,S′)-MNF treatment decreased HIF-1α and c-Myc expression, attenuated glycolysis, shifted fatty acid metabolism towards β-oxidation, and suppressed de novo pyrimidine biosynthesis in PANC-1 tumors. The results indicate a potential benefit of combined GPR55 antagonism and biased β2-AR agonism in PDAC therapy associated with the deprogramming of altered cellular metabolism.

It is increasingly evident that a more detailed molecular structure analysis of isomeric lipids is critical to better understand their roles in biological processes. The occurrence of isomeric interference complicates conventional tandem mass spectrometry (MS/MS)-based determination, necessitating the development of more specialised methodologies to separate lipid isomers. The present review examines and discusses recent lipidomic studies based on ion mobility spectrometry combined with mass spectrometry (IMS-MS). Selected examples of the separation and elucidation of structural and stereoisomers of lipids are described based on their ion mobility behaviour. These include fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, and sterol lipids. Recent approaches for specific applications to improve isomeric lipid structural information using direct infusion, coupling imaging, or liquid chromatographic separation workflows prior to IMS-MS are also discussed, including: 1) strategies to improve ion mobility shifts; 2) advanced tandem MS methods based on activation of lipid ions with electrons or photons, or gas-phase ion-molecule reactions; and 3) the use of chemical derivatisation techniques for lipid characterisation.

ABSTRACT The reprogramming of cellular metabolism of immune cells is an essential process in the regulation of antifungal immune responses. In particular, glucose metabolism has been shown to be required for protective immunity against infection with Aspergillus fumigatus. However, given the intricate cross talk between multiple metabolic networks and signals, it is likely that cellular metabolic pathways other than glycolysis are also relevant during fungal infection. In this study, we demonstrate that glutamine metabolism is required for the activation of macrophage effector functions against A. fumigatus. Glutamine metabolism was found to be upregulated early after fungal infection and glutamine depletion or the pharmacological inhibition of enzymes involved in its metabolism impaired phagocytosis and the production of both proinflammatory and T-cell-derived cytokines. In an in vivo model, inhibition of glutaminase increased susceptibility to experimental aspergillosis, as revealed by the increased fungal burden and inflammatory pathology, and the defective cytokine production in the lungs. Moreover, genetic variants in glutamine metabolism genes were found to regulate cytokine production in response to A. fumigatus stimulation. Taken together, our results demonstrate that glutamine metabolism represents an important component of the immunometabolic response of macrophages against A. fumigatus both in vitro and in vivo. IMPORTANCE The fungal pathogen Aspergillus fumigatus can cause severe and life-threatening forms of infection in immunocompromised patients. The reprogramming of cellular metabolism is essential for innate immune cells to mount effective antifungal responses. In this study, we report the pivotal contribution of glutaminolysis to the host defense against A. fumigatus. Glutamine metabolism was essential both in vitro as well as in in vivo models of infection, and genetic variants in human glutamine metabolism genes regulated cytokine production in response to fungal stimulation. This work highlights the relevance of glutaminolysis to the pathogenesis of aspergillosis and supports a role for interindividual genetic variation influencing glutamine metabolism in susceptibility to infection.

ABSTRACT Plasmid-mediated antimicrobial resistance is one of the major threats to public health worldwide. The mechanisms involved in the plasmid/host coadaptation are still poorly characterized, and their understanding is crucial to comprehend the genesis and evolution of multidrug-resistant bacteria. With this purpose, we designed an experimental evolution using Haemophilus influenzae RdKW20 as the model strain carrying the ColE1-like plasmid pB1000. Five H. influenzae populations adapted previously to the culture conditions were transformed with pB1000 and subsequently evolved to compensate for the plasmid-associated fitness cost. Afterward, we performed an integrative multiomic analysis combining genomics, transcriptomics, and metabolomics to explore the molecular mechanisms involved in the compensatory evolution of the plasmid. Our results demonstrate that minimal modifications in the host are responsible for plasmid adaptation. Among all of them, the most enriched process was amino acid metabolism, especially those pathways related to serine, tryptophan, and arginine, eventually related to the genesis and resolution of plasmid dimers. Additional rearrangements occurred during the plasmid adaptation, such as an overexpression of the ribonucleotide reductases and metabolic modifications within specific membrane phospholipids. All these findings demonstrate that the plasmid compensation occurs through the combination of diverse host-mediated mechanisms, of which some are beyond genomic and transcriptomic modifications. IMPORTANCE The ability of bacteria to horizontally transfer genetic material has turned antimicrobial resistance into one of the major sanitary crises of the 21st century. Plasmid conjugation is considered the main mechanism responsible for the mobilization of resistance genes, and its understanding is crucial to tackle this crisis. It is generally accepted that the acquisition and maintenance of mobile genetic elements entail a fitness cost to its host, which is susceptible to be alleviated through a coadaptation process or compensatory evolution. Notwithstanding, despite recent major efforts, the underlying mechanisms involved in this adaptation remain poorly characterized. Analyzing the plasmid/host coadaptation from a multiomic perspective sheds light on the physiological processes involved in the compensation, providing a new understanding on the genesis and evolution of plasmid-mediated antimicrobial-resistant bacteria.

Abstract The lack of knowledge about the onset and progression of Parkinson’s disease (PD) hampers its early diagnosis and treatment. Metabolomics might shed light on the PD imprint seeking a broader view of the biochemical remodeling induced by this disease in an early and pre-symptomatic stage and unveiling potential biomarkers. To achieve this goal, we took advantage of the great potential of the European Prospective Study on Nutrition and Cancer (EPIC) cohort to apply metabolomics searching for early diagnostic PD markers. This cohort consisted of healthy volunteers that were followed for around 15 years until June 2011 to ascertain incident PD. For this untargeted metabolomics-based study, baseline preclinical plasma samples of 39 randomly selected individuals that developed PD (Pre-PD group) and the corresponding control group were analyzed using a multiplatform approach. Data were statistically analyzed and exposed alterations in 33 metabolites levels, including significantly lower levels of free fatty acids (FFAs) in the preclinical samples from PD subjects. These results were then validated by adopting a targeted HPLC-QqQ-MS approach. After integrating all the metabolites affected, our finding revealed alterations in FFAs metabolism, mitochondrial dysfunction, oxidative stress, and gut–brain axis dysregulation long before the development of PD hallmarks. Although the biological purpose of these events is still unknown, the remodeled metabolic pathways highlighted in this work might be considered worthy prognostic biomarkers of early prodromal PD. The findings revealed by this work are of inestimable value since this is the first study conducted with samples collected many years before the disease development.

Renal cell carcinoma (RCC) is a disease with no specific diagnostic method or treatment. Thus, the evaluation of novel diagnostic tools or treatment possibilities is essential. In this study, a multiplatform untargeted metabolomics analysis of urine was applied to search for a metabolic pattern specific for RCC, which could enable comprehensive assessment of its biochemical background. Thirty patients with diagnosed RCC and 29 healthy volunteers were involved in the first stage of the study. Initially, the utility of the application of the selected approach was checked for RCC with no differentiation for cancer subtypes. In the second stage, this approach was used to study clear cell renal cell carcinoma (ccRCC) in 38 ccRCC patients and 38 healthy volunteers. Three complementary analytical platforms were used: reversed-phase liquid chromatography coupled with time-of-flight mass spectrometry (RP-HPLC-TOF/MS), capillary electrophoresis coupled with time-of-flight mass spectrometry (CE-TOF/MS), and gas chromatography triple quadrupole mass spectrometry (GC-QqQ/MS). As a result of urine sample analyses, two panels of metabolites specific for RCC and ccRCC were selected. Disruptions in amino acid, lipid, purine, and pyrimidine metabolism, the TCA cycle and energetic processes were observed. The most interesting differences were observed for modified nucleosides. This is the first time that the levels of these compounds were found to be changed in RCC and ccRCC patients, providing a framework for further studies. Moreover, the application of the CE-MS technique enabled the determination of statistically significant changes in symmetric dimethylarginine (SDMA) in RCC.

Asthma is a multifactorial, heterogeneous disease that has a challenging management. It can be divided in non-allergic and allergic (usually associated with house dust mites (HDM) sensitization). There are several treatments options for asthma (corticosteroids, bronchodilators, antileukotrienes, anticholinergics,…); however, there is a subset of patients that do not respond to any of the treatments, who can display either a T2 or a non-T2 phenotype. A deeper understanding of the differential mechanisms underlying each phenotype will help to decipher the contribution of allergy to the acquisition of this uncontrolled severe phenotype. Here, we aim to elucidate the biological pathways associated to allergy in the uncontrolled severe asthmatic phenotype. To do so, twenty-three severe uncontrolled asthmatic patients both with and without HDM-allergy were recruited from Hospital Universitario de Gran Canaria Dr. Negrin. A metabolomic fingerprint was obtained through liquid chromatography coupled to mass spectrometry, and identified metabolites were associated with their pathways. 9/23 patients had uncontrolled HDM-allergic asthma (UCA), whereas 14 had uncontrolled, non-allergic asthma (UCNA). 7/14 (50%) of the UCNA patients had Aspirin Exacerbated Respiratory Disease. There were no significant differences regarding gender or body mass index; but there were significant differences in age and onset age, which were higher in UCNA patients; and in total IgE, which was higher in UCA. The metabolic fingerprint revealed that 103 features were significantly different between UCNA and UCA (p < 0.05), with 97 being increased in UCA and 6 being decreased. We identified lysophosphocholines (LPC) 18:2, 18:3 and 20:4 (increased in UCA patients); and deoxycholic acid and palmitoleoylcarnitine (decreased in UCA). These metabolites were related with a higher activation of phospholipase A2 (PLA2) and other phospholipid metabolism pathways. Our results show that allergy induces the activation of specific inflammatory pathways, such as the PLA2 pathway, which supports its role in the development of an uncontrolled asthma phenotype. There are also clinical differences, such as higher levels of IgE and earlier onset ages for the allergic asthmatic group, as expected. These results provide evidences to better understand the contribution of allergy to the establishment of a severe uncontrolled phenotype.

Risk factors for type 2 diabetes mellitus (T2DM) consist of a combination of an unhealthy, imbalanced diet and genetic factors that may interact with each other. Single nucleotide polymorphism (SNP) in the prospero homeobox 1 (PROX1) gene is a strong genetic susceptibility factor for this metabolic disorder and impaired β-cell function. As the role of this gene in T2DM development remains unclear, novel approaches are needed to advance the understanding of the mechanisms of T2DM development. Therefore, in this study, for the first time, postprandial changes in plasma metabolites were analysed by GC–MS in nondiabetic men with different PROX1 genotypes up to 5 years prior to prediabetes appearance. Eighteen contestants (12 with high risk (HR) and 6 with low risk (LR) genotype) participated in high-carbohydrate (HC) and normo-carbohydrate (NC) meal-challenge tests. Our study concluded that both meal-challenge tests provoked changes in 15 plasma metabolites (amino acids, carbohydrates, fatty acids and others) in HR, but not LR genotype carriers. Postprandial changes in the levels of some of the detected metabolites may be a source of potential specific early disturbances possibly associated with the future development of T2DM. Thus, accurate determination of these metabolites can be important for the early diagnosis of this metabolic disease.

Sphingolipids, ceramides and cholesterol are integral components of cellular membranes, and they also play important roles in signal transduction by regulating the dynamics of membrane receptors through their effects on membrane fluidity. Here, we combined biochemical and functional assays with single-particle tracking analysis of diffusion in the plasma membrane to demonstrate that the local lipid environment regulates CXCR4 organization and function and modulates chemokine-triggered directed cell migration. Prolonged treatment of T cells with bacterial sphingomyelinase promoted the complete and sustained breakdown of sphingomyelins and the accumulation of the corresponding ceramides, which altered both membrane fluidity and CXCR4 nanoclustering and dynamics. Under these conditions CXCR4 retained some CXCL12-mediated signaling activity but failed to promote efficient directed cell migration. Our data underscore a critical role for the local lipid composition at the cell membrane in regulating the lateral mobility of chemokine receptors, and their ability to dynamically increase receptor density at the leading edge to promote efficient cell migration.

One of the biggest challenges in the search for more effective treatments for diseases is understanding their etiology. Cardiovascular diseases (CVD) are an important example of this, given the high number of deaths annually. Oxidative stress (the imbalance between oxidant and antioxidant species in biological system) is one of the factors responsible for CVD occurrence, demanding extensive investigation. Excess of reactive oxygen species (ROS) are primarily responsible for this condition, and clinical and scientific literature have reported a significant increase in ROS when therapeutic drugs, such as doxorubicin and isoproterenol, are administered. In this context, the aim of this study is the investigation of potential biomarkers that might be associated with oxidative stress in cardiomyocytes. For this purpose, H9c2 cardiomyocytes were submitted to oxidative stress conditions by treatment with doxorubicin (DOX), isoproterenol (ISO) and hydrogen peroxide (PER). Metabolomics analyses of the cell extract and the supernatant obtained from the culture medium were then evaluated by CE-ESI(+)-TOF-MS. Following signal processing, statistical analyses, and molecular features annotations, the results indicate changes in the aspartate, serine, pantothenic acid, glycerophosphocholine and glutathione metabolism in the cell extract.

Backgroundmetabolic changes through SARS-CoV-2 infection has been reported but not fully comprehended. This metabolic dysregulation affects multiple organs during COVID-19 and its early detection can be used as a prognosis marker of severity. Therefore, we aimed to characterize metabolic and cytokine profile at COVID-19 onset and its relationship with disease severity to identify metabolic profiles predicting disease progression.Material and Methodswe performed a retrospective cross-sectional study in 123 COVID-19 patients which were stratified as asymptomatic/mild, moderate and severe according to the highest COVID-19 severity status, and a group of healthy controls. We performed an untargeted plasma metabolic profiling (gas chromatography and capillary electrophoresis-mass spectrometry (GC and CE-MS)) and cytokine evaluation.ResultsAfter data filtering and identification we observed 105 metabolites dysregulated (66 GC-MS and 40 CE-MS) which shown different expression patterns for each COVID-19 severity status. These metabolites belonged to different metabolic pathways including amino acid, energy, and nitrogen metabolism among others. Severity-specific metabolic dysregulation was observed, as an increased transformation of L-tryptophan into L-kynurenine. Thus, metabolic profiling at hospital admission differentiate between severe and moderate patients in the later phase of worse evolution. Several plasma pro-inflammatory biomarkers showed significant correlation with deregulated metabolites, specially with L-kynurenine and L-tryptophan. Finally, we describe a strong sex-related dysregulation of metabolites, cytokines and chemokines between severe and moderate patients. In conclusion, metabolic profiling of COVID-19 patients at disease onset is a powerful tool to unravel the SARS-CoV-2 molecular pathogenesis.ConclusionsThis technique makes it possible to identify metabolic phenoconversion that predicts disease progression and explains the pronounced pathogenesis differences between sexes.

BackgroundParkinson's disease (PD) is a progressive neurodegenerative disorder, diagnosed according to the clinical criteria that occur in already advanced stages of PD. The definition of biomarkers for the early diagnosis of PD represents a challenge that might improve treatment and avoid complications in this disease. Therefore, we propose a set of reliable samples for the identification of altered metabolites to find potential prognostic biomarkers for early PD.MethodsThis case–control study included plasma samples of 12 patients with PD and 21 control subjects, from the Spanish European Prospective Investigation into Cancer and Nutrition (EPIC)-Navarra cohort, part of the EPIC-Spain study. All the case samples were provided by healthy volunteers who were followed-up for 15.9 (±4.1) years and developed PD disease later on, after the sample collection. Liquid chromatography coupled to tandem mass spectrometry was used for the analysis of samples.ResultsOut of 40 that were selected and studied due to their involvement in established cases of PD, seven significantly different metabolites between PD cases and healthy control subjects were obtained in this study (benzoic acid, palmitic acid, oleic acid, stearic acid, myo-inositol, sorbitol, and quinolinic acid). These metabolites are related to mitochondrial dysfunction, the oxidative stress, and the mechanisms of energy production.ConclusionWe propose the samples from the EPIC study as reliable and invaluable samples for the search of early biomarkers of PD. Likewise, this study might also be a starting point in the establishment of a well-founded panel of metabolites that can be used for the early detection of this disease.

Macrophages undergo a Warburg-like switch from oxidative phosphorylation to glycolysis in response to inflammatory stimulus. Here the authors show that fungal melanin can trigger this switch in human macrophages by sequestering calcium in the phagosome and enabling protection against Aspergillus fumigatus infection.

Glioblastoma (GBM) is one of the most malignant central nervous system tumor types. Comparative analysis of GBM tissues has rendered four major molecular subtypes. From them, two molecular subtypes are mainly found in their glioblastoma cancer stem-like cells (GSCs) derived in vitro: proneural (PN) and mesenchymal (MES) with nodular (MES-N) and semi-nodular (MES-SN) disseminations, which exhibit different metabolic, growth, and malignancy properties. Many studies suggest that cancer cells communicate between them, and the surrounding microenvironment, via exosomes. Identifying molecular markers that allow the specific isolation of GSC-derived exosomes is key in the development of new therapies. However, the differential exosome composition produced by main GSCs remains unknown. The aim of this study was to determine ceramide (Cer) composition, one of the critical lipids in both cells and their cell-derived exosomes, from the main three GSC phenotypes using mass spectrometry-based lipidomics. GSCs from human tissue samples and their cell-derived exosomes were measured using ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC/Q-TOF-MS) in an untargeted analysis. Complete characterization of the ceramide profile, in both cells and cell-derived exosomes from GSC phenotypes, showed differential distributions among them. Results indicate that such differences of ceramide are chain-length dependent. Significant changes for the C16 Cer and C24:1 Cer and their ratio were observed among GSC phenotypes, being different for cells and their cell-derived exosomes.

Current risk stratification strategies for coronary artery disease (CAD) have low predictive value in asymptomatic subjects classified as intermediate cardiovascular risk. This is relevant because not all coronary events occur in individuals with traditional multiple risk factors. Most importantly, the first manifestation of the disease may be either sudden cardiac death or acute coronary syndrome, after rupture and thrombosis of an unstable non-obstructive atherosclerotic plaque, which was previously silent. The inaccurate stratification using the current models may ultimately subject the individual to excessive or insufficient preventive therapies. A breakthrough in the comprehension of the molecular mechanisms governing the atherosclerosis pathology has driven many researches toward the necessity for a better risk stratification. In this Review, we discuss how metabolomics screening integrated with traditional risk assessments becomes a powerful approach to improve non-invasive CAD subclinical diagnostics. In addition, this Review highlights the findings of metabolomics studies performed by two relevant analytical platforms in current use–mass spectrometry (MS) hyphenated to separation techniques and nuclear magnetic resonance spectroscopy (NMR) –and evaluates critically the challenges for further clinical implementation of metabolomics data. We also discuss the modern understanding of the pathophysiology of atherosclerosis and the limitations of traditional analytical methods. Our aim is to show how discriminant metabolites originated from metabolomics approaches may become promising candidate molecules to aid intermediate risk patient stratification for cardiovascular events and how these tools could successfully meet the demands to translate cardiovascular metabolic biomarkers into clinical settings.

Liquid Chromatography-High Resolution Mass Spectrometry (LC-HRMS) based lipidomics has become the most versatile analytical tool to discover and detect lipids using a non-targeted approach. A way to improve the ionization performance of specific lipid classes in electrospray sources is to modify their electrostatic interactions with both mobile and stationary phases. So far, studies on mobile phases additives, in particular ammonium fluoride, have focused on increasing ionization efficiency and reproducibility of the conditions. However, little attention has been paid to the different rules that apply in adducts formation: type of adducts, their relative intensities, and how this affects the annotation/identification process. In this study, we evaluated the performance of ammonium fluoride as an additive salt in a non-targeted MS-based lipidomic study under both the positive and negative electrospray ionization modes. The new molecular ion adducts observed can lead to wrong identifications if they are not known or considered, while the disappearance of other adducts such as those with sodium can change the traditional identification rules.

Due to many adverse effects of gestational diabetes mellitus (GDM) on the mother and fetus, its diagnosis is crucial. The presence of GDM can be confirmed by an abnormal fasting plasma glucose level (aFPG) and/or oral glucose tolerance test (OGTT) performed mostly between 24 and 28 gestational week. Both aFPG and abnormal glucose tolerance (aGT) are used to diagnose GDM. In comparison to measurement of FPG, OGTT is time-consuming, usually inconvenient for the patient, and very often needs to be repeated. Therefore, it is necessary to seek tests that will be helpful and convenient to diagnose GDM. For this reason, we investigated the differences in fasting serum metabolites between GDM women with abnGM and normal FPG (aGT-GDM group), with aFPG and normal glucose metabolism (aFPG-GDM group) as well as pregnant women with normal glucose tolerance (NGT) being a control group. Serum metabolites were measured by an untargeted approach using gas chromatography–mass spectrometry (GC–MS). In the discovery phase, fasting serum samples collected from 79 pregnant women (aFPG-GDM, n = 24; aGT-GDM, n = 26; NGT, n = 29) between 24 and 28 weeks of gestation (gwk) were fingerprinted. A set of metabolites (α–hydroxybutyric acid (α–HB), β–hydroxybutyric acid (β–HB), and several fatty acids) significant in aGT-GDM vs NGT but not significant in aFPG-GDM vs NGT comparison in the discovery phase was selected for validation. These metabolites were quantified by a targeted GC–MS method in a validation cohort consisted of 163 pregnant women (aFPG-GDM, n = 51; aGT-GDM, n = 44; and NGT, n = 68). Targeted analyses were also performed on the serum collected from 92 healthy women in the first trimester (8–14 gwk) who were NGT at this time, but in the second trimester (24–28 gwk) they were diagnosed with GDM. It was found that α–HB, β–HB, and several fatty acids were associated with aGT-GDM. A combination of α–HB, β–HB, and myristic acid was found highly specific and sensitive for the diagnosis of GDM manifested by aGT-GDM (AUC = 0.828) or to select women at a risk of aGT-GDM in the first trimester (AUC = 0.791). Our findings provide new potential markers of GDM and may have implications for its early diagnosis.

Abstract Background Several studies have shown a correlation between an altered metabolome and respiratory allergies. The epithelial barrier hypothesis proposes that an epithelial barrier dysfunction can result in allergic diseases development. Der p 1 allergen from house dust mite is a renowned epithelial barrier disruptor and allergy initiator due to its cysteine‐protease activity. Here, we compared the metabolic profile of the bronchial epithelium exposed or not to Der p 1 during barrier establishment to understand its active role in allergy development. Methods Calu‐3 cells were cultivated in air‐liquid interface cultures and exposed to either Der p 1 or Ole e 1 allergens during barrier establishment. The comparative metabolomics analysis of apical and basolateral media were performed using liquid chromatography and capillary electrophoresis both coupled to mass spectrometry. Results We showed that epithelial barrier disruption by Der p 1 was associated with a specific metabolic profile, which was highly dependent on the state of the epithelium at the time of contact. Moreover, an apical‐basolateral distribution of the metabolites was also observed, indicating a compartmentalization of the response with differential metabolic patterns. A number of metabolites were changed by Der p 1, mainly related to amino acids metabolism, such as L‐arginine, L‐kynurenine and L‐methionine. Conclusion This work is the first report on the metabolic response in human bronchial epithelial cells associated with cysteine‐protease Der p 1 activity, which could contribute to allergy development. Moreover, it supports a reformulated epithelial barrier hypothesis that might help to explain allergies and their increasing prevalence.

The eicosanoids are a family of lipid mediators of pain and inflammation involved in multiple pathologies, including asthma, hypertension, cancer, atherosclerosis, and neurodegenerative diseases. These signaling mediators act locally, but are rapidly metabolized and transported to the systemic circulation as a mixture of primary and secondary metabolites. Accordingly, urine has become a useful readily accessible biofluid for monitoring the endogenous synthesis of these molecules. Herein, we present the validation of a rapid, repeatable, and precise method for the extraction and quantification of 32 eicosanoid urinary metabolites by LC-MS/MS. For 12 out of 17 deconjugated glucuronide eicosanoids, there was no improvement in recovered signal. These metabolites cover the major synthetic pathways, including prostaglandins, leukotrienes, and isoprostanes. The method linearity was >0.99 for all metabolites analyzed, the limit of detection ranged from 0.05–5 ng/ml, and the average extraction recoveries were >90%. All analytes were stable for at least three freeze/thaw cycles. The method was formatted for large-scale analysis of clinical cohorts, and the long-term repeatability was demonstrated over 15 months of acquisition, evidencing high precision (CV

Chronic rhinosinusitis with nasal polyps (CRSwNP) is characterized by persistent symptoms associated to the development of nasal polyps. To this day, the molecular mechanisms involved are still not well defined. However, it has been suggested that a sustained inflammation as allergy is involved in its onset. In this exploratory study, the aim was to investigate the effect of the allergic status in the development of CRSwNP. To achieve this, we recruited 22 patients with CRSwNP and classified them in non-allergic and allergic using ImmunoCAP ISAC molecular diagnosis. Plasma samples were analyzed using liquid chromatography coupled to mass spectrometry (LC-MS). Subsequently, significant metabolites from plasma that were commercially available were then analyzed by targeted analysis in some nasal polyps. Additionally, nasal polyp and nasal mucosa samples were examined for eosinophils, neutrophils, CD3+ and CD11c+ cells, as well as collagen deposition and goblet cell hyperplasia. We found that 9 out of the 22 patients were sensitized to some aeroallergens (named as allergic CRSwNP). The other 13 patients had no sensitizations (non-allergic CRSwNP). Regarding metabolomics, bilirubin, cortisol, lysophosphatidylcholines (LPCs) 16:0, 18:0 and 20:4 and lysophosphatidylinositol (LPI) 20:4, which are usually related to a sustained allergic inflammation, were unexpectedly increased in plasma of non-allergic CRSwNP compared to allergic CRSwNP. LPC 16:0, LPC 18:0 and LPI 20:4 followed the same trend in nasal polyp as they did in plasma. Comparison of nasal polyps with nasal mucosa showed a significant increase in eosinophils (p < 0.001) and neutrophils (p < 0.01) in allergic CRSwNP. There were more eosinophils in polyps of non-allergic CRSwNP than in their nasal mucosa (p < 0.01). Polyps from non-allergic CRSwNP had less eosinophils than the polyps of allergic CRSwNP (p < 0.05) and reduced amounts of collagen compared to their nasal mucosa (p < 0.001). Our data suggests that there is a systemic inflammatory response associated to CRSwNP in the absence of allergy, which could be accountable for the nasal polyp development. Allergic CRSwNP presented a higher number of eosinophils in nasal polyps, suggesting that eosinophilia might be connected to the development of nasal polyps in this phenotype.

The transition from mild to severe allergic phenotypes is still poorly understood and there is an urgent need of incorporating new therapies, accompanied by personalized diagnosis approaches. This work presents the development of a novel targeted metabolomic methodology for the analysis of 36 metabolites related to allergic inflammation, including mostly sphingolipids, lysophospholipids, amino acids, and those of energy metabolism previously identified in non-targeted studies. The methodology consisted of two complementary chromatography methods, HILIC and reversed-phase. These were developed using liquid chromatography, coupled to triple quadrupole mass spectrometry (LC-QqQ-MS) in dynamic multiple reaction monitoring (dMRM) acquisition mode and were validated using ICH guidelines. Serum samples from two clinical models of allergic asthma patients were used for method application, which were as follows: (1) corticosteroid-controlled (ICS, n = 6) versus uncontrolled (UC, n = 4) patients, and immunotherapy-controlled (IT, n = 23) versus biologicals-controlled (BIO, n = 12) patients. The results showed significant differences mainly in lysophospholipids using univariate analyses in both models. Multivariate analysis for model 1 was able to distinguish both groups, while for model 2, the results showed the correct classification of all BIO samples within their group. Thus, this methodology can be of great importance for further understanding the role of these metabolites in allergic diseases as potential biomarkers for disease severity and for predicting patient treatment response.

Objective: Non-alcoholic steatohepatitis (NASH) is characterized by a robust pro-inflammatory component at both hepatic and systemic levels together with a disease-specific gut microbiome signature. Protein tyrosine phosphatase 1 B (PTP1B) plays distinct roles in non-immune and immune cells, in the latter inhibiting pro-inflammatory signaling cascades. In this study, we have explored the role of PTP1B in the composition of gut microbiota and gut barrier dynamics in methionine and choline-deficient (MCD) diet-induced NASH in mice. Methods: Gut features and barrier permeability were characterized in wild-type (PTP1B WT) and PTP1B-deficient knockout (PTP1B KO) mice fed a chow or methionine/choline-deficient (MCD) diet for 4 weeks. The impact of inflammation was studied in intestinal epithelial and enteroendocrine cells. The secretion of GLP-1 was evaluated in primary colonic cultures and plasma of mice. Results: We found that a shift in the gut microbiota shape, disruption of gut barrier function, higher levels of serum bile acids, and decreased circulating glucagon-like peptide (GLP)-1 are features during NASH. Surprisingly, despite the pro-inflammatory phenotype of global PTP1B-deficient mice, they were partly protected against the alterations in gut microbiota composition during NASH and presented better gut barrier integrity and less permeability under this pathological condition. These effects concurred with higher colonic mucosal inflammation, decreased serum bile acids, and protection against the decrease in circulating GLP-1 levels during NASH compared with their WT counterparts together with increased expression of GLP-2-sensitive genes in the gut. At the molecular level, stimulation of enteroendocrine STC-1 cells with a pro-inflammatory conditioned medium (CM) from lipopolysaccharide (LPS)-stimulated macrophages triggered pro-inflammatory signaling cascades that were further exacerbated by a PTP1B inhibitor. Likewise, the pro-inflammatory CM induced GLP-1 secretion in primary colonic cultures, an effect augmented by PTP1B inhibition. Conclusion: Altogether our results have unraveled a potential role of PTP1B in the gut–liver axis during NASH, likely mediated by increased sensitivity to GLPs, with potential therapeutic value. Keywords: NASH, PTP1B, Inflammation, Gut microbiota, GLP-1, GLP-2

The Lipid Annotation Service (LAS) is a representational state transfer (REST) application programming interface (API) service designed to aid researchers performing lipid annotation. It assigns certainty levels (very unlikely, unlikely, likely, and very likely) to the putative annotations received as input and explains the rationale of such assignments. Its rules, obtained from the Centre for Metabolomics and Bioanalysis (CEMBIO) and from a literature review, enable LAS to extract evidence to support or refute the annotations automatically by checking the inter-rule relationships.LAS is the first metabolite annotation tool capable of explaining in natural language (English) the evidence that supports or refutes the annotations. This facilitates the understanding of the results by the user and, thus, increases the user's confidence in the results. Concerning its performance, in an evaluation of blood plasma samples whose compounds had previously been identified using well-established standards, LAS yielded an F-measure higher than 80%. Keywords: Lipid annotation, Explanations in natural language, Knowledge based system, REST API service

Schizophrenia, depression and posttraumatic stress disorder (PTSD) are severe mental disorders and complicated diagnostic entities, due to their phenotypic, biological and genetic heterogeneity, unknown etiology, and poorly understood alterations in biological pathways and biological mechanisms. Disturbed homeostasis between overproduction of oxidant species, overcoming redox regulation and a lack of cellular antioxidant defenses, resulting in free radical-mediated pathology and subsequent neurotoxicity contributes to development of depression, schizophrenia and PTSD, their heterogeneous clinical presentation and resistance to treatment. Metabolomics is a discipline that combines different strategies with the aim to extract, detect, identify and quantify all metabolites that are present in a biological sample and might provide mechanistic insights into the etiology of various psychiatric disorders. Therefore, oxidative stress research combined with metabolomics might offer a novel approach in dissecting psychiatric disorders, since these data-driven but not necessarily hypothesis-driven methods might identify new targets, molecules and pathways responsible for development of schizophrenia, depression or PTSD. Findings from the oxidative research in psychiatry together with metabolomics data might facilitate development of specific and validated prognostic, therapeutic and clinical biomarkers. These methods might reveal bio-signatures of individual patients, leading to individualized treatment approach. In reviewing findings related to oxidative stress and metabolomics in selected psychiatric disorders, we have highlighted how these novel approaches might make a unique contribution to deeper understanding of psychopathological alterations underlying schizophrenia, depression and PTSD. Keywords: Schizophrenia, Depression, Posttraumatic stress disorder, Oxidative stress, Lipid peroxidation, Metabolomics, Biomarkers

Association of oxidative stress with carcinogenesis is well known, but not understood well, as is pathophysiology of oxidative stress generated during different types of anti-cancer treatments. Moreover, recent findings indicate that cancer associated lipid peroxidation might eventually help defending adjacent nonmalignant cells from cancer invasion. Therefore, untargeted metabolomics studies designed for advanced translational and clinical studies are needed to understand the existing paradoxes in oncology, including those related to controversial usage of antioxidants aiming to prevent or treat cancer. In this short review we have tried to put emphasis on the importance of pathophysiology of oxidative stress and lipid peroxidation in cancer development in relation to metabolic adaptation of particular types of cancer allowing us to conclude that adaptation to oxidative stress is one of the main driving forces of cancer pathophysiology. With the help of metabolomics many novel findings are being achieved thus encouraging further scientific breakthroughs. Combined with targeted qualitative and quantitative methods, especially immunochemistry, further research might reveal bio-signatures of individual patients and respective malignant diseases, leading to individualized treatment approach, according to the concepts of modern integrative medicine. Keywords: Carcinogenesis, Cancer, Oxidative stress, Lipid peroxidation, 4-hydroxynonenal, Glutathione, Metabolomics, Immunochemistry, Biomarkers, Omics science

Abstract Background Cachexia is a metabolic syndrome that affects up to 50–80% of cancer patients. The pathophysiology is characterized by a variable combination of reduced food intake and abnormal metabolism, including systemic inflammation and negative protein and energy balance. Despite its high clinical significance, defined diagnostic criteria and established therapeutic strategies are lacking. The ‘omics’ technologies provide a global view of biological systems. We hypothesize that blood‐based metabolomics might identify findings in cachectic patients that could provide clues to gain knowledge on its pathophysiology, and eventually postulate new therapeutic strategies. Methods This is a cross‐sectional observational study in two cohorts of cancer patients, with and without cachexia. Patients were consecutively recruited from routine clinical practice of a General Oncology Department at ‘12 de Octubre’ University Hospital. Selected clinical and biochemical features were collected. Blood metabolite fingerprinting was performed using three analytical platforms, gas chromatography coupled to mass spectrometry (GC–MS), capillary electrophoresis coupled to mass spectrometry (CE–MS), and liquid chromatography coupled to mass spectrometry (LC–MS). Besides, we performed pathway‐based metabolite analyses to obtain more information on biological functions. Results A total of 15 subjects were included in this study, 8 cachectic and 7 non‐cachectic patients. Metabolomic analyses were able to correctly classify their samples in 80% (GC–MS), 97% (CE–MS), 96% [LC–MS (positive mode)], and 89% [LC–MS (negative mode)] of the cases. The most prominent metabolic alteration in plasma of cachectic patients was the decrease of amino acids and derivatives [especially arginine, tryptophan, indolelactic acid, and threonine, with 0.4‐fold change (FC) compared with non‐cachectic patients], along with the reduction of glycerophospholipids [mainly lysophosphatidylcholines(O‐16:0) and lysophosphatidylcholines(20:3) sn‐1, FC = 0.1] and sphingolipids [SM(d30:0), FC = 0.5]. The metabolite with the highest increase was cortisol (FC = 1.6). Such alterations suggest a role of the following metabolic pathways in the pathophysiology of cancer cachexia: arginine and proline metabolism; alanine, aspartate, and glutamate metabolism; phenylalanine metabolism; lysine degradation; aminoacyl‐tRNA biosynthesis; fatty acid elongation in mitochondria; tricarboxylic acids cycle; among others. Conclusions These findings suggest that plasma amino acids and lipids profiling has great potential to find the mechanisms involved in the pathogenesis of cachexia. Metabolic profiling of plasma from cancer patients show differences between cachexia and non‐cachexia in amino acids and lipids that might be related to mechanisms involved in its pathophysiology. A better understanding of these mechanisms might identify novel therapeutic approaches to palliate this unmet medical condition.

It has been considered that proline dehydrogenase/proline oxidase (PRODH/POX) is involved in antineoplastic activity of metformin (MET). The aim of this study is identification of key metabolites of glycolysis, pentose phosphate pathway (PPP), tricarboxylic acids (TCA), urea cycles (UC) and some amino acids in MET-treated MCF-7 cells and PRODH/POX-knocked out MCF-7 (MCF-7crPOX) cells. MCF-7crPOX cells were generated by using CRISPR-Cas9. Targeted metabolomics was performed by LC-MS/MS/QqQ. Expression of pro-apoptotic proteins was evaluated by Western blot. In the absence of glutamine, MET treatment or PRODH/POX-knock out of MCF-7 cells contributed to similar inhibition of glycolysis (drastic increase in intracellular glucose and pyruvate) and increase in the utilization of phospho-enol-pyruvic acid, glucose-6-phosphate and some metabolites of TCA and UC, contributing to apoptosis. However, in the presence of glutamine, MET treatment or PRODH/POX-knock out of MCF-7 cells contributed to utilization of some studied metabolites (except glucose), facilitating pro-survival phenotype of MCF-7 cells in these conditions. It suggests that MET treatment or PRODH/POX-knock out induce similar metabolic effects (glucose starvation) and glycolysis is tightly linked to glutamine metabolism in MCF-7 breast cancer cells. The data provide insight into mechanism of anticancer activity of MET as an approach to further studies on experimental breast cancer therapy.

Abstract Ferroplasmaceae represent ubiquitous iron-oxidising extreme acidophiles with a number of unique physiological traits. In a genome-based study of Ferroplasma acidiphilum YT, the only species of the genus Ferroplasma with a validly published name, we assessed its central metabolism and genome stability during a long-term cultivation experiment. Consistently with physiology, the genome analysis points to F. acidiphilum YT having an obligate peptidolytic oligotrophic lifestyle alongside with anaplerotic carbon assimilation. This narrow trophic specialisation abridges the sugar uptake, although all genes for glycolysis and gluconeogenesis, including bifunctional unidirectional fructose 1,6-bisphosphate aldolase/phosphatase, have been identified. Pyruvate and 2-oxoglutarate dehydrogenases are substituted by ‘ancient’ CoA-dependent pyruvate and alpha-ketoglutarate ferredoxin oxidoreductases. In the lab culture, after ~550 generations, the strain exhibited the mutation rate of ≥1.3 × 10−8 single nucleotide substitutions per site per generation, which is among the highest values recorded for unicellular organisms. All but one base substitutions were G:C to A:T, their distribution between coding and non-coding regions and synonymous-to-non-synonymous mutation ratios suggest the neutral drift being a prevalent mode in genome evolution in the lab culture. Mutations in nature seem to occur with lower frequencies, as suggested by a remarkable genomic conservation in F. acidiphilum YT variants from geographically distant populations.