Cross-Validation of Metabolic Phenotypes in SARS-CoV-2 Infected Subpopulations Using Targeted Liquid Chromatography-Mass Spectrometry (LC-MS).

To ensure biological validity in metabolic phenotyping, findings must be replicated in independent sample sets. Targeted workflows have long been heralded as ideal platforms for such validation due to their robust quantitative capability. We evaluated the capability of liquid chromatography-mass spectrometry (LC-MS) assays targeting organic acids and bile acids to validate metabolic phenotypes of SARS-CoV-2 infection. Two independent sample sets were collected: (1) Australia: plasma, SARS-CoV-2 positive (n = 20), noninfected healthy controls (n = 22) and COVID-19 disease-like symptoms but negative for SARS-CoV-2 infection (n = 22). (2) Spain: serum, SARS-CoV-2 positive (n = 33) and noninfected healthy controls (n = 39). Multivariate modeling using orthogonal projections to latent structures discriminant analyses (OPLS-DA) classified healthy controls from SARS-CoV-2 positive (Australia; R2 = 0.17, ROC-AUC = 1; Spain R2 = 0.20, ROC-AUC = 1). Univariate analyses revealed 23 significantly different (p < 0.05) metabolites between healthy controls and SARS-CoV-2 positive individuals across both cohorts. Significant metabolites revealed consistent perturbations in cellular energy metabolism (pyruvic acid, and 2-oxoglutaric acid), oxidative stress (lactic acid, 2-hydroxybutyric acid), hypoxia (2-hydroxyglutaric acid, 5-aminolevulinic acid), liver activity (primary bile acids), and host-gut microbial cometabolism (hippuric acid, phenylpropionic acid, indole-3-propionic acid). These data support targeted LC-MS metabolic phenotyping workflows for biological validation in independent sample sets.

Preovulatory follicular fluid secretome added to in vitro maturation medium influences the metabolism of equine cumulus-oocyte complexes.

BACKGROUND: In vitro embryo production is a highly demanded reproductive technology in horses, which requires the recovery (in vivo or post-mortem) and in vitro maturation (IVM) of oocytes. Oocytes subjected to IVM exhibit poor developmental competence compared to their in vivo counterparts, being this related to a suboptimal composition of commercial maturation media. The objective of this work was to study the effect of different concentrations of secretome obtained from equine preovulatory follicular fluid (FF) on cumulus-oocyte complexes (COCs) during IVM. COCs retrieved in vivo by ovum pick up (OPU) or post-mortem from a slaughterhouse (SLA) were subjected to IVM in the presence or absence of secretome (Control: 0 µg/ml, S20: 20 µg/ml or S40: 40 µg/ml). After IVM, the metabolome of the medium used for oocyte maturation prior (Pre-IVM) and after IVM (Post-IVM), COCs mRNA expression, and oocyte meiotic competence were analysed. RESULTS: IVM leads to lactic acid production and an acetic acid consumption in COCs obtained from OPU and SLA. However, glucose consumption after IVM was higher in COCs from OPU when S40 was added (Control Pre-IVM vs. S40 Post-IVM: 117.24 ± 7.72 vs. 82.69 ± 4.24; Mean µM ± SEM; p < 0.05), while this was not observed in COCs from SLA. Likewise, secretome enhanced uptake of threonine (Control Pre-IVM vs. S20 Post-IVM vs. S40 Post-IVM: 4.93 ± 0.33 vs. 3.04 ± 0.25 vs. 2.84 ± 0.27; Mean µM ± SEM; p < 0.05) in COCs recovered by OPU. Regarding the relative mRNA expression of candidate genes related to metabolism, Lactate dehydrogenase A (LDHA) expression was significantly downregulated when secretome was added during IVM at 20-40 µg/ml in OPU-derived COCs (Control vs. S20 vs. S40: 1.77 ± 0.14 vs. 1 ± 0.25 vs. 1.23 ± 0.14; fold change ± SEM; p < 0.05), but not in SLA COCs. CONCLUSIONS: The addition of secretome during in vitro maturation (IVM) affects the gene expression of LDHA, glucose metabolism, and amino acid turnover in equine cumulus-oocyte complexes (COCs), with diverging outcomes observed between COCs retrieved using ovum pick up (OPU) and slaughterhouse-derived COCs (SLA).

Metabolic subtypes of patients with NAFLD exhibit distinctive cardiovascular risk profiles.

BACKGROUND AND AIMS: We previously identified subsets of patients with NAFLD with different metabolic phenotypes. Here we align metabolomic signatures with cardiovascular disease (CVD) and genetic risk factors. APPROACH AND RESULTS: We analyzed serum metabolome from 1154 individuals with biopsy-proven NAFLD, and from four mouse models of NAFLD with impaired VLDL-triglyceride (TG) secretion, and one with normal VLDL-TG secretion. We identified three metabolic subtypes: A (47%), B (27%), and C (26%). Subtype A phenocopied the metabolome of mice with impaired VLDL-TG secretion; subtype C phenocopied the metabolome of mice with normal VLDL-TG; and subtype B showed an intermediate signature. The percent of patients with NASH and fibrosis was comparable among subtypes, although subtypes B and C exhibited higher liver enzymes. Serum VLDL-TG levels and secretion rate were lower among subtype A compared with subtypes B and C. Subtype A VLDL-TG and VLDL-apolipoprotein B concentrations were independent of steatosis, whereas subtypes B and C showed an association with these parameters. Serum TG, cholesterol, VLDL, small dense LDL5,6 , and remnant lipoprotein cholesterol were lower among subtype A compared with subtypes B and C. The 10-year high risk of CVD, measured with the Framingham risk score, and the frequency of patatin-like phospholipase domain-containing protein 3 NAFLD risk allele were lower in subtype A. CONCLUSIONS: Metabolomic signatures identify three NAFLD subgroups, independent of histological disease severity. These signatures align with known CVD and genetic risk factors, with subtype A exhibiting a lower CVD risk profile. This may account for the variation in hepatic versus cardiovascular outcomes, offering clinically relevant risk stratification.

Prospective Metabolomic Studies in Precision Medicine: The AKRIBEA Project.

For a long time, conventional medicine has analysed biomolecules to diagnose diseases. Yet, this approach has proven valid only for a limited number of metabolites and often through a bijective relationship with the disease (i.e. glucose relationship with diabetes), ultimately offering incomplete diagnostic value. Nowadays, precision medicine emerges as an option to improve the prevention and/or treatment of numerous pathologies, focusing on the molecular mechanisms, acting in a patient-specific dimension, and leveraging multiple contributing factors such as genetic, environmental, or lifestyle. Metabolomics grasps the required subcellular complexity while being sensitive to all these factors, which results in a most suitable technique for precision medicine. The aim of this chapter is to describe how NMR-based metabolomics can be integrated in the design of a precision medicine strategy, using the Precision Medicine Initiative of the Basque Country (the AKRIBEA project) as a case study. To that end, we will illustrate the procedures to be followed when conducting an NMR-based metabolomics study with a large cohort of individuals, emphasizing the critical points. The chapter will conclude with the discussion of some relevant biomedical applications.

Integrative Plasma Metabolic and Lipidomic Modelling of SARS-CoV-2 Infection in Relation to Clinical Severity and Early Mortality Prediction.

An integrative multi-modal metabolic phenotyping model was developed to assess the systemic plasma sequelae of SARS-CoV-2 (rRT-PCR positive) induced COVID-19 disease in patients with different respiratory severity levels. Plasma samples from 306 unvaccinated COVID-19 patients were collected in 2020 and classified into four levels of severity ranging from mild symptoms to severe ventilated cases. These samples were investigated using a combination of quantitative Nuclear Magnetic Resonance (NMR) spectroscopy and Mass Spectrometry (MS) platforms to give broad lipoprotein, lipidomic and amino acid, tryptophan-kynurenine pathway, and biogenic amine pathway coverage. All platforms revealed highly significant differences in metabolite patterns between patients and controls (n = 89) that had been collected prior to the COVID-19 pandemic. The total number of significant metabolites increased with severity with 344 out of the 1034 quantitative variables being common to all severity classes. Metabolic signatures showed a continuum of changes across the respiratory severity levels with the most significant and extensive changes being in the most severely affected patients. Even mildly affected respiratory patients showed multiple highly significant abnormal biochemical signatures reflecting serious metabolic deficiencies of the type observed in Post-acute COVID-19 syndrome patients. The most severe respiratory patients had a high mortality (56.1%) and we found that we could predict mortality in this patient sub-group with high accuracy in some cases up to 61 days prior to death, based on a separate metabolic model, which highlighted a different set of metabolites to those defining the basic disease. Specifically, hexosylceramides (HCER 16:0, HCER 20:0, HCER 24:1, HCER 26:0, HCER 26:1) were markedly elevated in the non-surviving patient group (Cliff's delta 0.91-0.95) and two phosphoethanolamines (PE.O 18:0/18:1, Cliff's delta = -0.98 and PE.P 16:0/18:1, Cliff's delta = -0.93) were markedly lower in the non-survivors. These results indicate that patient morbidity to mortality trajectories is determined relatively soon after infection, opening the opportunity to select more intensive therapeutic interventions to these "high risk" patients in the early disease stages.

Uneven metabolic and lipidomic profiles in recovered COVID-19 patients as investigated by plasma NMR metabolomics.

COVID-19 is a systemic infectious disease that may affect many organs, accompanied by a measurable metabolic dysregulation. The disease is also associated with significant mortality, particularly among the elderly, patients with comorbidities, and solid organ transplant recipients. Yet, the largest segment of the patient population is asymptomatic, and most other patients develop mild to moderate symptoms after SARS-CoV-2 infection. Here, we have used NMR metabolomics to characterize plasma samples from a cohort of the abovementioned group of COVID-19 patients (n = 69), between 3 and 10 months after diagnosis, and compared them with a set of reference samples from individuals never infected by the virus (n = 71). Our results indicate that half of the patient population show abnormal metabolism including porphyrin levels and altered lipoprotein profiles six months after the infection, while the other half show little molecular record of the disease. Remarkably, most of these patients are asymptomatic or mild COVID-19 patients, and we hypothesize that this is due to a metabolic reflection of the immune response stress.

Direct low field J-edited diffusional proton NMR spectroscopic measurement of COVID-19 inflammatory biomarkers in human serum.

A JEDI NMR pulse experiment incorporating relaxational, diffusional and J-modulation peak editing has been implemented for a low field (80 MHz proton resonance frequency) spectrometer system to measure quantitatively two recently discovered plasma markers of SARS-CoV-2 infection and general inflammation. JEDI spectra capture a unique signature of two biomarker signals from acetylated glycoproteins (Glyc) and the supramolecular phospholipid composite (SPC) signals that are relatively enhanced by the combination of relaxation, diffusion and J-editing properties of the JEDI experiment that strongly attenuate contributions from the other molecular species in plasma. The SPC/Glyc ratio data were essentially identical in the 600 MHz and 80 MHz spectra obtained (R2 = 0.97) and showed significantly different ratios for control (n = 28) versus SARS-CoV-2 positive patients (n = 29) (p = 5.2 × 10-8 and 3.7 × 10-8 respectively). Simplification of the sample preparation allows for data acquisition in a similar time frame to high field machines (∼4 min) and a high-throughput version with 1 min experiment time could be feasible. These data show that these newly discovered inflammatory biomarkers can be measured effectively on low field NMR instruments that do not not require housing in a complex laboratory environment, thus lowering the barrier to clinical translation of this diagnostic technology.

Integrative Modeling of Plasma Metabolic and Lipoprotein Biomarkers of SARS-CoV-2 Infection in Spanish and Australian COVID-19 Patient Cohorts.

Quantitative plasma lipoprotein and metabolite profiles were measured on an autonomous community of the Basque Country (Spain) cohort consisting of hospitalized COVID-19 patients (n = 72) and a matched control group (n = 75) and a Western Australian (WA) cohort consisting of (n = 17) SARS-CoV-2 positives and (n = 20) healthy controls using 600 MHz 1H nuclear magnetic resonance (NMR) spectroscopy. Spanish samples were measured in two laboratories using one-dimensional (1D) solvent-suppressed and T2-filtered methods with in vitro diagnostic quantification of lipoproteins and metabolites. SARS-CoV-2 positive patients and healthy controls from both populations were modeled and cross-projected to estimate the biological similarities and validate biomarkers. Using the top 15 most discriminatory variables enabled construction of a cross-predictive model with 100% sensitivity and specificity (within populations) and 100% sensitivity and 82% specificity (between populations). Minor differences were observed between the control metabolic variables in the two cohorts, but the lipoproteins were virtually indistinguishable. We observed highly significant infection-related reductions in high-density lipoprotein (HDL) subfraction 4 phospholipids, apolipoproteins A1 and A2,that have previously been associated with negative regulation of blood coagulation and fibrinolysis. The Spanish and Australian diagnostic SARS-CoV-2 biomarkers were mathematically and biologically equivalent, demonstrating that NMR-based technologies are suitable for the study of the comparative pathology of COVID-19 via plasma phenotyping.

A molecular signature for the metabolic syndrome by urine metabolomics.

BACKGROUND: Metabolic syndrome (MetS) is a multimorbid long-term condition without consensual medical definition and a diagnostic based on compatible symptomatology. Here we have investigated the molecular signature of MetS in urine. METHODS: We used NMR-based metabolomics to investigate a European cohort including urine samples from 11,754 individuals (18-75 years old, 41% females), designed to populate all the intermediate conditions in MetS, from subjects without any risk factor up to individuals with developed MetS (4-5%, depending on the definition). A set of quantified metabolites were integrated from the urine spectra to obtain metabolic models (one for each definition), to discriminate between individuals with MetS. RESULTS: MetS progression produces a continuous and monotonic variation of the urine metabolome, characterized by up- or down-regulation of the pertinent metabolites (17 in total, including glucose, lipids, aromatic amino acids, salicyluric acid, maltitol, trimethylamine N-oxide, and p-cresol sulfate) with some of the metabolites associated to MetS for the first time. This metabolic signature, based solely on information extracted from the urine spectrum, adds a molecular dimension to MetS definition and it was used to generate models that can identify subjects with MetS (AUROC values between 0.83 and 0.87). This signature is particularly suitable to add meaning to the conditions that are in the interface between healthy subjects and MetS patients. Aging and non-alcoholic fatty liver disease are also risk factors that may enhance MetS probability, but they do not directly interfere with the metabolic discrimination of the syndrome. CONCLUSIONS: Urine metabolomics, studied by NMR spectroscopy, unravelled a set of metabolites that concomitantly evolve with MetS progression, that were used to derive and validate a molecular definition of MetS and to discriminate the conditions that are in the interface between healthy individuals and the metabolic syndrome.

1H NMR-Based Urine Metabolomics Reveals Signs of Enhanced Carbon and Nitrogen Recycling in Prostate Cancer.

Prostate cancer is the second most common tumor and the fifth cause of cancer-related death among men worldwide. PC cells exhibit profound signaling and metabolic reprogramming that account for the acquisition of aggressive features. Although the metabolic understanding of this disease has increased in recent years, the analysis of such alterations through noninvasive methodologies in biofluids remains limited. Here, we used NMR-based metabolomics on a large cohort of urine samples (more than 650) from PC and benign prostate hyperplasia (BPH) patients to investigate the molecular basis of this disease. Multivariate analysis failed to distinguish between the two classes, highlighting the modest impact of prostate alterations on urine composition and the multifactorial nature of PC. However, univariate analysis of urine metabolites unveiled significant changes, discriminating PC from BPH. Metabolites with altered abundance in urine from PC patients revealed changes in pathways related to cancer biology, including glycolysis and the urea cycle. We found out that metabolites from such pathways were diminished in the urine from PC individuals, strongly supporting the notion that PC reduces nitrogen and carbon waste in order to maximize their usage in anabolic processes that support cancer cell growth.

Effect of age and dietary habits on Red Blood Cell membrane fatty acids in a Southern Europe population (Basque Country).

The levels of blood eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) are very variable and, in general, low in most of the world population. In this study, the effects of age, sex, COVID-19, and dietary habits on the lipid profile of the erythrocyte membranes were assessed in a sub-cohort of healthy population (N = 203) from a large cohort of individuals from the Basque Country, Spain, (AKRIBEA). Sex did not have an effect on RBC lipid profile. COVID-19 infected participants showed higher levels of DGLA. Oldest participants showed higher oleic acid, EPA and DHA levels. Arachidonic acid in RBC correlated positively with the intake of sunflower oil, butter, eggs, processed and red meat, whereas DHA and EPA correlated positively with oily and lean fish. Basque Country population showed lipid profiles similar to other high fish consuming countries, such as Italy and Japan. Baseline levels of the whole lipidomic profile of the RBC including SFA, MUFA and PUFA should be examined to obtain a better description of the health and nutritional status.

Characterization of preovulatory follicular fluid secretome and its effects on equine oocytes during in vitro maturation.

In vitro maturation (IVM) of oocytes is clinically used in horses to produce blastocysts but current conditions used for horses are suboptimal. We analyzed the composition of equine preovulatory follicular fluid (FF) secretome and tested its effects on meiotic competence and gene expression in oocytes subjected to IVM. Preovulatory FF was obtained, concentrated using ultrafiltration with cut-off of 10 kDa, and stored at -80 °C. The metabolic and proteomic composition was analyzed, and its ultrastructural composition was assessed by cryo-transmission microscopy. Oocytes obtained post-mortem or by ovum pick up (OPU) were subjected to IVM in the absence (control) or presence of 20 or 40 µg/ml (S20 or S40) of secretome. Oocytes were then analyzed for chromatin configuration or snap frozen for gene expression analysis. Proteomic analysis detected 255 proteins in the Equus caballus database, mostly related to the complement cascade and cholesterol metabolism. Metabolomic analysis yielded 14 metabolites and cryo-transmission electron microscopy analysis revealed the presence of extracellular vesicles (EVs). No significant differences were detected in maturation rates among treatments. However, the expression of GDF9 and BMP15 significantly increased in OPU-derived oocytes compared to post-mortem oocytes (fold increase ± SEM: 9.4 ± 0.1 vs. 1 ± 0.5 for BMP15 and 9.9 ± 0.3 vs. 1 ± 0.5 for GDF9, respectively; p < 0.05). Secretome addition increased the expression of TNFAIP6 in S40 regardless of the oocyte source. Further research is necessary to fully understand whether secretome addition influences the developmental competence of equine oocytes.

Serum and Urine Metabolomic Profiling of Newly Diagnosed Treatment-Naïve Inflammatory Bowel Disease Patients.

BACKGROUND AND AIMS: Inflammatory bowel disease (IBD) is a prevalent chronic noncurable disease associated with profound metabolic changes. The discovery of novel molecular indicators for unraveling IBD etiopathogenesis and the diagnosis and prognosis of IBD is therefore pivotal. We sought to determine the distinctive metabolic signatures from the different IBD subgroups before treatment initiation. METHODS: Serum and urine samples from newly diagnosed treatment-naïve IBD patients and age and sex-matched healthy control (HC) individuals were investigated using proton nuclear magnetic resonance spectroscopy. Metabolic differences were identified based on univariate and multivariate statistical analyses. RESULTS: A total of 137 Crohn's disease patients, 202 ulcerative colitis patients, and 338 HC individuals were included. In the IBD cohort, several distinguishable metabolites were detected within each subgroup comparison. Most of the differences revealed alterations in energy and amino acid metabolism in IBD patients, with an increased demand of the body for energy mainly through the ketone bodies. As compared with HC individuals, differences in metabolites were more marked and numerous in Crohn's disease than in ulcerative colitis patients, and in serum than in urine. In addition, clustering analysis revealed 3 distinct patient profiles with notable differences among them based on the analysis of their clinical, anthropometric, and metabolomic variables. However, relevant phenotypical differences were not found among these 3 clusters. CONCLUSIONS: This study highlights the molecular alterations present within the different subgroups of newly diagnosed treatment-naïve IBD patients. The metabolomic profile of these patients may provide further understanding of pathogenic mechanisms of IBD subgroups. Serum metabotype seemed to be especially sensitive to the onset of IBD.

The RNA-binding protein human antigen R controls global changes in gene expression during Schwann cell development.

An important prerequisite to myelination in peripheral nerves is the establishment of one-to-one relationships between axons and Schwann cells. This patterning event depends on immature Schwann cell proliferation, apoptosis, and morphogenesis, which are governed by coordinated changes in gene expression. Here, we found that the RNA-binding protein human antigen R (HuR) was highly expressed in immature Schwann cells, where genome-wide identification of its target mRNAs in vivo in mouse sciatic nerves using ribonomics showed an enrichment of functionally related genes regulating these processes. HuR coordinately regulated expression of several genes to promote proliferation, apoptosis, and morphogenesis in rat Schwann cells, in response to NRG1, TGFß, and laminins, three major signals implicated in this patterning event. Strikingly, HuR also binds to several mRNAs encoding myelination-related proteins but, contrary to its typical function, negatively regulated their expression, likely to prevent ectopic myelination during development. These functions of HuR correlated with its abundance and subcellular localization, which were regulated by different signals in Schwann cells.

Human antigen R contributes to hepatic stellate cell activation and liver fibrosis.

UNLABELLED: RNA-binding proteins (RBPs) play a major role in the control of messenger RNA (mRNA) turnover and translation rates. We examined the role of the RBP, human antigen R (HuR), during cholestatic liver injury and hepatic stellate cell (HSC) activation. HuR silencing attenuated fibrosis development in vivo after BDL, reducing liver damage, oxidative stress, inflammation, and collagen and alpha smooth muscle actin (α-SMA) expression. HuR expression increased in activated HSCs from bile duct ligation mice and during HSC activation in vitro, and HuR silencing markedly reduced HSC activation. HuR regulated platelet-derived growth factor (PDGF)-induced proliferation and migration and controlled the expression of several mRNAs involved in these processes (e.g., Actin, matrix metalloproteinase 9, and cyclin D1 and B1). These functions of HuR were linked to its abundance and cytoplasmic localization, controlled by PDGF, by extracellular signal-regulated kinases (ERK) and phosphatidylinositol 3-kinase activation as well as ERK/LKB1 (liver kinase B1) activation, respectively. More important, we identified the tumor suppressor, LKB1, as a novel downstream target of PDGF-induced ERK activation in HSCs. HuR also controlled transforming growth factor beta (TGF-ß)-induced profibrogenic actions by regulating the expression of TGF-ß, α-SMA, and p21. This was likely the result of an increased cytoplasmic localization of HuR, controlled by TGF-ß-induced p38 mitogen-activated protein kinase activation. Finally, we found that HuR and LKB1 (Ser428) levels were highly expressed in activated HSCs in human cirrhotic samples. CONCLUSION: Our results show that HuR is important for the pathogenesis of liver fibrosis development in the cholestatic injury model, for HSC activation, and for the response of activated HSC to PDGF and TGF-ß.

Murine double minute 2 regulates Hu antigen R stability in human liver and colon cancer through NEDDylation.

UNLABELLED: Hu antigen R (HuR) is a central RNA-binding protein regulating cell dedifferentiation, proliferation, and survival, which are well-established hallmarks of cancer. HuR is frequently overexpressed in tumors correlating with tumor malignancy, which is in line with a role for HuR in tumorigenesis. However, the precise mechanism leading to changes in HuR expression remains unclear. In the liver, HuR plays a crucial role in hepatocyte proliferation, differentiation, and transformation. Here, we unraveled a novel mean of regulation of HuR expression in hepatocellular carcinoma (HCC) and colon cancer. HuR levels correlate with the abundance of the oncogene, murine double minute 2 (Mdm2), in human HCC and colon cancer metastases. HuR is stabilized by Mdm2-mediated NEDDylation in at least three lysine residues, ensuring its nuclear localization and protection from degradation. CONCLUSION: This novel Mdm2/NEDD8/HuR regulatory framework is essential for the malignant transformation of tumor cells, which, in turn, unveils a novel signaling paradigm that is pharmacologically amenable for cancer therapy.

Sirtuin 1 regulation of developmental genes during differentiation of stem cells.

The longevity-promoting NAD+-dependent class III histone deacetylase Sirtuin 1 (SIRT1) is involved in stem cell function by controlling cell fate decision and/or by regulating the p53-dependent expression of NANOG. We show that SIRT1 is down-regulated precisely during human embryonic stem cell differentiation at both mRNA and protein levels and that the decrease in Sirt1 mRNA is mediated by a molecular pathway that involves the RNA-binding protein HuR and the arginine methyltransferase coactivator-associated arginine methyltransferase 1 (CARM1). SIRT1 down-regulation leads to reactivation of key developmental genes such as the neuroretinal morphogenesis effectors DLL4, TBX3, and PAX6, which are epigenetically repressed by this histone deacetylase in pluripotent human embryonic stem cells. Our results indicate that SIRT1 is regulated during stem cell differentiation in the context of a yet-unknown epigenetic pathway that controls specific developmental genes in embryonic stem cells.

Metabolomics as a powerful tool for diagnostic, pronostic and drug intervention analysis in COVID-19.

COVID-19 currently represents one of the major health challenges worldwide. Albeit its infectious character, with onset affectation mainly at the respiratory track, it is clear that the pathophysiology of COVID-19 has a systemic character, ultimately affecting many organs. This feature enables the possibility of investigating SARS-CoV-2 infection using multi-omic techniques, including metabolomic studies by chromatography coupled to mass spectrometry or by nuclear magnetic resonance (NMR) spectroscopy. Here we review the extensive literature on metabolomics in COVID-19, that unraveled many aspects of the disease including: a characteristic metabotipic signature associated to COVID-19, discrimination of patients according to severity, effect of drugs and vaccination treatments and the characterization of the natural history of the metabolic evolution associated to the disease, from the infection onset to full recovery or long-term and long sequelae of COVID.

Metabolic Features of Increased Gut Permeability, Inflammation, and Altered Energy Metabolism Distinguish Agricultural Workers at Risk for Mesoamerican Nephropathy.

Mesoamerican nephropathy (MeN) is a form of chronic kidney disease found predominantly in young men in Mesoamerica. Strenuous agricultural labor is a consistent risk factor for MeN, but the pathophysiologic mechanism leading to disease is poorly understood. We compared the urine metabolome among men in Nicaragua engaged in sugarcane harvest and seed cutting (n = 117), a group at high risk for MeN, against three referents: Nicaraguans working less strenuous jobs at the same sugarcane plantations (n = 78); Nicaraguans performing non-agricultural work (n = 102); and agricultural workers in Spain (n = 78). Using proton nuclear magnetic resonance, we identified 136 metabolites among participants. Our non-hypothesis-based approach identified distinguishing urine metabolic features in the high-risk group, revealing increased levels of hippurate and other gut-derived metabolites and decreased metabolites related to central energy metabolism when compared to referent groups. Our complementary hypothesis-based approach, focused on nicotinamide adenine dinucleotide (NAD+) related metabolites, and revealed a higher kynurenate/tryptophan ratio in the high-risk group (p = 0.001), consistent with a heightened inflammatory state. Workers in high-risk occupations are distinguishable by urinary metabolic features that suggest increased gut permeability, inflammation, and altered energy metabolism. Further study is needed to explore the pathophysiologic implications of these findings.