Stratification of Sepsis Patients on Admission into the Intensive Care Unit According to Differential Plasma Metabolic Phenotypes.

Delayed diagnosis of patients with sepsis or septic shock is associated with increased mortality and morbidity. UPLC-MS and NMR spectroscopy were used to measure panels of lipoproteins, lipids, biogenic amines, amino acids, and tryptophan pathway metabolites in blood plasma samples collected from 152 patients within 48 h of admission into the Intensive Care Unit (ICU) where 62 patients had no sepsis, 71 patients had sepsis, and 19 patients had septic shock. Patients with sepsis or septic shock had higher concentrations of neopterin and lower levels of HDL cholesterol and phospholipid particles in comparison to nonsepsis patients. Septic shock could be differentiated from sepsis patients based on different concentrations of 10 lipids, including significantly lower concentrations of five phosphatidylcholine species, three cholesterol esters, one dihydroceramide, and one phosphatidylethanolamine. The Supramolecular Phospholipid Composite (SPC) was reduced in all ICU patients, while the composite markers of acute phase glycoproteins were increased in the sepsis and septic shock patients within 48 h admission into ICU. We show that the plasma metabolic phenotype obtained within 48 h of ICU admission is diagnostic for the presence of sepsis and that septic shock can be differentiated from sepsis based on the lipid profile.

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.

MetSCORE: a molecular metric to evaluate the risk of metabolic syndrome based on serum NMR metabolomics.

BACKGROUND: Metabolic syndrome (MetS) is a cluster of medical conditions and risk factors correlating with insulin resistance that increase the risk of developing cardiometabolic health problems. The specific criteria for diagnosing MetS vary among different medical organizations but are typically based on the evaluation of abdominal obesity, high blood pressure, hyperglycemia, and dyslipidemia. A unique, quantitative and independent estimation of the risk of MetS based only on quantitative biomarkers is highly desirable for the comparison between patients and to study the individual progression of the disease in a quantitative manner. METHODS: We used NMR-based metabolomics on a large cohort of donors (n = 21,323; 37.5% female) to investigate the diagnostic value of serum or serum combined with urine to estimate the MetS risk. Specifically, we have determined 41 circulating metabolites and 112 lipoprotein classes and subclasses in serum samples and this information has been integrated with metabolic profiles extracted from urine samples. RESULTS: We have developed MetSCORE, a metabolic model of MetS that combines serum lipoprotein and metabolite information. MetSCORE discriminate patients with MetS (independently identified using the WHO criterium) from general population, with an AUROC of 0.94 (95% CI 0.920-0.952, p < 0.001). MetSCORE is also able to discriminate the intermediate phenotypes, identifying the early risk of MetS in a quantitative way and ranking individuals according to their risk of undergoing MetS (for general population) or according to the severity of the syndrome (for MetS patients). CONCLUSIONS: We believe that MetSCORE may be an insightful tool for early intervention and lifestyle modifications, potentially preventing the aggravation of metabolic syndrome.

Congenital erythropoietic porphyria.

Congenital erythropoietic porphyria (CEP) is a rare autosomal recessive disease due to the deficient, but not absent, activity of uroporphyrinogen III synthase (UROS), the fourth enzyme in the heme biosynthesis pathway. Biallelic variants in the UROS gene result in decreased UROS enzymatic activity and the accumulation of non-physiologic Type I porphyrins in cells and fluids. Overproduced uroporphyrins in haematopoietic cells are released into the circulation and distributed to tissues, inducing primarily hematologic and dermatologic symptoms. The clinical manifestations vary in severity ranging from non-immune hydrops fetalis in utero to mild dermatologic manifestations in adults. Here, the biochemical, molecular and clinical features of CEP as well as current and new treatment options, including the rescue of UROS enzyme activity by chaperones, are presented.

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).

Conformation-sensitive antibody reveals an altered cytosolic PAS/CNBh assembly during hERG channel gating.

The human ERG (hERG) K+ channel has a crucial function in cardiac repolarization, and mutations or channel block can give rise to long QT syndrome and catastrophic ventricular arrhythmias. The cytosolic assembly formed by the Per-Arnt-Sim (PAS) and cyclic nucleotide binding homology (CNBh) domains is the defining structural feature of hERG and related KCNH channels. However, the molecular role of these two domains in channel gating remains unclear. We have previously shown that single-chain variable fragment (scFv) antibodies can modulate hERG function by binding to the PAS domain. Here, we mapped the scFv2.12 epitope to a site overlapping with the PAS/CNBh domain interface using NMR spectroscopy and mutagenesis and show that scFv binding in vitro and in the cell is incompatible with the PAS interaction with CNBh. By generating a fluorescently labeled scFv2.12, we demonstrate that association with the full-length hERG channel is state dependent. We detect Förster resonance energy transfer (FRET) with scFv2.12 when the channel gate is open but not when it is closed. In addition, state dependence of scFv2.12 FRET signal disappears when the R56Q mutation, known to destabilize the PAS-CNBh interaction, is introduced in the channel. Altogether, these data are consistent with an extensive structural alteration of the PAS/CNBh assembly when the cytosolic gate opens, likely favoring PAS domain dissociation from the CNBh domain.

Quantitative Analysis of the Human Semen Phosphorometabolome by 31P-NMR.

Phosphorus-containing metabolites occupy a prominent position in cell pathways. The phosphorometabolomic approach in human sperm samples will deliver valuable information as new male fertility biomarkers could emerge. This study analyzed, by 31P-NMR, seminal plasma and whole semen from asthenozoospermic and normozoospermic samples (71% vs. 27% and 45% vs. 17%, total and progressive sperm motility, respectively), and also ejaculates from healthy donors. At least 16 phosphorus-containing metabolites involved in central energy metabolism and phospholipid, nucleotide, and nicotinamide metabolic pathways were assigned and different abundances between the samples with distinct sperm quality was detected. Specifically, higher levels of phosphocholine, glucose-1-phosphate, and to a lesser degree, acetyl phosphate were found in the asthenozoospermic seminal plasma. Notably, the phosphorometabolites implicated in lipid metabolism were highlighted in the seminal plasma, while those associated with carbohydrate metabolism were more abundant in the spermatozoa. Higher levels of phosphocholine, glucose-1-phosphate, and acetyl phosphate in the seminal plasma with poor quality suggest their crucial role in supporting sperm motility through energy metabolic pathways. In the seminal plasma, phosphorometabolites related to lipid metabolism were prominent; however, spermatozoa metabolism is more dependent on carbohydrate-related energy pathways. Understanding the presence and function of sperm phosphorylated metabolites will enhance our knowledge of the metabolic profile of healthy human sperm, improving assessment and differential diagnosis.

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.

NMR Investigation of Protein-Carbohydrate Interactions: The Recognition of Glycans by Galectins Engineered with Fluorotryptophan Residues.

Fluorine (19 F) incorporation into glycan-binding proteins (lectins) has been achieved and exploited to monitor the binding to carbohydrate ligands by nuclear magnetic resonance (NMR) spectroscopy. Galectins are a family of lectins that bind carbohydrates, generally with weak affinities, through a combination of intermolecular interactions including a key CH-π stacking involving a conserved tryptophan residue. Herein, Galectin-3 (Gal3) and Galectin-8 (Gal8) with one and two carbohydrate recognition domains (CRDs), respectively, were selected. Gal3 contains one Trp, whereas Gal8 contains three, one at each binding site and a third one not involved in sugar binding; these were substituted by the corresponding F-Trp analogues. The presence of fluorine did not significantly modify the affinity for glycan binding, which was in slow exchange on the 19 F NMR chemical-shift timescale, even for weak ligands, and allowed binding events taking place at two different binding sites within the same lectin to be individualized.

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.

The use of pharmacological chaperones in rare diseases caused by reduced protein stability.

Rare diseases are most often caused by inherited genetic disorders that, after translation, will result in a protein with altered function. Decreased protein stability is the most frequent mechanism associated with a congenital pathogenic missense mutation and it implies the destabilization of the folded conformation in favour of unfolded or misfolded states. In the cellular context and when experimental data is available, a mutant protein with altered thermodynamic stability often also results in impaired homeostasis, with the deleterious accumulation of protein aggregates, metabolites and/or metabolic by-products. In the last decades, a significant effort has enabled the characterization of rare diseases associated to protein stability defects and triggered the development of innovative therapeutic intervention lines, say, the use of pharmacological chaperones to correct the intracellular impaired homeostasis. Here, we review the current knowledge on rare diseases caused by reduced protein stability, paying special attention to the thermodynamic aspects of the protein destabilization, also focusing on some examples where pharmacological chaperones are being tested.

ALAD Inhibition by Porphobilinogen Rationalizes the Accumulation of δ-Aminolevulinate in Acute Porphyrias.

Patients with major forms of acute hepatic porphyria present acute neurological attacks with overproduction of porphobilinogen (PBG) and δ-aminolevulinic acid (ALA). Even if ALA is considered the most likely agent inducing the acute symptoms, the mechanism of its accumulation has not been experimentally demonstrated. In the most frequent form, acute intermittent porphyria (AIP), inherited gene mutations induce a deficiency in PBG deaminase; thus, accumulation of the substrate PBG is biochemically obligated but not that of ALA. A similar scenario is observed in other forms of acute hepatic porphyria (i.e., porphyria variegate, VP) in which PBG deaminase is inhibited by metabolic intermediates. Here, we have investigated the molecular basis of δ-aminolevulinate accumulation using in vitro fluxomics monitored by NMR spectroscopy and other biophysical techniques. Our results show that porphobilinogen, the natural product of δ-aminolevulinate deaminase, effectively inhibits its anabolic enzyme at abnormally low concentrations. Structurally, this high affinity can be explained by the interactions that porphobilinogen generates with the active site, most of them shared with the substrate. Enzymatically, our flux analysis of an altered heme pathway demonstrates that a minimum accumulation of porphobilinogen will immediately trigger the accumulation of δ-aminolevulinate, a long-lasting observation in patients suffering from acute porphyrias.

Inhibition of carnitine palmitoyltransferase 1A in hepatic stellate cells protects against fibrosis.

BACKGROUND & AIMS: The pathogenesis of liver fibrosis requires activation of hepatic stellate cells (HSCs); once activated, HSCs lose intracellular fatty acids but the role of fatty acid oxidation and carnitine palmitoyltransferase 1A (CPT1A) in this process remains largely unexplored. METHODS: CPT1A was found in HSCs of patients with fibrosis. Pharmacological and genetic manipulation of CPT1A were performed in human HSC cell lines and primary HCSs. Finally, we induced fibrosis in mice lacking CPT1A specifically in HSCs. RESULTS: Herein, we show that CPT1A expression is elevated in HSCs of patients with non-alcoholic steatohepatitis, showing a positive correlation with the fibrosis score. This was corroborated in rodents with fibrosis, as well as in primary human HSCs and LX-2 cells activated by transforming growth factor ß1 (TGFß1) and fetal bovine serum (FBS). Furthermore, both pharmacological and genetic silencing of CPT1A prevent TGFß1- and FBS-induced HSC activation by reducing mitochondrial activity. The overexpression of CPT1A, induced by saturated fatty acids and reactive oxygen species, triggers mitochondrial activity and the expression of fibrogenic markers. Finally, mice lacking CPT1A specifically in HSCs are protected against fibrosis induced by a choline-deficient high-fat diet, a methionine- and choline-deficient diet, or treatment with carbon tetrachloride. CONCLUSIONS: These results indicate that CPT1A plays a critical role in the activation of HSCs and is implicated in the development of liver fibrosis, making it a potentially actionable target for fibrosis treatment. LAY SUMMARY: We show that the enzyme carnitine palmitoyltransferase 1A (CPT1A) is elevated in hepatic stellate cells (HSCs) in patients with fibrosis and mouse models of fibrosis, and that CPT1A induces the activation of these cells. Inhibition of CPT1A ameliorates fibrosis by preventing the activation of HSCs.

J-Edited DIffusional Proton Nuclear Magnetic Resonance Spectroscopic Measurement of Glycoprotein and Supramolecular Phospholipid Biomarkers of Inflammation in Human Serum.

Proton nuclear magnetic resonance (NMR) N-acetyl signals (Glyc) from glycoproteins and supramolecular phospholipids composite peak (SPC) from phospholipid quaternary nitrogen methyls in subcompartments of lipoprotein particles) can give important systemic metabolic information, but their absolute quantification is compromised by overlap with interfering resonances from lipoprotein lipids themselves. We present a J-Edited DIffusional (JEDI) proton NMR spectroscopic approach to selectively augment signals from the inflammatory marker peaks Glyc and SPCs in blood serum NMR spectra, which enables direct integration of peaks associated with molecules found in specific compartments. We explore a range of pulse sequences that allow editing based on peak J-modulation, translational diffusion, and T2 relaxation time and validate them for untreated blood serum samples from SARS-CoV-2 infected patients (n = 116) as well as samples from healthy controls and pregnant women with physiological inflammation and hyperlipidemia (n = 631). The data show that JEDI is an improved approach to selectively investigate inflammatory signals in serum and may have widespread diagnostic applicability to disease states associated with systemic inflammation.

Exploration of Human Serum Lipoprotein Supramolecular Phospholipids Using Statistical Heterospectroscopy in n-Dimensions (SHY-n): Identification of Potential Cardiovascular Risk Biomarkers Related to SARS-CoV-2 Infection.

SARS-CoV-2 infection causes a significant reduction in lipoprotein-bound serum phospholipids give rise to supramolecular phospholipid composite (SPC) signals observed in diffusion and relaxation edited 1H NMR spectra. To characterize the chemical structural components and compartmental location of SPC and to understand further its possible diagnostic properties, we applied a Statistical HeterospectroscopY in n-dimensions (SHY-n) approach. This involved statistically linking a series of orthogonal measurements made on the same samples, using independent analytical techniques and instruments, to identify the major individual phospholipid components giving rise to the SPC signals. Thus, an integrated model for SARS-CoV-2 positive and control adults is presented that relates three identified diagnostic subregions of the SPC signal envelope (SPC1, SPC2, and SPC3) generated using diffusion and relaxation edited (DIRE) NMR spectroscopy to lipoprotein and lipid measurements obtained by in vitro diagnostic NMR spectroscopy and ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). The SPC signals were then correlated sequentially with (a) total phospholipids in lipoprotein subfractions; (b) apolipoproteins B100, A1, and A2 in different lipoproteins and subcompartments; and (c) MS-measured total serum phosphatidylcholines present in the NMR detection range (i.e., PCs: 16.0,18.2; 18.0,18.1; 18.2,18.2; 16.0,18.1; 16.0,20.4; 18.0,18.2; 18.1,18.2), lysophosphatidylcholines (LPCs: 16.0 and 18.2), and sphingomyelin (SM 22.1). The SPC3/SPC2 ratio correlated strongly (r = 0.86) with the apolipoprotein B100/A1 ratio, a well-established marker of cardiovascular disease risk that is markedly elevated during acute SARS-CoV-2 infection. These data indicate the considerable potential of using a serum SPC measurement as a metric of cardiovascular risk based on a single NMR experiment. This is of specific interest in relation to understanding the potential for increased cardiovascular risk in COVID-19 patients and risk persistence in post-acute COVID-19 syndrome (PACS).

Metabolic Landscape of the Mouse Liver by Quantitative 31 P Nuclear Magnetic Resonance Analysis of the Phosphorome.

BACKGROUND AND AIMS: The liver plays a central role in all metabolic processes in the body. However, precise characterization of liver metabolism is often obscured by its inherent complexity. Phosphorylated metabolites occupy a prominent position in all anabolic and catabolic pathways. Here, we develop a 31 P nuclear magnetic resonance (NMR)-based method to study the liver "phosphorome" through the simultaneous identification and quantification of multiple hydrophilic and hydrophobic phosphorylated metabolites. APPROACH AND RESULTS: We applied this technique to define the metabolic landscape in livers from a mouse model of the rare disease disorder congenital erythropoietic porphyria (CEP) as well as two well-known murine models of nonalcoholic steatohepatitis: one genetic, methionine adenosyltransferase 1A knockout mice, and the other dietary, mice fed a high-fat choline-deficient diet. We report alterations in the concentrations of phosphorylated metabolites that are readouts of the balance between glycolysis, gluconeogenesis, the pentose phosphate pathway, the tricarboxylic acid cycle, and oxidative phosphorylation and of phospholipid metabolism and apoptosis. Moreover, these changes correlate with the main histological features: steatosis, apoptosis, iron deposits, and fibrosis. Strikingly, treatment with the repurposed drug ciclopirox improves the phosphoromic profile of CEP mice, an effect that was mirrored by the normalization of liver histology. CONCLUSIONS: In conclusion, these findings indicate that NMR-based phosphoromics may be used to unravel metabolic phenotypes of liver injury and to identify the mechanism of drug action.

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.

Cosolute modulation of protein oligomerization reactions in the homeostatic timescale.

Protein oligomerization processes are widespread and of crucial importance to understand degenerative diseases and healthy regulatory pathways. One particular case is the homo-oligomerization of folded domains involving domain swapping, often found as a part of the protein homeostasis in the crowded cytosol, composed of a complex mixture of cosolutes. Here, we have investigated the effect of a plethora of cosolutes of very diverse nature on the kinetics of a protein dimerization by domain swapping. In the absence of cosolutes, our system exhibits slow interconversion rates, with the reaction reaching the equilibrium within the average protein homeostasis timescale (24-48 h). In the presence of crowders, though, the oligomerization reaction in the same time frame will, depending on the protein's initial oligomeric state, either reach a pure equilibrium state or get kinetically trapped into an apparent equilibrium. Specifically, when the reaction is initiated from a large excess of dimer, it becomes unsensitive to the effect of cosolutes and reaches the same equilibrium populations as in the absence of cosolute. Conversely, when the reaction starts from a large excess of monomer, the reaction during the homeostatic timescale occurs under kinetic control, and it is exquisitely sensitive to the presence and nature of the cosolute. In this scenario (the most habitual case in intracellular oligomerization processes), the effect of cosolutes on the intermediate conformation and diffusion-mediated encounters will dictate how the cellular milieu affects the domain-swapping reaction.