Untargeted Metabolic Profiling Research Articles

Metabolic Profile Reflects Stages of Fibrosis in Patients with Non-Alcoholic Fatty Liver Disease.

Nonalcoholic fatty liver disease (NAFLD) is a leading cause of chronic liver disease worldwide, with fibrosis stage being the main predictor for clinical outcomes. Here, we present the metabolic profile of NAFLD patients with regards to fibrosis progression. We included all consecutive new referrals for NAFLD services between 2011 and 2019. Demographic, anthropometric and clinical features and noninvasive markers of fibrosis were recorded at baseline and at follow-up. Significant and advanced fibrosis were defined using liver stiffness measurement (LSM) as LSM ≥ 8.1 kPa and LSM ≥ 12.1 kPa, respectively. Cirrhosis was diagnosed either histologically or clinically. Fast progressors of fibrosis were defined as those with delta stiffness ≥ 1.03 kPa/year (25% upper quartile of delta stiffness distribution). Targeted and untargeted metabolic profiles were analysed on fasting serum samples using Proton nuclear magnetic resonance (1H NMR). A total of 189 patients were included in the study; 111 (58.7%) underwent liver biopsy. Overall, 11.1% patients were diagnosed with cirrhosis, while 23.8% were classified as fast progressors. A combination of metabolites and lipoproteins could identify the fast fibrosis progressors (AUROC 0.788, 95% CI: 0.703-0.874, p < 0.001) and performed better than noninvasive markers. Specific metabolic profiles predict fibrosis progression in patients with nonalcoholic fatty liver disease. Algorithms combining metabolites and lipids could be integrated in the risk-stratification of these patients.

Comparative Untargeted Metabolic Profiling of Different Parts of Citrus sinensis Fruits via Liquid Chromatography-Mass Spectrometry Coupled with Multivariate Data Analyses to Unravel Authenticity.

Differences between seven authentic samples of Citrus sinensis var. Valencia peel (albedo and flavedo) and juices from Spain and Uruguay, in addition to a concentrate obtained from Brazil, were investigated by untargeted metabolic profiling. Sixty-six metabolites were detected by nano-liquid chromatography coupled to a high-resolution electrospray-ionization quadrupole time-of-flight mass spectrometer (nLC-ESI-qTOF-MS) belonging to phenolic acids, coumarins, flavonoid glycosides, limonoids, terpenes, and fatty acids. Eleven metabolites were detected for the first time in Citrus sinensis and identified as citroside A, sinapic acid pentoside, apigenin-C-hexosyl-O-pentoside, chrysoeriol-C-hexoside, di-hexosyl-diosmetin, perilloside A, gingerol, ionone epoxide hydroxy-sphingenine, xanthomicrol, and coumaryl alcohol-O-hexoside. Some flavonoids were completely absent from the juice, while present most prominently in the Citrus peel, conveying more industrial and economic prospects to the latter. Multivariate data analyses clarified that the differences among orange parts overweighed the geographical source. PCA analysis of ESI-(-)-mode data revealed for hydroxylinoleic acid abundance in flavedo peel from Uruguay the most distant cluster from all others. The PCA analysis of ESI-(+)-mode data provided a clear segregation of the different Citrus sinensis parts primarily due to the large diversity of flavonoids and coumarins among the studied samples.

Unraveling the secrets of plant roots: Simplified method for large scale root exudate sampling and analysis in Arabidopsis thaliana

Background: Plants exude a plethora of compounds to communicate with their environment. Although much is known about above-ground plant communication, we are only beginning to fathom the complexities of below ground chemical communication channels. Studying root-exuded compounds and their role in plant communication has been difficult due to a lack of standardized methodologies. Here, we develop an interdisciplinary workflow to explore the natural variation in root exudate chemical composition of the model plant Arabidopsis thaliana. We highlight key challenges associated with sampling strategies and develop a framework for analyzing both narrow and broad scale patterns of root exudate composition in a large set of natural A. thaliana accessions. Methods: Our method involves cultivating individual seedlings in vitro inside a plastic mesh, followed by a short hydroponic sampling period in small quantities of ultrapure water. The mesh makes it easy to handle plants of different sizes and allows for large-scale characterization of individual plant root exudates in axenic conditions. This setup can also be easily extended for prolonged temporal exudate collection experiments. Furthermore, the short sampling time minimizes the duration of the experiment while still providing sufficient signal even with a small volume of sampling solution. We used ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) for untargeted metabolic profiling, followed by tentative compound identification using MZMine3 and SIRIUS 5 software, to capture a broad overview of root exudate composition in A. thaliana accessions. Results: Based on 28 replicates of Columbia genotype (Col-0) compared with 10 random biological controls, MZMine3 identified 354 metabolites to be present only in Col-0 by negative ionization. Of these, 313 compounds could be annotated by SIRIUS 5 software. Conclusions: The methodology developed in this study can be used to broadly investigate the role of root exudates as chemical signals in plant belowground interactions.

Metabolic Profiling Reveals Changes in Serum Predictive of Venous Ulcer Healing.

The aim of this study was to identify potential biomarkers predictive of healing or failure to heal in a population with venous leg ulceration. Venous leg ulceration presents important physical, psychological, social and financial burdens. Compression therapy is the main treatment, but it can be painful and time-consuming, with significant recurrence rates. The identification of a reliable biochemical signature with the ability to identify nonhealing ulcers has important translational applications for disease prognostication, personalized health care and the development of novel therapies. Twenty-eight patients were assessed at baseline and at 20 weeks. Untargeted metabolic profiling was performed on urine, serum, and ulcer fluid, using mass spectrometry and nuclear magnetic resonance spectroscopy. A differential metabolic phenotype was identified in healing (n = 15) compared to nonhealing (n = 13) venous leg ulcer patients. Analysis of the assigned metabolites found ceramide and carnitine metabolism to be relevant pathways. In this pilot study, only serum biofluids could differentiate between healing and nonhealing patients. The ratio of carnitine to ceramide was able to differentiate between healing phenotypes with 100% sensitivity, 79% specificity, and 91% accuracy. This study reports a metabolic signature predictive of healing in venous leg ulceration and presents potential translational applications for disease prognostication and development of targeted therapies.

Mitochondrial supercomplex assembly regulates metabolic features and glutamine dependency in mammalian cells.

Rationale: Mitochondria generate ATP via the oxidative phosphorylation system, which mainly comprises five respiratory complexes found in the inner mitochondrial membrane. A high-order assembly of respiratory complexes is called a supercomplex. COX7A2L is a supercomplex assembly factor that has been well-investigated for studying supercomplex function and assembly. To date, the effects of mitochondrial supercomplexes on cell metabolism have not been elucidated. Methods: We depleted COX7A2L or Cox7a2l in human and mouse cells to generate cell models lacking mitochondrial supercomplexes as well as in DBA/2J mice as animal models. We tested the effect of impaired supercomplex assembly on cell proliferation with different nutrient supply. We profiled the metabolic features in COX7A2L-/- cells and Cox7a2l-/- mice via the combined use of targeted and untargeted metabolic profiling and metabolic flux analysis. We further tested the role of mitochondrial supercomplexes in pancreatic ductal adenocarcinoma (PDAC) through PDAC cell lines and a nude mouse model. Results: Impairing mitochondrial supercomplex assembly by depleting COX7A2L in human cells reprogrammed metabolic pathways toward anabolism and increased glutamine metabolism, cell proliferation and antioxidative defense. Similarly, knockout of Cox7a2l in DBA/2J mice promoted the use of proteins/amino acids as oxidative carbon sources. Mechanistically, impaired supercomplex assembly increased electron flux from CII to CIII/CIV and promoted CII-dependent respiration in COX7A2L-/- cells which further upregulated glutaminolysis and glutamine oxidation to accelerate the reactions of the tricarboxylic acid cycle. Moreover, the proliferation of PDAC cells lacking COX7A2L was inhibited by glutamine deprivation. Conclusion: Our results reveal the regulatory role of mitochondrial supercomplexes in glutaminolysis which may fine-tune the fate of cells with different nutrient availability.

The effects of dietary self-monitoring intervention on anthropometric and metabolic changes via a mobile application or paper-based diary: a randomized trial.

Weight loss via a mobile application (App) or a paper-based diary (Paper) may confer favorable metabolic and anthropometric changes. A randomized parallel trial was conducted among 57 adults whose body mass indices (BMIs) were 25 kg/m2 or greater. Participants randomly assigned to either the App group (n = 30) or the Paper group (n = 27) were advised to record their foods and supplements through App or Paper during the 12-week intervention period. Relative changes of anthropometries and biomarker levels were compared between the 2 intervention groups. Untargeted metabolic profiling was identified to discriminate metabolic profiles. Out of the 57 participants, 54 participants completed the trial. Changes in body weight and BMI were not significantly different between the 2 groups (P = 0.11). However, body fat and low-density lipoprotein (LDL)-cholesterol levels increased in the App group but decreased in the Paper group, and the difference was statistically significant (P = 0.03 for body fat and 0.02 for LDL-cholesterol). In the metabolomics analysis, decreases in methylglyoxal and (S)-malate in pyruvate metabolism and phosphatidylcholine (lecithin) in linoleic acid metabolism from pre- to post-intervention were observed in the Paper group. In the 12-week randomized parallel trial of weight loss through a App or a Paper, we found no significant difference in change in BMI or weight between the App and Paper groups, but improvement in body fatness and LDL-cholesterol levels only in the Paper group under the circumstances with minimal contact by dietitians or health care providers. Clinical Research Information Service Identifier: KCT0004226.

Erythrocyte Sphingosine 1 Phosphate Is Essential to Combat HIF1α-Dependent Creatine Shuttle, Macrophage Polarization and Fibrosis

Erythrocytes have long been considered as the major reservoir and supplier for plasma sphingosine 1 phosphate (S1P), which is a potent biolipid signaling via its specific receptors responsible for immune cell trafficking and polarization of tissue macrophages. Currently, emerging evidence has revealed that erythrocyte intracellular S1P has its own function to promote oxygen (O2) delivery to counteract tissue hypoxia. However, whether O2 delivery mediated by erythrocyte S1P is involved in tissue macrophage polarization, inflammation and fibrosis remains unrecognized. Here we report that genetic ablation of erythrocyte SphK1 (the only enzyme to generate S1P in erythrocyte eSphK1-/-) resulted in less O2 delivery from erythrocytes, thus leading to severe hypoxic tissue microenvironment, kidney damage and fibrosis in a well-accepted pathological hypoxic model infused with angiotensin II (a potent vasoconstrictor known to be elevated in hypertensive patients). Surprisingly, although plasma S1P levels were reduced to 50% in Ang II-infused eSphK1-/- mice, these mice displayed preferentially elevated pro-fibrosis M2 macrophages surrounding the hypoxic renal tubules (one of the most hypoxic sites with Ang II infusion). Metabolically, untargeted high-throughput metabolic profiling in macrophages purified from mouse kidney revealed a substantial reduction of amino acids (AAs) and fatty acids (FAs) but increased creatine. Further studies demonstrated that no significant differences of S1P level in either kidney or renal macrophages between Ang II-infused controls and eSphK1-/- mice, ruling out the possibility of difference of kidney or macrophage S1P levels responsible for renal M2 macrophage polarization in Ang II-infused eSphK1-/- mice. Instead, we revealed that reduced O2 offload from erythrocytes was previously unrecognized but essential to promote tissue M2 polarization and fibrosis by upregulating creatine shuttle to meet rapid intracellular energy needs when FAs, AAs and O2 were insufficient due to hypoxia in Ang II-infused eSphK1-/- mice. At cellular and molecular level, we demonstrated that hypoxia signaling via HIF-1a directly induced M2 polarization as well as expression of Slc6a8 (a gene encoding creatine transport), M2 specific marker gene and fibrotic marker gene in cultured murine BMDMs. Overall, our work has revealed that erythrocyte S1P combats HIF1α-dependent creatine shuttle, tissue macrophage polarization and fibrosis and highlighted potential diagnostic and therapeutic possibilities for macrophage polarization and tissue fibrosis. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Morphological, Molecular and Metabolic Characterization of the Pigmented Fungus Subramaniula asteroids.

Chaetomiaceae fungi are ascosporulating fungi whose importance as human pathogens has been frequently ignored. In the current study, a new isolate of the genus Subramaniula was described. The fungus was isolated from the soil of Wadi Om Nefa'a, Hurghada in the Red Sea Governorate, Egypt. Previously, Subramaniula were misidentified as Papulaspora spp. According to molecular analysis, the fungus was identified as Subramaniula asteroids OP484336. Remarkably, this species has been found among other fungi responsible for keratitis in humans and has been recorded for the first time in Egypt. Analysing the Subramaniula asteroids' metabolic profile was one of the objectives of the current study because little is known about this family's metabolome. The fungal extract's untargeted metabolic profiling was carried out by gas chromatography-mass spectroscopy (GC/MS), 1H and 1H-HSQC nuclear magnetic resonance (NMR) data, and their corresponding databases. In total, fifty-nine metabolites have been reported in the polar and non-polar extracts. The majority of polar metabolites are amino acids and carbohydrates. The non-polar extract's main components were 1-dodecanamine, N,N-dimethyl-, 1-tetradecanamine, N,N-dimethyl-, and 9-octadecenoic acid ethyl ester. The current study is the first to provide a metabolic profile of Subramaniula asteroids, which can be used in chemotaxonomical classification, antifungal drug development, and biological activity investigation of the studied species.

Metabolomic Analysis of Exosomes Derived from Lung Cancer Cell Line H460 Treated with SH003 and Docetaxel

Exosomes released from tumor cells treated with cancer-targeting drugs reflect altered metabolic processes within the cells. Therefore, metabolites in exosomes can be used as markers to predict the therapeutic response or identify therapeutic targets. In this study, metabolite changes in exosomes were investigated by co-administration of the herbal extract SH003 and docetaxel (DTX), which exert a synergistic anti-cancer effect on lung cancer cells. Exosomes released from cells treated with SH003 and DTX were purified, and untargeted metabolic profiling was performed by liquid chromatography-tandem mass spectrometry. Analysis of altered metabolic-based pathways showed that the combined treatment synergistically increased pyrimidine metabolism compared with single-drug treatment. Additionally, xenobiotic metabolism by cytochrome P450 was specifically increased in cells treated with the combination. However, the released exosomes and increased metabolites in exosomes did not affect the anti-cancer effect of SH003 and DTX. Therefore, our study suggests that metabolite profiling can be used to evaluate the efficacy of combined treatments. Furthermore, such exosome-based metabolism may facilitate understanding the physiological endpoints of combination therapy in human biofluids.

Metabolome-wide association study on ABCA7 indicates a role of ceramide metabolism in Alzheimer’s disease

Genome-wide association studies (GWASs) have identified genetic loci associated with the risk of Alzheimer's disease (AD), but the molecular mechanisms by which they confer risk are largely unknown. We conducted a metabolome-wide association study (MWAS) of AD-associated loci from GWASs using untargeted metabolic profiling (metabolomics) by ultraperformance liquid chromatography-mass spectrometry (UPLC-MS). We identified an association of lactosylceramides (LacCer) with AD-related single-nucleotide polymorphisms (SNPs) in ABCA7 (P = 5.0 × 10-5 to 1.3 × 10-44). We showed that plasma LacCer concentrations are associated with cognitive performance and genetically modified levels of LacCer are associated with AD risk. We then showed that concentrations of sphingomyelins, ceramides, and hexosylceramides were altered in brain tissue from Abca7 knockout mice, compared with wild type (WT) (P = 0.049-1.4 × 10-5), but not in a mouse model of amyloidosis. Furthermore, activation of microglia increases intracellular concentrations of hexosylceramides in part through induction in the expression of sphingosine kinase, an enzyme with a high control coefficient for sphingolipid and ceramide synthesis. Our work suggests that the risk for AD arising from functional variations in ABCA7 is mediated at least in part through ceramides. Modulation of their metabolism or downstream signaling may offer new therapeutic opportunities for AD.

Using follicular fluid metabolomics to investigate the association between air pollution and oocyte quality

Background and aimOur objective was to use metabolomics in a toxicological-relevant target tissue to gain insight into the biological processes that may underlie the negative association between air pollution exposure and oocyte quality. MethodsOur study included 125 women undergoing in vitro fertilization at an academic fertility center in Massachusetts, US (2005–2015). A follicular fluid sample was collected during oocyte retrieval and untargeted metabolic profiling was conducted using liquid chromatography with ultra-high-resolution mass spectrometry and two chromatography columns (C18 and HILIC). Daily exposure to nitrogen dioxide (NO2), ozone, fine particulate matter, and black carbon was estimated at the women’s residence using spatiotemporal models and averaged over the period of ovarian stimulation (2-weeks). Multivariable linear regression models were used to evaluate the associations between the air pollutants, number of mature oocytes, and metabolic feature intensities. A meet-in-the-middle approach was used to identify overlapping features and metabolic pathways. ResultsOf the air pollutants, NO2 exposure had the largest number of overlapping metabolites (C18: 105; HILIC: 91) and biological pathways (C18: 3; HILIC: 6) with number of mature oocytes. Key pathways of overlap included vitamin D3 metabolism (both columns), bile acid biosynthesis (both columns), C21-steroid hormone metabolism (HILIC), androgen and estrogen metabolism (HILIC), vitamin A metabolism (HILIC), carnitine shuttle (HILIC), and prostaglandin formation (C18). Three overlapping metabolites were confirmed with level-1 or level-2 evidence. For example, hypoxanthine, a metabolite that protects against oxidant-induced cell injury, was positively associated with NO2 exposure and negatively associated with number of mature oocytes. Minimal overlap was observed between the other pollutants and the number of mature oocytes. ConclusionsHigher exposure to NO2 during ovarian stimulation was associated with many metabolites and biologic pathways involved in endogenous vitamin metabolism, hormone synthesis, and oxidative stress that may mediate the observed associations with lower oocyte quality.

Study on plasma metabolomics for HIV/AIDS patients treated by HAART based on LC/MS-MS.

Background: Metabolomics can be applied to the clinical diagnosis and treatment evaluation of acquired immune deficiency syndrome (AIDS). AIDS biomarkers have become a new direction of AIDS research providing clinical guidance for diagnosis. Objective: We sought to apply both untargeted and targeted metabolomic profiling to identify potential biomarkers for AIDS patients. Methods: A liquid chromatography-tandem mass spectrometry (LC-MS/MS) based untargeted metabolomic profiling was performed on plasma samples of patients before and after highly active antiretroviral therapy (HAART) treatment as well as healthy volunteers to identify potential AIDS biomarkers. Targeted quantitative analysis was performed on the potential biomarkers screened from untargeted metabolic profiling for verification. Results: Using the Mass Profiler Professional and the MassHunter, several potential biomarkers have been found by LC-MS/MS in the untargeted metabolomic study. High-resolution MS and MS/MS were used to analyze fragmentation rules of the metabolites, with comparisons of related standards. Several potential biomarkers have been identified, including PS(O-18:0/0:0), sphingosine, PE (21:0/0:0), and 1-Linoleoyl Glycerol. Targeted quantitative analysis showed that sphingosine and 1-Linoleoyl Glycerol might be closely related to HIV/AIDS, which may be the potential biomarkers to the diagnosis. Conclusion: We conducted untargeted metabolomic profiling, which indicates that several metabolites should be considered potential biomarkers for AIDS patients. Further targeted metabolomic research verified that d-Sphingosine and 1-Linoleoyl glycerol as the diagnostic biomarker of AIDS.

Endophytic Klebsiella aerogenes HGG15 stimulates mulberry growth in hydro-fluctuation belt and the potential mechanisms as revealed by microbiome and metabolomics.

Growth promotion and stress tolerance induced by endophytes have been observed in various plants, but their effects on mulberry regularly suffering flood in the hydro-fluctuation belt are less understood. In the present study, endophytic Klebsiella aerogenes HGG15 was screened out from 28 plant growth promotion (PGP) bacteria as having superior PGP traits in vitro and in planta as well as biosafety for silkworms. K. aerogenes HGG15 could actively colonize into roots of mulberry and subsequently transferred to stems and leaves. The 16S ribosomal RNA (V3–V4 variable regions) amplicon sequencing revealed that exogenous application of K. aerogenes HGG15 altered the bacterial community structures of mulberry roots and stems. Moreover, the genus of Klebsiella was particularly enriched in inoculated mulberry roots and was positively correlated with mulberry development and soil potassium content. Untargeted metabolic profiles uncovered 201 differentially abundant metabolites (DEMs) between inoculated and control mulberry, with lipids and organo-heterocyclic compounds being particularly abundant DEMs. In addition, a high abundance of abiotic stress response factors and promotion growth stimulators such as glycerolipid, sphingolipid, indole, pyridine, and coumarin were observed in inoculated mulberry. Collectively, the knowledge gained from this study sheds light on potential strategies to enhance mulberry growth in hydro-fluctuation belt, and microbiome and metabolite analyses provide new insights into the growth promotion mechanisms used by plant-associated bacteria.

A Lactobacilli diet that confers MRSA resistance causes amino acid depletion and increased antioxidant levels in the C. elegans host.

Probiotic bacteria are increasingly popular as dietary supplements and have the potential as alternatives to traditional antibiotics. We have recently shown that pretreatment with Lactobacillus spp. Lb21 increases the life span of C. elegans and results in resistance toward pathogenic methicillin-resistant Staphylococcus aureus (MRSA). The Lb21-mediated MRSA resistance is dependent on the DBL-1 ligand of the TGF-β signaling pathway. However, the underlying changes at the metabolite level are not understood which limits the application of probiotic bacteria as timely alternatives to traditional antibiotics. In this study, we have performed untargeted nuclear magnetic resonance-based metabolic profiling. We report the metabolomes of Lactobacillus spp. Lb21 and control E. coli OP50 bacteria as well as the nematode-host metabolomes after feeding with these diets. We identify 48 metabolites in the bacteria samples and 51 metabolites in the nematode samples and 63 across all samples. Compared to the control diet, the Lactobacilli pretreatment significantly alters the metabolic profile of the worms. Through sparse Partial Least Squares discriminant analyses, we identify the 20 most important metabolites distinguishing probiotics from the regular OP50 food and worms fed the two different bacterial diets, respectively. Among the changed metabolites, we find lower levels of essential amino acids as well as increased levels of the antioxidants, ascorbate, and glutathione. Since the probiotic diet offers significant protection against MRSA, these metabolites could provide novel ways of combatting MRSA infections.

Bias caused by incomplete metabolite extraction and matrix effect: Evaluation of critical factors for plasma sample preparation prior to metabolomics

Metabolomics is an omics strategy to study the metabolite alteration in the biological system. Unbiased observation of the metabolite level is essential for targeted metabolite quantification and untargeted metabolic profiling. State-of-the-art instruments and versatile tools have been developed for accurate observation of metabolic alterations in various studies. Several analytical pitfalls, such as sample overloading and signal-saturation-induced bias, have been revealed and addressed. In this study, we proposed incomplete-metabolite-extraction-caused bias is also an important issue that results in biased observation when performing metabolomics. In the demonstration example, numerous metabolites exhibited no significant difference between extracted plasma samples with different plasma contents, which is attributed to incomplete-metabolite-extraction-caused bias and matrix effect. Matrix effect is a well-known factor that result in biased observation, it can be reduced by sample dilution and compensated by using stable isotope labelled internal standards. The detection of metabolite signals in the following consecutive extractions provided further evidence of incomplete metabolite extraction. The completeness of metabolite extraction is crucial for unbiased observation of metabolic profile changes. To address this issue, we optimized the extraction time and methanol volume to reduce the incomplete-metabolite-extraction-caused bias and evaluated the metabolite signals in consecutive extractions. Methanol extraction performed with a plasma-to-methanol ratio of 1:14 resulted in metabolite responses of less than 18.1 % in the second extractions observed by metabolomic profiling. Finally, the optimized sample preparation procedure and untargeted profiling platform were applied to detect metabolite alterations associated with patients with cerebrovascular diseases and several features with significant difference were successfully identified. This study revealed and evaluated the bias caused by incomplete metabolite extraction and matrix effect in the commonly used methanol extraction method for human plasma sample preparation for metabolomics. We anticipate the proposed metabolite extraction evaluation method could benefit more clinical and biological metabolomics studies.

ADP-dependent glucokinase (ADPGK) is not critical for the activation of human macrophages by LPS

Background: Activated immune cells show an enhanced glucose metabolism, suggesting that the inhibition of this pathway selective in immune cells could be a potential approach to combat inflammatory diseases. We studied here whether ADP-dependent glucokinase (ADPGK), a glucose-phosphorylating enzyme predominantly expressed in immune cells, could be a suitable target for the inhibition of macrophage activation. Methods: The regulation and role of ADPGK in human primary macrophages differentiated from blood monocytes was studied using Real-time quantitative PCR (RT-qPCR), gene silencing, whole-cell MALDI-mass spectrometry (MS) imaging as well as immune-based and enzymatic medium analyzes. Results: The expression of ADPGK was induced in response to the activation of toll-like receptors (TLRs). The most robust effect was observed with the TLR4 ligand Lipopolysaccharide (LPS) leading to an approximately 4-fold increase of ADPGK RNA levels. For this induction, the activation of p38 MAPK and IKKε was important. Silencing of ADPGK expression using siRNAs had neither an effect on LPS-induced expression and release of proinflammatory cytokines nor on cellular ATP levels and lactate production. Untargeted metabolic cell profiling by whole-cell MALDI-MS imaging did not reveal any metabolic regulations after ADPGK down-regulation suggesting no specific metabolic pathway involvement. Conclusions: ADPGK neither catalyzes a rate-limiting step of glucose metabolism in LPS-activated macrophages nor is required for the proinflammatory phenotype of these cells in vitro. Our data do not indicate that ADPGK inhibition could be a pharmacological approach to modulate immunometabolism.

Metabolic Profiling at COVID-19 Onset Shows Disease Severity and Sex-Specific Dysregulation.

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.

Custom‐made design of metabolite composition in N. benthamiana leaves using CRISPR activators

SummaryTranscriptional regulators based on CRISPR architecture expand our ability to reprogramme endogenous gene expression in plants. One of their potential applications is the customization of plant metabolome through the activation of selected enzymes in a given metabolic pathway. Using the previously described multiplexable CRISPR activator dCasEV2.1, we assayed the selective enrichment in Nicotiana benthamiana leaves of four different flavonoids, namely, naringenin, eriodictyol, kaempferol, and quercetin. After careful selection of target genes and guide RNAs combinations, we created successful activation programmes for each of the four metabolites, each programme activating between three and seven genes, and with individual gene activation levels ranging from 4‐ to 1500‐fold. Metabolic analysis of the flavonoid profiles of each multigene activation programme showed a sharp and selective enrichment of the intended metabolites and their glycosylated derivatives. Remarkably, principal component analysis of untargeted metabolic profiles clearly separated samples according to their activation treatment, and hierarchical clustering separated the samples into five groups, corresponding to the expected four highly enriched metabolite groups, plus an un‐activated control. These results demonstrate that dCasEV2.1 is a powerful tool for re‐routing metabolic fluxes towards the accumulation of metabolites of interest, opening the door for the custom‐made design of metabolic contents in plants.

Metabonomic Characteristics of Myocardial Diastolic Dysfunction in Type 2 Diabetic Cardiomyopathy Patients.

Diabetic cardiomyopathy (DCM) is one of the most essential cardiovascular complications in diabetic patients associated with glucose and lipid metabolism disorder, fibrosis, oxidative stress, and inflammation in cardiomyocytes. Despite increasing research on the molecular pathogenesis of DCM, it is still unclear whether metabolic pathways and alterations are probably involved in the development of DCM. This study aims to characterize the metabolites of DCM and to identify the relationship between metabolites and their biological processes or biological states through untargeted metabolic profiling. UPLC-MS/MS was applied to profile plasma metabolites from 78 patients with diabetes (39 diabetes with DCM and 39 diabetes without DCM as controls). A total of 2,806 biochemical were detected. Compared to those of DM patients, 78 differential metabolites in the positive-ion mode were identified in DCM patients, including 33 up-regulated and 45 down-regulated metabolites; however, there were only six differential metabolites identified in the negative mode including four up-regulated and two down-regulated metabolites. Alterations of several serum metabolites, including lipids and lipid-like molecules, organic acids and derivatives, organic oxygen compounds, benzenoids, phenylpropanoids and polyketides, and organoheterocyclic compounds, were associated with the development of DCM. KEGG enrichment analysis showed that there were three signaling pathways (metabolic pathways, porphyrin, chlorophyll metabolism, and lysine degradation) that were changed in both negative- and positive-ion modes. Our results demonstrated that differential metabolites and lipids have specific effects on DCM. These results expanded our understanding of the metabolic characteristics of DCM and may provide a clue in the future investigation of reducing the incidence of DCM. Furthermore, the metabolites identified here may provide clues for clinical management and the development of effective drugs.

Profiling Urinary Sulfate Metabolites With Mass Spectrometry.

The study of urinary phase II sulfate metabolites is central to understanding the role and fate of endogenous and exogenous compounds in biological systems. This study describes a new workflow for the untargeted metabolic profiling of sulfated metabolites in a urine matrix. Analysis was performed using ultra-high-performance liquid chromatography-high resolution tandem mass spectrometry (UHPLC-HRMS/MS) with data dependent acquisition (DDA) coupled to an automated script-based data processing pipeline and differential metabolite level analysis. Sulfates were identified through k-means clustering analysis of sulfate ester derived MS/MS fragmentation intensities. The utility of the method was highlighted in two applications. Firstly, the urinary metabolome of a thoroughbred horse was examined before and after administration of the anabolic androgenic steroid (AAS) testosterone propionate. The analysis detected elevated levels of ten sulfated steroid metabolites, three of which were identified and confirmed by comparison with synthesised reference materials. This included 5α-androstane-3β,17α-diol 3-sulfate, a previously unreported equine metabolite of testosterone propionate. Secondly, the hydrolytic activity of four sulfatase enzymes on pooled human urine was examined. This revealed that Pseudomonas aeruginosa arylsulfatases (PaS) enzymes possessed higher selectivity for the hydrolysis of sulfated metabolites than the commercially available Helix pomatia arylsulfatase (HpS). This novel method provides a rapid tool for the systematic, untargeted metabolic profiling of sulfated metabolites in a urinary matrix.