A compendium of multi-omics data illuminating host responses to lethal human virus infections.

Human infections caused by viral pathogens trigger a complex gamut of host responses that limit disease, resolve infection, generate immunity, and contribute to severe disease or death. Here, we present experimental methods and multi-omics data capture approaches representing the global host response to infection generated from 45 individual experiments involving human viruses from the Orthomyxoviridae, Filoviridae, Flaviviridae, and Coronaviridae families. Analogous experimental designs were implemented across human or mouse host model systems, longitudinal samples were collected over defined time courses, and global multi-omics data (transcriptomics, proteomics, metabolomics, and lipidomics) were acquired by microarray, RNA sequencing, or mass spectrometry analyses. For comparison, we have included transcriptomics datasets from cells treated with type I and type II human interferon. Raw multi-omics data and metadata were deposited in public repositories, and we provide a central location linking the raw data with experimental metadata and ready-to-use, quality-controlled, statistically processed multi-omics datasets not previously available in any public repository. This compendium of infection-induced host response data for reuse will be useful for those endeavouring to understand viral disease pathophysiology and network biology.

Atherosclerosis, gut microbiome, and exercise in a meta-omics perspective: a literature review.

Background: Cardiovascular diseases are the leading cause of death worldwide, significantly impacting public health. Atherosclerotic cardiovascular diseases account for the majority of these deaths, with atherosclerosis marking the initial and most critical phase of their pathophysiological progression. There is a complex relationship between atherosclerosis, the gut microbiome's composition and function, and the potential mediating role of exercise. The adaptability of the gut microbiome and the feasibility of exercise interventions present novel opportunities for therapeutic and preventative approaches. Methodology: We conducted a comprehensive literature review using professional databases such as PubMed and Web of Science. This review focuses on the application of meta-omics techniques, particularly metagenomics and metabolomics, in studying the effects of exercise interventions on the gut microbiome and atherosclerosis. Results: Meta-omics technologies offer unparalleled capabilities to explore the intricate connections between exercise, the microbiome, the metabolome, and cardiometabolic health. This review highlights the advancements in metagenomics and metabolomics, their applications in research, and examines how exercise influences the gut microbiome. We delve into the mechanisms connecting these elements from a metabolic perspective. Metagenomics provides insight into changes in microbial strains post-exercise, while metabolomics sheds light on the shifts in metabolites. Together, these approaches offer a comprehensive understanding of how exercise impacts atherosclerosis through specific mechanisms. Conclusions: Exercise significantly influences atherosclerosis, with the gut microbiome serving as a critical intermediary. Meta-omics technology holds substantial promise for investigating the gut microbiome; however, its methodologies require further refinement. Additionally, there is a pressing need for more extensive cohort studies to enhance our comprehension of the connection among these element.

Untargeted metabolomics reveals that declined PE and PC in obesity may be associated with prostate hyperplasia.

BACKGROUND: Recent studies have shown that obesity may contribute to the pathogenesis of benign prostatic hyperplasia (BPH). However, the mechanism of this pathogenesis is not fully understood. METHODS: A prospective case-control study was conducted with 30 obese and 30 nonobese patients with BPH. Prostate tissues were collected and analyzed using ultra performance liquid chromatography ion mobility coupled with quadrupole time-of-flight mass spectrometry (UPLC-IMS-Q-TOF). RESULTS: A total of 17 differential metabolites (3 upregulated and 14 downregulated) were identified between the obese and nonobese patients with BPH. Topological pathway analysis indicated that glycerophospholipid (GP) metabolism was the most important metabolic pathway involved in BPH pathogenesis. Seven metabolites were enriched in the GP metabolic pathway. lysoPC (P16:0/0:0), PE (20:0/20:0), PE (24:1(15Z)/18:0), PC (24:1(15Z)/14:0), PC (15:0/24:0), PE (24:0/18:0), and PC (16:0/18:3(9Z,12Z,15Z)) were all significantly downregulated in the obesity group, and the area under the curve (AUC) of LysoPC (P-16:0/0/0:0) was 0.9922. The inclusion of the seven differential metabolites in a joint prediction model had an AUC of 0.9956. Thus, both LysoPC (P-16:0/0/0:0) alone and the joint prediction model demonstrated good predictive ability for obesity-induced BPH mechanisms. CONCLUSIONS: In conclusion, obese patients with BPH had a unique metabolic profile, and alterations in PE and PC in these patients be associated with the development and progression of BPH.

4-phenylbutyric acid improves sepsis-induced cardiac dysfunction by modulating amino acid metabolism and lipid metabolism via Comt/Ptgs2/Ppara.

INTRODUCTION: Cardiac dysfunction after sepsis the most common and severe sepsis-related organ failure. The severity of cardiac damage in sepsis patients was positively associated to mortality. It is important to look for drugs targeting sepsis-induced cardiac damage. Our previous studies found that 4-phenylbutyric acid (PBA) was beneficial to septic shock by improving cardiovascular function and survival, while the specific mechanism is unclear. OBJECTIVES: We aimed to explore the specific mechanism and PBA for protecting cardiac function in sepsis. METHODS: The cecal ligation and puncture-induced septic shock models were used to observe the therapeutic effects of PBA on myocardial contractility and the serum levels of cardiac troponin-T. The mechanisms of PBA against sepsis were explored by metabolomics and network pharmacology. RESULTS: The results showed that PBA alleviated the sepsis-induced cardiac damage. The metabolomics results showed that there were 28 metabolites involving in the therapeutic effects of PBA against sepsis. According to network pharmacology, 11 hub genes were found that were involved in lipid metabolism and amino acid transport following PBA treatment. The further integrated analysis focused on 7 key targets, including Comt, Slc6a4, Maoa, Ppara, Pparg, Ptgs2 and Trpv1, as well as their core metabolites and pathways. In an in vitro assay, PBA effectively inhibited sepsis-induced reductions in Comt, Ptgs2 and Ppara after sepsis. CONCLUSIONS: PBA protects sepsis-induced cardiac injury by targeting Comt/Ptgs2/Ppara, which regulates amino acid metabolism and lipid metabolism. The study reveals the complicated mechanisms of PBA against sepsis.

Multiple-matrix metabolomics analysis for the distinct detection of colorectal cancer and adenoma.

OBJECTIVES: Although colorectal cancer (CRC) is the leading cause of cancer-related morbidity and mortality, current diagnostic tests for early-stage CRC and colorectal adenoma (CRA) are suboptimal. Therefore, there is an urgent need to explore less invasive screening procedures for CRC and CRA diagnosis. METHODS: Untargeted gas chromatography-mass spectrometry (GC-MS) metabolic profiling approach was applied to identify candidate metabolites. We performed metabolomics profiling on plasma samples from 412 subjects including 200 CRC patients, 160 CRA patients and 52 normal controls (NC). Among these patients, 45 CRC patients, 152 CRA patients and 50 normal controls had their fecal samples tested simultaneously. RESULTS: Differential metabolites were screened in the adenoma-carcinoma sequence. Three diagnostic models were further developed to identify cancer group, cancer stage, and cancer microsatellite status using those significant metabolites. The three-metabolite-only classifiers used to distinguish the cancer group always keeps the area under the receiver operating characteristic curve (AUC) greater than 0.7. The AUC performance of the classifiers applied to discriminate CRC stage is generally greater than 0.8, and the classifiers used to distinguish microsatellite status of CRC is greater than 0.9. CONCLUSION: This finding highlights potential early-driver metabolites in CRA and early-stage CRC. We also find potential metabolic markers for discriminating the microsatellite state of CRC. Our study and diagnostic model have potential applications for non-invasive CRC and CRA detection.

Gut microbiome and metabolome profiling in Framingham heart study reveals cholesterol-metabolizing bacteria.

Accumulating evidence suggests that cardiovascular disease (CVD) is associated with an altered gut microbiome. Our understanding of the underlying mechanisms has been hindered by lack of matched multi-omic data with diagnostic biomarkers. To comprehensively profile gut microbiome contributions to CVD, we generated stool metagenomics and metabolomics from 1,429 Framingham Heart Study participants. We identified blood lipids and cardiovascular health measurements associated with microbiome and metabolome composition. Integrated analysis revealed microbial pathways implicated in CVD, including flavonoid, γ-butyrobetaine, and cholesterol metabolism. Species from the Oscillibacter genus were associated with decreased fecal and plasma cholesterol levels. Using functional prediction and in vitro characterization of multiple representative human gut Oscillibacter isolates, we uncovered conserved cholesterol-metabolizing capabilities, including glycosylation and dehydrogenation. These findings suggest that cholesterol metabolism is a broad property of phylogenetically diverse Oscillibacter spp., with potential benefits for lipid homeostasis and cardiovascular health.

Elucidating ascorbate and aldarate metabolism pathway characteristics via integration of untargeted metabolomics and transcriptomics of the kidney of high-fat diet-fed obese mice.

Obesity is a major independent risk factor for chronic kidney disease and can activate renal oxidative stress injury. Ascorbate and aldarate metabolism is an important carbohydrate metabolic pathway that protects cells from oxidative damage. However the effect of oxidative stress on this pathway is still unclear. Therefore, the primary objective of this study was to investigate the ascorbate and aldarate metabolism pathway in the kidneys of high-fat diet-fed obese mice and determine the effects of oxidative stress. Male C57BL/6J mice were fed on a high-fat diet for 12 weeks to induce obesity. Subsequently, non-targeted metabolomics profiling was used to identify metabolites in the kidney tissues of the obese mice, followed by RNA sequencing using transcriptomic methods. The integrated analysis of metabolomics and transcriptomics revealed the alterations in the ascorbate and aldarate metabolic pathway in the kidneys of these high-fat diet-fed obese mice. The high-fat diet-induced obesity resulted in notable changes, including thinning of the glomerular basement membrane, alterations in podocyte morphology, and an increase in oxidative stress. Metabolomics analysis revealed 649 metabolites in the positive-ion mode, and 470 metabolites in the negative-ion mode. Additionally, 659 differentially expressed genes (DEGs) were identified in the obese mice, of which 34 were upregulated and 625 downregulated. Integrated metabolomics and transcriptomics analyses revealed two DEGs and 13 differential metabolites in the ascorbate and aldarate metabolic pathway. The expression levels of ugt1a9 and ugt2b1 were downregulated, and the ascorbate level in kidney tissue of obese mice was reduced. Thus, renal oxidative stress injury induced by high-fat diet affects metabolic regulation of ascorbate and aldarate metabolism in obese mice. Ascorbate emerged as a potential marker for predicting kidney damage due to high-fat diet-induced obesity.

From the grapevine to the glass: A wine metabolomics tale by FT-ICR-MS.

Wine is one of the most consumed beverages around the world. Its unique characteristics arise from numerous processes, from the selection of grapevine varieties and grapes, the effect of the terroir and geographical origin, through the biochemical process of fermentation by microorganisms, until its aging. All molecules found in wine define its chemical fingerprint and can be used to tell the story of its origin, production, authenticity and quality. Wine's chemical composition can be characterized using an untargeted metabolomics approach based on extreme resolution mass spectrometry. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) is currently the most powerful analytical technique to analyse such complex sample, providing the most comprehensive analysis of the chemical fingerprint of wine.

[Metabolomics of quality formation of different cultivars of Peucedanum praeruptorum].

This study aims to reveal the quality formation of different cultivars of Peucedanum praeruptorum based on the metabolic differences and provide a theoretical basis for the development and utilization of this medicinal herb. The non-target metabonomics analysis based on ultra-high performance liquid chromatography tandem mass spectrometry(UHPLC-MS/MS) was conducted for six cultivars(YS, H, LZ, LY, LX, and Z) of P. praeruptorum of the same origin and at the same development stage. The principal component analysis, orthogonal partial least squares discriminant analysis, and univariate statistical analysis were carried out to screen the differential metabolites of different cultivars. The potential biomarkers associated with quality formation were predicted based on the mass-to-charge ratio, Kyoto Encyclopedia of Genes and Genomes pathway enrichment, information of relevant literature, and correlation analysis. The results showed that metabolites differed significantly among the six cultivars, and 571 and 465 differential metabolites were obtained in the positive and negative ion modes, respectively. From the differential metabolites, 22 potential biomarkers related to quality formation were predicted, which involved 9 metabolic pathways, including phenylalanine, tyrosine and tryptophan biosynthesis, biosynthesis of phenylpropanoids, and biosynthesis of plant hormones. Compared with the YS cultivar, other cultivars showed decreased concentrations of psoralen, imperatorin, and luvangetin and increased concentrations of 7-hydroxycoumarine, esculetin, columbianetin, and jasmonic acid, which were involved in the biosynthesis of phenylpropanoids. The concentrations of 2-succinylbenzoate, heraclenol, and L-tyrosine involved in other metabolic pathways decreased, especially in the Z and H cultivars. Therefore, regulating the biosynthesis of phenylpropanoids is one of the key mechanisms for improving the cultivar quality of P. praeruptorum. The Z and H cultivars have better quality and metabolic processes than other cultivars and thus can be used for the screening and breeding of high-quality germplasm.

[Research on mechanism of hypolipidemic effect of Massa Medicata Fermentata based on metabolomics].

This paper aims to study the therapeutic effect of Massa Medicata Fermentata on hyperlipidemia model rats and investigate its mechanism of hypolipidemic effect with the help of non-targeted metabolomics. The mixed hyperlipidemia model rats were constructed by giving high-fat chow. After successful modeling, the rats were divided into the model group, pravastatin sodium group(4.4 mg·kg~(-1)), lipotropic group(0.1 g·kg~(-1)), high-dose group(2.4 g·kg~(-1)), medium-dose group(1.2 g·kg~(-1)), and low-dose group(0.6 g·kg~(-1)) of Massa Medicata Fermentata, and they were administered for four weeks once daily. An equal volume of ultrapure water was given to the blank group and model group. Serum lipid level and liver hematoxylin-eosin(HE) staining were used as indicators to estimate the intervention effect of Massa Medicata Fermentata on mixed hyperlipidemia, and the changes in metabolites in plasma of mixed hyperlipidemia model rats were analyzed by non-targeted metabolomics. The mechanism of the hypolipidemic effect of Massa Medicata Fermentata was analyzed through metabolite pathway enrichment. The results showed that compared with the model group, the Massa Medicata Fermentata administration group, especially the high-dose group, could significantly reduce the content of total cholesterol(TC), triglyceride(TG), and low-density lipoprotein cholesterol(LDL-c)(P<0.05 or P<0.01), and liver HE staining revealed that the number of adipocytes in the high-dose group was reduced to some extent. The potential biomarkers obtained by non-targeted metabolomics screening included glycerol 3-phosphate, sphingomyelin, sphingosine 1-phosphate, and deoxyuridine, which were mainly involved in the sphingolipid metabolism process, glycerophospholipid metabolism process, glycerol ester metabolism pathway, and pyrimidine metabolism pathway, totaling four possible metabolic pathways related to lipid metabolism. This study provides a reference for an in-depth investigation of the hypolipidemic mechanism of Massa Medicata Fermentata, which is of great significance for further promoting the clinical application of Massa Medicata Fermentata and increasing the indications.

[Non-targeted metabolomics of spleen and liver metabolism in mice treated with Pruni Semen processed with different methods].

Ultra performance liquid chromatography-quadrupole time-of-flight mass spectrometry(UPLC-Q-TOF-MS) was employed to investigate the impacts of Pruni Semen processed with different methods(raw and fried) on the liver and spleen metabolism in mice. A total of 24 male mice were randomly assigned to three groups: raw Pruni Semen group, fried Pruni Semen group, and control(deionized water) group. Mice in the three groups were orally administrated with 0.01 g·mL~(-1) Pruni Semen decoction or deionized water for one week. After that, the liver and spleen tissues were collected, and liquid chromatography-mass spectrometry(LC-MS)-based metabolomic analysis was carried out to investigate the impact of Pruni Semen on the liver and spleen metabolism in mice. Compared with thte control group, the raw Pruni Semen group showed up-regulation of 11 metabolites and down-regulation of 57 metabolites in the spleen(P<0.05), as well as up-regulation of 15 metabolites and down-regulation of 58 metabolites in the liver(P<0.05). The fried Pruni Semen group showed up-regulation of 31 metabolites and down-regulation of 10 metabolites in the spleen(P<0.05), along with up-regulation of 26 metabolites and down-regulation of 61 metabolites in the liver(P<0.05). The differential metabolites identified in the raw Pruni Semen group were primarily associated with alanine, aspartate, and glutamate metabolism, purine metabolism, amino sugar and nucleotide sugar metabolism, and D-glutamine and D-glutamate metabolism. The differential metabolites identified in the fried Pruni Semen group predominantly involved riboflavin metabolism, amino sugar and nucleotide sugar metabolism, purine metabolism, alanine, aspartate, and glutamate metabolism, D-glutamine and D-glutamate metabolism, and glutathione metabolism. The findings suggest that both raw and fried Pruni Semen have the potential to modulate the metabolism of the liver and spleen in mice by influencing the glutamine and glutamate metabolism.

Metabolomics-driven investigation of plant defense response against pest and pathogen attack.

The advancement of metabolomics has assisted in the identification of various bewildering characteristics of the biological system. Metabolomics is a standard approach, facilitating crucial aspects of system biology with absolute quantification of metabolites using minimum samples, based on liquid/gas chromatography, mass spectrometry and nuclear magnetic resonance. The metabolome profiling has narrowed the wide gaps of missing information and has enhanced the understanding of a wide spectrum of plant-environment interactions by highlighting the complex pathways regulating biochemical reactions and cellular physiology under a particular set of conditions. This high throughput technique also plays a prominent role in combined analyses of plant metabolomics and other omics datasets. Plant metabolomics has opened a wide paradigm of opportunities for developing stress-tolerant plants, ensuring better food quality and quantity. However, despite advantageous methods and databases, the technique has a few limitations, such as ineffective 3D capturing of metabolites, low comprehensiveness, and lack of cell-based sampling. In the future, an expansion of plant-pathogen and plant-pest response towards the metabolite architecture is necessary to understand the intricacies of plant defence against invaders, elucidation of metabolic pathway operational during defence and developing a direct correlation between metabolites and biotic stresses. Our aim is to provide an overview of metabolomics and its utilities for the identification of biomarkers or key metabolites associated with biotic stress, devising improved diagnostic methods to efficiently assess pest and pathogen attack and generating improved crop varieties with the help of combined application of analytical and molecular tools.

Associations of birth weight, plasma metabolome in adulthood and risk of type 2 diabetes.

AIMS: We aimed to examine the longitudinal associations of birth weight with plasma metabolites in adulthood, and further quantify the proportions of the links between birth weight and incident adult type 2 diabetes (T2D) that were mediated by plasma metabolites. MATERIALS AND METHODS: A total of 62,033 participants with complete nuclear magnetic resonance metabolomics and birth weight data from the UK Biobank were included in this study. Linear regression was used to assess the associations between birth weight and metabolites. Cox regression was used to estimate hazard ratios for T2D associated with metabolites. We further performed mediation analyses to estimate the extent to which metabolites might mediate the association between birth weight and T2D risk. RESULTS: Low birth weight was associated with the adverse metabolic responses across multiple metabolic pathways, including lipoprotein subclasses, amino acids, fatty acids (FA), and inflammation. Metabolites associated with higher birth weight tended to be associated with a lower risk of T2D (Pearson correlation coefficient: -0.85). A total of 62 metabolites showed statistically significant mediation effects in the protective association of higher birth weight and T2D risk, including large-sized very low-density lipoprotein particles and triglyceride concentrations as well as saturated, and monounsaturated FA and glycoprotein acetyls. CONCLUSIONS: We identified a range of metabolites that reflect the adult metabolic response to birth weight, some of which might lie on the pathway between birth weight and adult T2D risk.

Bayesian functional analysis for untargeted metabolomics data with matching uncertainty and small sample sizes.

Untargeted metabolomics based on liquid chromatography-mass spectrometry technology is quickly gaining widespread application, given its ability to depict the global metabolic pattern in biological samples. However, the data are noisy and plagued by the lack of clear identity of data features measured from samples. Multiple potential matchings exist between data features and known metabolites, while the truth can only be one-to-one matches. Some existing methods attempt to reduce the matching uncertainty, but are far from being able to remove the uncertainty for most features. The existence of the uncertainty causes major difficulty in downstream functional analysis. To address these issues, we develop a novel approach for Bayesian Analysis of Untargeted Metabolomics data (BAUM) to integrate previously separate tasks into a single framework, including matching uncertainty inference, metabolite selection and functional analysis. By incorporating the knowledge graph between variables and using relatively simple assumptions, BAUM can analyze datasets with small sample sizes. By allowing different confidence levels of feature-metabolite matching, the method is applicable to datasets in which feature identities are partially known. Simulation studies demonstrate that, compared with other existing methods, BAUM achieves better accuracy in selecting important metabolites that tend to be functionally consistent and assigning confidence scores to feature-metabolite matches. We analyze a COVID-19 metabolomics dataset and a mouse brain metabolomics dataset using BAUM. Even with a very small sample size of 16 mice per group, BAUM is robust and stable. It finds pathways that conform to existing knowledge, as well as novel pathways that are biologically plausible.

An untargeted metabolomics approach to study changes of the medium during human cornea culture.

INTRODUCTION: Two main approaches (organ culture and hypothermia) for the preservation and storage of human donor corneas are globally adopted for corneal preservation before the transplant. Hypothermia is a hypothermic storage which slows down cellular metabolism while organ culture, a corneal culture performed at 28-37 °C, maintains an active corneal metabolism. Researchers, till now, have just studied the impact of organ culture on human cornea after manipulating and disrupting tissues. OBJECTIVES: The aim of the current work was to optimize an analytical procedure which can be useful for discovering biomarkers capable of predicting tissue health status. For the first time, this research proposed a preliminary metabolomics study on medium for organ culture without manipulating and disrupting the valuable human tissues which could be still used for transplantation. METHODS: In particular, the present research proposed a method for investigating changes in the medium, over a storage period of 20 days, in presence and absence of a human donor cornea. An untargeted metabolomics approach using UHPLC-QTOF was developed to deeply investigate the differences on metabolites and metabolic pathways and the influence of the presence of the cornea inside the medium. RESULTS: Differences in the expression of some compounds emerged from this preliminary metabolomics approach, in particular in medium maintained for 10 and 20 days in presence but also in the absence of cornea. A total of 173 metabolites have been annotated and 36 pathways were enriched by pathway analysis. CONCLUSION: The results revealed a valuable untargeted metabolomics approach which can be applied in organ culture metabolomics.

Study on the Neuroprotective Effects of Eight Iridoid Components Using Cell Metabolomics.

Iridoid components have been reported to have significant neuroprotective effects. However, it is not yet clear whether the efficacy and mechanisms of iridoid components with similar structures are also similar. This study aimed to compare the neuroprotective effects and mechanisms of eight iridoid components (catalpol (CAT), genipin (GE), geniposide (GEN), geniposidic acid (GPA), aucubin (AU), ajugol (AJU), rehmannioside C (RC), and rehmannioside D (RD)) based on corticosterone (CORT)-induced injury in PC12 cells. PC12 cells were randomly divided into a normal control group (NC), model group (M), positive drug group (FLX), and eight iridoid administration groups. Firstly, PC12 cells were induced with CORT to simulate neuronal injury. Then, the MTT method and flow cytometry were applied to evaluate the protective effects of eight iridoid components on PC12 cell damage. Thirdly, a cell metabolomics study based on ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry (UPLC-Q/TOF-MS) was performed to explore changes in relevant biomarkers and metabolic pathways following the intervention of administration. The MTT assay and flow cytometry analysis showed that the eight iridoid components can improve cell viability, inhibit cell apoptosis, reduce intracellular ROS levels, and elevate MMP levels. In the PCA score plots, the sample points of the treatment groups showed a trend towards approaching the NC group. Among them, AU, AJU, and RC had a weaker effect. There were 38 metabolites (19 metabolites each in positive and negative ion modes, respectively) identified as potential biomarkers during the experiment, among which 23 metabolites were common biomarkers of the eight iridoid groups. Pathway enrichment analysis revealed that the eight iridoid components regulated the metabolism mainly in relation to D-glutamine and D-glutamate metabolism, arginine biosynthesis, the TCA cycle, purine metabolism, and glutathione metabolism. In conclusion, the eight iridoid components could reverse an imbalanced metabolic state by regulating amino acid neurotransmitters, interfering with amino acid metabolism and energy metabolism, and harmonizing the level of oxidized substances to exhibit neuroprotective effects.

Dietary Methionine Restriction Improves Gut Health and Alters the Plasma Metabolomic Profile in Rats by Modulating the Composition of the Gut Microbiota.

Dietary methionine restriction (MetR) offers an integrated set of beneficial health effects, including delaying aging, extending health span, preventing fat accumulation, and reducing oxidative stress. This study aimed to investigate whether MetR exerts entero-protective effects by modulating intestinal flora, and the effect of MetR on plasma metabolites in rats. Rats were fed diets containing 0.86% methionine (CON group) and 0.17% methionine (MetR group) for 6 weeks. Several indicators of inflammation, gut microbiota, plasma metabolites, and intestinal barrier function were measured. 16S rRNA gene sequencing was used to analyze the cecal microbiota. The MetR diet reduced the plasma and colonic inflammatory factor levels. The MetR diet significantly improved intestinal barrier function by increasing the mRNA expression of tight junction proteins, such as zonula occludens (ZO)-1, claudin-3, and claudin-5. In addition, MetR significantly increased the levels of short-chain fatty acids (SCFAs) by increasing the abundance of SCFAs-producing Erysipclotxichaceae and Clostridium_sensu_stricto_1 and decreasing the abundance of pro-inflammatory bacteria Proteobacteria and Escherichia-Shigella. Furthermore, MetR reduced the plasma levels of taurochenodeoxycholate-7-sulfate, taurocholic acid, and tauro-ursodeoxycholic acid. Correlation analysis identified that colonic acetate, total colonic SCFAs, 8-acetylegelolide, collettiside I, 6-methyladenine, and cholic acid glucuronide showed a significant positive correlation with Clostridium_sensu_stricto_1 abundance but a significant negative correlation with Escherichia-Shigella and Enterococcus abundance. MetR improved gut health and altered the plasma metabolic profile by regulating the gut microbiota in rats.

Metabolic Profiling as an Approach to Differentiate T-Cell Acute Lymphoblastic Leukemia Cell Lines Belonging to the Same Genetic Subgroup.

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive tumor mainly affecting children and adolescents. It is driven by multiple genetic mutations that together define the leukemic phenotype. Interestingly, based on genetic alterations and/or deregulated expression, at least six genetic subgroups have been recognized. The TAL/LMO subgroup is one of the most represented genetic subgroups, characterizing 30-45% of pediatric T-ALL cases. The study of lipid and metabolic profiles is increasingly recognized as a valuable tool for comprehending the development and progression of tumors. In this study, metabolic and lipidomic analysis via LC/MS have been carried out on four T-ALL cell lines belonging to the TAL/LMO subgroup (Jurkat, Molt-4, Molt-16, and CCRF-CEM) to identify new potential metabolic biomarkers and to provide a subclassification of T-ALL cell lines belonging to the same subgroup. A total of 343 metabolites were annotated, including 126 polar metabolites and 217 lipid molecules. The statistical analysis, for both metabolic and lipid profiles, shows significant differences and similarities among the four cell lines. The Molt-4 cell line is the most distant cell line and CCRF-CEM shows a high activity in specific pathways when compared to the other cell lines, while Molt-16 and Jurkat show a similar metabolic profile. Additionally, this study highlighted the pathways that differ in each cell line and the possible enzymes involved using bioinformatic tools, capable of predicting the pathways involved by studying the differences in the metabolic profiles. This experiment offers an approach to differentiate T-ALL cell lines and could open the way to verify and confirm the obtained results directly in patients.

Plasma-Induced Changes in the Metabolome Following Vistula Tart Cherry Consumption.

Evidence suggests that tart cherry (TC) supplementation has beneficial effects on health indices and recovery following strenuous exercise. However, little is known about the mechanisms and how TC might modulate the human metabolome. The aim of this study was to evaluate the influence of an acute high- and low-dose of Vistula TC supplementation on the metabolomic profile in humans. In a randomised, double-blind, placebo controlled, cross-over design, 12 healthy participants (nine male and three female; mean ± SD age, stature, and mass were 29 ± 7 years old, 1.75 ± 0.1 m, and 77.3 ± 10.5 kg, respectively) visited the laboratory on three separate occasions (high dose; HI, low dose; LO, or placebo), separated by at least seven days. After an overnight fast, a baseline venous blood sample was taken, followed by consumption of a standardised breakfast and dose conditions (HI, LO, or placebo). Subsequent blood draws were taken 1, 2, 3, 5, and 8 h post consumption. Following sample preparation, an untargeted metabolomics approach was adopted, and the extracts analysed by LCMS/MS. When all time points were collated, a principal component analysis showed a significant difference between the conditions (p < 0.05), such that the placebo trial had homogeneity, and HI showed greater heterogeneity. In a sub-group analysis, cyanidine-3-O-glucoside (C3G), cyanidine-3-O-rutinoside (C3R), and vanillic acid (VA) were detected in plasma and showed significant differences (p < 0.05) following acute consumption of Vistula TC, compared to the placebo group. These results provide evidence that phenolics are bioavailable in plasma and induce shifts in the metabolome following acute Vistula TC consumption. These data could be used to inform future intervention studies where changes in physiological outcomes could be influenced by metabolomic shifts following acute supplementation.

Assessment of estrogenic potential from exudates of microcystin-producing and non-microcystin-producing Microcystis by metabolomics, machine learning and E-screen assay.

Cyanobacterial blooms, often dominated by Microcystis aeruginosa, are capable of producing estrogenic effects. It is important to identify specific estrogenic compounds produced by cyanobacteria, though this can prove challenging owing to the complexity of exudate mixtures. In this study, we used untargeted metabolomics to compare components of exudates from microcystin-producing and non-microcystin-producing M. aeruginosa strains that differed with respect to their ability to produce microcystins, and across two growth phases. We identified 416 chemicals and found that the two strains produced similar components, mainly organoheterocyclic compounds (20.2%), organic acids and derivatives (17.3%), phenylpropanoids and polyketides (12.7%), benzenoids (12.0%), lipids and lipid-like molecules (11.5%), and organic oxygen compounds (10.1%). We then predicted estrogenic compounds from this group using random forest machine learning. Six compounds (daidzin, biochanin A, phenylethylamine, rhein, o-Cresol, and arbutin) belonging to phenylpropanoids and polyketides (3), benzenoids (2), and organic oxygen compound (1) were tested and exhibited estrogenic potency based upon the E-screen assay. This study confirmed that both Microcystis strains produce exudates that contain compounds with estrogenic properties, a growing concern in cyanobacteria management.