Seasonal variations and sensory profiles of oolong tea: Insights from metabolic analysis of Tieguanyin cultivar.

The impact of seasonal variations on the quality of oolong tea products remains a subject of ongoing exploration. This study delves into the intricate relationships between seasonality, metabolites, and sensory characteristics in finished oolong tea products. Metabolomic data from 266 Tieguanyin oolong tea products harvested in both spring and autumn, along with corresponding sensory evaluations, were acquired. Using OPLS-DA and PLS-DA models with UPLC-QToF/MS data, our findings showed that seasonal effects were notably more pronounced in light-scented Tieguanyin products (lightly-roasted) compared to strong-scented products (moderately-roasted). Furthermore, over half of the identified key seasonal discriminant metabolites happened to be crucial for determining the sensory grade. The study marks the first-time recognition of triterpene saponins as critical factors in determining both the harvest season and the sensory grade of oolong tea. These insights deepen our understanding of the interplays between seasonal variations, metabolites, and sensory attributes in oolong tea products.

Genus-specific secondary metabolome in Allokutzneria and Kibdelosporangium.

Rare actinomycete genera are highly recognized as a promising source of structurally diverse and bioactive natural products. Among these genera, Allokutzneria and Kibdelosporangium are two phylogenetically closely related and have been reported to encode some valuable biosynthetic enzymes and secondary metabolites. However, there is currently no relevant systematic research available to outline the linkage of genomic and metabolomics for specific secondary metabolites in these two promising genera. In this study, we first investigated the genus-specific secondary metabolic potential in Allokutzneria and Kibdelosporangium by comparing the diversity and novelty of their secondary metabolite biosynthetic gene clusters (BGCs). The specific secondary metabolites produced by two representative strains of these genera were comprehensively investigated using untargeted metabolomics techniques. The findings unveiled that the majority (95.4%) of the gene cluster families (GCFs) encoded by Allokutzneria and Kibdelosporangium were genus-specific, including NRPS GCFs encoding siderophores. The untargeted metabolomics analysis revealed that the metabolic profiles of two representative strains exhibit extensive specificity, with the culture medium having a big impact on the metabolic profiles. Besides, an MS-cluster featuring a series of hydroxamate-type siderophores was identified from Allokutzneria albata JCM 9917, with two of them, including a novel one (N-deoxy arthrobactin A), being experimentally validated. The present study offers valuable insights for the targeted discovery of genus-specific natural products from microorganisms.

Enhancing mass spectrometry interpretability by ComDim-ICA multi-block analysis: Geographical and varietal traceability of Brazilian Coffea canephora.

Mass spectrometry can gain analytical interpretability by studying complementarity and synergy between the data obtained by the same technique. To explore its potential in an untargeted metabolomic application, the objective of this work was to obtain organic and aqueous coffee extracts of three coffee Canephora groups produced in Brazil with distinctive aspects: geographical origin and botanical variety. Aqueous and organic extracts of roasted coffee beans were analyzed by direct infusion electrospray ionization mass spectrometry. Due to the large number of samples, the injector of the liquid chromatography system was used to automate the analysis. The column was removed, and a peak tube was added to connect the system directly to the mass spectrometer to inject both polar and nonpolar fractions of the coffee extracts individually. The technique provided characteristic fingerprinting mass spectra that not only allowed for differentiation of geographical origins but also between robusta and conilon botanical varieties. The mass spectra of the organic and water extracts represented two separate data blocks to be analyzed by the ComDim-ICA multi-block data analysis method. While the classical ComDim is based on applying PCA to the iteratively reweighted concatenated matrices, in the ComDim-ICA, the factorization is done using independent components analysis, which promotes specific improvements since it is based on extracting components that are statistically independent of one another. The results highlighted by ComDim-ICA show that both water and organic extracts contributed with important ions to the characterization of the coffee composition. However, the results revealed a high variability of metabolomic composition within each botanical variety (Robusta Amazônico and Conilon Capixaba) and geographical provenance (Rondônia indigenous-1, Rondônia non-indigenous-2 and Espírito Santo-3). Even so, water mass spectra differentiated the botanical variety Conilon from Robusta based on significant ions related to trigonelline, caffeic acid, caffeoylquinic acid, and methylpyridinium; both water and organic mass spectra differentiated Rondônia indigenous from Rondônia non-indigenous and Espírito Santo Conilon based on significant ions related to benzoic acid, pentose, coumaric acid, caffeine in the organic extract and malonic acid, pentose, caffeoylquinic acid, methyl pyridinium, caffeine, and sucrose present in the water extract. With the proposed approach acquiring ion fingerprints of different coffee extracts and their subsequent analysis by ComDim-ICA, new complementary chemical aspects of Brazilian Coffea canephora were put in evidence.

HS-SPME-GC-MS untargeted metabolomics reveals key volatile compound changes during Liupao tea fermentation.

This study used headspace solid-phase microextraction-gas chromatography-mass spectrometry and multivariate statistical analysis to comprehensively analyze the volatile components in Liupao tea samples throughout fermentation. In total, 1009 volatile organic compounds were detected and identified, including terpenoids, heterocyclic compounds, esters, ketones, hydrocarbons, alcohols, aromatics, and acids. Principal component and hierarchical cluster analyses, characterize the volatile components of Liupao tea samples were characterized at various fermentation stages. Orthogonal partial least squares discriminant analysis identified 248 differentiating compounds (VIP ≥ 1, P < 0.05, and |Log2FC| ≥ 1.0) during fermentation. K-means clustering analysis showed that 11 metabolites increased significantly throughout the fermentation process, whereas 31 metabolites decreased continuously. Annotation of these differential compounds revealed significant changes in sensory flavor characteristics in "green, sweet, fruity, floral, and woody" flavors. The results demonstrated significant variations in the volatile components of Liupao tea fermentation, along with notable changes in flavor characteristics.

Adaptive physiological and metabolic alterations in Staphylococcus aureus evolution under vancomycin exposure.

Staphylococcus aureus can develop antibiotic resistance and evade immune responses, causing infections in different body sites. However, the metabolic changes underlying this process are poorly understood. A variant strain, C1V, was derived from the parental strain C1 by exposing it to increasing concentrations of vancomycin in vitro. C1V exhibited a vancomycin-intermediate phenotype and physiological changes compared to C1. It showed higher survival rates than C1 when phagocytosed by Raw264.7 cells. Metabolomics analysis identified significant metabolic differences pre- and post-induction (C1 + SC1 vs. C1V + SC1V: 201 metabolites) as well as pre- and post-phagocytosis (C1 vs. SC1: 50 metabolites; C1V vs. SC1V: 95 metabolites). The variant strain had distinct morphological characteristics, decreased adhesion ability, impaired virulence, and enhanced resistance to phagocytosis compared to the parental strain. Differential metabolites may contribute to S. aureus ' resistance to antibiotics and phagocytosis, offering insights into potential strategies for altering vancomycin nonsusceptibility and enhancing phagocyte killing by manipulating bacterial metabolism.

Probiotic Lactobacillus plantarum 299v supplementation in patients with major depression in a double-blind, randomized, placebo-controlled trial: A metabolomics study.

BACKGROUND: Understanding the multifactorial nature of major depressive disorder (MDD) is crucial for tailoring treatments. However, the complex interplay of various factors underlying the development and progression of MDD poses significant challenges. Our previous study demonstrated improvements in cognitive functions in MDD patients undergoing treatment with selective serotonin reuptake inhibitors (SSRIs) supplemented with Lactobacillus plantarum 299v (LP299v). METHODS: To elucidate the biochemical mechanisms underlying cognitive functions improvements, we explored underlying metabolic changes. We employed multi-platform metabolomics, including LC-QTOF-MS and CE-TOF-MS profiling, alongside chiral LC-QqQ-MS analysis for amino acids. RESULTS: Supplementation of SSRI treatment with LP299v intensified the reduction of long-chain acylcarnitines, potentially indicating improved mitochondrial function. LP299v supplementation reduced N-acyl taurines more than four times compared to the placebo, suggesting a substantial impact on restoring biochemical balance. The LP299v-supplemented group showed increased levels of oxidized glycerophosphocholine (oxPC). Additionally, LP299v supplementation led to higher levels of sphingomyelins, L-histidine, D-valine, and p-cresol. LIMITATIONS: This exploratory study suggests potential metabolic pathways influenced by LP299v supplementation. However, the need for further research hinders the ability to draw definitive conclusions. CONCLUSIONS: Observed metabolic changes were linked to mitochondrial dysfunction, inflammation, oxidative stress, and gut microbiota disruption. Despite the subtle nature of this alterations, our research successfully detected these differences and connected them to the metabolic disruptions associated with MDD. Our findings emphasise the intricate relationship between metabolism, gut microbiota, and mental health prompting further research into the mechanisms of action of probiotics in MDD treatment.

Synergistic effect and mechanism of monoacylglycerol lipase inhibitor and Icaritin in the treatment of ulcerative colitis.

Ulcerative colitis (UC) is a chronic, relapsing nonspecific intestinal inflammatory disease. It is difficult for a single drug to treat UC effectively and maintain long-term efficacy. There is an urgent need to find new drugs and treatment strategies. MAGL11 is a new kind of single acylglycerol lipase (MAGL) inhibitor. Icaritin (Y003) is the major metabolite of icariin in vivo. Several studies have confirmed the role of MAGL inhibitors and icariin in anti-inflammatory and regulation of intestinal stability. Therefore, this study adopted a new strategy of combining MAGL inhibitor with Icaritin to further explore the role and mechanism of drugs in the treatment of UC. Enzyme-linked immunosorbent assay (ELISA), hematoxylin-eosin staining (HE), immunohistochemical (IHC) and Western blot were used to detect the synergistic protective effects of MAGL11 and Y003 on intestinal pathological injury, intestinal mucosal permeability and inflammation in UC mice. 16S rDNA sequencing was used to detect the synergistic effect of MAGL11 and Y003 on gut microbiota. The effects of MAGL11 and Y003 combined therapy on serum and fecal metabolism of UC mice were analyzed by untargeted metabolomics. Proteomics method was applied to investigate the molecular mechanisms underlying MAGL11 and Y003 synergy in the treatment of UC. The results showed that MAGL11 and Y003 could synergistically improve the clinical symptoms, reduce intestinal inflammation and pathological damage, and improve intestinal mucosal permeability in UC mice. The mechanism study found that MAGL11 and Y003 could synergistically inhibit Toll-like receptors 4 (TLR4) / Myeloid differentiation primary response gene (Myd88)/Nuclear factor kappa-B (NF-κB) pathway and further regulate gut microbiota imbalance and metabolic disorders to treat UC.

Untargeted metabolomics analysis of the urinary metabolic signature of acute and chronic gout.

BACKGROUND: Gout is a common kind of inflammatory arthritis with metabolic disorders. However, the detailed pathogenesis of gout is complex and not fully clear. We investigated the urine metabolic profiling of gout patients by ultra-performance liquid chromatograph quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). METHOD: Urine metabolites were extracted from 26 acute gout patients, 31 chronic gout patients, and 32 healthy controls. Metabolite extracts were analyzed by UPLC-Q-TOF-MS for untargeted metabolomics. The peak area of creatinine was used to correct the content variations of urine samples for the semi-quantitative analysis. The value of variable importance in the projection (VIP) was obtained through the orthogonal partial least squares-discrimination analysis (OPLS-DA), and several differential metabolites were screened out. RESULTS: The potential metabolic markers of gout in different stages were found based on the t-test. Finally, 18 different metabolites were identified through Human Metabolome Database (HMDB) and Targeted-MS/MS. The receiver operating characteristic (ROC) curve results revealed that all the screened biomarkers exerted high accuracy and diagnostic value. Pathway analysis indicated that the significantly different metabolites were mainly involved in purine metabolism and amino acid metabolism. CONCLUSION: The identified potential biomarkers are mainly involved in purine metabolism and amino acid metabolism, which leads us to further explore the pathogenesis of gout. This will lead us to further explore the pathogenesis of gout and provide the basis and ideas for the prevention and treatment of gout.

Untargeted metabolomics combined with chemometrics reveals distinct metabolic profiles across two sparkling cider fermentation stages.

This study aimed to examine the metabolic profiles of Saccharomyces cerevisiae yeasts (WLS21 and Y41) in two phases of sparkling cider making (normal and pressure fermentation) by combining untargeted metabolomic with chemometrics. The results showed that of the 634 nonvolatile metabolites identified using LC-MS and 83 volatile metabolites identified by GC-MS, the differential metabolites were 226 and 54, respectively. Metabolic pathway and correlation analyses showed that aspartic acid, phenylalanine and tyrosine, glutamic acid and purine metabolism were associated with flavor formation. The pressure fermentation process increased apigenin, naringenin, toxifolin, pyridoxine and thiamine contents in the final cider. These findings provide useful information and new research ideas for the formation of flavor in sparkling cider and the regulation of phenolic and vitamin production by microbial stress fermentation.

Single-colony MALDI mass spectrometry imaging reveals spatial differences in metabolite abundance between natural and cultured Trichodesmium morphotypes.

Trichodesmium, a globally significant N2-fixing marine cyanobacterium, forms extensive surface blooms in nutrient-poor ocean regions. These blooms consist of a dynamic assemblage of Trichodesmium species that form distinct colony morphotypes and are inhabited by diverse microorganisms. Trichodesmium colony morphotypes vary in ecological niche, nutrient uptake, and organic molecule release, differentially impacting ocean carbon and nitrogen biogeochemical cycles. Here, we assessed the poorly studied spatial abundance of metabolites within and between three morphologically distinct Trichodesmium colonies collected from the Red Sea. We also compared these results with two morphotypes of the cultivable Trichodesmium strain IMS101. Using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) coupled with liquid extraction surface analysis (LESA) tandem mass spectrometry (MS2), we identified and localized a wide range of small metabolites associated with single-colony Trichodesmium morphotypes. Our untargeted MALDI-MSI approach revealed 80 unique features (metabolites) shared between Trichodesmium morphotypes. Discrimination analysis showed spatial variations in 57 shared metabolites, accounting for 62% of the observed variation between morphotypes. The greatest variations in metabolite abundance were observed between the cultured morphotypes compared to the natural colony morphotypes, suggesting substantial differences in metabolite production between the cultivable strain IMS101 and the naturally occurring colony morphotypes that the cultivable strain is meant to represent. This study highlights the variations in metabolite abundance between natural and cultured Trichodesmium morphotypes and provides valuable insights into metabolites common to morphologically distinct Trichodesmium colonies, offering a foundation for future targeted metabolomic investigations.IMPORTANCEThis work demonstrates that the application of spatial mass spectrometry imaging at single-colony resolution can successfully resolve metabolite differences between natural and cultured Trichodesmium morphotypes, shedding light on their distinct biochemical profiles. Understanding the morphological differences between Trichodesmium colonies is crucial because they impact nutrient uptake, organic molecule production, and carbon and nitrogen export, and subsequently influence ocean biogeochemical cycles. As such, our study serves as an important initial assessment of metabolite differences between distinct Trichodesmium colony types, identifying features that can serve as ideal candidates for future targeted metabolomic studies.

Non-targeted metabolomics reveals the characteristics of the unique bitterness substances in quinoa.

Bitterness is a key factor that affects the consumption of quinoa products, even if they are nutritious. In this study, a non-targeted metabolomics approach based on UHPLC-Orbitrap-MS was applied to comprehensively profile the characteristic metabolites of twenty-two quinoas. A total of twenty key metabolites were identified correlated with bitterness, among which, fifteen were triterpenoid saponins. In addition, these metabolites bind to the active site of the human bitter taste receptor and are the main compounds that produce the bitter taste of quinoa. Our results contribute to a deeper understanding of the origin of quinoa bitterness and provide directions for optimizing its flavor to improve market acceptance.

Untargeted Metabolomics and Soil Community Metagenomics Analyses Combined with Machine Learning Evaluation Uncover Geographic Differences in Ginseng from Different Locations.

Panax ginseng C.A. Meyer, known as the "King of Herbs," has been used as a nutritional supplement for both food and medicine with the functions of relieving fatigue and improving immunity for thousands of years in China. In agricultural planting, soil environments of different geographical origins lead to obvious differences in the quality of ginseng, but the potential mechanism of the differences remains unclear. In this study, 20 key differential metabolites, including ginsenoside Rb1, glucose 6-phosphate, etc., were found in ginseng from 10 locations in China using an ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS)-untargeted metabolomics approach. The soil properties were analyzed and combined with metagenomics technology to explore the possible relationships among microbial elements in planting soil. Through Spearman correlation analysis, it was found that the top 10 microbial colonies with the highest abundance in the soil were significantly correlated with key metabolites. In addition, the relationship model established by the random forest algorithm and the quantitative relationship between soil microbial abundance and ginseng metabolites were successfully predicted. The XGboost model was used to determine 20(R)-ginseng Rg2 and 2'(R)-ginseng Rg3 as feature labeled metabolites, and the optimal ginseng production area was discovered. These results prove that the accumulation of metabolites in ginseng was influenced by microorganisms in the planting soil, which led to geographical differences in ginseng quality.

Untargeted metabolomics profiling of Morus alba twigs extract and antibacterial activity of pure metabolites.

Plant natural products offer promise in combating multi-drug resistance by acting as antibacterial agents through various mechanisms. A metabolomic-guided phytochemical investigation, based on a LC-HRMS/MS and Molecular Networking combined approach, was carried out on an extract of M. alba L. (mulberry) twigs, a common of byproduct of mulberry utilization. Molecular Networking uncovered different clusters of prenylated polyphenols, glycosylated phenolic compounds, and Diels-Alder dimers, steering the phytochemical profiling of this extract. This led to the swift annotation and subsequent isolation of 17 secondary metabolites including stilbenoids, flavonoids, and flavanones. Isolated metabolites were tested for their antimicrobial activity against Staphylococcus species. The most active compound resulted to be kuwanon C, exhibiting a MIC value of 8 µg/mL against the methicillin resistant S. aureus (MRSA) strain and a biofilm producer strain of S. epidermidis. We also observed an interaction between 4 µg/mL of kuwanon C in combination with low oxacillin dosage against the MRSA. Thanks to the high chemical structure similarity of isolated metabolites, structure-activity relationships of these versatile scaffolds have been postulated.

Analysis of Metabolic Profiles and Antioxidant Activity of Chinese Cordyceps, Ophiocordyceps sinensis, and Paecilomyces hepiali Based on Untargeted Metabolomics.

Chinese cordyceps (GL) is a traditional medicinal fungus, with Ophiocordyceps sinensis (O. sinensis, BL) and Paecilomyces hepiali (P. hepiali, JSB) being fungi isolated from wild Chinese cordyceps. These three species share similar chemical composition and pharmacological effects. Existing studies have primarily compared the metabolites of Chinese cordyceps and O. sinensis, overlooking the assessment of antioxidant capacity in Chinese cordyceps, P. hepiali, and O. sinensis. In this study, LC-MS/MS was employed to analyze metabolites in GL, JSB, and BL. Utilizing principal component analysis (PCA), supervised orthogonal partial least squares discriminant analysis (OPLS-DA), and hierarchical cluster analysis (HCA), it was observed that the majority of differential metabolites (DMs) primarily accumulated in organic acids and derivatives, lipids and lipid-like molecules, and organoheterocyclic compounds. Antioxidant activity analysis indicated that GL exhibited the higher 2,2-diphenyl-1-picrylhydrazyl radical scavenging ability (DPPH•, scavenging rate is 81.87 ± 0.97%), hydroxyl free radical scavenging capacity (•OH, scavenging rate is 98.10 ± 0.60%), and superoxide anion radical scavenging capacity (O2•-, scavenging rate is 69.74 ± 4.36%), while JSB demonstrated the higher FRAP total antioxidant capacity of 8.26 µmol Trolox/g (p < 0.05). Correlation analysis revealed a positive correlation between DMs (fatty acyls and amino acids) and DPPH•, FRAP, •OH, and O2•- (p < 0.05). Additionally, glycerophospholipid DMs were found to be positively correlated with FRAP (p < 0.05). Through KEGG pathway analysis, it was determined that the accumulation of DMs in pathways such as cutin, suberine and wax biosynthesis has a higher impact on influencing the antioxidant activity of the samples. These results shed light on the antioxidant capacity and metabolic characteristics of Chinese cordyceps and its substitutes and offer valuable insights into how different DMs impact the strength of antioxidant activity, aiding in the advancement and application of Chinese cordyceps and its substitutes.

Effects of Dietary Zinc Chloride and Zinc Sulfate on Life History Performance and Hemolymph Metabolism of Spodoptera litura (Lepidoptera: Noctuidae).

Zinc is an essential micronutrient crucial in various biological processes of an organism. However, the effects of zinc vary depending on its chemical form. Therefore, the aim of this study was to conduct a comparative analysis of the life history performances and hemolymph metabolism of Spodoptera litura exposed to different concentrations of dietary zinc chloride (ZnCl2) and zinc sulfate (ZnSO4), utilizing two-sex life tables and untargeted metabolomics. The preadult survival rate of S. litura significantly decreased, while the preadult developmental period of S. litura was prolonged as the dietary ZnCl2 concentration increased. However, the fecundity of S. litura at 50 mg/kg dietary ZnCl2 was significantly increased. The intrinsic rate of increase (r) and the finite rate of increase (λ) in S. litura in the control group (CK, no exogenous ZnCl2 or ZnSO4 added) and with 50 mg/kg dietary ZnCl2 were significantly higher than those at 100 mg/kg, 200 mg/kg, and 300 mg/kg. Dietary ZnSO4 exerts a devastating effect on the survival of S. litura. Even at the lowest concentration of 50 mg/kg dietary ZnSO4, only 1% of S. litura could complete the entire life cycle. Furthermore, as the dietary ZnSO4 concentration increased, the developmental stage achievable by the S. litura larvae declined. High-throughput untargeted metabolomics demonstrated that both 100 mg/kg dietary ZnCl2 and ZnSO4 decreased the hemolymph vitamins levels and increased the vitamin C content, thereby helping S. litura larvae to counteract the stress induced by ZnCl2 and ZnSO4. Simultaneously, dietary ZnCl2 obstructed the chitin synthesis pathway in the hemolymph of S. litura, thus extending the developmental period of S. litura larvae. These results indicate that low concentrations of Zn2+ positively impact populations of S. litura, but the effectiveness and toxicity of Zn depend on its chemical form and concentration.

Sulfated Bile Acids in Serum as Potential Biomarkers of Disease Severity and Mortality in COVID-19.

The fight against coronavirus disease 2019 (COVID-19) continues. Since the pandemic's onset, several biomarkers have been proposed to assess the diagnosis and prognosis of this disease. This research aimed to identify potential disease severity biomarkers in serum samples of patients with COVID-19 during the disease course. Data were collected using untargeted and targeted mass spectrometry methods. The results were interpreted by performing univariate and multivariate analyses. Important metabolite classes were identified by qualitative untargeted metabolomics in 15 serum samples from survivors of COVID-19. Quantitative targeted metabolomics on a larger patient cohort including 15 non-survivors confirmed serum 3-sulfate bile acids (i.e. GLCA-3S) were significantly increased in non-survivors compared to survivors during the early disease stage (p-value < 0.0001). Notably, it was associated with a higher risk of mortality (odds ratio of 26). A principal component analysis showed the ability to discriminate between survivors and non-survivors using the BA concentrations. Furthermore, increased BA-S is highly correlated with known parameters altered in severe clinical conditions.

Role of human plasma metabolites in prediabetes and type 2 diabetes from the IMI-DIRECT study.

AIMS/HYPOTHESIS: Type 2 diabetes is a chronic condition that is caused by hyperglycaemia. Our aim was to characterise the metabolomics to find their association with the glycaemic spectrum and find a causal relationship between metabolites and type 2 diabetes. METHODS: As part of the Innovative Medicines Initiative - Diabetes Research on Patient Stratification (IMI-DIRECT) consortium, 3000 plasma samples were measured with the Biocrates AbsoluteIDQ p150 Kit and Metabolon analytics. A total of 911 metabolites (132 targeted metabolomics, 779 untargeted metabolomics) passed the quality control. Multivariable linear and logistic regression analysis estimates were calculated from the concentration/peak areas of each metabolite as an explanatory variable and the glycaemic status as a dependent variable. This analysis was adjusted for age, sex, BMI, study centre in the basic model, and additionally for alcohol, smoking, BP, fasting HDL-cholesterol and fasting triacylglycerol in the full model. Statistical significance was Bonferroni corrected throughout. Beyond associations, we investigated the mediation effect and causal effects for which causal mediation test and two-sample Mendelian randomisation (2SMR) methods were used, respectively. RESULTS: In the targeted metabolomics, we observed four (15), 34 (99) and 50 (108) metabolites (number of metabolites observed in untargeted metabolomics appear in parentheses) that were significantly different when comparing normal glucose regulation vs impaired glucose regulation/prediabetes, normal glucose regulation vs type 2 diabetes, and impaired glucose regulation vs type 2 diabetes, respectively. Significant metabolites were mainly branched-chain amino acids (BCAAs), with some derivatised BCAAs, lipids, xenobiotics and a few unknowns. Metabolites such as lysophosphatidylcholine a C17:0, sum of hexoses, amino acids from BCAA metabolism (including leucine, isoleucine, valine, N-lactoylvaline, N-lactoylleucine and formiminoglutamate) and lactate, as well as an unknown metabolite (X-24295), were associated with HbA1c progression rate and were significant mediators of type 2 diabetes from baseline to 18 and 48 months of follow-up. 2SMR was used to estimate the causal effect of an exposure on an outcome using summary statistics from UK Biobank genome-wide association studies. We found that type 2 diabetes had a causal effect on the levels of three metabolites (hexose, glutamate and caproate [fatty acid (FA) 6:0]), whereas lipids such as specific phosphatidylcholines (PCs) (namely PC aa C36:2, PC aa C36:5, PC ae C36:3 and PC ae C34:3) as well as the two n-3 fatty acids stearidonate (18:4n3) and docosapentaenoate (22:5n3) potentially had a causal role in the development of type 2 diabetes. CONCLUSIONS/INTERPRETATION: Our findings identify known BCAAs and lipids, along with novel N-lactoyl-amino acid metabolites, significantly associated with prediabetes and diabetes, that mediate the effect of diabetes from baseline to follow-up (18 and 48 months). Causal inference using genetic variants shows the role of lipid metabolism and n-3 fatty acids as being causal for metabolite-to-type 2 diabetes whereas the sum of hexoses is causal for type 2 diabetes-to-metabolite. Identified metabolite markers are useful for stratifying individuals based on their risk progression and should enable targeted interventions.

Untargeted Liquid Chromatography-High-Resolution Mass Spectrometry Metabolomic Investigation Reveals Altered Lipid Content in Leishmania infantum Lacking Lipid Droplet Protein Kinase.

Leishmaniasis is a complex disease caused by different species of Leishmania. To date, no vaccine for humans or ideal therapy has been developed owing to the limited efficacy and toxicity of available drugs, as well as the emergence of resistant strains. Therefore, it is necessary to identify novel therapeutic targets and discover therapeutic options for leishmaniasis. In this study, we evaluated the impact of deleting the lipid droplet protein kinase (LDK) enzyme in Leishmania infantum using an untargeted metabolomics approach performed using liquid chromatography and high-resolution mass spectrometry. LDK is involved in lipid droplet biogenesis in trypanosomatids. Thirty-nine lipid metabolites altered in the stationary and logarithmic growth phases were noted and classified into five classes: (1) sterols, (2) fatty and conjugated acids, (3) ceramides, (4) glycerophosphocholine and its derivatives, and (5) glycerophosphoethanolamine and its derivatives. Our data demonstrated that glycerophosphocholine and its derivatives were the most affected after LDK deletion, suggesting that the absence of this enzyme promotes the remodeling of lipid composition in L. infantum, thus contributing to a better understanding of the function of LDK in this parasite.

Combined LC-MS/MS feature grouping, statistical prioritization, and interactive networking in msFeaST.

SUMMARY: Computational metabolomics workflows have revolutionized the untargeted metabolomics field. However, the organization and prioritization of metabolite features remains a laborious process. Organizing metabolomics data is often done through mass fragmentation-based spectral similarity grouping, resulting in feature sets that also represent an intuitive and scientifically meaningful first stage of analysis in untargeted metabolomics. Exploiting such feature sets, feature-set testing has emerged as an approach that is widely used in genomics and targeted metabolomics pathway enrichment analyses. It allows for formally combining groupings with statistical testing into more meaningful pathway enrichment conclusions. Here, we present msFeaST (mass spectral Feature Set Testing), a feature-set testing and visualization workflow for LC-MS/MS untargeted metabolomics data. Feature-set testing involves statistically assessing differential abundance patterns for groups of features across experimental conditions. We developed msFeaST to make use of spectral similarity-based feature groupings generated using k-medoids clustering, where the resulting clusters serve as a proxy for grouping structurally similar features with potential biosynthesis pathway relationships. Spectral clustering done in this way allows for feature group-wise statistical testing using the globaltest package, which provides high power to detect small concordant effects via joint modeling and reduced multiplicity adjustment penalties. Hence, msFeaST provides interactive integration of the semi-quantitative experimental information with mass-spectral structural similarity information, enhancing the prioritization of features and feature sets during exploratory data analysis. AVAILABILITY AND IMPLEMENTATION: The msFeaST workflow is freely available through https://github.com/kevinmildau/msFeaST and built to work on MacOS and Linux systems. SUPPLEMENTARY INFORMATION: Supplementary information is available at Bioinformatics online.

Orientia tsutsugamushi infection reduces host gluconeogenic but not glycolytic substrates.

Orientia tsutsugamushi a causal agent of scrub typhus, is an obligate intracellular bacterium that, akin to other rickettsiae, is dependent on host cell-derived nutrients for survival and thus pathogenesis. Based on limited experimental evidence and genome-based in silico predictions, O. tsutsugamushi is hypothesized to parasitize host central carbon metabolism (CCM). Here, we (re-)evaluated O. tsutsugamushi dependency on host cell CCM as initiated by glucose and glutamine. Orientia infection had no effect on host glucose and glutamine consumption or lactate accumulation, indicating no change in overall flux through CCM. However, host cell mitochondrial activity and ATP levels were reduced during infection and correspond with lower intracellular glutamine and glutamate pools. To further probe the essentiality of host CCM in O. tsutsugamushi proliferation, we developed a minimal medium for host cell cultivation and paired it with chemical inhibitors to restrict the intermediates and processes related to glucose and glutamine metabolism. These conditions failed to negatively impact O. tsutsugamushi intracellular growth, suggesting the bacterium is adept at scavenging from host CCM. Accordingly, untargeted metabolomics was utilized to evaluate minor changes in host CCM metabolic intermediates across O. tsutsugamushi infection and revealed that pathogen proliferation corresponds with reductions in critical CCM building blocks, including amino acids and TCA cycle intermediates, as well as increases in lipid catabolism. This study directly correlates O. tsutsugamushi proliferation to alterations in host CCM and identifies metabolic intermediates that are likely critical for pathogen fitness.IMPORTANCEObligate intracellular bacterial pathogens have evolved strategies to reside and proliferate within the eukaryotic intracellular environment. At the crux of this parasitism is the balance between host and pathogen metabolic requirements. The physiological basis driving O. tsutsugamushi dependency on its mammalian host remains undefined. By evaluating alterations in host metabolism during O. tsutsugamushi proliferation, we discovered that bacterial growth is independent of the host's nutritional environment but appears dependent on host gluconeogenic substrates, including amino acids. Given that O. tsutsugamushi replication is essential for its virulence, this study provides experimental evidence for the first time in the post-genomic era of metabolic intermediates potentially parasitized by a scrub typhus agent.