Project description:The rapidly increasing number of engineered nanoparticles (NPs), and products containing NPs, raises concerns for human exposure and safety. With this increasing, and ever changing, catalogue of NPs it is becoming more difficult to adequately assess the toxic potential of new materials in a timely fashion. It is therefore important to develop methods which can provide high-throughput screening of biological responses. The use of omics technologies, including metabolomics, can play a vital role in this process by providing relatively fast, comprehensive, and cost-effective assessment of cellular responses. These techniques thus provide the opportunity to identify specific toxicity pathways and to generate hypotheses on how to reduce or abolish toxicity.We have used untargeted metabolome analysis to determine differentially expressed metabolites in human lung epithelial cells (A549) exposed to copper oxide nanoparticles (CuO NPs). Toxicity hypotheses were then generated based on the affected pathways, and critically tested using more conventional biochemical and cellular assays. CuO NPs induced regulation of metabolites involved in oxidative stress, hypertonic stress, and apoptosis. The involvement of oxidative stress was clarified more easily than apoptosis, which involved control experiments to confirm specific metabolites that could be used as standard markers for apoptosis; based on this we tentatively propose methylnicotinamide as a generic metabolic marker for apoptosis.Our findings are well aligned with the current literature on CuO NP toxicity. We thus believe that untargeted metabolomics profiling is a suitable tool for NP toxicity screening and hypothesis generation.
Project description:Untargeted metabolomics is frequently performed on human fecal samples in conjunction with sequencing to unravel the gut microbiome functionality. As sample collection efforts are rapidly expanding, with individuals often collecting specimens at home, metabolomics experiments should adapt to accommodate the safety and needs of bulk off-site collections and improve high throughput. Here, we show that a 95% ethanol, safe to be shipped and handled, extraction part of the Matrix Method pipeline recovers comparable amounts of metabolites as a validated 50% methanol extraction, preserving metabolic profile differences between investigated subjects. Additionally, we show that the fecal metabolome remains relatively stable when stored in 95% ethanol for up to 1 week at room temperature. Finally, we suggest a metabolomics data analysis workflow based on robust centered log ratio transformation, which removes the variance introduced by possible different sample weights and concentrations, allowing for reliable and integration-ready untargeted metabolomics experiments in gut microbiome research.
Project description:Ascidians and their associated microbiota are prolific producers of bioactive marine natural products. Recent culture-independent studies have revealed that the tunic of the solitary ascidian Cionaintestinalis (sea vase) is colonized by a diverse bacterial community, however, the biotechnological potential of this community has remained largely unexplored. In this study, we aimed at isolating the culturable microbiota associated with the tunic of C.intestinalis collected from the North and Baltic Seas, to investigate their antimicrobial and anticancer activities, and to gain first insights into their metabolite repertoire. The tunic of the sea vase was found to harbor a rich microbial community, from which 89 bacterial and 22 fungal strains were isolated. The diversity of the tunic-associated microbiota differed from that of the ambient seawater samples, but also between sampling sites. Fungi were isolated for the first time from the tunic of Ciona. The proportion of bioactive extracts was high, since 45% of the microbial extracts inhibited the growth of human pathogenic bacteria, fungi or cancer cell lines. In a subsequent bioactivity- and metabolite profiling-based approach, seven microbial extracts were prioritized for in-depth chemical investigations. Untargeted metabolomics analyses of the selected extracts by a UPLC-MS/MS-based molecular networking approach revealed a vast chemical diversity with compounds assigned to 22 natural product families, plus many metabolites that remained unidentified. This initial study indicates that bacteria and fungi associated with the tunic of C.intestinalis represent an untapped source of putatively new marine natural products with pharmacological relevance.
Project description:It is widely accepted that the commensal gut microbiota contributes to the health and well-being of its host. The solitary tunicate Ciona intestinalis emerges as a model organism for studying host-microbe interactions taking place in the gut, however, the potential of its gut-associated microbiota for marine biodiscovery remains unexploited. In this study, we set out to investigate the diversity, chemical space, and pharmacological potential of the gut-associated microbiota of C. intestinalis collected from the Baltic and North Seas. In a culture-based approach, we isolated 61 bacterial and 40 fungal strains affiliated to 33 different microbial genera, indicating a rich and diverse gut microbiota dominated by Gammaproteobacteria. In vitro screening of the crude microbial extracts indicated their antibacterial (64% of extracts), anticancer (22%), and/or antifungal (11%) potential. Nine microbial crude extracts were prioritized for in-depth metabolome mining by a bioactivity- and chemical diversity-based selection procedure. UPLC-MS/MS-based metabolomics combining automated (feature-based molecular networking and in silico dereplication) and manual approaches significantly improved the annotation rates. A high chemical diversity was detected where peptides and polyketides were the predominant classes. Many compounds remained unknown, including two putatively novel lipopeptides produced by a Trichoderma sp. strain. This is the first study assessing the chemical and pharmacological profile of the cultivable gut microbiota of C. intestinalis.
Project description:Oncogene-associated metabolic signatures in prostate cancer, identified by an integrative analysis of cultured cells and murine and human tumors, suggest that AKT activation results in a glycolytic phenotype whereas MYC induces aberrant lipid metabolism. Heterogeneity in human tumors makes this simplistic interpretation obtained from experimental models more challenging. Metabolic reprogramming as a function of distinct molecular aberrations has major diagnostic and therapeutic implications.
Project description:Evidence is accumulating that the establishment of the gut microbiome in early life influences the development of atopic eczema. In this longitudinal study, we used integrated multi-omics analyses to infer functional mechanisms by which the microbiome modulates atopic eczema risk. We measured the functionality of the gut microbiome and metabolome of 63 infants between ages 3 weeks and 12 months with well-defined eczema cases and controls in a sub-cohort from the Growing Up in Singapore Toward healthy Outcomes (GUSTO) mother-offspring cohort. At 3 weeks, the microbiome and metabolome of allergen-sensitized atopic eczema infants were characterized by an enrichment of Escherichia coli and Klebsiella pneumoniae, associated with increased stool D-glucose concentration and increased gene expression of associated virulence factors. A delayed colonization by beneficial Bacteroides fragilis and subsequent delayed accumulation of butyrate and propionate producers after 3 months was also observed. Here, we describe an aberrant developmental trajectory of the gut microbiome and stool metabolome in allergen sensitized atopic eczema infants. The infographic describes an impaired developmental trajectory of the gut microbiome and metabolome in allergen-sensitized atopic eczema (AE) infants and infer its contribution in modulating allergy risk in the Singaporean mother-offspring GUSTO cohort. The key microbial signature of AE is characterized by (1) an enrichment of Escherichia coli and Klebsiella pneumoniae which are associated with accumulation of pre-glycolysis intermediates (D-glucose) via the trehalose metabolic pathway, increased gene expression of associated virulence factors (invasin, adhesin, flagellin and lipopolysaccharides) by utilizing ATP from oxidative phosphorylation and delayed production of butyrate and propionate, (2) depletion of Bacteroides fragilis which resulted in lower expression of immunostimulatory bacterial cell envelope structure and folate (vitamin B9) biosynthesis pathway, and (3) accompanied depletion of bacterial groups with the ability to derive butyrate and propionate through direct or indirect pathways which collectively resulted in reduced glycolysis, butyrate and propionate biosynthesis.
Project description:MotivationCarbohydrate Active enzyme (CAZyme) families, encoded by human gut microflora, play a crucial role in breakdown of complex dietary carbohydrates into components that can be absorbed by our intestinal epithelium. Since nutritional wellbeing of an individual is dependent on the nutrient harvesting capability of the gut microbiome, it is important to understand how CAZyme repertoire in the gut is influenced by factors like age, geography and food habits.ResultsThis study reports a comprehensive in-silico analysis of CAZyme profiles in the gut microbiomes of 448 individuals belonging to different geographies, using similarity searches of the corresponding gut metagenomic contigs against the carbohydrate active enzymes database. The study identifies a core group of 89 CAZyme families that are present across 85% of the gut microbiomes. The study detects several geography/age-specific trends in gut CAZyme repertoires of the individuals. Notably, a group of CAZymes having a positive correlation with BMI has been identified. Further this group of BMI-associated CAZymes is observed to be specifically abundant in the Firmicutes phyla. One of the major findings from this study is identification of three distinct groups of individuals, referred to as 'CAZotypes', having similar CAZyme profiles. Distinct taxonomic drivers for these CAZotypes as well as the probable dietary basis for such trends have also been elucidated. The results of this study provide a global view of CAZyme profiles across individuals of various geographies and age-groups. These results reiterate the need of a more precise understanding of the role of carbohydrate active enzymes in human nutrition.
Project description:Coal workers' pneumoconiosis (CWP) is a severe occupational disease resulting from prolonged exposure to coal dust. However, its pathogenesis remains elusive, compounded by a lack of early detection markers and effective treatments. Although the impact of gut microbiota on lung diseases is acknowledged, its specific role in CWP is unclear. This study aims to explore changes in the gut microbiome and metabolome in CWP, while also assessing the correlation between gut microbes and alterations in lung function. Fecal specimens from 43 CWP patients and 48 dust-exposed workers (DEW) were examined using 16S rRNA gene sequencing for microbiota and liquid chromatography-mass spectrometry for metabolite profiling. We observed similar gut microbial α-diversity but significant differences in flora composition (β-diversity) between patients with CWP and the DEW group. After adjusting for age using multifactorial linear regression analysis (MaAsLin2), the distinct gut microbiome profile in CWP patients revealed an increased presence of pro-inflammatory microorganisms such as Klebsiella and Haemophilus. Furthermore, in CWP patients, alterations in gut microbiota-particularly reduced α-diversity and changes in microbial composition-were significantly correlated with impaired pulmonary function, a relationship not observed in DEW. This underscores the specific impact of gut microbiota on pulmonary health in individuals with CWP. Metabolomic analysis of fecal samples from CWP patients and DEW identified 218 differential metabolites between the two groups, with a predominant increase in metabolites in CWP patients, suggesting enhanced metabolic activity in CWP. Key altered metabolites included various lipids, amino acids, and organic compounds, with silibinin emerging as a potential biomarker. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis linked these metabolites to pathways relevant to the development of pulmonary fibrosis. Additionally, studies on the interaction between microbiota and metabolites showed positive correlations between certain bacteria and increased metabolites in CWP, further elucidating the complex interplay in this disease state. Our findings suggest a potential contributory role of gut microbiota in CWP pathogenesis through metabolic regulation, with implications for diagnostic biomarkers and understanding disease mechanisms, warranting further molecular investigation.ImportanceThe findings have significant implications for the early diagnosis and treatment of coal workers' pneumoconiosis, highlighting the potential of gut microbiota as diagnostic biomarkers. They pave the way for new research into gut microbiota-based therapeutic strategies, potentially focusing on modifying gut microbiota to mitigate disease progression.
Project description:Liquid chromatography-high-resolution mass spectrometry (LC-MS)-based metabolomics aims to identify and quantify all metabolites, but most LC-MS peaks remain unidentified. Here we present a global network optimization approach, NetID, to annotate untargeted LC-MS metabolomics data. The approach aims to generate, for all experimentally observed ion peaks, annotations that match the measured masses, retention times and (when available) tandem mass spectrometry fragmentation patterns. Peaks are connected based on mass differences reflecting adduction, fragmentation, isotopes, or feasible biochemical transformations. Global optimization generates a single network linking most observed ion peaks, enhances peak assignment accuracy, and produces chemically informative peak-peak relationships, including for peaks lacking tandem mass spectrometry spectra. Applying this approach to yeast and mouse data, we identified five previously unrecognized metabolites (thiamine derivatives and N-glucosyl-taurine). Isotope tracer studies indicate active flux through these metabolites. Thus, NetID applies existing metabolomic knowledge and global optimization to substantially improve annotation coverage and accuracy in untargeted metabolomics datasets, facilitating metabolite discovery.
Project description:Studies of isotopically labeled compounds have been fundamental to understanding metabolic pathways and fluxes. They have traditionally, however, been used in conjunction with targeted analyses that identify and quantify a limited number of labeled downstream metabolites. Here we describe an alternative workflow that leverages recent advances in untargeted metabolomic technologies to track the fates of isotopically labeled metabolites in a global, unbiased manner. This untargeted approach can be applied to discover novel biochemical pathways and characterize changes in the fates of labeled metabolites as a function of altered biological conditions such as disease. To facilitate the data analysis, we introduce X(13)CMS, an extension of the widely used mass spectrometry-based metabolomic software package XCMS. X(13)CMS uses the XCMS platform to detect metabolite peaks and perform retention-time alignment in liquid chromatography/mass spectrometry (LC/MS) data. With the use of the XCMS output, the program then identifies isotopologue groups that correspond to isotopically labeled compounds. The retrieval of these groups is done without any a priori knowledge besides the following input parameters: (i) the mass difference between the unlabeled and labeled isotopes, (ii) the mass accuracy of the instrument used in the analysis, and (iii) the estimated retention-time reproducibility of the chromatographic method. Despite its name, X(13)CMS can be used to track any isotopic label. Additionally, it detects differential labeling patterns in biological samples collected from parallel control and experimental conditions. We validated the ability of X(13)CMS to accurately retrieve labeled metabolites from complex biological matrices both with targeted LC/MS/MS analysis of a subset of the hits identified by the program and with labeled standards spiked into cell extracts. We demonstrate the full functionality of X(13)CMS with an analysis of cultured rat astrocytes treated with uniformly labeled (U-)(13)C-glucose during lipopolysaccharide (LPS) challenge. Our results show that out of 223 isotopologue groups enriched from U-(13)C-glucose, 95 have statistically significant differential labeling patterns in astrocytes challenged with LPS compared to unchallenged control cells. Only two of these groups overlap with the 32 differentially regulated peaks identified by XCMS, indicating that X(13)CMS uncovers different and complementary information from untargeted metabolomic studies. Like XCMS, X(13)CMS is implemented in R. It is available from our laboratory website at http://pattilab.wustl.edu/x13cms.php .