Pancreatic adenocarcinomas (PAs) have very poor prognoses even when surgery is possible. Currently, there are no tissular biomarkers to predict long-term survival in patients with PA. The aims of this study were to (1) describe the metabolome of pancreatic parenchyma (PP) and PA, (2) determine the impact of neoadjuvant chemotherapy on PP and PA, and (3) find tissue metabolic biomarkers associated with long-term survivors, using metabolomics analysis.
The metabolic phenotype varies widely due to external factors such as diet and gut microbiome composition, among others. Despite these temporal fluctuations, urine metabolite profiling studies have suggested that there are highly individual phenotypes that persist over extended periods of time. This hypothesis was tested by analyzing the exhaled breath of a group of subjects during nine days by mass spectrometry. Consistent with previous metabolomic studies based on urine, we conclude that individual signatures of breath composition exist. The confirmation of the existence of stable and specific breathprints may contribute to strengthen the inclusion of breath as a biofluid of choice in metabolomic studies. In addition, the fact that the method is rapid and totally non-invasive, yet individualized profiles can be tracked, makes it an appealing approach.
ABSTRACT Microorganisms grow under a remarkable range of extreme conditions. Environmental transcriptomic and proteomic studies have highlighted metabolic pathways active in extremophilic communities. However, metabolites directly linked to their physiology are less well defined because metabolomics methods lag behind other omics technologies due to a wide range of experimental complexities often associated with the environmental matrix. We identified key metabolites associated with acidophilic and metal-tolerant microorganisms using stable isotope labeling coupled with untargeted, high-resolution mass spectrometry. We observed >3,500 metabolic features in biofilms growing in pH ~0.9 acid mine drainage solutions containing millimolar concentrations of iron, sulfate, zinc, copper, and arsenic. Stable isotope labeling improved chemical formula prediction by >50% for larger metabolites (>250 atomic mass units), many of which were unrepresented in metabolic databases and may represent novel compounds. Taurine and hydroxyectoine were identified and likely provide protection from osmotic stress in the biofilms. Community genomic, transcriptomic, and proteomic data implicate fungi in taurine metabolism. Leptospirillum group II bacteria decrease production of ectoine and hydroxyectoine as biofilms mature, suggesting that biofilm structure provides some resistance to high metal and proton concentrations. The combination of taurine, ectoine, and hydroxyectoine may also constitute a sulfur, nitrogen, and carbon currency in the communities. IMPORTANCE Microbial communities are central to many critical global processes and yet remain enigmatic largely due to their complex and distributed metabolic interactions. Metabolomics has the possibility of providing mechanistic insights into the function and ecology of microbial communities. However, our limited knowledge of microbial metabolites, the difficulty of identifying metabolites from complex samples, and the inability to link metabolites directly to community members have proven to be major limitations in developing advances in systems interactions. Here, we show that combining stable-isotope-enabled metabolomics with genomics, transcriptomics, and proteomics can illuminate the ecology of microorganisms at the community scale.
- Metabolomics : Official journal of the Metabolomic Society
- Published about 6 years ago
An overview of the metabolic diversity in ripe fruits of a collection of 32 diverse pepper (Capsicum sp.) accessions was obtained by measuring the composition of both semi-polar and volatile metabolites in fruit pericarp, using untargeted LC-MS and headspace GC-MS platforms, respectively. Accessions represented C. annuum, C. chinense, C. frutescens and C. baccatum species, which were selected based on variation in morphological characters, pungency and geographic origin. Genotypic analysis using AFLP markers confirmed the phylogenetic clustering of accessions according to Capsicum species and separated C. baccatum from the C. annuum-C. chinense-C. frutescens complex. Species-specific clustering was also observed when accessions were grouped based on their semi-polar metabolite profiles. In total 88 semi-polar metabolites could be putatively identified. A large proportion of these metabolites represented conjugates of the main pepper flavonoids (quercetin, apigenin and luteolin) decorated with different sugar groups at different positions along the aglycone. In addition, a large group of acyclic diterpenoid glycosides, called capsianosides, was found to be highly abundant in all C. annuum genotypes. In contrast to the variation in semi-polar metabolites, the variation in volatiles corresponded well to the differences in pungency between the accessions. This was particularly true for branched fatty acid esters present in pungent accessions, which may reflect the activity through the acyl branch of the metabolic pathway leading to capsaicinoids. In addition, large genetic variation was observed for many well-established pepper aroma compounds. These profiling data can be used in breeding programs aimed at improving metabolite-based quality traits such as flavour and health-related metabolites in pepper fruits. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-012-0432-6) contains supplementary material, which is available to authorized users.
Novel techniques for high-throughput steady-state metabolomic profiling yield information about changes of nearly thousands of metabolites. Such metabolomic profiles, when analyzed together with transcriptional profiles, can reveal novel insights about underlying biological processes. While a number of conceptual approaches have been developed for data integration, easily accessible tools for integrated analysis of mammalian steady-state metabolomic and transcriptional data are lacking. Here we present GAM (‘genes and metabolites’): a web-service for integrated network analysis of transcriptional and steady-state metabolomic data focused on identification of the most changing metabolic subnetworks between two conditions of interest. In the web-service, we have pre-assembled metabolic networks for humans, mice, Arabidopsis and yeast and adapted exact solvers for an optimal subgraph search to work in the context of these metabolic networks. The output is the most regulated metabolic subnetwork of size controlled by false discovery rate parameters. The subnetworks are then visualized online and also can be downloaded in Cytoscape format for subsequent processing. The web-service is available at:https://artyomovlab.wustl.edu/shiny/gam/.
Berries are associated with health benefits. Little is known about the effect of baseline metabolome on the overall metabolic responses to berry intake.
Illuminating a plant’s tissue-specific metabolic diversity using computational metabolomics and information theory
- Proceedings of the National Academy of Sciences of the United States of America
- Published over 2 years ago
Secondary metabolite diversity is considered an important fitness determinant for plants' biotic and abiotic interactions in nature. This diversity can be examined in two dimensions. The first one considers metabolite diversity across plant species. A second way of looking at this diversity is by considering the tissue-specific localization of pathways underlying secondary metabolism within a plant. Although these cross-tissue metabolite variations are increasingly regarded as important readouts of tissue-level gene function and regulatory processes, they have rarely been comprehensively explored by nontargeted metabolomics. As such, important questions have remained superficially addressed. For instance, which tissues exhibit prevalent signatures of metabolic specialization? Reciprocally, which metabolites contribute most to this tissue specialization in contrast to those metabolites exhibiting housekeeping characteristics? Here, we explore tissue-level metabolic specialization in Nicotiana attenuata, an ecological model with rich secondary metabolism, by combining tissue-wide nontargeted mass spectral data acquisition, information theory analysis, and tandem MS (MS/MS) molecular networks. This analysis was conducted for two different methanolic extracts of 14 tissues and deconvoluted 895 nonredundant MS/MS spectra. Using information theory analysis, anthers were found to harbor the most specialized metabolome, and most unique metabolites of anthers and other tissues were annotated through MS/MS molecular networks. Tissue-metabolite association maps were used to predict tissue-specific gene functions. Predictions for the function of two UDP-glycosyltransferases in flavonoid metabolism were confirmed by virus-induced gene silencing. The present workflow allows biologists to amortize the vast amount of data produced by modern MS instrumentation in their quest to understand gene function.
Despite recent advances in understanding mechanism of toxicity, the development of biomarkers (biochemicals that vary significantly with exposure to chemicals) for pesticides and environmental contaminants exposure is still a challenging task. Carbofuran is one of the most commonly used pesticides in agriculture and said to be most toxic carbamate pesticide. It is necessary to identify the biochemicals that can vary significantly after carbofuran exposure on earthworms which will help to assess the soil ecotoxicity. Initially, we have optimized the extraction conditions which are suitable for high-throughput gas chromatography mass spectrometry (GC-MS) based metabolomics for the tissue of earthworm, Metaphire posthuma. Upon evaluation of five different extraction solvent systems, 80% methanol was found to have good extraction efficiency based on the yields of metabolites, multivariate analysis, total number of peaks and reproducibility of metabolites. Later the toxicity evaluation was performed to characterize the tissue specific metabolomic perturbation of earthworm, Metaphire posthuma after exposure to carbofuran at three different concentration levels (0.15, 0.3 and 0.6 mg/kg of soil). Seventeen metabolites, contributing to the best classification performance of highest dose dependent carbofuran exposed earthworms from healthy controls were identified. This study suggests that GC-MS based metabolomic approach was precise and sensitive to measure the earthworm responses to carbofuran exposure in soil, and can be used as a promising tool for environmental eco-toxicological studies.
The páramo ecosystem has the highest rate of diversification across plant lineages on earth, of which the genus Espeletia (Asteraceae) is a prime example. The current distribution and molecular phylogeny of Espeletia suggest the influence of Andean geography and past climatic fluctuations on the diversification of this genus. However, molecular markers have failed to reveal subtle biogeographical trends in Espeletia diversification, and metabolomic evidence for allopatric segregation in plants has never been reported. Here, we present for the first time a metabolomics approach based on liquid chromatography-mass spectrometry for revealing subtle biogeographical trends in Espeletia diversification. We demonstrate that Espeletia lineages can be distinguished by means of different metabolic fingerprints correlated to the country of origin on a global scale and to the páramo massif on a regional scale. Distinctive patterns in the accumulation of secondary metabolites according to the main diversification centers of Espeletia are also identified and a comprehensive phytochemical characterization is reported. These findings demonstrate that a variation in the metabolic fingerprints of Espeletia lineages followed the biogeography of this genus, suggesting that our untargeted metabolomics approach can be potentially used as a model to understand the biogeographic history of additional plant groups in the páramo ecosystem.
Coptis chinensis Franch has been used in Traditional Chinese Medicine (TCM) for treating infectious and inflammatory diseases for over two thousand years. Berberine (BN), an isoquinoline alkaloid, is the main component of Coptis chinensis. The pharmacological basis for its therapeutic effects, which include hepatoprotective effects on liver injuries, has been studied intensively, yet the therapy of liver injuries and underlying mechanism remain unclear. We investigated the detoxification mechanism of Coptis chinensis and berberine using metabolomics of urine and serum in the present study. After the treatment with Coptis chinensis and berberine, compared with the cinnabar group, Coptis chinensis and berberine can regulate the concentration of the endogenous metabolites. PLS-DA score plots demonstrated that the urine and serum metabolic profiles in rats of the Coptis chinensis and berberine groups were similar those of the control group, yet remarkably apart from the cinnabar group. The mechanism may be related to the endogenous metabolites including energy metabolism, amino acid metabolism and metabolism of intestinal flora in rats. Meanwhile, liver and kidney histopathology examinations and serum clinical chemistry analysis verified the experimental results of metabonomics.