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Metabolites, Volume 9, Issue 8 (August 2019)

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Cover Story (view full-size image) Enniatins (ENNs) are fungal secondary metabolites that frequently occur in grain in temperate [...] Read more.
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Open AccessArticle
Far-Red Light Acclimation for Improved Mass Cultivation of Cyanobacteria
Metabolites 2019, 9(8), 170; https://doi.org/10.3390/metabo9080170 - 19 Aug 2019
Viewed by 574
Abstract
Improving mass cultivation of cyanobacteria is a goal for industrial biotechnology. In this study, the mass cultivation of the thermophilic cyanobacterium Chlorogloeopsis fritschii was assessed for biomass production under light-emitting diode white light (LEDWL), far-red light (FRL), and combined white light and far-red [...] Read more.
Improving mass cultivation of cyanobacteria is a goal for industrial biotechnology. In this study, the mass cultivation of the thermophilic cyanobacterium Chlorogloeopsis fritschii was assessed for biomass production under light-emitting diode white light (LEDWL), far-red light (FRL), and combined white light and far-red light (WLFRL) adaptation. The induction of chl f was confirmed at 24 h after the transfer of culture from LEDWL to FRL. Using combined light (WLFRL), chl f, a, and d, maintained the same level of concentration in comparison to FRL conditions. However, phycocyanin and xanthophylls (echinone, caloxanthin, myxoxanthin, nostoxanthin) concentration increased 2.7–4.7 times compared to LEDWL conditions. The productivity of culture was double under WLFRL compared with LEDWL conditions. No significant changes in lipid, protein, and carbohydrate concentrations were found in the two different light conditions. The results are important for informing on optimum biomass cultivation of this species for biomass production and bioactive product development. Full article
(This article belongs to the Special Issue Metabolites from Phototrophic Prokaryotes and Algae Volume 2)
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Open AccessReview
Advances of Metabolomics in Fungal Pathogen–Plant Interactions
Metabolites 2019, 9(8), 169; https://doi.org/10.3390/metabo9080169 - 15 Aug 2019
Cited by 1 | Viewed by 548
Abstract
Plant disease caused by fungus is one of the major threats to global food security, and understanding fungus–plant interactions is important for plant disease control. Research devoted to revealing the mechanisms of fungal pathogen–plant interactions has been conducted using genomics, transcriptomics, proteomics, and [...] Read more.
Plant disease caused by fungus is one of the major threats to global food security, and understanding fungus–plant interactions is important for plant disease control. Research devoted to revealing the mechanisms of fungal pathogen–plant interactions has been conducted using genomics, transcriptomics, proteomics, and metabolomics. Metabolomics research based on mass spectrometric techniques is an important part of systems biology. In the past decade, the emerging field of metabolomics in plant pathogenic fungi has received wide attention. It not only provides a qualitative and quantitative approach for determining the pathogenesis of pathogenic fungi but also helps to elucidate the defense mechanisms of their host plants. This review focuses on the methods and progress of metabolomics research in fungal pathogen–plant interactions. In addition, the prospects and challenges of metabolomics research in plant pathogenic fungi and their hosts are addressed. Full article
(This article belongs to the Special Issue Fungal and Mycotoxin Metabolism)
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Open AccessArticle
NMR Based Metabolomic Analysis of Health Promoting Phytochemicals in Lentils
Metabolites 2019, 9(8), 168; https://doi.org/10.3390/metabo9080168 - 13 Aug 2019
Viewed by 510
Abstract
Lentils are a high-protein plant food and a valuable source of human nutrition, particularly in the Indian subcontinent. However, beyond sustenance, there is evidence that the consumption of lentils (and legumes in general) is associated with decreased risk of diseases, such as diabetes [...] Read more.
Lentils are a high-protein plant food and a valuable source of human nutrition, particularly in the Indian subcontinent. However, beyond sustenance, there is evidence that the consumption of lentils (and legumes in general) is associated with decreased risk of diseases, such as diabetes and cardiovascular disease. Lentils contain health-promoting phytochemicals, such as trigonelline and various polyphenolics. Fourteen lentil genotypes were grown at three locations to explore the variation in phytochemical composition in hulls and cotyledons. Significant differences were measured between genotypes and environments, with some genotypes more affected by environment than others. However, there was a strong genetic effect which indicated that future breeding programs could breed for lentils that product more of these health-promoting phytochemicals. Full article
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Open AccessArticle
Polar Lipids in Starch-Rich Commodities to be Analyzed with LC-MS-Based Metabolomics—Optimization of Ionization Parameters and High-Throughput Extraction Protocols
Metabolites 2019, 9(8), 167; https://doi.org/10.3390/metabo9080167 - 12 Aug 2019
Viewed by 562
Abstract
Metabolomics-based approaches are still receiving growing attention with regard to food authenticity testing. Such studies require enormous sample numbers with negligible experimental or analytical variations to obtain statistically reliable results. In this context, an extraction protocol in line with optimized ionization parameters was [...] Read more.
Metabolomics-based approaches are still receiving growing attention with regard to food authenticity testing. Such studies require enormous sample numbers with negligible experimental or analytical variations to obtain statistically reliable results. In this context, an extraction protocol in line with optimized ionization parameters was developed in consideration of potential starch-derived matrix effects focusing on the polar lipids of potatoes. Therefore, well-known extractions (Bligh and Dyer, Folch, Matyash, and a n-hexane-based procedure) were compared in a non-targeted and a targeted approach regarding the extractability of their lipids such as phosphatidylcholines, phosphatidylethanolamines, galacto- and glucocerebrosides, di- and triglycerides, and acylated steryl glucosides. The selected Folch method was also scrutinized in view of its ability to remove the matrix’s starch and consequently improved by substituting trichlormethane with ethyl acetate as a “greener” Folch approach. Moreover, the challenge of starch-derived contamination and imminent ion suppression in the electrospray ionization source (ESI) was addressed by an optimization of ionization parameters varying desolvation settings, removing injection peaks, and increasing the angles and distances of the ESI-device. Long-term stability tests over five days were performed successfully with a combination of appropriate extraction and decreased desolvation settings during ionization. In conclusion, the present methodology provided the basis for on-going large-scale metabolomic studies with respect to the botanical origin of potatoes using UPLC-IMS-QToF (ultra-high performance liquid chromatography ion mobility spectroscopy quadrupole-time of flight mass spectrometer). Full article
(This article belongs to the Special Issue Mass Spectrometry-Based Metabolomics: Challenges and Applications)
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Open AccessArticle
Differential Proteomics Based on TMT and PRM Reveal the Resistance Response of Bambusa pervariabilis × Dendrocalamopisis grandis Induced by AP-Toxin
Metabolites 2019, 9(8), 166; https://doi.org/10.3390/metabo9080166 - 10 Aug 2019
Viewed by 506
Abstract
Bambusa pervariabilis McClure × Dendrocalamopsis grandis (Q.H.Dai & X.l.Tao ex Keng f.) Ohrnb. blight is a widespread and dangerous forest fungus disease, and has been listed as a supplementary object of forest phytosanitary measures. In order to study the control of B. pervariabilis [...] Read more.
Bambusa pervariabilis McClure × Dendrocalamopsis grandis (Q.H.Dai & X.l.Tao ex Keng f.) Ohrnb. blight is a widespread and dangerous forest fungus disease, and has been listed as a supplementary object of forest phytosanitary measures. In order to study the control of B. pervariabilis × D. grandis blight, this experiment was carried out. In this work, a toxin purified from the pathogen Arthrinium phaeospermum (Corda) Elli, which causes blight in B. pervariabilis × D. grandis, with homologous heterogeneity, was used as an inducer to increase resistance to B. pervariabilis × D. grandis. A functional analysis of the differentially expressed proteins after induction using a tandem mass tag labeling technique was combined with mass spectrometry and liquid chromatography mass spectrometry in order to effectively screen for the proteins related to the resistance of B. pervariabilis × D. grandis to blight. After peptide labeling, a total of 3320 unique peptides and 1791 quantitative proteins were obtained by liquid chromatography mass spectrometry analysis. Annotation and enrichment analysis of these peptides and proteins using the Gene ontology and Kyoto Encyclopedia of Genes and Genomes databases with bioinformatics software show that the differentially expressed protein functional annotation items are mainly concentrated on biological processes and cell components. Several pathways that are prominent in the Kyoto Encyclopedia of Genes and Genomes annotation and enrichment include metabolic pathways, the citrate cycle, and phenylpropanoid biosynthesis. In the Protein-protein interaction networks four differentially expressed proteins-sucrose synthase, adenosine triphosphate-citrate synthase beta chain protein 1, peroxidase, and phenylalanine ammonia-lyase significantly interact with multiple proteins and significantly enrich metabolic pathways. To verify the results of tandem mass tag, the candidate proteins were further verified by parallel reaction monitoring, and the results were consistent with the tandem mass tag data analysis results. It is confirmed that the data obtained by tandem mass tag technology are reliable. Therefore, the differentially expressed proteins and signaling pathways discovered here is the primary concern for subsequent disease resistance studies. Full article
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Open AccessArticle
Microbial Transformations of Organically Fermented Foods
Metabolites 2019, 9(8), 165; https://doi.org/10.3390/metabo9080165 - 10 Aug 2019
Viewed by 1067
Abstract
Fermenting food is an ancient form of preservation ingrained many in human societies around the world. Westernized diets have moved away from such practices, but even in these cultures, fermented foods are seeing a resurgent interested due to their believed health benefits. Here, [...] Read more.
Fermenting food is an ancient form of preservation ingrained many in human societies around the world. Westernized diets have moved away from such practices, but even in these cultures, fermented foods are seeing a resurgent interested due to their believed health benefits. Here, we analyze the microbiome and metabolome of organically fermented vegetables, using a salt brine, which is a common ‘at-home’ method of food fermentation. We found that the natural microbial fermentation had a strong effect on the food metabolites, where all four foods (beet, carrot, peppers and radishes) changed through time, with a peak in molecular diversity after 2–3 days and a decrease in diversity during the final stages of the 4-day process. The microbiome of all foods showed a stark transition from one that resembled a soil community to one dominated by Enterobacteriaceae, such as Erwinia spp., within a single day of fermentation and increasing amounts of Lactobacillales through the fermentation process. With particular attention to plant natural products, we observed significant transformations of polyphenols, triterpenoids and anthocyanins, but the degree of this metabolism depended on the food type. Beets, radishes and peppers saw an increase in the abundance of these compounds as the fermentation proceeded, but carrots saw a decrease through time. This study showed that organically fermenting vegetables markedly changed their chemistry and microbiology but resulted in high abundance of Enterobacteriaceae which are not normally considered as probiotics. The release of beneficial plant specialized metabolites was observed, but this depended on the fermented vegetable. Full article
(This article belongs to the Special Issue Mass Spectrometry-Based Metabolomics: Challenges and Applications)
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Open AccessReview
Metabolomics-Based Studies Assessing Exercise-Induced Alterations of the Human Metabolome: A Systematic Review
Metabolites 2019, 9(8), 164; https://doi.org/10.3390/metabo9080164 - 09 Aug 2019
Viewed by 610
Abstract
This systematic review provides a qualitative appraisal of 24 high-quality metabolomics-based studies published over the past decade exploring exercise-induced alterations of the human metabolome. Of these papers, 63% focused on acute metabolite changes following intense and prolonged exercise. The best studies utilized liquid [...] Read more.
This systematic review provides a qualitative appraisal of 24 high-quality metabolomics-based studies published over the past decade exploring exercise-induced alterations of the human metabolome. Of these papers, 63% focused on acute metabolite changes following intense and prolonged exercise. The best studies utilized liquid chromatography mass spectrometry (LC-MS/MS) analytical platforms with large chemical standard libraries and strong, multivariate bioinformatics support. These studies reported large-fold changes in diverse lipid-related metabolites, with more than 100 increasing two-fold or greater within a few hours post-exercise. Metabolite shifts, even after strenuous exercise, typically return to near pre-exercise levels after one day of recovery. Few studies investigated metabolite changes following acute exercise bouts of shorter durations (< 60 min) and workload volumes. Plasma metabolite shifts in these types of studies are modest in comparison. More cross-sectional and exercise training studies are needed to improve scientific understanding of the human system’s response to varying, chronic exercise workloads. The findings derived from this review provide direction for future investigations focused on the body’s metabolome response to exercise. Full article
(This article belongs to the Special Issue Exercise Metabonomics)
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Open AccessArticle
The Biosynthetic Pathway of Major Avenanthramides in Oat
Metabolites 2019, 9(8), 163; https://doi.org/10.3390/metabo9080163 - 07 Aug 2019
Viewed by 485
Abstract
Avenanthramides are a group of N-cinnamoylanthranilic acids, with health-promoting properties mainly found in oat (Avena sativa L.). However, the biosynthetic mechanism for the main three types of avenanthramides (Avn-A, Avn-B and Avn-C) is not completely understood. In the present study, we [...] Read more.
Avenanthramides are a group of N-cinnamoylanthranilic acids, with health-promoting properties mainly found in oat (Avena sativa L.). However, the biosynthetic mechanism for the main three types of avenanthramides (Avn-A, Avn-B and Avn-C) is not completely understood. In the present study, we report molecular identification and functional characterization of three different types of genes from oat encoding 4-coumarate-CoA ligase (4CL), hydroxycinnamoyl-CoA:hydroxyanthranilate N-hydroxycinnamoyl transferase (HHT) and a caffeoyl-CoA O-methyltransferase (CCoAOMT) enzymes, all involved in the biosynthesis of these avenanthramides. In vitro enzymatic assays using the proteins expressed in Escherichia coli showed that oat 4CL could convert p-coumaric acid, caffeic acid and ferulic acid to their CoA thioesters. Oat HHTs were only responsible for the biosynthesis of Avn-A and Avn-C using hydroxyanthranilic acid as an acyl acceptor and p-coumaroyl-CoA and caffeoyl-CoA as an acyl donor, respectively. Avn-B was synthesized by a CCoAOMT enzyme through the methylation of Avn-C. Collectively, these results have elucidated the molecular mechanisms for the biosynthesis of three major avenanthramides in vitro and paved the way for metabolic engineering of the biosynthetic pathway in heterologous systems to produce nutraceutically important compounds and make possible genetic improvement of this nutritional trait in oat through marker-assisted breeding. Full article
(This article belongs to the Special Issue Molecular Nutrition and Metabolism)
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Open AccessArticle
rMSIKeyIon: An Ion Filtering R Package for Untargeted Analysis of Metabolomic LDI-MS Images
Metabolites 2019, 9(8), 162; https://doi.org/10.3390/metabo9080162 - 02 Aug 2019
Viewed by 656
Abstract
Many MALDI-MS imaging experiments make a case versus control studies of different tissue regions in order to highlight significant compounds affected by the variables of study. This is a challenge because the tissue samples to be compared come from different biological entities, and [...] Read more.
Many MALDI-MS imaging experiments make a case versus control studies of different tissue regions in order to highlight significant compounds affected by the variables of study. This is a challenge because the tissue samples to be compared come from different biological entities, and therefore they exhibit high variability. Moreover, the statistical tests available cannot properly compare ion concentrations in two regions of interest (ROIs) within or between images. The high correlation between the ion concentrations due to the existence of different morphological regions in the tissue means that the common statistical tests used in metabolomics experiments cannot be applied. Another difficulty with the reliability of statistical tests is the elevated number of undetected MS ions in a high percentage of pixels. In this study, we report a procedure for discovering the most important ions in the comparison of a pair of ROIs within or between tissue sections. These ROIs were identified by an unsupervised segmentation process, using the popular k-means algorithm. Our ion filtering algorithm aims to find the up or down-regulated ions between two ROIs by using a combination of three parameters: (a) the percentage of pixels in which a particular ion is not detected, (b) the Mann–Whitney U ion concentration test, and (c) the ion concentration fold-change. The undetected MS signals (null peaks) are discarded from the histogram before the calculation of (b) and (c) parameters. With this methodology, we found the important ions between the different segments of a mouse brain tissue sagittal section and determined some lipid compounds (mainly triacylglycerols and phosphatidylcholines) in the liver of mice exposed to thirdhand smoke. Full article
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Open AccessArticle
Comparative Metabolomic Analysis of Rapeseeds from Three Countries
Metabolites 2019, 9(8), 161; https://doi.org/10.3390/metabo9080161 - 01 Aug 2019
Viewed by 587
Abstract
Rapeseed is an important oilseed with proper fatty acid composition and abundant bioactive components. Canada and China are the two major rapeseed-producing countries all over the world. Meanwhile, Canada and Mongolia are major importers of rapeseed due to the great demand for rapeseed [...] Read more.
Rapeseed is an important oilseed with proper fatty acid composition and abundant bioactive components. Canada and China are the two major rapeseed-producing countries all over the world. Meanwhile, Canada and Mongolia are major importers of rapeseed due to the great demand for rapeseed in China. To investigate the metabolites in rapeseeds from three countries, ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS)-based metabolomics was employed to analyze rapeseeds from China, Canada, and Mongolia. As results, 67, 53, and 68 metabolites showed significant differences between Chinese and Canadian, Chinese and Mongolian, and Canadian and Mongolian rapeseeds, respectively. Differential metabolites were mainly distributed in the metabolic pathways including phenylpropanoid biosynthesis, flavone and flavonol biosynthesis, and ubiquinone and other terpenoid-quinone biosynthesis. Among the differential metabolites, contents of sinapate and sinapine were higher in Chinese rapeseeds, while the contents of brassicasterol, stigmasterol, and campestanol were higher in Canadian rapeseeds. These findings might provide insight into the metabolic characteristics of rapeseeds from three countries to guide processing and consumption of the products of rapeseed. Full article
(This article belongs to the Special Issue Plant Metabolomics)
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Open AccessArticle
Improved Small Molecule Identification through Learning Combinations of Kernel Regression Models
Metabolites 2019, 9(8), 160; https://doi.org/10.3390/metabo9080160 - 01 Aug 2019
Viewed by 668
Abstract
In small molecule identification from tandem mass (MS/MS) spectra, input–output kernel regression (IOKR) currently provides the state-of-the-art combination of fast training and prediction and high identification rates. The IOKR approach can be simply understood as predicting a fingerprint vector from the MS/MS spectrum [...] Read more.
In small molecule identification from tandem mass (MS/MS) spectra, input–output kernel regression (IOKR) currently provides the state-of-the-art combination of fast training and prediction and high identification rates. The IOKR approach can be simply understood as predicting a fingerprint vector from the MS/MS spectrum of the unknown molecule, and solving a pre-image problem to find the molecule with the most similar fingerprint. In this paper, we bring forward the following improvements to the IOKR framework: firstly, we formulate the IOKRreverse model that can be understood as mapping molecular structures into the MS/MS feature space and solving a pre-image problem to find the molecule whose predicted spectrum is the closest to the input MS/MS spectrum. Secondly, we introduce an approach to combine several IOKR and IOKRreverse models computed from different input and output kernels, called IOKRfusion. The method is based on minimizing structured Hinge loss of the combined model using a mini-batch stochastic subgradient optimization. Our experiments show a consistent improvement of top-k accuracy both in positive and negative ionization mode data. Full article
(This article belongs to the Special Issue Compound Identification of Small Molecules)
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Open AccessArticle
Serum Adipocyte Fatty Acid-Binding Protein Level is Negatively Associated with Vascular Reactivity Index Measured by Digital Thermal Monitoring in Kidney Transplant Patients
Metabolites 2019, 9(8), 159; https://doi.org/10.3390/metabo9080159 - 31 Jul 2019
Viewed by 484
Abstract
Adipocyte fatty acid-binding protein (A-FABP) is abundantly found in mature adipocytes and is involved in cardiovascular disease. Our aim is to investigate the association between serum A-FABP levels and endothelial function among kidney transplant (KT) patients. Fasting blood samples were obtained from 80 [...] Read more.
Adipocyte fatty acid-binding protein (A-FABP) is abundantly found in mature adipocytes and is involved in cardiovascular disease. Our aim is to investigate the association between serum A-FABP levels and endothelial function among kidney transplant (KT) patients. Fasting blood samples were obtained from 80 KT patients. Serum A-FABP levels were measured using a commercially available enzyme immunoassay kit. Endothelial function and vascular reactivity index (VRI) were measured using digital thermal monitoring test. In this study, VRI < 1.0, VRI 1.0–1.9, and VRI ≥ 2.0 were defined as poor, intermediate, and good vascular reactivity, respectively. There were 12 (15.0%), 30 (37.5%), and 38 (47.5%) KT patients categorized as having poor, intermediate, and good vascular reactivity, respectively. Increased serum levels of alkaline phosphatase (p = 0.012), γ-glutamyltranspeptidase (GGT; p = 0.032), and A-FABP (p < 0.001) were associated with decreased vascular reactivity. Multivariable forward stepwise linear regression analysis revealed that age (β = −0.283, adjusted R2 change = 0.072; p = 0.003) and serum log-A-FABP level (β = −0.514, adjusted R2 change = 0.268; p < 0.001) were significantly associated with VRI values in KT patients. We concluded that serum fasting A-FABP level is negatively associated with VRI values and plays a role in endothelial dysfunction of KT patients. Full article
(This article belongs to the Special Issue Adipose Tissue and Metabolic Health)
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Open AccessArticle
Biotransformation of the Mycotoxin Enniatin B1 by CYP P450 3A4 and Potential for Drug-Drug Interactions
Metabolites 2019, 9(8), 158; https://doi.org/10.3390/metabo9080158 - 27 Jul 2019
Viewed by 578
Abstract
Enniatins (ENNs) are fungal secondary metabolites that frequently occur in grain in temperate climates. Their toxic potency is connected to their ionophoric character and lipophilicity. The biotransformation of ENNs predominantly takes place via cytochrome P450 3A (CYP 3A)-dependent oxidation reactions. Possible interaction with [...] Read more.
Enniatins (ENNs) are fungal secondary metabolites that frequently occur in grain in temperate climates. Their toxic potency is connected to their ionophoric character and lipophilicity. The biotransformation of ENNs predominantly takes place via cytochrome P450 3A (CYP 3A)-dependent oxidation reactions. Possible interaction with ENNs is relevant since CYP3A4 is the main metabolic enzyme for numerous drugs and contaminants. In the present study, we have determined the kinetic characteristics and inhibitory potential of ENNB1 in human liver microsomes (HLM) and CYP3A4-containing nanodiscs (ND). We showed in both in vitro systems that ENNB1 is mainly metabolised by CYP3A4, producing at least eleven metabolites. Moreover, ENNB1 significantly decreased the hydroxylation rates of the typical CYP3A4-substrate midazolam (MDZ). Deoxynivalenol (DON), which is the most prevalent mycotoxin in grain and usually co-occurrs with the ENNs, was not metabolised by CYP3A4 or binding to its active site. Nevertheless, DON affected the efficiency of this biotransformation pathway both in HLM and ND. The metabolite formation rates of ENNB1 and the frequently used drugs progesterone (PGS) and atorvastatin (ARVS) lactone were noticeably reduced, which indicated a certain affinity of DON to the enzyme with subsequent conformational changes. Our results emphasise the importance of drug–drug interaction studies, also with regard to natural toxins. Full article
(This article belongs to the Special Issue Fungal and Mycotoxin Metabolism)
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Open AccessArticle
Bronchoalveolar Lavage Fluid from COPD Patients Reveals More Compounds Associated with Disease than Matched Plasma
Metabolites 2019, 9(8), 157; https://doi.org/10.3390/metabo9080157 - 25 Jul 2019
Viewed by 760
Abstract
Smoking causes chronic obstructive pulmonary disease (COPD). Though recent studies identified a COPD metabolomic signature in blood, no large studies examine the metabolome in bronchoalveolar lavage (BAL) fluid, a more direct representation of lung cell metabolism. We performed untargeted liquid chromatography–mass spectrometry (LC–MS) [...] Read more.
Smoking causes chronic obstructive pulmonary disease (COPD). Though recent studies identified a COPD metabolomic signature in blood, no large studies examine the metabolome in bronchoalveolar lavage (BAL) fluid, a more direct representation of lung cell metabolism. We performed untargeted liquid chromatography–mass spectrometry (LC–MS) on BAL and matched plasma from 115 subjects from the SPIROMICS cohort. Regression was performed with COPD phenotypes as the outcome and metabolites as the predictor, adjusted for clinical covariates and false discovery rate. Weighted gene co-expression network analysis (WGCNA) grouped metabolites into modules which were then associated with phenotypes. K-means clustering grouped similar subjects. We detected 7939 and 10,561 compounds in BAL and paired plasma samples, respectively. FEV1/FVC (Forced Expiratory Volume in One Second/Forced Vital Capacity) ratio, emphysema, FEV1 % predicted, and COPD exacerbations associated with 1230, 792, eight, and one BAL compounds, respectively. Only two plasma compounds associated with a COPD phenotype (emphysema). Three BAL co-expression modules associated with FEV1/FVC and emphysema. K-means BAL metabolomic signature clustering identified two groups, one with more airway obstruction (34% of subjects, median FEV1/FVC 0.67), one with less (66% of subjects, median FEV1/FVC 0.77; p < 2 × 10−4). Associations between metabolites and COPD phenotypes are more robustly represented in BAL compared to plasma. Full article
(This article belongs to the Special Issue Metabolomics and Chronic Obstructive Lung Diseases)
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Open AccessReview
Pre-Analytical Factors that Affect Metabolite Stability in Human Urine, Plasma, and Serum: A Review
Metabolites 2019, 9(8), 156; https://doi.org/10.3390/metabo9080156 - 25 Jul 2019
Viewed by 728
Abstract
Metabolomics provides a comprehensive assessment of numerous small molecules in biological samples. As it integrates the effects of exogenous exposures, endogenous metabolism, and genetic variation, metabolomics is well-suited for studies examining metabolic profiles associated with a variety of chronic diseases. In this review, [...] Read more.
Metabolomics provides a comprehensive assessment of numerous small molecules in biological samples. As it integrates the effects of exogenous exposures, endogenous metabolism, and genetic variation, metabolomics is well-suited for studies examining metabolic profiles associated with a variety of chronic diseases. In this review, we summarize the studies that have characterized the effects of various pre-analytical factors on both targeted and untargeted metabolomic studies involving human plasma, serum, and urine and were published through 14 January 2019. A standardized protocol was used for extracting data from full-text articles identified by searching PubMed and EMBASE. For plasma and serum samples, metabolomic profiles were affected by fasting status, hemolysis, collection time, processing delays, particularly at room temperature, and repeated freeze/thaw cycles. For urine samples, collection time and fasting, centrifugation conditions, filtration and the use of additives, normalization procedures and multiple freeze/thaw cycles were found to alter metabolomic findings. Consideration of the effects of pre-analytical factors is a particularly important issue for epidemiological studies where samples are often collected in nonclinical settings and various locations and are subjected to time and temperature delays prior being to processed and frozen for storage. Full article
(This article belongs to the Special Issue Metabolomics in Epidemiological Studies)
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Open AccessArticle
Urinary Metabolomics Validates Metabolic Differentiation Between Renal Cell Carcinoma Stages and Reveals a Unique Metabolic Profile for Oncocytomas
Metabolites 2019, 9(8), 155; https://doi.org/10.3390/metabo9080155 - 24 Jul 2019
Viewed by 666
Abstract
Renal cell carcinoma (RCC) is a heterogeneous malignancy which often develops and progresses asymptomatically. Benign oncocytomas are morphologically similar to malignant chromophobe RCC and distinguishing between these two forms on cross-sectional imaging remains a challenge. Therefore, RCC-specific biomarkers are urgently required for accurate [...] Read more.
Renal cell carcinoma (RCC) is a heterogeneous malignancy which often develops and progresses asymptomatically. Benign oncocytomas are morphologically similar to malignant chromophobe RCC and distinguishing between these two forms on cross-sectional imaging remains a challenge. Therefore, RCC-specific biomarkers are urgently required for accurate and non-invasive, pre-surgical diagnosis of benign lesions. We have previously shown that dysregulation in glycolytic and tricarboxylic acid cycle intermediates can distinguish benign lesions from RCC in a stage-specific manner. In this study, preoperative fasting urine samples from patients with renal masses were assessed by ¹H nuclear magnetic resonance (NMR). Significant alterations in levels of tricarboxylic acid cycle intermediates, carnitines and its derivatives were detected in RCC relative to benign masses and in oncocytomas vs. chromophobe RCC. Orthogonal Partial Least Square Discriminant Analysis plots confirmed stage discrimination between benign vs. pT1 (R2 = 0.42, Q2 = 0.27) and benign vs. pT3 (R2 = 0.48, Q2 = 0.32) and showed separation for oncocytomas vs. chromophobe RCC (R2 = 0.81, Q2 = 0.57) and oncocytomas vs. clear cell RCC (R2 = 0.32, Q2 = 0.20). This study validates our previously described metabolic profile distinguishing benign tumors from RCC and presents a novel metabolic signature for oncocytomas which may be exploited for diagnosis before cross-sectional imaging. Full article
(This article belongs to the Special Issue Cancer Metabolomics 2019)
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