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Metabolites, Volume 9, Issue 5 (May 2019)

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Open AccessReview
Breast Cancer Metabolomics: From Analytical Platforms to Multivariate Data Analysis. A Review
Metabolites 2019, 9(5), 102; https://doi.org/10.3390/metabo9050102
Received: 7 February 2019 / Revised: 13 May 2019 / Accepted: 17 May 2019 / Published: 22 May 2019
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Abstract
Cancer is a major health issue worldwide for many years and has been increasing significantly. Among the different types of cancer, breast cancer (BC) remains the leading cause of cancer-related deaths in women being a disease caused by a combination of genetic and [...] Read more.
Cancer is a major health issue worldwide for many years and has been increasing significantly. Among the different types of cancer, breast cancer (BC) remains the leading cause of cancer-related deaths in women being a disease caused by a combination of genetic and environmental factors. Nowadays, the available diagnostic tools have aided in the early detection of BC leading to the improvement of survival rates. However, better detection tools for diagnosis and disease monitoring are still required. In this sense, metabolomic NMR, LC-MS and GC-MS-based approaches have gained attention in this field constituting powerful tools for the identification of potential biomarkers in a variety of clinical fields. In this review we will present the current analytical platforms and their applications to identify metabolites with potential for BC biomarkers based on the main advantages and advances in metabolomics research. Additionally, chemometric methods used in metabolomics will be highlighted. Full article
(This article belongs to the Special Issue Cancer Metabolomics 2018)
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Open AccessData Descriptor
A Comprehensive Plasma Metabolomics Dataset for a Cohort of Mouse Knockouts within the International Mouse Phenotyping Consortium
Metabolites 2019, 9(5), 101; https://doi.org/10.3390/metabo9050101
Received: 30 April 2019 / Revised: 11 May 2019 / Accepted: 13 May 2019 / Published: 22 May 2019
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Abstract
Mouse knockouts facilitate the study ofgene functions. Often, multiple abnormal phenotypes are induced when a gene is inactivated. The International Mouse Phenotyping Consortium (IMPC) has generated thousands of mouse knockouts and catalogued their phenotype data. We have acquired metabolomics data from 220 plasma [...] Read more.
Mouse knockouts facilitate the study ofgene functions. Often, multiple abnormal phenotypes are induced when a gene is inactivated. The International Mouse Phenotyping Consortium (IMPC) has generated thousands of mouse knockouts and catalogued their phenotype data. We have acquired metabolomics data from 220 plasma samples from 30 unique mouse gene knockouts and corresponding wildtype mice from the IMPC. To acquire comprehensive metabolomics data, we have used liquid chromatography (LC) combined with mass spectrometry (MS) for detecting polar and lipophilic compounds in an untargeted approach. We have also used targeted methods to measure bile acids, steroids and oxylipins. In addition, we have used gas chromatography GC-TOFMS for measuring primary metabolites. The metabolomics dataset reports 832 unique structurally identified metabolites from 124 chemical classes as determined by ChemRICH software. The GCMS and LCMS raw data files, intermediate and finalized data matrices, R-Scripts, annotation databases, and extracted ion chromatograms are provided in this data descriptor. The dataset can be used for subsequent studies to link genetic variants with molecular mechanisms and phenotypes. Full article
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Open AccessArticle
Effects of Long-Term Storage at −80 °C on the Human Plasma Metabolome
Metabolites 2019, 9(5), 99; https://doi.org/10.3390/metabo9050099
Received: 20 March 2019 / Revised: 26 April 2019 / Accepted: 14 May 2019 / Published: 17 May 2019
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Abstract
High-quality biological samples are required for the favorable outcome of research studies, and valid data sets are crucial for successful biomarker identification. Prolonged storage of biospecimens may have an artificial effect on compound levels. In order to investigate the potential effects of long-term [...] Read more.
High-quality biological samples are required for the favorable outcome of research studies, and valid data sets are crucial for successful biomarker identification. Prolonged storage of biospecimens may have an artificial effect on compound levels. In order to investigate the potential effects of long-term storage on the metabolome, human ethylenediaminetetraacetic acid (EDTA) plasma samples stored for up to 16 years were analyzed by gas and liquid chromatography-tandem mass spectrometry-based metabolomics. Only 2% of 231 tested plasma metabolites were altered in the first seven years of storage. However, upon longer storage periods of up to 16 years and more time differences of few years significantly affected up to 26% of the investigated metabolites when analyzed within subject age groups. Ontology classes that were most affected included complex lipids, fatty acids, energy metabolism molecules, and amino acids. In conclusion, the human plasma metabolome is adequately stable to long-term storage at −80 °C for up to seven years but significant changes occur upon longer storage. However, other biospecimens may display different sensitivities to long-term storage. Therefore, in retrospective studies on EDTA plasma samples, analysis is best performed within the first seven years of storage. Full article
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Open AccessArticle
Urate and Nonanoate Mark the Relationship between Sugar-Sweetened Beverage Intake and Blood Pressure in Adolescent Girls: A Metabolomics Analysis in the ELEMENT Cohort
Metabolites 2019, 9(5), 100; https://doi.org/10.3390/metabo9050100
Received: 5 March 2019 / Revised: 14 May 2019 / Accepted: 15 May 2019 / Published: 17 May 2019
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Abstract
We sought to identify metabolites that mark the relationship of sugar-sweetened beverage (SSB) intake with adiposity and metabolic risk among boys (n = 114) and girls (n = 128) aged 8–14 years. We conducted the analysis in three steps: (1) linear [...] Read more.
We sought to identify metabolites that mark the relationship of sugar-sweetened beverage (SSB) intake with adiposity and metabolic risk among boys (n = 114) and girls (n = 128) aged 8–14 years. We conducted the analysis in three steps: (1) linear regression to examine associations of SSB intake (quartiles) with adiposity, glycemia, lipids, and blood pressure (BP); (2) least absolute shrinkage and selection operator (LASSO) regression to identify SSB-associated metabolites from an untargeted dataset of 938 metabolites; and (3) linear regression to determine whether SSB-related metabolites are also associated with adiposity and metabolic risk. In girls, SSB intake was associated with marginally higher BP (Q2 vs, Q1: 1.11 [−3.90, 6.13], Q3 vs. Q1: 1.16 [−3.81, 6.13], Q4 vs. Q1: 4.65 [−0.22, 9.53] mmHg systolic blood pressure (SBP); P-trend = 0.07). In boys, SSB intake corresponded with higher C-peptide insulin resistance (Q2 vs. Q1: 0.06 [−0.06, 0.19], Q3 vs. Q1: 0.01 [−0.12, 0.14], Q4 vs. Q1: 0.17 [0.04, 0.30] ng/mL; P-trend = 0.03) and leptin (P-trend = 0.02). LASSO identified 6 annotated metabolites in girls (5-methyl-tetrohydrofolate, phenylephrine, urate, nonanoate, deoxyuridine, sn-glycero-3-phosphocholine) and 3 annotated metabolites in boys (2-piperidinone, octanoylcarnitine, catechol) associated with SSB intake. Among girls, urate and nonanoate marked the relationship of SSB intake with BP. None of the SSB-associated metabolites were related to health outcomes in boys. Full article
(This article belongs to the Special Issue Metabolomics in Epidemiological Studies)
Open AccessArticle
Temporal Effects on Radiation Responses in Nonhuman Primates: Identification of Biofluid Small Molecule Signatures by Gas Chromatography–Mass Spectrometry Metabolomics
Metabolites 2019, 9(5), 98; https://doi.org/10.3390/metabo9050098
Received: 25 April 2019 / Revised: 7 May 2019 / Accepted: 10 May 2019 / Published: 15 May 2019
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Abstract
Whole body exposure to ionizing radiation damages tissues leading to physical symptoms which contribute to acute radiation syndrome. Radiation biodosimetry aims to determine characteristic early biomarkers indicative of radiation exposure and is necessary for effective triage after an unanticipated radiological incident. Radiation metabolomics [...] Read more.
Whole body exposure to ionizing radiation damages tissues leading to physical symptoms which contribute to acute radiation syndrome. Radiation biodosimetry aims to determine characteristic early biomarkers indicative of radiation exposure and is necessary for effective triage after an unanticipated radiological incident. Radiation metabolomics can address this aim by assessing metabolic perturbations following exposure. Gas chromatography–mass spectrometry (GC-MS) is a standardized platform ideal for compound identification. We performed GC time-of-flight MS for the global profiling of nonhuman primate urine and serum samples up to 60 d after a single 4 Gy γ-ray total body exposure. Multivariate statistical analysis showed higher group separation in urine vs. serum. We identified biofluid markers involved in amino acid, lipid, purine, and serotonin metabolism, some of which may indicate host microbiome dysbiosis. Sex differences were observed for amino acid fold changes in serum samples. Additionally, we explored mitochondrial dysfunction by tricarboxylic acid intermediate analysis in the first week with a GC tandem quadrupole MS platform. By adding this temporal component to our previous work exploring dose effects at 7 d, we observed the highest fold changes occurring at 3 d, returning closer to basal levels by 7 d. These results emphasize the utility of both MS-based metabolomics for biodosimetry and complementary analytical platforms for increased metabolome coverage. Full article
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Open AccessArticle
The Health Promoting Bioactivities of Lactuca sativa can be Enhanced by Genetic Modulation of Plant Secondary Metabolites
Metabolites 2019, 9(5), 97; https://doi.org/10.3390/metabo9050097
Received: 5 April 2019 / Revised: 28 April 2019 / Accepted: 1 May 2019 / Published: 12 May 2019
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Abstract
Plant secondary metabolites are protective dietary constituents and rol genes evidently increase the synthesis of these versatile phytochemicals. This study subjected a globally important vegetable, lettuce (Lactuca sativa) to a combination of untargeted metabolomics (LC-QTof-MS) and in vitro bioactivity assays. Specifically, [...] Read more.
Plant secondary metabolites are protective dietary constituents and rol genes evidently increase the synthesis of these versatile phytochemicals. This study subjected a globally important vegetable, lettuce (Lactuca sativa) to a combination of untargeted metabolomics (LC-QTof-MS) and in vitro bioactivity assays. Specifically, we examined the differences between untransformed cultured lettuce (UnT), lettuce transformed with either rolABC (RA) or rolC (RC) and commercially grown (COM) lettuce. Of the 5333 metabolite features aligned, deconvoluted and quantified 3637, 1792 and 3737 significantly differed in RA, RC and COM, respectively, compared with UnT. In all cases the number of downregulated metabolites exceeded the number increased. In vitro bioactivity assays showed that RA and RC (but not COM) significantly improved the ability of L. sativa to inhibit α-glucosidase, inhibit dipeptidyl peptidase-4 (DPP-4) and stimulate GLP-1 secretion. We putatively identified 76 lettuce metabolites (sesquiterpene lactones, non-phenolic and phenolic compounds) some of which were altered by several thousand percent in RA and RC. Ferulic acid levels increased 3033–9777%, aminooxononanoic acid increased 1141–1803% and 2,3,5,4′tetrahydroxystilbene-2-O-β-d-glucoside increased 40,272–48,008%. Compound activities were confirmed using commercially obtained standards. In conclusion, rol gene transformation significantly alters the metabolome of L.sativa and enhances its antidiabetic properties. There is considerable potential to exploit rol genes to modulate secondary metabolite production for the development of novel functional foods. This investigation serves as a new paradigm whereby genetic manipulation, metabolomic analysis and bioactivity techniques can be combined to enable the discovery of novel natural bioactives and determine the functional significance of plant metabolites. Full article
Open AccessArticle
Inhibitory Effects of Green Tea Polyphenols on Microbial Metabolism of Aromatic Amino Acids in Humans Revealed by Metabolomic Analysis
Metabolites 2019, 9(5), 96; https://doi.org/10.3390/metabo9050096
Received: 7 April 2019 / Revised: 9 May 2019 / Accepted: 9 May 2019 / Published: 11 May 2019
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Abstract
The bioactivities and potential health benefits of green tea polyphenols (GTP) have been extensively investigated, but the metabolic impact of chronic GTP intake on humans is not well defined. In this study, fecal and urine samples from postmenopausal female subjects taking a GTP [...] Read more.
The bioactivities and potential health benefits of green tea polyphenols (GTP) have been extensively investigated, but the metabolic impact of chronic GTP intake on humans is not well defined. In this study, fecal and urine samples from postmenopausal female subjects taking a GTP supplement or placebo for 12 months were compared by liquid chromatography-mass spectrometry-based metabolomic analysis. The GTP-derived and GTP-responsive metabolites were identified and characterized by structural elucidation and quantitative analysis of the metabolites contributing to the separation of control and treatment samples in the multivariate models. Major GTP and their direct sulfate and glucuronide metabolites were absent in feces and urine. In contrast, GTP-derived phenyl-γ-valerlactone and phenylvaleric acid metabolites were identified as the most abundant GTP-derived metabolites in feces and urine, suggesting extensive microbial biotransformation of GTP in humans. Interestingly, GTP decreased the levels of microbial metabolites of aromatic amino acids (AAA), including indoxyl sulfate, phenylacetylglutamine, and hippuric acid, in urine. However, it did not affect the levels of AAA, as well as other microbial metabolites, including short-chain fatty acids and secondary bile acids, in feces. 16S rRNA gene sequencing indicated that the fecal microbiome was not significantly affected by chronic consumption of GTP. Overall, microbial metabolism is responsible for the formation of GTP metabolites while GTP metabolism may inhibit the formation of AAA metabolites from microbial metabolism. Because these GTP-derived and GTP-responsive metabolites have diverse bioactivities, microbial metabolism of GTP and AAA may play important roles in the beneficial health effects of green tea consumption in humans. Full article
(This article belongs to the Special Issue Metabolite Markers of Phytochemicals)
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Open AccessCommunication
Ovothiol A is the Main Antioxidant in Fish Lens
Metabolites 2019, 9(5), 95; https://doi.org/10.3390/metabo9050095
Received: 18 April 2019 / Revised: 8 May 2019 / Accepted: 8 May 2019 / Published: 10 May 2019
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Abstract
Tissue protection from oxidative stress by antioxidants is of vital importance for cellular metabolism. The lens mostly consists of fiber cells lacking nuclei and organelles, having minimal metabolic activity; therefore, the defense of the lens tissue from the oxidative stress strongly relies on [...] Read more.
Tissue protection from oxidative stress by antioxidants is of vital importance for cellular metabolism. The lens mostly consists of fiber cells lacking nuclei and organelles, having minimal metabolic activity; therefore, the defense of the lens tissue from the oxidative stress strongly relies on metabolites. Protein-free extracts from lenses and gills of freshwater fish, Sander lucioperca and Rutilus rutilus lacustris, were subjected to analysis using high-field 1H NMR spectroscopy and HPLC with optical and high-resolution mass spectrometric detection. It was found that the eye lenses of freshwater fish contain high concentrations of ovothiol A (OSH), i.e., one of the most powerful antioxidants exciting in nature. OSH was identified and quantified in millimolar concentrations. The concentration of OSH in the lens and gills depends on the fish genus and on the season. A possible mechanism of the reactive oxygen species deactivation in fish lenses is discussed. This work is the first to report on the presence of OSH in vertebrates. The presence of ovothiol in the fish tissue implies that it may be a significantly more common antioxidant in freshwater and marine animals than was previously thought. Full article
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Open AccessArticle
Improved Algal Toxicity Test System for Robust Omics-Driven Mode-of-Action Discovery in Chlamydomonas reinhardtii
Metabolites 2019, 9(5), 94; https://doi.org/10.3390/metabo9050094
Received: 12 April 2019 / Revised: 6 May 2019 / Accepted: 7 May 2019 / Published: 10 May 2019
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Abstract
Algae are key components of aquatic food chains. Consequently, they are internationally recognised test species for the environmental safety assessment of chemicals. However, existing algal toxicity test guidelines are not yet optimized to discover molecular modes of action, which require highly-replicated and carefully [...] Read more.
Algae are key components of aquatic food chains. Consequently, they are internationally recognised test species for the environmental safety assessment of chemicals. However, existing algal toxicity test guidelines are not yet optimized to discover molecular modes of action, which require highly-replicated and carefully controlled experiments. Here, we set out to develop a robust, miniaturised and scalable Chlamydomonas reinhardtii toxicity testing approach tailored to meet these demands. We primarily investigated the benefits of synchronised cultures for molecular studies, and of exposure designs that restrict chemical volatilisation yet yield sufficient algal biomass for omics analyses. Flow cytometry and direct-infusion mass spectrometry metabolomics revealed significant and time-resolved changes in sample composition of synchronised cultures. Synchronised cultures in sealed glass vials achieved adequate growth rates at previously unachievably-high inoculation cell densities, with minimal pH drift and negligible chemical loss over 24-h exposures. Algal exposures to a volatile test compound (chlorobenzene) yielded relatively high reproducibility of metabolic phenotypes over experimental repeats. This experimental test system extends existing toxicity testing formats to allow highly-replicated, omics-driven, mode-of-action discovery. Full article
(This article belongs to the Special Issue Metabolites from Phototrophic Prokaryotes and Algae Volume 2)
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Open AccessArticle
NMR-Based Tissular and Developmental Metabolomics of Tomato Fruit
Metabolites 2019, 9(5), 93; https://doi.org/10.3390/metabo9050093
Received: 11 April 2019 / Revised: 30 April 2019 / Accepted: 7 May 2019 / Published: 9 May 2019
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Abstract
Fruit is a complex organ containing seeds and several interconnected tissues with dedicated roles. However, most biochemical or molecular studies about fleshy fruit development concern the entire fruit, the fruit without seeds, or pericarp only. We studied tomato (Solanum lycopersicum) fruit [...] Read more.
Fruit is a complex organ containing seeds and several interconnected tissues with dedicated roles. However, most biochemical or molecular studies about fleshy fruit development concern the entire fruit, the fruit without seeds, or pericarp only. We studied tomato (Solanum lycopersicum) fruit at four stages of development (12, 20, 35, and 45 days post-anthesis). We separated the seeds and the other tissues, exocarp, mesocarp, columella with placenta and locular tissue, and analyzed them individually using proton NMR metabolomic profiling for the quantification of major polar metabolites, enzymatic analysis of starch, and LC-DAD analysis of isoprenoids. Pericarp tissue represented about half of the entire fruit mass only. The composition of each fruit tissue changed during fruit development. An ANOVA-PCA highlighted common, and specific metabolite trends between tissues e.g., higher contents of chlorogenate in locular tissue and of starch in columella. Euclidian distances based on compositional data showed proximities within and between tissues. Several metabolic regulations differed between tissues as revealed by the comparison of metabolite networks based on correlations between compounds. This work stressed the role of specific tissues less studied than pericarp but that impact fruit organoleptic quality including its shape and taste, and fruit processing quality. Full article
(This article belongs to the Special Issue NMR-based Metabolomics and Its Applications Volume 2)
Open AccessArticle
Comparison of Bi- and Tri-Linear PLS Models for Variable Selection in Metabolomic Time-Series Experiments
Metabolites 2019, 9(5), 92; https://doi.org/10.3390/metabo9050092
Received: 3 March 2019 / Revised: 7 May 2019 / Accepted: 8 May 2019 / Published: 9 May 2019
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Abstract
Metabolomic studies with a time-series design are widely used for discovery and validation of biomarkers. In such studies, changes of metabolic profiles over time under different conditions (e.g., control and intervention) are compared, and metabolites responding differently between the conditions are identified as [...] Read more.
Metabolomic studies with a time-series design are widely used for discovery and validation of biomarkers. In such studies, changes of metabolic profiles over time under different conditions (e.g., control and intervention) are compared, and metabolites responding differently between the conditions are identified as putative biomarkers. To incorporate time-series information into the variable (biomarker) selection in partial least squares regression (PLS) models, we created PLS models with different combinations of bilinear/trilinear X and group/time response dummy Y. In total, five PLS models were evaluated on two real datasets, and also on simulated datasets with varying characteristics (number of subjects, number of variables, inter-individual variability, intra-individual variability and number of time points). Variables showing specific temporal patterns observed visually and determined statistically were labelled as discriminating variables. Bootstrapped-VIP scores were calculated for variable selection and the variable selection performance of five PLS models were assessed based on their capacity to correctly select the discriminating variables. The results showed that the bilinear PLS model with group × time response as dummy Y provided the highest recall (true positive rate) of 83–95% with high precision, independent of most characteristics of the datasets. Trilinear PLS models tend to select a small number of variables with high precision but relatively high false negative rate (lower power). They are also less affected by the noise compared to bilinear PLS models. In datasets with high inter-individual variability, bilinear PLS models tend to provide higher recall while trilinear models tend to provide higher precision. Overall, we recommend bilinear PLS with group x time response Y for variable selection applications in metabolomics intervention time series studies. Full article
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Open AccessArticle
Postprandial Metabolic Effects of Fiber Mixes Revealed by in vivo Stable Isotope Labeling in Humans
Metabolites 2019, 9(5), 91; https://doi.org/10.3390/metabo9050091
Received: 10 April 2019 / Revised: 2 May 2019 / Accepted: 5 May 2019 / Published: 7 May 2019
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Abstract
Food supplementation with a fiber mix of guar gum and chickpea flour represents a promising approach to reduce the risk of type 2 diabetes mellitus (T2DM) by attenuating postprandial glycemia. To investigate the effects on postprandial metabolic fluxes of glucose-derived metabolites in response [...] Read more.
Food supplementation with a fiber mix of guar gum and chickpea flour represents a promising approach to reduce the risk of type 2 diabetes mellitus (T2DM) by attenuating postprandial glycemia. To investigate the effects on postprandial metabolic fluxes of glucose-derived metabolites in response to this fiber mix, a randomized, cross-over study was designed. Twelve healthy, male subjects consumed three different flatbreads either supplemented with 2% guar gum or 4% guar gum and 15% chickpea flour or without supplementation (control). The flatbreads were enriched with ~2% of 13C-labeled wheat flour. Blood was collected at 16 intervals over a period of 360 min after bread intake and plasma samples were analyzed by GC-MS based metabolite profiling combined with stable isotope-assisted metabolomics. Although metabolite levels of the downstream metabolites of glucose, specifically lactate and alanine, were not altered in response to the fiber mix, supplementation of 4% guar gum was shown to significantly delay and reduce the exogenous formation of these metabolites. Metabolic modeling and computation of appearance rates revealed that the effects induced by the fiber mix were strongest for glucose and attenuated downstream of glucose. Further investigations to explore the potential of fiber mix supplementation to counteract the development of metabolic diseases are warranted. Full article
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Open AccessArticle
Screening for Preterm Birth: Potential for a Metabolomics Biomarker Panel
Metabolites 2019, 9(5), 90; https://doi.org/10.3390/metabo9050090
Received: 28 March 2019 / Revised: 24 April 2019 / Accepted: 30 April 2019 / Published: 7 May 2019
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Abstract
The aim of this preliminary study was to investigate the potential of maternal serum to provide metabolomic biomarker candidates for the prediction of spontaneous preterm birth (SPTB) in asymptomatic pregnant women at 15 and/or 20 weeks’ gestation. Metabolomics LC-MS datasets from serum samples [...] Read more.
The aim of this preliminary study was to investigate the potential of maternal serum to provide metabolomic biomarker candidates for the prediction of spontaneous preterm birth (SPTB) in asymptomatic pregnant women at 15 and/or 20 weeks’ gestation. Metabolomics LC-MS datasets from serum samples at 15- and 20-weeks’ gestation from a cohort of approximately 50 cases (GA < 37 weeks) and 55 controls (GA > 41weeks) were analysed for candidate biomarkers predictive of SPTB. Lists of the top ranked candidate biomarkers from both multivariate and univariate analyses were produced. At the 20 weeks’ GA time-point these lists had high concordance with each other (85%). A subset of 4 of these features produce a biomarker panel that predicts SPTB with a partial Area Under the Curve (pAUC) of 12.2, a sensitivity of 87.8%, a specificity of 57.7% and a p-value of 0.0013 upon 10-fold cross validation using PanelomiX software. This biomarker panel contained mostly features from groups already associated in the literature with preterm birth and consisted of 4 features from the biological groups of “Bile Acids”, “Prostaglandins”, “Vitamin D and derivatives” and “Fatty Acids and Conjugates”. Full article
(This article belongs to the Special Issue Metabolomics of Complex Traits)
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Open AccessArticle
The Metabolomics Society—Current State of the Membership and Future Directions
Metabolites 2019, 9(5), 89; https://doi.org/10.3390/metabo9050089
Received: 7 April 2019 / Revised: 26 April 2019 / Accepted: 26 April 2019 / Published: 3 May 2019
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Abstract
Background: In 2017, the Metabolomics Society conducted a survey among its members to assess the degree of its current success, define opportunities for improving its service to the community and make plans to establish future goals and direction of the Society. Methods: A [...] Read more.
Background: In 2017, the Metabolomics Society conducted a survey among its members to assess the degree of its current success, define opportunities for improving its service to the community and make plans to establish future goals and direction of the Society. Methods: A 32-question online survey was sent via e-mail to all Metabolomics Society members as of 19 June 2017 (n = 644). In addition to the direct e-mails, the link to access the survey was made available through social media. The survey was open until 10 August 2017. Question-specific data were reported using the summary data generated by SurveyMonkey and additional stratified analyses performed using Stata 15. Results: The number of respondents was 394 (61%) with 348 (88%) completing the multiple-choice questions in survey. Metabolomics Society annual meetings, networking and the opportunity to join the global metabolomics community were among the most important benefits expressed by the Metabolomics Society members. Conclusions: The survey collected the first data focusing on membership issues from Society members. The Society should focus on collecting and monitoring of demographic data during the membership registration process; continuing to support the early-career members of the Society; and developing initiatives that focus on member networking to retain and increase Society membership. Full article
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Open AccessArticle
Using Pathway Covering to Explore Connections among Metabolites
Metabolites 2019, 9(5), 88; https://doi.org/10.3390/metabo9050088
Received: 16 March 2019 / Revised: 24 April 2019 / Accepted: 26 April 2019 / Published: 2 May 2019
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Abstract
Interpreting changes in metabolite abundance in response to experimental treatments or disease states remains a major challenge in metabolomics. Pathway Covering is a new algorithm that takes a list of metabolites (compounds) and determines a minimum-cost set of metabolic pathways in an organism [...] Read more.
Interpreting changes in metabolite abundance in response to experimental treatments or disease states remains a major challenge in metabolomics. Pathway Covering is a new algorithm that takes a list of metabolites (compounds) and determines a minimum-cost set of metabolic pathways in an organism that includes (covers) all the metabolites in the list. We used five functions for assigning costs to pathways, including assigning a constant for all pathways, which yields a solution with the smallest pathway count; two methods that penalize large pathways; one that prefers pathways based on the pathway’s assigned function, and one that loosely corresponds to metabolic flux. The pathway covering set computed by the algorithm can be displayed as a multi-pathway diagram (“pathway collage”) that highlights the covered metabolites. We investigated the pathway covering algorithm by using several datasets from the Metabolomics Workbench. The algorithm is best applied to a list of metabolites with significant statistics and fold-changes with a specified direction of change for each metabolite. The pathway covering algorithm is now available within the Pathway Tools software and BioCyc website. Full article
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Open AccessReview
Marine Algae Metabolites as Promising Therapeutics for the Prevention and Treatment of HIV/AIDS
Metabolites 2019, 9(5), 87; https://doi.org/10.3390/metabo9050087
Received: 21 March 2019 / Revised: 18 April 2019 / Accepted: 26 April 2019 / Published: 2 May 2019
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Abstract
This review presents an analysis of works devoted to the anti-human immunodeficiency virus (HIV) activity of algae metabolites—sulfated polysaccharides (fucoidans, carrageenans), lectins, laminarans, and polyphenols. Despite the presence of a significant number of antiretroviral drugs, the development of new therapeutic and prophylactic agents [...] Read more.
This review presents an analysis of works devoted to the anti-human immunodeficiency virus (HIV) activity of algae metabolites—sulfated polysaccharides (fucoidans, carrageenans), lectins, laminarans, and polyphenols. Despite the presence of a significant number of antiretroviral drugs, the development of new therapeutic and prophylactic agents against this infection remains very urgent problem. This is due to the variability of HIV, the absence of an animal model (except monkeys) and natural immunity to this virus and the toxicity of therapeutic agents and their high cost. In this regard, the need for new therapeutic approaches and broad-spectrum drugs, which in addition to antiviral effects can have anti-inflammatory, antioxidant, and immunomodulatory effects, and to which the minimum resistance of HIV strains would be formed. These requirements meet the biologically active substances of marine algae. The results of experimental and clinical studies conducted in vitro and in vivo are presented, and the issues of the anti-HIV activity of these compounds are considered depending on their structural features. On the whole, the presented data prove the high efficiency of seaweed metabolites and justify the possibility of their use as a potential basis for the development of new drugs with a wide spectrum of activity. Full article
(This article belongs to the Special Issue Seaweeds Metabolites)
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Open AccessArticle
Innovative Alcoholic Drinks Obtained by Co-Fermenting Grape Must and Fruit Juice
Metabolites 2019, 9(5), 86; https://doi.org/10.3390/metabo9050086
Received: 20 April 2019 / Revised: 26 April 2019 / Accepted: 27 April 2019 / Published: 30 April 2019
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Abstract
In this study, Cabernet Sauvignon and Chardonnay musts, and fruit juices from cherry, kiwi, peach, and strawberry were co-fermented with Saccharomyces cerevisiae EC1118 and Torulaspora delbrueckii UMY196 at two different proportions (80:20 (v/v) and 60:40 (v/v [...] Read more.
In this study, Cabernet Sauvignon and Chardonnay musts, and fruit juices from cherry, kiwi, peach, and strawberry were co-fermented with Saccharomyces cerevisiae EC1118 and Torulaspora delbrueckii UMY196 at two different proportions (80:20 (v/v) and 60:40 (v/v)). The most pleasant fruit-based drink was obtained with Cabernet Sauvignon must and kiwi juice in a proportion of 60:40 and fermented with T. delbrueckii. This beverage was produced in higher volume to simulate a scale-up, and the aromatic profile, sensory description, and consumer acceptability were determined. The most powerful odorants of the kiwi-based drink were ethyl octanoate, phenylethanal, ethyl hexanoate, vinyl-guaiacol, benzaldehyde, and nonanal, for which the odor activity values were 21.1, 3.3, 2.6, 2.2, 1.9, and 1.6, respectively. These findings were in accordance with the sensory analysis, since the emerged descriptors were fruity (ethyl octanoate), honey and floral (phenylethanal), apple and peach (ethyl hexanoate), and citrus (nonanal). The consumers judged the kiwi-based drink acceptable (67%) and 39% of them would buy it. The reliable fermentation of a grape must/fruit juice was demonstrated. The kiwi-based drink represents an innovative and pleasant beverage with a positive impact on sustainability as its production can limit the loss of fresh fruits, as well as contribute to the enological field. Full article
(This article belongs to the Special Issue Metabolomics in Yeast and Fermentation)
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Open AccessArticle
DynaStI: A Dynamic Retention Time Database for Steroidomics
Metabolites 2019, 9(5), 85; https://doi.org/10.3390/metabo9050085
Received: 25 February 2019 / Revised: 12 April 2019 / Accepted: 24 April 2019 / Published: 30 April 2019
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Abstract
Steroidomics studies face the challenge of separating analytical compounds with very similar structures (i.e., isomers). Liquid chromatography (LC) is commonly used to this end, but the shared core structure of this family of compounds compromises effective separations among the numerous chemical analytes with [...] Read more.
Steroidomics studies face the challenge of separating analytical compounds with very similar structures (i.e., isomers). Liquid chromatography (LC) is commonly used to this end, but the shared core structure of this family of compounds compromises effective separations among the numerous chemical analytes with comparable physico-chemical properties. Careful tuning of the mobile phase gradient and an appropriate choice of the stationary phase can be used to overcome this problem, in turn modifying the retention times in different ways for each compound. In the usual workflow, this approach is suboptimal for the annotation of features based on retention times since it requires characterizing a library of known compounds for every fine-tuned configuration. We introduce a software solution, DynaStI, that is capable of annotating liquid chromatography-mass spectrometry (LC–MS) features by dynamically generating the retention times from a database containing intrinsic properties of a library of metabolites. DynaStI uses the well-established linear solvent strength (LSS) model for reversed-phase LC. Given a list of LC–MS features and some characteristics of the LC setup, this software computes the corresponding retention times for the internal database and then annotates the features using the exact masses with predicted retention times at the working conditions. DynaStI is able to automatically calibrate its predictions to compensate for deviations in the input parameters. The database also includes identification and structural information for each annotation, such as IUPAC name, CAS number, SMILES string, metabolic pathways, and links to external metabolomic or lipidomic databases. Full article
(This article belongs to the Special Issue Compound Identification of Small Molecules)
Open AccessArticle
Effects of Copper and pH on the Growth and Physiology of Desmodesmus sp. AARLG074
Metabolites 2019, 9(5), 84; https://doi.org/10.3390/metabo9050084
Received: 3 April 2019 / Revised: 26 April 2019 / Accepted: 27 April 2019 / Published: 30 April 2019
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Abstract
Copper (Cu) is a heavy metal that is widely used in industry and as such wastewater from mining or industrial operations can contain high levels of Cu. Some aquatic algal species can tolerate and bioaccumulate Cu and so could play a key role [...] Read more.
Copper (Cu) is a heavy metal that is widely used in industry and as such wastewater from mining or industrial operations can contain high levels of Cu. Some aquatic algal species can tolerate and bioaccumulate Cu and so could play a key role in bioremediating and recovering Cu from polluted waterways. One such species is the green alga Desmodesmus sp. AARLG074. The aim of this study was to determine how Desmodesmus is able to tolerate large alterations in its external Cu and pH environment. Specifically, we set out to measure the variations in the Cu removal efficiency, growth, ultrastructure, and cellular metabolite content in the algal cells that are associated with Cu exposure and acidity. The results showed that Desmodesmus could remove up to 80% of the copper presented in Jaworski’s medium after 30 min exposure. There was a decrease in the ability of Cu removal at pH 4 compared to pH 6 indicating both pH and Cu concentration affected the efficiency of Cu removal. Furthermore, Cu had an adverse effect on algal growth and caused ultrastructural changes. Metabolite fingerprinting (FT-IR and GC-MS) revealed that the polysaccharide and amino acid content were the main metabolites affected under acid and Cu exposure. Fructose, lactose and sorbose contents significantly decreased under both acidic and Cu conditions, whilst glycerol and melezitose contents significantly increased at pH 4. The pathway analysis showed that pH had the highest impact score on alanine, aspartate and glutamate metabolism whereas Cu had the highest impact on arginine and proline metabolism. Notably both Cu and pH had impact on glutathione and galactose metabolism. Full article
(This article belongs to the Special Issue Metabolites from Phototrophic Prokaryotes and Algae Volume 2)
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Open AccessArticle
Metabolites Associated with Vigor to Frailty Among Community-Dwelling Older Black Men
Metabolites 2019, 9(5), 83; https://doi.org/10.3390/metabo9050083
Received: 20 March 2019 / Revised: 19 April 2019 / Accepted: 26 April 2019 / Published: 30 April 2019
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Abstract
Black versus white older Americans are more likely to experience frailty, a condition associated with adverse health outcomes. To reduce racial disparities in health, a complete understanding of the pathophysiology of frailty is needed. Metabolomics may further our understanding by characterizing differences in [...] Read more.
Black versus white older Americans are more likely to experience frailty, a condition associated with adverse health outcomes. To reduce racial disparities in health, a complete understanding of the pathophysiology of frailty is needed. Metabolomics may further our understanding by characterizing differences in the body during a vigorous versus frail state. We sought to identify metabolites and biological pathways associated with vigor to frailty among 287 black men ages 70–81 from the Health, Aging, and Body Composition study. Using liquid chromatography-mass spectrometry, 350 metabolites were measured in overnight-fasting plasma. The Scale of Aging Vigor in Epidemiology (SAVE) measured vigor to frailty based on weight change, strength, energy, gait speed, and physical activity. Thirty-seven metabolites correlated with SAVE scores (p < 0.05), while adjusting for age and site. Fourteen metabolites remained significant after multiple comparisons adjustment (false discovery rate < 0.30). Lower values of tryptophan, methionine, tyrosine, asparagine, C14:0 sphingomyelin, and 1-methylnicotinamide, and higher values of glucoronate, N-carbamoyl-beta-alanine, isocitrate, creatinine, C4-OH carnitine, cystathionine, hydroxyphenylacetate, and putrescine were associated with frailer SAVE scores. Pathway analyses identified nitrogen metabolism, aminoacyl-tRNA biosynthesis, and the citric acid cycle. Future studies need to confirm these SAVE-associated metabolites and pathways that may indicate novel mechanisms involved in the frailty syndrome. Full article
(This article belongs to the Special Issue Metabolomics in Epidemiological Studies)
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Open AccessConcept Paper
Multi-Omics Analyses Detail Metabolic Reprogramming in Lipids, Carnitines, and Use of Glycolytic Intermediates between Prostate Small Cell Neuroendocrine Carcinoma and Prostate Adenocarcinoma
Metabolites 2019, 9(5), 82; https://doi.org/10.3390/metabo9050082
Received: 16 March 2019 / Revised: 24 April 2019 / Accepted: 24 April 2019 / Published: 26 April 2019
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Abstract
As the most common cancer in men, prostate cancer is molecularly heterogeneous. Contributing to this heterogeneity are the poorly understood metabolic adaptations of the two main types of prostate cancer, i.e., adenocarcinoma and small cell neuroendocrine carcinoma (SCNC), the latter being more aggressive [...] Read more.
As the most common cancer in men, prostate cancer is molecularly heterogeneous. Contributing to this heterogeneity are the poorly understood metabolic adaptations of the two main types of prostate cancer, i.e., adenocarcinoma and small cell neuroendocrine carcinoma (SCNC), the latter being more aggressive and lethal. Using transcriptomics, untargeted metabolomics and lipidomics profiling on LASCPC-01 (prostate SCNC) and LNCAP (prostate adenocarcinoma) cell lines, we found significant differences in the cellular phenotypes of the two cell lines. Gene set enrichment analysis on the transcriptomics data showed 62 gene sets were upregulated in LASCPC-01, while 112 gene sets were upregulated in LNCAP. ChemRICH analysis on metabolomics and lipidomics data revealed a total of 25 metabolite clusters were significantly different. LASCPC-01 exhibited a higher glycolytic activity and lower levels of triglycerides, while the LNCAP cell line showed increases in one-carbon metabolism as an exit route of glycolytic intermediates and a decrease in carnitine, a mitochondrial lipid transporter. Our findings pinpoint differences in prostate neuroendocrine carcinoma versus prostate adenocarcinoma that could lead to new therapeutic targets in each type. Full article
(This article belongs to the Special Issue Mass Spectrometry-Based Metabolomics: Challenges and Applications)
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Open AccessArticle
The Fate of Glutamine in Human Metabolism. The Interplay with Glucose in Proliferating Cells
Metabolites 2019, 9(5), 81; https://doi.org/10.3390/metabo9050081
Received: 22 February 2019 / Accepted: 23 April 2019 / Published: 26 April 2019
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Abstract
Genome-scale models of metabolism (GEM) are used to study how metabolism varies in different physiological conditions. However, the great number of reactions involved in GEM makes it difficult to understand these variations. In order to have a more understandable tool, we developed a [...] Read more.
Genome-scale models of metabolism (GEM) are used to study how metabolism varies in different physiological conditions. However, the great number of reactions involved in GEM makes it difficult to understand these variations. In order to have a more understandable tool, we developed a reduced metabolic model of central carbon and nitrogen metabolism, C2M2N with 77 reactions, 54 internal metabolites, and 3 compartments, taking into account the actual stoichiometry of the reactions, including the stoichiometric role of the cofactors and the irreversibility of some reactions. In order to model oxidative phosphorylation (OXPHOS) functioning, the proton gradient through the inner mitochondrial membrane is represented by two pseudometabolites DPH (∆pH) and DPSI (∆ψ). To illustrate the interest of such a reduced and quantitative model of metabolism in mammalian cells, we used flux balance analysis (FBA) to study all the possible fates of glutamine in metabolism. Our analysis shows that glutamine can supply carbon sources for cell energy production and can be used as carbon and nitrogen sources to synthesize essential metabolites. Finally, we studied the interplay between glucose and glutamine for the formation of cell biomass according to ammonia microenvironment. We then propose a quantitative analysis of the Warburg effect. Full article
(This article belongs to the Special Issue Bioinformatics in Metabolomics)
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