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Metabolites, Volume 9, Issue 1 (January 2019)

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Cover Story (view full-size image) Breast cancer patients undergoing combination chemotherapy with palbociclib and fulvestrant have [...] Read more.
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Open AccessArticle GC-MS Metabolomics Reveals Distinct Profiles of Low- and High-Grade Bladder Cancer Cultured Cells
Metabolites 2019, 9(1), 18; https://doi.org/10.3390/metabo9010018
Received: 26 December 2018 / Revised: 11 January 2019 / Accepted: 15 January 2019 / Published: 18 January 2019
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Abstract
Previous studies have shown that metabolomics can be a useful tool to better understand the mechanisms of carcinogenesis; however, alterations in biochemical pathways that lead to bladder cancer (BC) development have hitherto not been fully investigated. In this study, gas chromatography-mass spectrometry (GC-MS)-based [...] Read more.
Previous studies have shown that metabolomics can be a useful tool to better understand the mechanisms of carcinogenesis; however, alterations in biochemical pathways that lead to bladder cancer (BC) development have hitherto not been fully investigated. In this study, gas chromatography-mass spectrometry (GC-MS)-based metabolomics was applied to unveil the metabolic alterations between low-grade and high-grade BC cultured cell lines. Multivariable analysis revealed a panel of metabolites responsible for the separation between the two tumorigenic cell lines. Significantly lower levels of fatty acids, including myristic, palmitic, and palmitoleic acids, were found in high-grade versus low-grade BC cells. Furthermore, significantly altered levels of some amino acids were observed between low- and high-grade BC, namely glycine, leucine, methionine, valine, and aspartic acid. This study successfully demonstrated the potential of metabolomic analysis to discriminate BC cells according to tumor aggressiveness. Moreover, these findings suggest that bladder tumorigenic cell lines of different grades disclose distinct metabolic profiles, mainly affecting fatty acid biosynthesis and amino acid metabolism to compensate for higher energetic needs. Full article
(This article belongs to the Special Issue Cancer Metabolomics 2018)
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Open AccessArticle A Metabolomic Study of the Variability of the Chemical Composition of Commonly Consumed Coffee Brews
Metabolites 2019, 9(1), 17; https://doi.org/10.3390/metabo9010017
Received: 25 November 2018 / Revised: 4 January 2019 / Accepted: 16 January 2019 / Published: 18 January 2019
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Abstract
Coffee drinking has been associated with a lower risk of certain chronic diseases and overall mortality. Its effects on disease risk may vary according to the type of coffee brew consumed and its chemical composition. We characterized variations in the chemical profiles of [...] Read more.
Coffee drinking has been associated with a lower risk of certain chronic diseases and overall mortality. Its effects on disease risk may vary according to the type of coffee brew consumed and its chemical composition. We characterized variations in the chemical profiles of 76 coffee brew samples representing different brew methods, roast levels, bean species, and caffeine types, either prepared or purchased from outlets in Rockville, Maryland, United States of America. Samples were profiled using liquid chromatography coupled with high-resolution mass spectrometry, and the main sources of chemical variability identified by the principal component partial R-square multivariable regression were found to be brew methods (Rpartial2 = 36%). A principal component analysis (PCA) was run on 18 identified coffee compounds after normalization for total signal intensity. The three first principal components were driven by roasting intensity (41% variance), type of coffee beans (29%), and caffeine (8%). These variations were mainly explained by hydroxycinnamoyl esters and diketopiperazines (roasting), N-caffeoyltryptophan, N-p-coumaroyltryptophan, feruloylquinic acids, and theophylline (coffee bean variety) and theobromine (decaffeination). Instant coffees differed from all coffee brews by high contents of diketopiperazines, suggesting a higher roast of the extracted beans. These variations will be important to consider for understanding the effects of different coffee brews on disease risk. Full article
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Open AccessBrief Report 1D “Spikelet” Projections from Heteronuclear 2D NMR Data—Permitting 1D Chemometrics While Preserving 2D Dispersion
Metabolites 2019, 9(1), 16; https://doi.org/10.3390/metabo9010016
Received: 13 December 2018 / Revised: 8 January 2019 / Accepted: 9 January 2019 / Published: 16 January 2019
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Abstract
Nuclear magnetic resonance (NMR) spectroscopy is a powerful tool for the non-targeted metabolomics of intact biofluids and even living organisms. However, spectral overlap can limit the information that can be obtained from 1D 1H NMR. For example, magnetic susceptibility broadening in living organisms [...] Read more.
Nuclear magnetic resonance (NMR) spectroscopy is a powerful tool for the non-targeted metabolomics of intact biofluids and even living organisms. However, spectral overlap can limit the information that can be obtained from 1D 1H NMR. For example, magnetic susceptibility broadening in living organisms prevents any metabolic information being extracted from solution-state 1D 1H NMR. Conversely, the additional spectral dispersion afforded by 2D 1H-13C NMR allows a wide range of metabolites to be assigned in-vivo in 13C enriched organisms, as well as a greater depth of information for biofluids in general. As such, 2D 1H-13C NMR is becoming more and more popular for routine metabolic screening of very complex samples. Despite this, there are only a very limited number of statistical software packages that can handle 2D NMR datasets for chemometric analysis. In comparison, a wide range of commercial and free tools are available for analysis of 1D NMR datasets. Overtime, it is likely more software solutions will evolve that can handle 2D NMR directly. In the meantime, this application note offers a simple alternative solution that converts 2D 1H-13C Heteronuclear Single Quantum Correlation (HSQC) data into a 1D “spikelet” format that preserves not only the 2D spectral information, but also the 2D dispersion. The approach allows 2D NMR data to be converted into a standard 1D Bruker format that can be read by software packages that can only handle 1D NMR data. This application note uses data from Daphnia magna (water fleas) in-vivo to demonstrate how to generate and interpret the converted 1D spikelet data from 2D datasets, including the code to perform the conversion on Bruker spectrometers. Full article
(This article belongs to the Special Issue NMR-based Metabolomics and Its Applications Volume 2)
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Open AccessArticle Univariate Statistical Analysis as a Guide to 1H-NMR Spectra Signal Assignment by Visual Inspection
Metabolites 2019, 9(1), 15; https://doi.org/10.3390/metabo9010015
Received: 20 December 2018 / Revised: 8 January 2019 / Accepted: 10 January 2019 / Published: 15 January 2019
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Abstract
In Proton Nuclear Magnetic Resonance (1H-NMR) spectroscopy, the signals assignment procedure is normally conducted by visual inspection of the spectra, by taking advantage of the innate predisposition of human eye for pattern recognition. In the case of untargeted metabolomics investigations on [...] Read more.
In Proton Nuclear Magnetic Resonance (1H-NMR) spectroscopy, the signals assignment procedure is normally conducted by visual inspection of the spectra, by taking advantage of the innate predisposition of human eye for pattern recognition. In the case of untargeted metabolomics investigations on food and body fluids, the complexity of the spectra may lead the user to overlook signals, independently from their biological relevance. Here, we describe a four steps procedure that is designed to guide signals assignment task by visual inspection. The procedure can be employed whenever an experimental plan allows for the application of a univariate statistical analysis on a point-by-point basis, which is commonly the case. By comparing, as a proof of concept, 1H-NMR spectra of vaginal fluids of healthy and bacterial vaginosis (BV) affected women, we show that the procedure is also readily usable by non-experts in three particularly challenging cases: overlapping multiplets, poorly aligned signals, and signals with very poor signal-to-noise ratio. The paper is accompanied by the necessary codes and examples written in R computational language to allow the interested user gaining a hands-on impression of the procedure’s strengths and weaknesses. Full article
(This article belongs to the Special Issue NMR-based Metabolomics and Its Applications Volume 2)
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Open AccessArticle Serum Amino Acids in Association with Prevalent and Incident Type 2 Diabetes in A Chinese Population
Metabolites 2019, 9(1), 14; https://doi.org/10.3390/metabo9010014
Received: 20 December 2018 / Revised: 4 January 2019 / Accepted: 9 January 2019 / Published: 14 January 2019
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Abstract
We aimed to simultaneously examine the associations of both essential and non-essential amino acids with both prevalent and incident type 2 diabetes in a Chinese population. A case-control study was nested within the Singapore Chinese Health Study. Participants included 144 cases with prevalent [...] Read more.
We aimed to simultaneously examine the associations of both essential and non-essential amino acids with both prevalent and incident type 2 diabetes in a Chinese population. A case-control study was nested within the Singapore Chinese Health Study. Participants included 144 cases with prevalent and 160 cases with incident type 2 diabetes and 304 controls. Cases and controls were individually matched on age, sex, and date of blood collection. Baseline serum levels of 9 essential and 10 non-essential amino acids were measured using liquid chromatography tandem mass spectrometry. We identified that five essential (isoleucine, leucine, lysine, phenylalanine, and valine) and five non-essential (alanine, glutamic acid, glutamine, glycine, and tyrosine) amino acids were associated with the prevalence of type 2 diabetes; four essential (isoleucine, leucine, tryptophan, and valine) and two non-essential (glutamine and tyrosine) amino acids were associated with the incidence of type 2 diabetes. Of these, valine and tyrosine independently led to a significant improvement in risk prediction of incident type 2 diabetes. This study demonstrates that both essential and non-essential amino acids were associated with the risk for prevalent and incident type 2 diabetes, and the findings could aid in diabetes risk assessment in this Chinese population. Full article
Open AccessArticle Rapid Cerebral Metabolic Shift during Neonatal Sepsis Is Attenuated by Enteral Colostrum Supplementation in Preterm Pigs
Metabolites 2019, 9(1), 13; https://doi.org/10.3390/metabo9010013
Received: 3 December 2018 / Revised: 4 January 2019 / Accepted: 7 January 2019 / Published: 11 January 2019
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Abstract
Sepsis, the clinical manifestation of serious infection, may disturb normal brain development, especially in preterm infants with an immature brain. We hypothesized that neonatal sepsis induces systemic metabolic alterations that rapidly affect metabolic signatures in immature brain and cerebrospinal fluid (CSF). Cesarean-delivered preterm [...] Read more.
Sepsis, the clinical manifestation of serious infection, may disturb normal brain development, especially in preterm infants with an immature brain. We hypothesized that neonatal sepsis induces systemic metabolic alterations that rapidly affect metabolic signatures in immature brain and cerebrospinal fluid (CSF). Cesarean-delivered preterm pigs systemically received 109 CFU/kg Staphylococcus epidermidis (SE) and were provided total parenteral nutrition (n = 9) or enteral supplementation with bovine colostrum (n = 10) and compared with uninfected pigs receiving parenteral nutrition (n = 7). Plasma, CSF, and brain tissue samples were collected after 24 h and analyzed by 1H NMR-based metabolomics. Both plasma and CSF metabolomes revealed SE-induced changes in metabolite levels that reflected a modified energy metabolism. Hence, increased plasma lactate, alanine, and succinate levels, as well as CSF lactate levels, were observed during SE infection (all p < 0.05, ANOVA analysis). Myo-inositol, a glucose derivative known for beneficial effects on lung maturation in preterm infants, was also increased in plasma and CSF following SE infection. Enteral colostrum supplementation attenuated the lactate accumulation in blood and CSF. Bloodstream infection in preterm newborns was found to induce a rapid metabolic shift in both plasma and CSF, which was modulated by colostrum feeding. Full article
(This article belongs to the Special Issue NMR-based Metabolomics and Its Applications Volume 2)
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Open AccessArticle Direct Infusion Based Metabolomics Identifies Metabolic Disease in Patients’ Dried Blood Spots and Plasma
Metabolites 2019, 9(1), 12; https://doi.org/10.3390/metabo9010012
Received: 19 December 2018 / Revised: 4 January 2019 / Accepted: 8 January 2019 / Published: 11 January 2019
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Abstract
In metabolic diagnostics, there is an emerging need for a comprehensive test to acquire a complete view of metabolite status. Here, we describe a non-quantitative direct-infusion high-resolution mass spectrometry (DI-HRMS) based metabolomics method and evaluate the method for both dried blood spots (DBS) [...] Read more.
In metabolic diagnostics, there is an emerging need for a comprehensive test to acquire a complete view of metabolite status. Here, we describe a non-quantitative direct-infusion high-resolution mass spectrometry (DI-HRMS) based metabolomics method and evaluate the method for both dried blood spots (DBS) and plasma. 110 DBS of 42 patients harboring 23 different inborn errors of metabolism (IEM) and 86 plasma samples of 38 patients harboring 21 different IEM were analyzed using DI-HRMS. A peak calling pipeline developed in R programming language provided Z-scores for ~1875 mass peaks corresponding to ~3835 metabolite annotations (including isomers) per sample. Based on metabolite Z-scores, patients were assigned a ‘most probable diagnosis’ by an investigator blinded for the known diagnoses of the patients. Based on DBS sample analysis, 37/42 of the patients, corresponding to 22/23 IEM, could be correctly assigned a ‘most probable diagnosis’. Plasma sample analysis, resulted in a correct ‘most probable diagnosis’ in 32/38 of the patients, corresponding to 19/21 IEM. The added clinical value of the method was illustrated by a case wherein DI-HRMS metabolomics aided interpretation of a variant of unknown significance (VUS) identified by whole-exome sequencing. In summary, non-quantitative DI-HRMS metabolomics in DBS and plasma is a very consistent, high-throughput and nonselective method for investigating the metabolome in genetic disease. Full article
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Open AccessReview Alteration of Metabolic Pathways in Osteoarthritis
Metabolites 2019, 9(1), 11; https://doi.org/10.3390/metabo9010011
Received: 17 November 2018 / Revised: 3 January 2019 / Accepted: 4 January 2019 / Published: 9 January 2019
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Abstract
Sir Archibald Edward Garrod, who pioneered the field of inborn errors of metabolism and first elucidated the biochemical basis of alkaptonuria over 100 years ago, suggested that inborn errors of metabolism were “merely extreme examples of variations of chemical behavior which are probably [...] Read more.
Sir Archibald Edward Garrod, who pioneered the field of inborn errors of metabolism and first elucidated the biochemical basis of alkaptonuria over 100 years ago, suggested that inborn errors of metabolism were “merely extreme examples of variations of chemical behavior which are probably everywhere present in minor degrees, just as no two individuals of a species are absolutely identical in bodily structure neither are their chemical processes carried out on exactly the same lines”, and that this “chemical individuality [confers] predisposition to and immunities from various mishaps which are spoken of as diseases”. Indeed, with advances in analytical biochemistry, especially the development of metabolomics in the post-genomic era, emerging data have been demonstrating that the levels of many metabolites do show substantial interindividual variation, and some of which are likely to be associated with common diseases, such as osteoarthritis (OA). Much work has been reported in the literature on the metabolomics of OA in recent years. In this narrative review, we provided an overview of the identified alteration of metabolic pathways in OA and discussed the role of those identified metabolites and related pathways in OA diagnosis, prognosis, and treatment. Full article
(This article belongs to the Special Issue Metabolomics of Complex Traits)
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Open AccessArticle Assessment of l-Asparaginase Pharmacodynamics in Mouse Models of Cancer
Metabolites 2019, 9(1), 10; https://doi.org/10.3390/metabo9010010
Received: 25 November 2018 / Revised: 24 December 2018 / Accepted: 4 January 2019 / Published: 9 January 2019
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Abstract
l-asparaginase (ASNase) is a metabolism-targeted anti-neoplastic agent used to treat acute lymphoblastic leukemia (ALL). ASNase’s anticancer activity results from the enzymatic depletion of asparagine (Asn) and glutamine (Gln), which are converted to aspartic acid (Asp) and glutamic acid (Glu), respectively, in the [...] Read more.
l-asparaginase (ASNase) is a metabolism-targeted anti-neoplastic agent used to treat acute lymphoblastic leukemia (ALL). ASNase’s anticancer activity results from the enzymatic depletion of asparagine (Asn) and glutamine (Gln), which are converted to aspartic acid (Asp) and glutamic acid (Glu), respectively, in the blood. Unfortunately, accurate assessment of the in vivo pharmacodynamics (PD) of ASNase is challenging because of the following reasons: (i) ASNase is resilient to deactivation; (ii) ASNase catalytic efficiency is very high; and (iii) the PD markers Asn and Gln are depleted ex vivo in blood samples containing ASNase. To address those issues and facilitate longitudinal studies in individual mice for ASNase PD studies, we present here a new LC-MS/MS bioanalytical method that incorporates rapid quenching of ASNase for measurement of Asn, Asp, Gln, and Glu in just 10 µL of whole blood, with limits of detection (s:n ≥ 10:1) estimated to be 2.3, 3.5, 0.8, and 0.5 µM, respectively. We tested the suitability of the method in a 5-day, longitudinal PD study in mice and found the method to be simple to perform with sufficient accuracy and precision for whole blood measurements. Overall, the method increases the density of data that can be acquired from a single animal and will facilitate optimization of novel ASNase treatment regimens and/or the development of new ASNase variants with desired kinetic properties. Full article
(This article belongs to the Special Issue Cancer Metabolomics 2018)
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Open AccessEditorial Acknowledgement to Reviewers of Metabolites in 2018
Metabolites 2019, 9(1), 9; https://doi.org/10.3390/metabo9010009
Published: 8 January 2019
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Abstract
Rigorous peer-review is the corner-stone of high-quality academic publishing [...] Full article
Open AccessArticle Untargeted Metabolomics Reveal Defensome-Related Metabolic Reprogramming in Sorghum bicolor against Infection by Burkholderia andropogonis
Metabolites 2019, 9(1), 8; https://doi.org/10.3390/metabo9010008
Received: 10 November 2018 / Revised: 21 December 2018 / Accepted: 24 December 2018 / Published: 2 January 2019
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Abstract
Burkholderia andropogonis is the causal agent of bacterial leaf stripe, one of the three major bacterial diseases affecting Sorghum bicolor. However, the biochemical aspects of the pathophysiological host responses are not well understood. An untargeted metabolomics approach was designed to understand molecular [...] Read more.
Burkholderia andropogonis is the causal agent of bacterial leaf stripe, one of the three major bacterial diseases affecting Sorghum bicolor. However, the biochemical aspects of the pathophysiological host responses are not well understood. An untargeted metabolomics approach was designed to understand molecular mechanisms underlying S. bicolorB. andropogonis interactions. At the 4-leaf stage, two sorghum cultivars (NS 5511 and NS 5655) differing in disease tolerance, were infected with B. andropogonis and the metabolic changes monitored over time. The NS 5511 cultivar displayed delayed signs of wilting and lesion progression compared to the NS 5655 cultivar, indicative of enhanced resistance. The metabolomics results identified statistically significant metabolites as biomarkers associated with the sorghum defence. These include the phytohormones salicylic acid, jasmonic acid, and zeatin. Moreover, metabolic reprogramming in an array of chemically diverse metabolites that span a wide range of metabolic pathways was associated with the defence response. Signatory biomarkers included aromatic amino acids, shikimic acid, metabolites from the phenylpropanoid and flavonoid pathways, as well as fatty acids. Enhanced synthesis and accumulation of apigenin and derivatives thereof was a prominent feature of the altered metabolomes. The analyses revealed an intricate and dynamic network of the sorghum defence arsenal towards B. andropogonis in establishing an enhanced defensive capacity in support of resistance and disease suppression. The results pave the way for future analysis of the biosynthesis of signatory biomarkers and regulation of relevant metabolic pathways in sorghum. Full article
(This article belongs to the Special Issue Metabolomics in Agriculture)
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Open AccessArticle Palbociclib and Fulvestrant Act in Synergy to Modulate Central Carbon Metabolism in Breast Cancer Cells
Metabolites 2019, 9(1), 7; https://doi.org/10.3390/metabo9010007
Received: 6 November 2018 / Revised: 19 December 2018 / Accepted: 21 December 2018 / Published: 2 January 2019
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Abstract
The aims of this study were to determine whether combination chemotherapeutics exhibit a synergistic effect on breast cancer cell metabolism. Palbociclib, is a selective inhibitor of cyclin-dependent kinases 4 and 6, and when patients are treated in combination with fulvestrant, an estrogen receptor [...] Read more.
The aims of this study were to determine whether combination chemotherapeutics exhibit a synergistic effect on breast cancer cell metabolism. Palbociclib, is a selective inhibitor of cyclin-dependent kinases 4 and 6, and when patients are treated in combination with fulvestrant, an estrogen receptor antagonist, they have improved progression-free survival. The mechanisms for this survival advantage are not known. Therefore, we analyzed metabolic and transcriptomic changes in MCF-7 cells following single and combination chemotherapy to determine whether selective metabolic pathways are targeted during these different modes of treatment. Individually, the drugs caused metabolic disruption to the same metabolic pathways, however fulvestrant additionally attenuated the pentose phosphate pathway and the production of important coenzymes. A comprehensive effect was observed when the drugs were applied together, confirming the combinatory therapy’s synergism in the cell model. This study also highlights the power of merging high-dimensional datasets to unravel mechanisms involved in cancer metabolism and therapy. Full article
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Open AccessArticle Brain Metabolomics Reveal the Antipyretic Effects of Jinxin Oral Liquid in Young Rats by Using Gas Chromatography–Mass Spectrometry
Metabolites 2019, 9(1), 6; https://doi.org/10.3390/metabo9010006
Received: 18 November 2018 / Revised: 15 December 2018 / Accepted: 20 December 2018 / Published: 1 January 2019
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Abstract
Pyrexia is considered as a part of host’s defense response to the invasion of microorganisms or inanimate matter recognized as pathogenic or alien, which frequently occurs in children. Jinxin oral liquid (JXOL) is a traditional Chinese medicine formula that has been widely used [...] Read more.
Pyrexia is considered as a part of host’s defense response to the invasion of microorganisms or inanimate matter recognized as pathogenic or alien, which frequently occurs in children. Jinxin oral liquid (JXOL) is a traditional Chinese medicine formula that has been widely used to treat febrile children in China. Experimental fever was induced by injecting yeast into young male Sprague-Dawley rats (80 ± 20 g) and the rectal temperature subsequently changed. Four hours later, the excessive production of interleukin (IL)-1β and prostaglandin (PG) E2 induced by yeast was regulated to normal by JXOL administration. A rat brain metabolomics investigation of pyrexia of yeast and antipyretic effect of JXOL was performed using gas chromatography-mass spectrometry (GC-MS). Clear separation was achieved between the model and normal group. Twenty-two significantly altered metabolites were found in pyretic rats as potential biomarkers of fever. Twelve metabolites, significantly adjusted by JXOL to help relieve pyrexia, were selected out as biomarkers of antipyretic mechanism of JXOL, which were involved in glycolysis, purine metabolism, tryptophan mechanism, etc. In conclusion, the brain metabolomics revealed potential biomarkers in the JXOL antipyretic process and the associated pathways, which may aid in advanced understanding of fever and therapeutic mechanism of JXOL. Full article
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Open AccessArticle Random Forest Analysis of Untargeted Metabolomics Data Suggests Increased Use of Omega Fatty Acid Oxidation Pathway in Drosophila Melanogaster Larvae Fed a Medium Chain Fatty Acid Rich High-Fat Diet
Metabolites 2019, 9(1), 5; https://doi.org/10.3390/metabo9010005
Received: 9 November 2018 / Revised: 27 December 2018 / Accepted: 27 December 2018 / Published: 31 December 2018
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Abstract
Obesity is a complex disease, shaped by both genetic and environmental factors such as diet. In this study, we use untargeted metabolomics and Drosophila melanogaster to model how diet and genotype shape the metabolome of obese phenotypes. We used 16 distinct outbred genotypes [...] Read more.
Obesity is a complex disease, shaped by both genetic and environmental factors such as diet. In this study, we use untargeted metabolomics and Drosophila melanogaster to model how diet and genotype shape the metabolome of obese phenotypes. We used 16 distinct outbred genotypes of Drosophila larvae raised on normal (ND) and high-fat (HFD) diets, to produce three distinct phenotypic classes; genotypes that stored more triglycerides on a ND relative to the HFD, genotypes that stored more triglycerides on a HFD relative to ND, and genotypes that showed no change in triglyceride storage on either of the two diets. Using untargeted metabolomics we characterized 350 metabolites: 270 with definitive chemical IDs and 80 that were chemically unidentified. Using random forests, we determined metabolites that were important in discriminating between the HFD and ND larvae as well as between the triglyceride phenotypic classes. We found that flies fed on a HFD showed evidence of an increased use of omega fatty acid oxidation pathway, an alternative to the more commonly used beta fatty acid oxidation pathway. Additionally, we observed no correlation between the triglyceride storage phenotype and free fatty acid levels (laurate, caprate, caprylate, caproate), indicating that the distinct metabolic profile of fatty acids in high-fat diet fed Drosophila larvae does not propagate into triglyceride storage differences. However, dipeptides did show moderate differences between the phenotypic classes. We fit Gaussian graphical models (GGMs) of the metabolic profiles for HFD and ND flies to characterize changes in metabolic network structure between the two diets, finding the HFD to have a greater number of edges indicating that metabolome varies more across samples on a HFD. Taken together, these results show that, in the context of obesity, metabolomic profiles under distinct dietary conditions may not be reliable predictors of phenotypic outcomes in a genetically diverse population. Full article
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Open AccessReview Metabolomics and Age-Related Macular Degeneration
Metabolites 2019, 9(1), 4; https://doi.org/10.3390/metabo9010004
Received: 21 November 2018 / Revised: 17 December 2018 / Accepted: 20 December 2018 / Published: 27 December 2018
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Abstract
Age-related macular degeneration (AMD) leads to irreversible visual loss, therefore, early intervention is desirable, but due to its multifactorial nature, diagnosis of early disease might be challenging. Identification of early markers for disease development and progression is key for disease diagnosis. Suitable biomarkers [...] Read more.
Age-related macular degeneration (AMD) leads to irreversible visual loss, therefore, early intervention is desirable, but due to its multifactorial nature, diagnosis of early disease might be challenging. Identification of early markers for disease development and progression is key for disease diagnosis. Suitable biomarkers can potentially provide opportunities for clinical intervention at a stage of the disease when irreversible changes are yet to take place. One of the most metabolically active tissues in the human body is the retina, making the use of hypothesis-free techniques, like metabolomics, to measure molecular changes in AMD appealing. Indeed, there is increasing evidence that metabolic dysfunction has an important role in the development and progression of AMD. Therefore, metabolomics appears to be an appropriate platform to investigate disease-associated biomarkers. In this review, we explored what is known about metabolic changes in the retina, in conjunction with the emerging literature in AMD metabolomics research. Methods for metabolic biomarker identification in the eye have also been discussed, including the use of tears, vitreous, and aqueous humor, as well as imaging methods, like fluorescence lifetime imaging, that could be translated into a clinical diagnostic tool with molecular level resolution. Full article
(This article belongs to the Special Issue Metabolomics in Neurodegenerative Disease)
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Open AccessArticle Annotating Nontargeted LC-HRMS/MS Data with Two Complementary Tandem Mass Spectral Libraries
Metabolites 2019, 9(1), 3; https://doi.org/10.3390/metabo9010003
Received: 4 December 2018 / Revised: 17 December 2018 / Accepted: 21 December 2018 / Published: 23 December 2018
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Abstract
Tandem mass spectral databases are indispensable for fast and reliable compound identification in nontargeted analysis with liquid chromatography–high resolution tandem mass spectrometry (LC-HRMS/MS), which is applied to a wide range of scientific fields. While many articles now review and compare spectral libraries, in [...] Read more.
Tandem mass spectral databases are indispensable for fast and reliable compound identification in nontargeted analysis with liquid chromatography–high resolution tandem mass spectrometry (LC-HRMS/MS), which is applied to a wide range of scientific fields. While many articles now review and compare spectral libraries, in this manuscript we investigate two high-quality and specialized collections from our respective institutes, recorded on different instruments (quadrupole time-of-flight or QqTOF vs. Orbitrap). The optimal range of collision energies for spectral comparison was evaluated using 233 overlapping compounds between the two libraries, revealing that spectra in the range of CE 20–50 eV on the QqTOF and 30–60 nominal collision energy units on the Orbitrap provided optimal matching results for these libraries. Applications to complex samples from the respective institutes revealed that the libraries, combined with a simple data mining approach to retrieve all spectra with precursor and fragment information, could confirm many validated target identifications and yield several new Level 2a (spectral match) identifications. While the results presented are not surprising in many ways, this article adds new results to the debate on the comparability of Orbitrap and QqTOF data and the application of spectral libraries to yield rapid and high-confidence tentative identifications in complex human and environmental samples. Full article
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Open AccessArticle Compositional Differences and Similarities between Typical Chinese Baijiu and Western Liquor as Revealed by Mass Spectrometry-Based Metabolomics
Metabolites 2019, 9(1), 2; https://doi.org/10.3390/metabo9010002
Received: 25 October 2018 / Revised: 4 December 2018 / Accepted: 12 December 2018 / Published: 21 December 2018
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Abstract
Distilled liquors are important products, both culturally and economically. Chemically, as a complex mixture, distilled liquor comprises various chemical compounds in addition to ethanol. However, the chemical components of distilled liquors are still insufficiently understood and compositional differences and similarities of distilled liquors [...] Read more.
Distilled liquors are important products, both culturally and economically. Chemically, as a complex mixture, distilled liquor comprises various chemical compounds in addition to ethanol. However, the chemical components of distilled liquors are still insufficiently understood and compositional differences and similarities of distilled liquors from different cultures have never been compared. For the first time, both volatile organic compounds (VOCs) and non-VOCs in distilled liquors were profiled using mass spectrometry-based metabolomic approaches. A total of 879 VOCs and 268 non-VOCs were detected in 24 distilled liquors including six typical Chinese baijiu and 18 typical Western liquors. Principal component analysis and a correlation network revealed important insights into the compositional differences and similarities of the distilled liquors that were assessed. Ethyl esters, a few benzene derivatives, and alcohols were shared by most distilled liquors assessed, suggesting their important contribution to the common flavor and mouthfeel of distilled liquors. Sugars and esters formed by fatty alcohol differ significantly between the assessed Chinese baijiu and Western liquors, and are potential marker compounds that could be used for their discrimination. Factors contributing to the differences in chemical composition are proposed. Our results improve our understanding of the chemical components of distilled liquors, which may contribute to more rigorous quality control of alcoholic beverages. Full article
(This article belongs to the Special Issue Metabolite Markers of Phytochemicals)
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Open AccessArticle Metabolic Profiling of Fish Meat by GC-MS Analysis, and Correlations with Taste Attributes Obtained Using an Electronic Tongue
Metabolites 2019, 9(1), 1; https://doi.org/10.3390/metabo9010001
Received: 22 November 2018 / Revised: 17 December 2018 / Accepted: 19 December 2018 / Published: 21 December 2018
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Abstract
To evaluate the taste of ordinary muscle from white-fleshed fish, we used GC-MS metabolomic analysis to characterise the compounds therein, and correlated the obtained data with taste measurements from an electronic tongue. Prediction models using orthogonal partial least squares were produced for different [...] Read more.
To evaluate the taste of ordinary muscle from white-fleshed fish, we used GC-MS metabolomic analysis to characterise the compounds therein, and correlated the obtained data with taste measurements from an electronic tongue. Prediction models using orthogonal partial least squares were produced for different taste attributes, and the primary metabolic components correlated with the taste attributes were identified. Clear differences were observed in the component profiles for different fish species. Using an electronic tongue, differences in tastes were noted among the fish species in terms of sourness, acidic bitterness, umami and saltiness. The obtained correlations allowed the construction of good taste prediction models, especially for sourness, acidic bitterness and saltiness. Compounds such as phosphoric acid, lactic acid and creatinine were found to be highly correlated with some taste attributes. Phosphoric acid in particular showed the highest variable important for prediction (VIP) scores in many of the taste prediction models, and it is therefore a candidate marker to evaluate the tastes of white-fleshed fish. Full article
(This article belongs to the Special Issue Mass Spectrometry-Based Metabolomics and Its Applications)
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Metabolites EISSN 2218-1989 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
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