Next Issue
Volume 10, August
Previous Issue
Volume 10, June
 
 

Metabolites, Volume 10, Issue 7 (July 2020) – 33 articles

Cover Story (view full-size image): Resistance to chemotherapeutics often relies on dysregulated cancer metabolism, which could serve as a treatment target. However, selection of the most appropriate model reflecting the tumor entity could be of a major challenge due to the lack of a microenvironment or time constraints. Here, we describe the potential robust platform for anticancer drug testing, combining a chicken embryo tumor model (in ovo) with metabolic phenotyping. We used an in ovo breast cancer model and monitored doxorubicin or vehicle response by untargeted metabolomics and lipidomics. We observed doxorubicin-induced tumor suppression, accompanied by a clear shift in the metabolic profile. Doxorubicin was found to inhibit glycolysis and synthesis of nucleotides and glycerophospholipids, potentially explaining the tumor shrinkage. Furthermore, we identified antioxidative pathways as a cancer survival mechanism and a potential [...] Read more.
  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Readerexternal link to open them.
Order results
Result details
Section
Select all
Export citation of selected articles as:
Article
Lipidomic Profiling of the Epidermis in a Mouse Model of Dermatitis Reveals Sexual Dimorphism and Changes in Lipid Composition before the Onset of Clinical Disease
Metabolites 2020, 10(7), 299; https://doi.org/10.3390/metabo10070299 - 21 Jul 2020
Cited by 6 | Viewed by 1155
Abstract
Atopic dermatitis (AD) is a multifactorial disease associated with alterations in lipid composition and organization in the epidermis. Multiple variants of AD exist with different outcomes in response to therapies. The evaluation of disease progression and response to treatment are observational assessments with [...] Read more.
Atopic dermatitis (AD) is a multifactorial disease associated with alterations in lipid composition and organization in the epidermis. Multiple variants of AD exist with different outcomes in response to therapies. The evaluation of disease progression and response to treatment are observational assessments with poor inter-observer agreement highlighting the need for molecular markers. SHARPIN-deficient mice (Sharpincpdm) spontaneously develop chronic proliferative dermatitis with features similar to AD in humans. To study the changes in the epidermal lipid-content during disease progression, we tested 72 epidermis samples from three groups (5-, 7-, and 10-weeks old) of cpdm mice and their WT littermates. An agnostic mass-spectrometry strategy for biomarker discovery termed multiple-reaction monitoring (MRM)-profiling was used to detect and monitor 1,030 lipid ions present in the epidermis samples. In order to select the most relevant ions, we utilized a two-tiered filter/wrapper feature-selection strategy. Lipid categories were compressed, and an elastic-net classifier was used to rank and identify the most predictive lipid categories for sex, phenotype, and disease stages of cpdm mice. The model accurately classified the samples based on phospholipids, cholesteryl esters, acylcarnitines, and sphingolipids, demonstrating that disease progression cannot be defined by one single lipid or lipid category. Full article
(This article belongs to the Special Issue Advances in Lipidomics: Biomedicine, Nutrients and Methodology)
Show Figures

Graphical abstract

Article
Exercise Induced Changes in Salivary and Serum Metabolome in Trained Standardbred, Assessed by 1H-NMR
Metabolites 2020, 10(7), 298; https://doi.org/10.3390/metabo10070298 - 21 Jul 2020
Cited by 2 | Viewed by 993
Abstract
In the present study, data related to the metabolomics of saliva and serum in trained standardbred horses are provided for the first time. Metabolomic analysis allows to analyze all the metabolites within selected biofluids, providing a better understanding of biochemistry modifications related to [...] Read more.
In the present study, data related to the metabolomics of saliva and serum in trained standardbred horses are provided for the first time. Metabolomic analysis allows to analyze all the metabolites within selected biofluids, providing a better understanding of biochemistry modifications related to exercise. On the basis of the current advances observed in metabolomic research on human athletes, we aimed to investigate the metabolites’ profile of serum and saliva samples collected from healthy standardbred horses and the relationship with physical exercise. Twelve trained standardbred horses were sampled for blood and saliva before (T0) and immediately after (T1) standardized exercise. Metabolomic analysis of both samples was performed by 1H-NMR spectroscopy. Forty-six metabolites in serum and 62 metabolites in saliva were detected, including alcohols, amino acids, organic acids, carbohydrates and purine derivatives. Twenty-six and 14 metabolites resulted to be significantly changed between T0 and T1 in serum and saliva, respectively. The findings of 2-hydroxyisobutyrate and 3-hydroxybutyrate in serum and GABA in equine saliva, as well as their modifications following exercise, provide new insights about the physiology of exercise in athletic horses. Glycerol might represent a novel biomarker for fitness evaluation in sport horses. Full article
(This article belongs to the Special Issue Metabolomic Applications in Animal Science)
Show Figures

Graphical abstract

Article
hcapca: Automated Hierarchical Clustering and Principal Component Analysis of Large Metabolomic Datasets in R
Metabolites 2020, 10(7), 297; https://doi.org/10.3390/metabo10070297 - 21 Jul 2020
Cited by 12 | Viewed by 2218
Abstract
Microbial natural product discovery programs face two main challenges today: rapidly prioritizing strains for discovering new molecules and avoiding the rediscovery of already known molecules. Typically, these problems have been tackled using biological assays to identify promising strains and techniques that model variance [...] Read more.
Microbial natural product discovery programs face two main challenges today: rapidly prioritizing strains for discovering new molecules and avoiding the rediscovery of already known molecules. Typically, these problems have been tackled using biological assays to identify promising strains and techniques that model variance in a dataset such as PCA to highlight novel chemistry. While these tools have shown successful outcomes in the past, datasets are becoming much larger and require a new approach. Since PCA models are dependent on the members of the group being modeled, large datasets with many members make it difficult to accurately model the variance in the data. Our tool, hcapca, first groups strains based on the similarity of their chemical composition, and then applies PCA to the smaller sub-groups yielding more robust PCA models. This allows for scalable chemical comparisons among hundreds of strains with thousands of molecular features. As a proof of concept, we applied our open-source tool to a dataset with 1046 LCMS profiles of marine invertebrate associated bacteria and discovered three new analogs of an established anticancer agent from one promising strain. Full article
(This article belongs to the Section Frontiers in Metabolomics)
Show Figures

Graphical abstract

Article
LC–MS Lipidomics: Exploiting a Simple High-Throughput Method for the Comprehensive Extraction of Lipids in a Ruminant Fat Dose-Response Study
Metabolites 2020, 10(7), 296; https://doi.org/10.3390/metabo10070296 - 17 Jul 2020
Cited by 9 | Viewed by 1654
Abstract
Typical lipidomics methods incorporate a liquid–liquid extraction with LC–MS quantitation; however, the classic sample extraction methods are not high-throughput and do not perform well at extracting the full range of lipids especially, the relatively polar species (e.g., acyl-carnitines and glycosphingolipids). In this manuscript, [...] Read more.
Typical lipidomics methods incorporate a liquid–liquid extraction with LC–MS quantitation; however, the classic sample extraction methods are not high-throughput and do not perform well at extracting the full range of lipids especially, the relatively polar species (e.g., acyl-carnitines and glycosphingolipids). In this manuscript, we present a novel sample extraction protocol, which produces a single phase supernatant suitable for high-throughput applications that offers greater performance in extracting lipids across the full spectrum of species. We applied this lipidomics pipeline to a ruminant fat dose–response study to initially compare and validate the different extraction protocols but also to investigate complex lipid biomarkers of ruminant fat intake (adjoining onto simple odd chain fatty acid correlations). We have found 100 lipids species with a strong correlation with ruminant fat intake. This novel sample extraction along with the LC–MS pipeline have shown to be sensitive, robust and hugely informative (>450 lipids species semi-quantified): with a sample preparation throughput of over 100 tissue samples per day and an estimated ~1000 biological fluid samples per day. Thus, this work facilitating both the epidemiological involvement of ruminant fat, research into odd chain lipids and also streamlining the field of lipidomics (both by sample preparation methods and data presentation). Full article
(This article belongs to the Special Issue Advances in Lipidomics: Biomedicine, Nutrients and Methodology)
Show Figures

Graphical abstract

Article
Application of Multiblock Analysis on Small Metabolomic Multi-Tissue Dataset
Metabolites 2020, 10(7), 295; https://doi.org/10.3390/metabo10070295 - 17 Jul 2020
Cited by 1 | Viewed by 911
Abstract
Data integration has been proven to provide valuable information. The information extracted using data integration in the form of multiblock analysis can pinpoint both common and unique trends in the different blocks. When working with small multiblock datasets the number of possible integration [...] Read more.
Data integration has been proven to provide valuable information. The information extracted using data integration in the form of multiblock analysis can pinpoint both common and unique trends in the different blocks. When working with small multiblock datasets the number of possible integration methods is drastically reduced. To investigate the application of multiblock analysis in cases where one has a few number of samples and a lack of statistical power, we studied a small metabolomic multiblock dataset containing six blocks (i.e., tissue types), only including common metabolites. We used a single model multiblock analysis method called the joint and unique multiblock analysis (JUMBA) and compared it to a commonly used method, concatenated principal component analysis (PCA). These methods were used to detect trends in the dataset and identify underlying factors responsible for metabolic variations. Using JUMBA, we were able to interpret the extracted components and link them to relevant biological properties. JUMBA shows how the observations are related to one another, the stability of these relationships, and to what extent each of the blocks contribute to the components. These results indicate that multiblock methods can be useful even with a small number of samples. Full article
(This article belongs to the Section Bioinformatics and Data Analysis)
Show Figures

Figure 1

Article
A Simple GC-MS/MS Method for Determination of Smoke Taint-Related Volatile Phenols in Grapes
Metabolites 2020, 10(7), 294; https://doi.org/10.3390/metabo10070294 - 17 Jul 2020
Cited by 8 | Viewed by 1566
Abstract
Volatile phenols (VPs) derived from smoke-exposed grapes are known to confer a smoky flavor to wine. Current methods for determination of VPs in grape berries either involve complex sample purification/derivatization steps or employ two analytical platforms for free and bound VP fractions. We [...] Read more.
Volatile phenols (VPs) derived from smoke-exposed grapes are known to confer a smoky flavor to wine. Current methods for determination of VPs in grape berries either involve complex sample purification/derivatization steps or employ two analytical platforms for free and bound VP fractions. We report here a simple gas chromatography-tandem mass spectrometry (GC-MS/MS) method for quantification of both free and bound VPs in grapes, based on optimized (1) GC-MS/MS parameters, (2) an analyte extraction procedure, and (3) phenol glycoside hydrolysis conditions. Requiring neither sample cleanup nor a derivatization step, this method is sensitive (LOD ≤ 1 ng/g berries) and reproducible (RSD < 12% for repeated analyses) and is expected to significantly reduce the sample turnover time for smoke taint detection in vineyards. Full article
(This article belongs to the Special Issue Phenolic Compounds and Metabolome)
Show Figures

Figure 1

Article
An NMR Metabolomics Approach to Investigate Factors Affecting the Yoghurt Fermentation Process and Quality
Metabolites 2020, 10(7), 293; https://doi.org/10.3390/metabo10070293 - 17 Jul 2020
Cited by 9 | Viewed by 1459
Abstract
A great number of factors can influence milk fermentation for yoghurt production such as fermentation conditions, starter cultures and milk characteristics. It is important for dairy companies to know the best combinations of these parameters for a controlled fermentation and for the desired [...] Read more.
A great number of factors can influence milk fermentation for yoghurt production such as fermentation conditions, starter cultures and milk characteristics. It is important for dairy companies to know the best combinations of these parameters for a controlled fermentation and for the desired qualities of yoghurt. This study investigates the use of a 1H-NMR metabolomics approach to monitor the changes in milk during fermentation from time 0 to 24 h, taking samples every hour in the first 8 h and then at the end-point at 24 h. Three different starter cultures (L. delbrueckii ssp. bulgaricus, S. thermophilus and their combination) were used and two different heat treatments (99 or 105 °C) were applied to milk. The results clearly show the breakdown of proteins and lactose as well as the concomitant increase in acetate, lactate and citrate during fermentation. Formate is found at different initial concentrations depending on the heat treatment of the milk and its different time trajectory depends on the starter cultures: Lactobacillus cannot produce formate, but needs it for growth, whilst Streptococcus is able to produce formate from pyruvate, therefore promoting the symbiotic relationship between the two strains. On the other hand, Lactobacillus can hydrolyze milk proteins into amino acids, enriching the quality of the final product. In this way, better insight into the protocooperation of lactic acid bacteria strains and information on the impact of a greater heat treatment in the initial matrix were obtained. The global chemical view on the fermentations provided using NMR is key information for yoghurt producers and companies producing starter cultures. Full article
(This article belongs to the Special Issue Metabolomic Analysis in Food Science)
Show Figures

Graphical abstract

Article
Optimized Protocol for the In Situ Derivatization of Glutathione with N-Ethylmaleimide in Cultured Cells and the Simultaneous Determination of Glutathione/Glutathione Disulfide Ratio by HPLC-UV-QTOF-MS
Metabolites 2020, 10(7), 292; https://doi.org/10.3390/metabo10070292 - 17 Jul 2020
Cited by 7 | Viewed by 1434
Abstract
Glutathione (GSH) and glutathione disulfide (GSSG) are commonly used to assess the oxidative status of a biological system. Various protocols are available for the analysis of GSH and GSSG in biomedical specimens. In this study, we present an optimized protocol for the in [...] Read more.
Glutathione (GSH) and glutathione disulfide (GSSG) are commonly used to assess the oxidative status of a biological system. Various protocols are available for the analysis of GSH and GSSG in biomedical specimens. In this study, we present an optimized protocol for the in situ derivatization of GSH with N-ethylmaleimide (NEM) to prevent GSH autooxidation, and thus to preserve the GSH/GSSG ratio during sample preparation. The protocol comprises the incubation of cells in NEM containing phosphate buffered saline (PBS), followed by metabolite extraction with 80% methanol. Further, to preserve the use of QTOF-MS, which may lack the linear dynamic range required for the simultaneous quantification of GSH and GSSG in non-targeted metabolomics, we combined liquid chromatographic separation with the online monitoring of UV absorbance of GS-NEM at 210 nm and the detection of GSSG and its corresponding stable isotope-labeled internal standard by QTOF-MS operated with a 10 Da Q1 window. The limit of detection (LOD) for GS-NEM was 7.81 µM and the linear range extended from 15.63 µM to 1000 µM with a squared correlation coefficient R2 of 0.9997. The LOD for GSSG was 0.001 µM, and the lower limit of quantification (LLOQ) was 0.01 µM, with the linear (R2 = 0.9994) range extending up to 10 µM. The method showed high repeatability with intra-run and inter-run coefficients of variation of 3.48% and 2.51% for GS-NEM, and 3.11% and 3.66% for GSSG, respectively. Mean recoveries of three different spike-in levels (low, medium, high) of GSSG and GS-NEM were above 92%. Finally, the method was applied to the determination of changes in the GSH/GSSG ratio either in response to oxidative stress in cells lacking one or both monocarboxylate transporters MCT1 and MCT4, or in adaptation to the NADPH (nicotinamide adenine dinucleotide phosphate) consuming production of D-2-hydroxyglutarate in cells carrying mutations in the isocitrate dehydrogenase genes IDH1 and IDH2. Full article
Show Figures

Graphical abstract

Article
Exploring Metabolic Signature of Protein Energy Wasting in Hemodialysis Patients
Metabolites 2020, 10(7), 291; https://doi.org/10.3390/metabo10070291 - 16 Jul 2020
Cited by 2 | Viewed by 1214
Abstract
End-stage renal disease patients undergoing maintenance hemodialysis (HD) are vulnerable to the protein energy wasting (PEW) syndrome. Identification and diagnosis of PEW relies on clinical processes of judgment dependent on fulfilling multiple criteria drawn from serum biochemistry, weight status, predictive muscle mass, dietary [...] Read more.
End-stage renal disease patients undergoing maintenance hemodialysis (HD) are vulnerable to the protein energy wasting (PEW) syndrome. Identification and diagnosis of PEW relies on clinical processes of judgment dependent on fulfilling multiple criteria drawn from serum biochemistry, weight status, predictive muscle mass, dietary energy and protein intakes. Therefore, we sought to explore the biomarkers’ signature with plasma metabolites of PEW by using 1H-nuclear magnetic resonance for an untargeted metabolomics approach in the HD population, to understand metabolic alteration of PEW. In this case-controlled study, a total of 53 patients undergoing chronic HD were identified having PEW based on established diagnostic criteria and were age- and sex-matched with non-PEW (n = 53) HD patients. Fasting predialysis plasma samples were analyzed. Partial least square discriminant analysis demonstrated a significant separation between groups for specific metabolic pattern alterations. Further quantitative analysis showed that the level of 3-hydroxybutyrate, acetate, arabinose, maltose, ribose, sucrose and tartrate were significantly increased whilst creatinine was significantly decreased (all p < 0.05) in PEW subjects. Pathway analysis indicated that PEW-related metabolites reflected perturbations in fatty acid mechanism and induction of glyoxylate and dicarboxylate pathway attributed to gluconeogenesis. These results provide preliminary data in understanding metabolic alteration of PEW and corresponding abnormal metabolites that could potentially serve as biomarkers of PEW. Full article
Show Figures

Graphical abstract

Article
Urine Metabolome during Parturition
Metabolites 2020, 10(7), 290; https://doi.org/10.3390/metabo10070290 - 16 Jul 2020
Cited by 1 | Viewed by 1026
Abstract
In recent years, some studies have described metabolic changes during human childbirth labor. Metabolomics today is recognized as a powerful approach in a prenatal research context, since it can provide detailed information during pregnancy and it may enable the identification of biomarkers with [...] Read more.
In recent years, some studies have described metabolic changes during human childbirth labor. Metabolomics today is recognized as a powerful approach in a prenatal research context, since it can provide detailed information during pregnancy and it may enable the identification of biomarkers with potential diagnostic or predictive. This is an observational, longitudinal, prospective cohort study of a total of 51 serial urine samples from 15 healthy pregnant women, aged 29–40 years, which were collected before the onset of labor (out of labor, OL). In the same women, during labor (in labor or dilating phase, IL-DP). Samples were analyzed by hydrophilic interaction ultra-performance liquid chromatography coupled with mass spectrometry (HILIC-UPLC-MS), a highly sensitive, accurate, and unbiased approach. Metabolites were then subjected to multivariate statistical analysis and grouped by metabolic pathway. This method was used to identify the potential biomarkers. The top 20 most discriminative metabolites contributing to the complete separation of OL and IL-DP were identified. Urinary metabolites displaying the largest differences between OL and IL-DP belonged to steroid hormone, particularly conjugated estrogens and amino acids much of this difference is determined by the fetal contribution. In addition, our results highlighted the efficacy of using urine samples instead of more invasive techniques to evaluate the difference in metabolic analysis between OL and IL-DP. Full article
Show Figures

Graphical abstract

Review
Metabolic Reprogramming of Chemoresistant Cancer Cells and the Potential Significance of Metabolic Regulation in the Reversal of Cancer Chemoresistance
Metabolites 2020, 10(7), 289; https://doi.org/10.3390/metabo10070289 - 16 Jul 2020
Cited by 29 | Viewed by 1552
Abstract
Metabolic reprogramming is one of the hallmarks of tumors. Alterations of cellular metabolism not only contribute to tumor development, but also mediate the resistance of tumor cells to antitumor drugs. The metabolic response of tumor cells to various chemotherapy drugs can be analyzed [...] Read more.
Metabolic reprogramming is one of the hallmarks of tumors. Alterations of cellular metabolism not only contribute to tumor development, but also mediate the resistance of tumor cells to antitumor drugs. The metabolic response of tumor cells to various chemotherapy drugs can be analyzed by metabolomics. Although cancer cells have experienced metabolic reprogramming, the metabolism of drug resistant cancer cells has been further modified. Metabolic adaptations of drug resistant cells to chemotherapeutics involve redox, lipid metabolism, bioenergetics, glycolysis, polyamine synthesis and so on. The proposed metabolic mechanisms of drug resistance include the increase of glucose and glutamine demand, active pathways of glutaminolysis and glycolysis, promotion of NADPH from the pentose phosphate pathway, adaptive mitochondrial reprogramming, activation of fatty acid oxidation, and up-regulation of ornithine decarboxylase for polyamine production. Several genes are associated with metabolic reprogramming and drug resistance. Intervening regulatory points described above or targeting key genes in several important metabolic pathways may restore cell sensitivity to chemotherapy. This paper reviews the metabolic changes of tumor cells during the development of chemoresistance and discusses the potential of reversing chemoresistance by metabolic regulation. Full article
Show Figures

Figure 1

Article
Metabolism of the Cyanogenic Glucosides in Developing Flax: Metabolic Analysis, and Expression Pattern of Genes
Metabolites 2020, 10(7), 288; https://doi.org/10.3390/metabo10070288 - 14 Jul 2020
Cited by 7 | Viewed by 1124
Abstract
Cyanogenic glucosides (CG), the monoglycosides linamarin and lotaustralin, as well as the diglucosides linustatin and neolinustatin, have been identified in flax. The roles of CG and hydrogen cyanide (HCN), specifically the product of their breakdown, differ and are understood only to a certain [...] Read more.
Cyanogenic glucosides (CG), the monoglycosides linamarin and lotaustralin, as well as the diglucosides linustatin and neolinustatin, have been identified in flax. The roles of CG and hydrogen cyanide (HCN), specifically the product of their breakdown, differ and are understood only to a certain extent. HCN is toxic to aerobic organisms as a respiratory inhibitor and to enzymes containing heavy metals. On the other hand, CG and HCN are important factors in the plant defense system against herbivores, insects and pathogens. In this study, fluctuations in CG levels during flax growth and development (using UPLC) and the expression of genes encoding key enzymes for their metabolism (valine N-monooxygenase, linamarase, cyanoalanine nitrilase and cyanoalanine synthase) using RT-PCR were analyzed. Linola cultivar and transgenic plants characterized by increased levels of sulfur amino acids were analyzed. This enabled the demonstration of a significant relationship between the cyanide detoxification process and general metabolism. Cyanogenic glucosides are used as nitrogen-containing precursors for the synthesis of amino acids, proteins and amines. Therefore, they not only perform protective functions against herbivores but are general plant growth regulators, especially since changes in their level have been shown to be strongly correlated with significant stages of plant development. Full article
(This article belongs to the Special Issue Metabolomics in Plant Environmental Physiology)
Show Figures

Figure 1

Article
Ethyl Pyruvate Increases Post-Ischemic Levels of Mitochondrial Energy Metabolites: A 13C-Labeled Cerebral Microdialysis Study
Metabolites 2020, 10(7), 287; https://doi.org/10.3390/metabo10070287 - 13 Jul 2020
Cited by 3 | Viewed by 1319
Abstract
Mitochondrial dysfunction after transient cerebral ischemia can be monitored by cerebral microdialysis (CMD) using changes in the lactate and pyruvate concentrations and ratio. Other metabolites associated with mitochondrial (dys)function are, e.g., tricyclic acid (TCA) and purine metabolites. Ethyl pyruvate (EP) is a putative [...] Read more.
Mitochondrial dysfunction after transient cerebral ischemia can be monitored by cerebral microdialysis (CMD) using changes in the lactate and pyruvate concentrations and ratio. Other metabolites associated with mitochondrial (dys)function are, e.g., tricyclic acid (TCA) and purine metabolites. Ethyl pyruvate (EP) is a putative neuroprotectant, supposedly targeting mitochondrial energy metabolism, but its effect on cerebral energy metabolism has never been described using microdialysis. In this study we monitored the metabolic effects of EP in the endothelin-1 (ET-1) rat model using perfusion with 13C-succinate and analysis of endogenous and 13C-labeled metabolites in the dialysates by liquid chromatography-mass spectrometry (LC-MS). Adult Sprague Dawley rats (n = 27 of which n = 11 were included in the study) were subjected to the microdialysis experiments. Microdialysis probes were perfused with 13C-labeled succinate (1 mM), and striatal dialysates were collected at 30 min intervals before induction of the insult, during intracerebral application of ET-1, and during intravenous treatment with either EP (40 mg/kg) or placebo, which was administered immediately after the insult. The rats were subjected to transient cerebral ischemia by unilateral microinjection of ET-1 in the piriform cortex, causing vasoconstriction of the medial cerebral artery. Monitoring was continued for 5 h after reperfusion, and levels of endogenous and 13C-labeled energy metabolites before and after ischemia-reperfusion were compared in EP-treated and control groups. Infarct volumes were assessed after 24 h. In both the EP-treated and placebo groups, ET-1-induced vasoconstriction resulted in a transient depression of interstitial glucose and elevation of lactate in the ipsilateral striatum. In the reperfusion phase, the concentrations of labeled malate, isocitrate, and lactate as well as endogenous xanthine were significantly higher in the EP-group than in the placebo-group: (mean ± SEM) labeled malate: 39.5% ± 14.9, p = 0.008; labeled isocitrate: 134.8% ± 67.9, p = 0.047; labeled lactate: 61% ± 22.0, p = 0.007; and endogenous xanthine: 93.9% ± 28.3, p = 0.0009. In the placebo group, significantly elevated levels of uridine were observed (mean ± SEM) 32.5% ± 12.7, p = 0.01. Infarct volumes were not significantly different between EP-treated and placebo groups, p = 0.4679. CMD labeled with 13C-succinate enabled detection of ischemic induction and EP treatment effects in the ET-1 rat model of transient focal cerebral ischemia. EP administered as a single intravenous bolus in the reperfusion-phase after transient cerebral ischemia increased de novo synthesis of several key intermediate energy metabolites (13C-malate, 13C-isocitrate, and endogenous xanthine). In summary, mitochondria process 13C-succinate more effectively after EP treatment. Full article
(This article belongs to the Special Issue Cerebral Metabolism)
Show Figures

Figure 1

Review
Find the Needle in the Haystack, Then Find It Again: Replication and Validation in the ‘Omics Era
Metabolites 2020, 10(7), 286; https://doi.org/10.3390/metabo10070286 - 12 Jul 2020
Cited by 6 | Viewed by 1214
Abstract
Advancements in high-throughput technologies have made it feasible to study thousands of biological pathways simultaneously for a holistic assessment of health and disease risk via ‘omics platforms. A major challenge in ‘omics research revolves around the reproducibility of findings—a feat that hinges upon [...] Read more.
Advancements in high-throughput technologies have made it feasible to study thousands of biological pathways simultaneously for a holistic assessment of health and disease risk via ‘omics platforms. A major challenge in ‘omics research revolves around the reproducibility of findings—a feat that hinges upon balancing false-positive associations with generalizability. Given the foundational role of reproducibility in scientific inference, replication and validation of ‘omics findings are cornerstones of this effort. In this narrative review, we define key terms relevant to replication and validation, present issues surrounding each concept with historical and contemporary examples from genomics (the most well-established and upstream ‘omics), discuss special issues and unique considerations for replication and validation in metabolomics (an emerging field and most downstream ‘omics for which best practices remain yet to be established), and make suggestions for future research leveraging multiple ‘omics datasets. Full article
(This article belongs to the Special Issue Integrative-Metabolomics in Epidemiological Studies)
Review
The Pentose Phosphate Pathway Dynamics in Cancer and Its Dependency on Intracellular pH
Metabolites 2020, 10(7), 285; https://doi.org/10.3390/metabo10070285 - 11 Jul 2020
Cited by 32 | Viewed by 3002
Abstract
The Pentose Phosphate Pathway (PPP) is one of the key metabolic pathways occurring in living cells to produce energy and maintain cellular homeostasis. Cancer cells have higher cytoplasmic utilization of glucose (glycolysis), even in the presence of oxygen; this is known as the [...] Read more.
The Pentose Phosphate Pathway (PPP) is one of the key metabolic pathways occurring in living cells to produce energy and maintain cellular homeostasis. Cancer cells have higher cytoplasmic utilization of glucose (glycolysis), even in the presence of oxygen; this is known as the “Warburg Effect”. However, cytoplasmic glucose utilization can also occur in cancer through the PPP. This pathway contributes to cancer cells by operating in many different ways: (i) as a defense mechanism via the reduced form of nicotinamide adenine dinucleotide phosphate (NADPH) to prevent apoptosis, (ii) as a provision for the maintenance of energy by intermediate glycolysis, (iii) by increasing genomic material to the cellular pool of nucleic acid bases, (iv) by promoting survival through increasing glycolysis, and so increasing acid production, and (v) by inducing cellular proliferation by the synthesis of nucleic acid, fatty acid, and amino acid. Each step of the PPP can be upregulated in some types of cancer but not in others. An interesting aspect of this metabolic pathway is the shared regulation of the glycolytic and PPP pathways by intracellular pH (pHi). Indeed, as with glycolysis, the optimum activity of the enzymes driving the PPP occurs at an alkaline pHi, which is compatible with the cytoplasmic pH of cancer cells. Here, we outline each step of the PPP and discuss its possible correlation with cancer. Full article
(This article belongs to the Section Cell Metabolism)
Show Figures

Figure 1

Article
Changes in Metabolites During an Oral Glucose Tolerance Test in Early and Mid-Pregnancy: Findings from the PEARLS Randomized, Controlled Lifestyle Trial
Metabolites 2020, 10(7), 284; https://doi.org/10.3390/metabo10070284 - 10 Jul 2020
Cited by 1 | Viewed by 1385
Abstract
The oral glucose tolerance test (OGTT) is used to diagnose gestational and other types of diabetes. We examined metabolite changes during an OGTT, and how a comprehensive diet and physical activity intervention may influence these changes in a population of overweight/obese Hispanic pregnant [...] Read more.
The oral glucose tolerance test (OGTT) is used to diagnose gestational and other types of diabetes. We examined metabolite changes during an OGTT, and how a comprehensive diet and physical activity intervention may influence these changes in a population of overweight/obese Hispanic pregnant women. Integration of changes in metabolites during an OGTT may help us gain preliminary insights into how glucose metabolism changes during pregnancy. Among women from the Pregnancy and EARly Lifestyle improvement Study (PEARLS), we measured metabolites during a multipoint OGTT (fasting, 30, 60 and 120 min) at early and mid-pregnancy. Metabolite levels were measured by liquid chromatography–mass spectrometry in plasma samples in the lifestyle intervention (n = 13) and control (n = 16) arms of the study. A total of 65 candidate metabolites were selected that displayed changes during an OGTT in previous studies. Paired and unpaired t-tests were used to examine differences in Δfast-120 min: (1) at early and mid-pregnancy; and (2) by intervention assignment. We applied principal component analysis (PCA) to identify those metabolites that differed by intervention assignment and OGTT time points. Most of the characteristic changes in metabolites post-OGTT were similar at both gestational time points. PCA identified characteristic metabolite patterns associated with OGTT time points at both early and mid-pregnancy. These metabolites included ketone bodies, tryptophan, acyl carnitines, polyunsaturated fatty acids, and biomarkers related to bile acid, urea cycle, arginine, and proline metabolism. PCA identified distinct Δfast-120 min in fatty acid, acyl carnitine, bile acid, ketone body, and amino acid levels at mid- compared to early pregnancy. Participants in the intervention group did not display mean decreases in Δfast-120 min of several long-chain acyl carnitines that were observed in the control group. These findings provide preliminary insight into metabolites, whose role in increased insulin resistance during pregnancy, should be explored further in future studies. Full article
(This article belongs to the Special Issue Integrative-Metabolomics in Epidemiological Studies)
Show Figures

Figure 1

Review
Transcriptional Regulation in Non-Alcoholic Fatty Liver Disease
Metabolites 2020, 10(7), 283; https://doi.org/10.3390/metabo10070283 - 09 Jul 2020
Cited by 14 | Viewed by 1852
Abstract
Obesity is the primary risk factor for the pathogenesis of non-alcoholic fatty liver disease (NAFLD), the worldwide prevalence of which continues to increase dramatically. The liver plays a pivotal role in the maintenance of whole-body lipid and glucose homeostasis. This is mainly mediated [...] Read more.
Obesity is the primary risk factor for the pathogenesis of non-alcoholic fatty liver disease (NAFLD), the worldwide prevalence of which continues to increase dramatically. The liver plays a pivotal role in the maintenance of whole-body lipid and glucose homeostasis. This is mainly mediated by the transcriptional activation of hepatic pathways that promote glucose and lipid production or utilization in response to the nutritional state of the body. However, in the setting of chronic excessive nutrition, the dysregulation of hepatic transcriptional machinery promotes lipid accumulation, inflammation, metabolic stress, and fibrosis, which culminate in NAFLD. In this review, we provide our current understanding of the transcription factors that have been linked to the pathogenesis and progression of NAFLD. Using publicly available transcriptomic data, we outline the altered activity of transcription factors among humans with NAFLD. By expanding this analysis to common experimental mouse models of NAFLD, we outline the relevance of mouse models to the human pathophysiology at the transcriptional level. Full article
(This article belongs to the Special Issue Metabolism and Metabolomics of Liver in Health and Disease)
Show Figures

Graphical abstract

Article
Development and Validation of a Highly Sensitive LC-MS/MS Method for the Analysis of Bile Acids in Serum, Plasma, and Liver Tissue Samples
Metabolites 2020, 10(7), 282; https://doi.org/10.3390/metabo10070282 - 09 Jul 2020
Cited by 10 | Viewed by 1833
Abstract
Bile acids control lipid homeostasis by regulating uptake from food and excretion. Additionally, bile acids are bioactive molecules acting through receptors and modulating various physiological processes. Impaired bile acid homeostasis is associated with several diseases and drug-induced liver injury. Individual bile acids may [...] Read more.
Bile acids control lipid homeostasis by regulating uptake from food and excretion. Additionally, bile acids are bioactive molecules acting through receptors and modulating various physiological processes. Impaired bile acid homeostasis is associated with several diseases and drug-induced liver injury. Individual bile acids may serve as disease and drug toxicity biomarkers, with a great demand for improved bile acid quantification methods. We developed, optimized, and validated an LC-MS/MS method for quantification of 36 bile acids in serum, plasma, and liver tissue samples. The simultaneous quantification of important free and taurine- and glycine-conjugated bile acids of human and rodent species has been achieved using a simple workflow. The method was applied to a mouse model of statin-induced myotoxicity to assess a possible role of bile acids. Treatment of mice for three weeks with 5, 10, and 25 mg/kg/d simvastatin, causing adverse skeletal muscle effects, did not alter plasma and liver tissue bile acid profiles, indicating that bile acids are not involved in statin-induced myotoxicity. In conclusion, the established LC-MS/MS method enables uncomplicated sample preparation and quantification of key bile acids in serum, plasma, and liver tissue of human and rodent species to facilitate future studies of disease mechanisms and drug-induced liver injury. Full article
Show Figures

Graphical abstract

Article
Changes in the Fecal Metabolome Are Associated with Feeding Fiber Not Health Status in Cats with Chronic Kidney Disease
Metabolites 2020, 10(7), 281; https://doi.org/10.3390/metabo10070281 - 09 Jul 2020
Cited by 4 | Viewed by 1250
Abstract
The objective was to determine the effects of feeding different fiber sources to cats with chronic kidney disease (CKD) compared with healthy cats (both n = 10) on fecal metabolites. A cross-over within split-plot study design was performed using healthy and CKD cats [...] Read more.
The objective was to determine the effects of feeding different fiber sources to cats with chronic kidney disease (CKD) compared with healthy cats (both n = 10) on fecal metabolites. A cross-over within split-plot study design was performed using healthy and CKD cats (IRIS stage 1, 2, and 3). After cats were fed a complete and balanced dry food designed to aid in the management of renal disease for 14 days during a pre-trial period, they were randomly assigned to two fiber treatments for 4 weeks each. The treatment foods were formulated similar to pre-trial food and contained 0.500% betaine, 0.586% oat beta glucan, and either 0.407% short chain fructooligosaccharides (scFOS) fiber or 3.44% apple pomace. Both treatment foods had similar crude fiber (2.0 and 2.1% for scFOS and apple pomace, respectively) whereas soluble fiber was 0.8 and 1.6%, respectively. At baseline, CKD had very little impact on the fecal metabolome. After feeding both fiber sources, some fecal metabolite concentrations were significantly different compared with baseline. Many fecal uremic toxins decreased, although in healthy cats some increased; and some more so when feeding apple pomace compared with scFOS, e.g., hippurate, 4-hydroxyhippurate, and 4-methylcatechol sulfate; the latter was also increased in CKD cats. Changes in secondary bile acid concentrations were more numerous in healthy compared with CKD cats, and cats in both groups had greater increases in some secondary bile acids after consuming apple pomace compared with scFOS, e.g., tauroursodeoxycholate and hyocholate. Although changes associated with feeding fiber were more significant than changes associated with disease status, differential modulation of the gut-kidney axis using dietary fiber may benefit cats. Full article
(This article belongs to the Section Nutrition and Metabolism)
Show Figures

Figure 1

Article
Potential Metabolite Nymphayol Isolated from Water Lily (Nymphaea stellata) Flower Inhibits MCF-7 Human Breast Cancer Cell Growth via Upregulation of Cdkn2a, pRb2, p53 and Downregulation of PCNA mRNA Expressions
Metabolites 2020, 10(7), 280; https://doi.org/10.3390/metabo10070280 - 08 Jul 2020
Cited by 2 | Viewed by 1184
Abstract
Controlled production of cyclin dependent kinases (CDK) and stabilization of tumor suppressor genes are the most important factors involved in preventing carcinogenesis. The present study aimed to explore the cyclin dependent apoptotic effect of nymphayol on breast cancer MCF-7 cells. In our previous [...] Read more.
Controlled production of cyclin dependent kinases (CDK) and stabilization of tumor suppressor genes are the most important factors involved in preventing carcinogenesis. The present study aimed to explore the cyclin dependent apoptotic effect of nymphayol on breast cancer MCF-7 cells. In our previous study, we isolated the crystal from a chloroform extract of Nymphaea stellata flower petals and it was confirmed as nymphayol (17-(hexan-2-yl)-10,13-dimethylhexadecahydro-1H-cyclopenta[a]phenanthren-3-ol) using x-ray diffraction (XRD), Fourier transform infrared (FTIR), and mass spectroscopy (MS) methods. The cytotoxic effect of nymphayol on MCF-7 cells were analyzed using the 3-(4,5-dimethylthiazol-2yl)-2,5-diphenyl tetrazolium bromide (MTT) assay. The cellular and nuclear damage was determined using propidium iodide (PI) and acridine orange/ethidium bromide (AO/ErBr) staining. Tumor suppressor and apoptosis related mRNA transcript levels were determined using real-time polymerase chain reaction (RT-PCR). Nymphayol potentially inhibits MCF-7 cell viability up to 78%, and the IC50 value was observed as 2.8 µM in 24 h and 1.4 µM in 48 h. Treatment with nymphayol significantly increased reactive oxygen species (ROS) level and the tunnel assay confirmed DNA damage. We found characteristically 76% apoptotic cells and 9% necrotic cells in PI and AO/ErBr staining after 48 h treatment with 2.8 µM of nymphayol. Gene expression analysis confirmed significantly (p ≤ 0.001) increased mRNA levels of cyclin dependent kinase inhibitor 2A (Cdkn2a), retinoblastoma protein 2 (pRb2), p53, nuclear factor erythroid 2-factor 2 (Nrf2), caspase-3, and decreased B-cell lymphoma 2 (Bcl-2), murine double minute 2 (mdm2), and proliferating cell nuclear antigen (PCNA) expression after 48 h. Nymphayol effectively inhibited breast cancer cell viability, and is associated with early expression of Cdkn2a, pRb2, and activation of p53 and caspases. Full article
(This article belongs to the Section Pharmacology and Drug Metabolism)
Show Figures

Figure 1

Review
Regulatory T Cell Metabolism in Atherosclerosis
Metabolites 2020, 10(7), 279; https://doi.org/10.3390/metabo10070279 - 08 Jul 2020
Cited by 8 | Viewed by 1523
Abstract
Regulatory T cells (Tregs) are capable of suppressing excessive immune responses to prevent autoimmunity and chronic inflammation. Decreased numbers of Tregs and impaired suppressive function are associated with the progression of atherosclerosis, a chronic inflammatory disease of the arterial wall and the leading [...] Read more.
Regulatory T cells (Tregs) are capable of suppressing excessive immune responses to prevent autoimmunity and chronic inflammation. Decreased numbers of Tregs and impaired suppressive function are associated with the progression of atherosclerosis, a chronic inflammatory disease of the arterial wall and the leading cause of cardiovascular disease. Therefore, therapeutic strategies to improve Treg number or function could be beneficial to preventing atherosclerotic disease development. A growing body of evidence shows that intracellular metabolism of Tregs is a key regulator of their proliferation, suppressive function, and stability. Here we evaluate the role of Tregs in atherosclerosis, their metabolic regulation, and the links between their metabolism and atherosclerosis. Full article
Show Figures

Figure 1

Communication
Can We Trust Score Plots?
Metabolites 2020, 10(7), 278; https://doi.org/10.3390/metabo10070278 - 08 Jul 2020
Cited by 7 | Viewed by 1592
Abstract
In this paper, we discuss the validity of using score plots of component models such as partial least squares regression, especially when these models are used for building classification models, and models derived from partial least squares regression for discriminant analysis (PLS-DA). Using [...] Read more.
In this paper, we discuss the validity of using score plots of component models such as partial least squares regression, especially when these models are used for building classification models, and models derived from partial least squares regression for discriminant analysis (PLS-DA). Using examples and simulations, it is shown that the currently accepted practice of showing score plots from calibration models may give misleading interpretations. It is suggested and shown that the problem can be solved by replacing the currently used calibrated score plots with cross-validated score plots. Full article
Show Figures

Figure 1

Article
Early Perturbations in Glucose Utilization in Malaria-Infected Murine Erythrocytes, Liver and Brain Observed by Metabolomics
Metabolites 2020, 10(7), 277; https://doi.org/10.3390/metabo10070277 - 07 Jul 2020
Cited by 2 | Viewed by 885
Abstract
Investigation of glucose utilization during an infection is central to the study of energy metabolism. The heavy utilization of glucose by the malaria parasite, and the consequences of this process, have been investigated extensively. However, host glucose utilization during early infection has not [...] Read more.
Investigation of glucose utilization during an infection is central to the study of energy metabolism. The heavy utilization of glucose by the malaria parasite, and the consequences of this process, have been investigated extensively. However, host glucose utilization during early infection has not been explored to date. In a first attempt, this article investigates the changes in the host glucose utilization in Balb/c mice infected with Plasmodium berghei ANKA using 13C-labeled glucose infusion followed by NMR spectroscopy. The results suggested significant alterations of liver, brain and red blood cell (RBC) glucose utilization during early infection when the parasitemia was <1%. At the pathway level, we observed a decrease in the shunt metabolite 2,3-bisphosphoglycerate in the RBCs. Glycolysis and pathways associated with it, along with fatty acid unsaturation, were altered in the liver. Significant changes were observed in the central carbon metabolic pathways in the brain. These results have implications in understanding the host physiology during early infection and pave the way for detailed flux analysis of the proposed perturbed pathways. Full article
Show Figures

Graphical abstract

Article
A High-Throughput Method for the Comprehensive Analysis of Terpenes and Terpenoids in Medicinal Cannabis Biomass
Metabolites 2020, 10(7), 276; https://doi.org/10.3390/metabo10070276 - 06 Jul 2020
Cited by 7 | Viewed by 2839
Abstract
Cannabis and its secondary metabolite content have recently seen a surge in research interest. Cannabis terpenes and terpenoids in particular are increasingly the focus of research efforts due to the possibility of their contribution to the overall therapeutic effect of medicinal cannabis. Current [...] Read more.
Cannabis and its secondary metabolite content have recently seen a surge in research interest. Cannabis terpenes and terpenoids in particular are increasingly the focus of research efforts due to the possibility of their contribution to the overall therapeutic effect of medicinal cannabis. Current methodology to quantify terpenes in cannabis biomass mostly relies on large quantities of biomass, long extraction protocols, and long GC gradient times, often exceeding 60 min. They are therefore not easily applicable in the high-throughput environment of a cannabis breeding program. The method presented here, however, is based on a simple hexane extract from 40 mg of biomass, with 50 μg/mL dodecane as internal standard, and a gradient of less than 30 min. The method can detect 48 individual terpenes and terpenoids and was validated for selectivity, linearity, LOD/LOQ, precision, intermediate precision, and accuracy (recovery) for 22 terpenes and terpenoids. The validation parameters are comparable to previously published studies that employ significantly longer runtimes and/or more complex extraction protocols. It is currently being applied to medicinal cannabis precision breeding programs. Full article
(This article belongs to the Section Metabolomic Profiling Technology)
Show Figures

Graphical abstract

Article
Integrative Analysis of Metabolomic and Transcriptomic Profiles Uncovers Biological Pathways of Feed Efficiency in Pigs
Metabolites 2020, 10(7), 275; https://doi.org/10.3390/metabo10070275 - 06 Jul 2020
Cited by 4 | Viewed by 1320
Abstract
Feed efficiency (FE) is an economically important trait. Thus, reliable predictors would help to reduce the production cost and provide sustainability to the pig industry. We carried out metabolome-transcriptome integration analysis on 40 purebred Duroc and Landrace uncastrated male pigs to identify potential [...] Read more.
Feed efficiency (FE) is an economically important trait. Thus, reliable predictors would help to reduce the production cost and provide sustainability to the pig industry. We carried out metabolome-transcriptome integration analysis on 40 purebred Duroc and Landrace uncastrated male pigs to identify potential gene-metabolite interactions and explore the molecular mechanisms underlying FE. To this end, we applied untargeted metabolomics and RNA-seq approaches to the same animals. After data quality control, we used a linear model approach to integrate the data and find significant differently correlated gene-metabolite pairs separately for the breeds (Duroc and Landrace) and FE groups (low and high FE) followed by a pathway over-representation analysis. We identified 21 and 12 significant gene-metabolite pairs for each group. The valine-leucine-isoleucine biosynthesis/degradation and arginine-proline metabolism pathways were associated with unique metabolites. The unique genes obtained from significant metabolite-gene pairs were associated with sphingolipid catabolism, multicellular organismal process, cGMP, and purine metabolic processes. While some of the genes and metabolites identified were known for their association with FE, others are novel and provide new avenues for further research. Further validation of genes, metabolites, and gene-metabolite interactions in larger cohorts will elucidate the regulatory mechanisms and pathways underlying FE. Full article
(This article belongs to the Special Issue Metabolomic Applications in Animal Science)
Show Figures

Figure 1

Article
Modulation of Phenylalanine and Tyrosine Metabolism in HIV-1 Infected Patients with Neurocognitive Impairment: Results from a Clinical Trial
Metabolites 2020, 10(7), 274; https://doi.org/10.3390/metabo10070274 - 03 Jul 2020
Cited by 3 | Viewed by 1284
Abstract
To investigate the effects of oral bacteriotherapy on intestinal phenylalanine and tyrosine metabolism, in this longitudinal, double-arm trial, 15 virally suppressed HIV+ individuals underwent blood and fecal sample collection at baseline and after 6 months of oral bacteriotherapy. A baseline fecal sample was [...] Read more.
To investigate the effects of oral bacteriotherapy on intestinal phenylalanine and tyrosine metabolism, in this longitudinal, double-arm trial, 15 virally suppressed HIV+ individuals underwent blood and fecal sample collection at baseline and after 6 months of oral bacteriotherapy. A baseline fecal sample was collected from 15 healthy individuals and served as control group for the baseline levels of fecal phenylalanine and tyrosine. CD4 and CD8 immune activation (CD38+) was evaluated by flow cytometry. Amino acid evaluation on fecal samples was conducted by Proton Nuclear Magnetic Resonance. Results showed that HIV+ participants displayed higher baseline phenylalanine/tyrosine ratio values than healthy volunteers. A significand reduction in phenylalanine/tyrosine ratio and peripheral CD4+ CD38+ activation was observed at the end of oral bacteriotherapy. In conclusion, probiotics beneficially affect the immune activation of HIV+ individuals. Therefore, the restoration of intestinal amino acid metabolism could represent the mechanisms through which probiotics exert these desirable effects. Full article
(This article belongs to the Section Frontiers in Metabolomics)
Show Figures

Graphical abstract

Article
Surviving Starvation: Proteomic and Lipidomic Profiling of Nutrient Deprivation in the Smallest Known Free-Living Eukaryote
Metabolites 2020, 10(7), 273; https://doi.org/10.3390/metabo10070273 - 03 Jul 2020
Cited by 1 | Viewed by 1319
Abstract
Marine phytoplankton, comprising cyanobacteria, micro- and pico-algae are key to photosynthesis, oxygen production and carbon assimilation on Earth. The unicellular green picoalga Ostreococcus tauri holds a key position at the base of the green lineage of plants, which makes it an interesting model [...] Read more.
Marine phytoplankton, comprising cyanobacteria, micro- and pico-algae are key to photosynthesis, oxygen production and carbon assimilation on Earth. The unicellular green picoalga Ostreococcus tauri holds a key position at the base of the green lineage of plants, which makes it an interesting model organism. O. tauri has adapted to survive in low levels of nitrogen and phosphorus in the open ocean and also during rapid changes in the levels of these nutrients in coastal waters. In this study, we have employed untargeted proteomic and lipidomic strategies to investigate the molecular responses of O. tauri to low-nitrogen and low-phosphorus environments. In the absence of external nitrogen, there was an elevation in the expression of ammonia and urea transporter proteins together with an accumulation of triglycerides. In phosphate-limiting conditions, the expression levels of phosphokinases and phosphate transporters were increased, indicating an attempt to maximise scavenging opportunities as opposed to energy conservation conditions. The production of betaine lipids was also elevated, highlighting a shift away from phospholipid metabolism. This finding was supported by the putative identification of betaine synthase in O. tauri. This work offers additional perspectives on the complex strategies that underpin the adaptive processes of the smallest known free-living eukaryote to alterations in environmental conditions. Full article
Show Figures

Graphical abstract

Article
Metabolic Signatures of 10 Processed and Non-processed Meat Products after In Vitro Digestion
Metabolites 2020, 10(7), 272; https://doi.org/10.3390/metabo10070272 - 03 Jul 2020
Cited by 4 | Viewed by 1316
Abstract
The intake of processed meat has been associated with several adverse health outcomes such as type II diabetes and cancer; however, the mechanisms are not fully understood. A better knowledge of the metabolite profiles of different processed and non-processed meat products from this [...] Read more.
The intake of processed meat has been associated with several adverse health outcomes such as type II diabetes and cancer; however, the mechanisms are not fully understood. A better knowledge of the metabolite profiles of different processed and non-processed meat products from this heterogeneous food group could help in elucidating the mechanisms associated with these health effects. Thirty-three different commercial samples of ten processed and non-processed meat products were digested in triplicate with a standardized static in vitro digestion method in order to mimic profiles of small molecules formed in the gut upon digestion. A metabolomics approach based on high-resolution mass spectrometry was used to identify metabolite profiles specific to the various meat products. Processed meat products showed metabolite profiles clearly distinct from those of non-processed meat. Several discriminant features related to either specific ingredients or processing methods were identified. Those were, in particular, syringol compounds deposited in meat during smoking, biogenic amines formed during meat fermentation and piperine and related compounds characteristic of pepper used as an ingredient. These metabolites, characteristic of specific processed meat products, might be used as potential biomarkers of intake for these foods. They may also help in understanding the mechanisms linking processed meat intake and adverse health outcomes such as cancer. Full article
(This article belongs to the Section Food Metabolomics)
Show Figures

Graphical abstract

Article
Systematic Evaluation of Normalization Methods for Glycomics Data Based on Performance of Network Inference
Metabolites 2020, 10(7), 271; https://doi.org/10.3390/metabo10070271 - 02 Jul 2020
Cited by 6 | Viewed by 1575
Abstract
Glycomics measurements, like all other high-throughput technologies, are subject to technical variation due to fluctuations in the experimental conditions. The removal of this non-biological signal from the data is referred to as normalization. Contrary to other omics data types, a systematic evaluation of [...] Read more.
Glycomics measurements, like all other high-throughput technologies, are subject to technical variation due to fluctuations in the experimental conditions. The removal of this non-biological signal from the data is referred to as normalization. Contrary to other omics data types, a systematic evaluation of normalization options for glycomics data has not been published so far. In this paper, we assess the quality of different normalization strategies for glycomics data with an innovative approach. It has been shown previously that Gaussian Graphical Models (GGMs) inferred from glycomics data are able to identify enzymatic steps in the glycan synthesis pathways in a data-driven fashion. Based on this finding, here, we quantify the quality of a given normalization method according to how well a GGM inferred from the respective normalized data reconstructs known synthesis reactions in the glycosylation pathway. The method therefore exploits a biological measure of goodness. We analyzed 23 different normalization combinations applied to six large-scale glycomics cohorts across three experimental platforms: Liquid Chromatography-ElectroSpray Ionization-Mass Spectrometry (LC-ESI-MS), Ultra High Performance Liquid Chromatography with Fluorescence Detection (UHPLC-FLD), and Matrix Assisted Laser Desorption Ionization-Furier Transform Ion Cyclotron Resonance-Mass Spectrometry (MALDI-FTICR-MS). Based on our results, we recommend normalizing glycan data using the ‘Probabilistic Quotient’ method followed by log-transformation, irrespective of the measurement platform. This recommendation is further supported by an additional analysis, where we ranked normalization methods based on their statistical associations with age, a factor known to associate with glycomics measurements. Full article
(This article belongs to the Section Bioinformatics and Data Analysis)
Show Figures

Figure 1

Article
Serum Metabolomic Alterations Associated with Cesium-137 Internal Emitter Delivered in Various Dose Rates
Metabolites 2020, 10(7), 270; https://doi.org/10.3390/metabo10070270 - 30 Jun 2020
Cited by 3 | Viewed by 1022
Abstract
Our laboratory and others have use radiation metabolomics to assess responses in order to develop biomarkers reflecting exposure and level of injury. To expand the types of exposure and compare to previously published results, metabolomic analysis has been carried out using serum samples [...] Read more.
Our laboratory and others have use radiation metabolomics to assess responses in order to develop biomarkers reflecting exposure and level of injury. To expand the types of exposure and compare to previously published results, metabolomic analysis has been carried out using serum samples from mice exposed to 137Cs internal emitters. Animals were injected intraperitoneally with 137CsCl solutions of varying radioactivity, and the absorbed doses were calculated. To determine the dose rate effect, serum samples were collected at 2, 3, 5, 7, and 14 days after injection. Based on the time for each group receiving the cumulative dose of 4 Gy, the dose rate for each group was determined. The dose rates analyzed were 0.16 Gy/day (low), 0.69 Gy/day (medium), and 1.25 Gy/day (high). The results indicated that at a cumulative dose of 4 Gy, the low dose rate group had the least number of statistically significantly differential spectral features. Some identified metabolites showed common changes for different dose rates. For example, significantly altered levels of oleamide and sphingosine 1-phosphate were seen in all three groups. On the other hand, the intensity of three amino acids, Isoleucine, Phenylalanine and Arginine, significantly decreased only in the medium dose rate group. These findings have the potential to be used in assessing the exposure and the biological effects of internal emitters. Full article
(This article belongs to the Special Issue Metabolomics/Lipidomics in Radiation Research)
Show Figures

Figure 1

Previous Issue
Next Issue
Back to TopTop