Metabolites

14 pages, 1150 KiB

Open AccessEditor’s ChoiceArticle

Integration of Liver Glycogen and Triglyceride NMR Isotopomer Analyses Provides a Comprehensive Coverage of Hepatic Glucose and Fructose Metabolism

by Ivan Viegas, Giada Di Nunzio, Getachew D. Belew, Alejandra N. Torres, João G. Silva, Luis Perpétuo, Cristina Barosa, Ludgero C. Tavares and John G. Jones

Metabolites 2022, 12(11), 1142; https://doi.org/10.3390/metabo12111142 - 19 Nov 2022

Cited by 2 | Viewed by 3790

Abstract

Dietary glucose and fructose are both efficiently assimilated by the liver but a comprehensive measurement of this process starting from their conversion to sugar phosphates, involvement of the pentose phosphate pathway (PPP), and conversion to glycogen and lipid storage products, remains incomplete. Mice [...] Read more.

Dietary glucose and fructose are both efficiently assimilated by the liver but a comprehensive measurement of this process starting from their conversion to sugar phosphates, involvement of the pentose phosphate pathway (PPP), and conversion to glycogen and lipid storage products, remains incomplete. Mice were fed a chow diet supplemented with 35 g/100 mL drinking water of a 55/45 fructose/glucose mixture for 18 weeks. On the final night, the sugar mixture was enriched with either [U-¹³C]glucose or [U-¹³C]fructose, and deuterated water (²H₂O) was also administered. ¹³C-isotopomers representing newly synthesized hepatic glucose-6-phosphate (glucose-6-P), glycerol-3-phosphate, and lipogenic acetyl-CoA were quantified by ²H and ¹³C NMR analysis of post-mortem liver glycogen and triglyceride. These data were applied to a metabolic model covering glucose-6-P, PPP, triose-P, and de novo lipogenesis (DNL) fluxes. The glucose supplement was converted to glucose-6-P via the direct pathway, while the fructose supplement was metabolized by the liver to gluconeogenic triose-P via fructokinase–aldolase–triokinase. Glucose-6-P from all carbohydrate sources accounted for 40–60% of lipogenic acetyl-CoA and 10–12% was oxidized by the pentose phosphate pathway (PPP). The yield of NADPH from PPP flux accounted for a minority (~30%) of the total DNL requirement. In conclusion, this approach integrates measurements of glucose-6-P, PPP, and DNL fluxes to provide a holistic and informative assessment of hepatic glucose and fructose metabolism. Full article

(This article belongs to the Special Issue Advances in Metabolic Profiling of Biological Samples)

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19 pages, 3328 KiB

Open AccessEditor’s ChoiceArticle

Exposure to Environmentally Relevant Levels of PFAS Causes Metabolic Changes in the Freshwater Amphipod Austrochiltonia subtenuis

by Georgia M. Sinclair, Sara M. Long, Navneet Singh, Timothy L. Coggan, Matthew P. J. Askeland and Oliver A. H. Jones

Metabolites 2022, 12(11), 1135; https://doi.org/10.3390/metabo12111135 - 18 Nov 2022

Cited by 1 | Viewed by 2128

Abstract

Per and polyfluoroalkyl substances (PFAS) are of concern to environmental regulators due to their widespread occurrence, persistence and reported toxicity. However, little data exist on the effects of PFAS at environmentally relevant concentrations. The development of molecular markers for PFAS exposure would therefore [...] Read more.

Per and polyfluoroalkyl substances (PFAS) are of concern to environmental regulators due to their widespread occurrence, persistence and reported toxicity. However, little data exist on the effects of PFAS at environmentally relevant concentrations. The development of molecular markers for PFAS exposure would therefore be useful to better understand the environmental risks of these compounds. In this study, we assessed if such markers could be developed using Gas Chromatography–Mass Spectrometry-based metabolomics. We exposed the freshwater amphipod Austrochiltonia subtenuis to a range of environmentally relevant concentrations of perfluoro-octane sulfonic acid (PFOS), hexafluoropropylene oxide dimer acid (GenX) and perfluorohexanesulphonic acid (PFHxS) for 7 days at five concentrations. A metabolic response was detected in all concentrations and treatments even though the survival rates only differed significantly at the highest exposure levels. The metabolic response differed between compounds but all three PFAS induced changes in the levels of amino acids, fatty acids, and cholesterol, in line with the literature. PFOS was found to bioaccumulate. Both GenX and PFHxS were eliminated from the amphipods, but PFHxS was eliminated at a slower rate than GenX. This information improves our understanding of the sublethal effects of PFAS as well as their environmental fate and behaviour. Full article

(This article belongs to the Special Issue Integrated Systems Biology: Challenges and Future Perspectives)

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19 pages, 4054 KiB

Open AccessEditor’s ChoiceArticle

Multiparametric Magnetic Resonance Imaging and Metabolic Characterization of Patient-Derived Xenograft Models of Clear Cell Renal Cell Carcinoma

by Joao Piraquive Agudelo, Deepti Upadhyay, Dalin Zhang, Hongjuan Zhao, Rosalie Nolley, Jinny Sun, Shubhangi Agarwal, Robert A. Bok, Daniel B. Vigneron, James D. Brooks, John Kurhanewicz, Donna M. Peehl and Renuka Sriram

Metabolites 2022, 12(11), 1117; https://doi.org/10.3390/metabo12111117 - 15 Nov 2022

Cited by 2 | Viewed by 1497

Abstract

Patient-derived xenografts (PDX) are high-fidelity cancer models typically credentialled by genomics, transcriptomics and proteomics. Characterization of metabolic reprogramming, a hallmark of cancer, is less frequent. Dysregulated metabolism is a key feature of clear cell renal cell carcinoma (ccRCC) and authentic preclinical models are [...] Read more.

Patient-derived xenografts (PDX) are high-fidelity cancer models typically credentialled by genomics, transcriptomics and proteomics. Characterization of metabolic reprogramming, a hallmark of cancer, is less frequent. Dysregulated metabolism is a key feature of clear cell renal cell carcinoma (ccRCC) and authentic preclinical models are needed to evaluate novel imaging and therapeutic approaches targeting metabolism. We characterized 5 PDX from high-grade or metastatic ccRCC by multiparametric magnetic resonance imaging (MRI) and steady state metabolic profiling and flux analysis. Similar to MRI of clinical ccRCC, T₂-weighted images of orthotopic tumors of most PDX were homogeneous. The increased hyperintense (cystic) areas observed in one PDX mimicked the cystic phenotype typical of some RCC. The negligible hypointense (necrotic) areas of PDX grown under the highly vascularized renal capsule are beneficial for preclinical studies. Mean apparent diffusion coefficient (ADC) values were equivalent to those of ccRCC in human patients. Hyperpolarized (HP) [1-¹³C]pyruvate MRI of PDX showed high glycolytic activity typical of high-grade primary and metastatic ccRCC with considerable intra- and inter-tumoral variability, as has been observed in clinical HP MRI of ccRCC. Comparison of steady state metabolite concentrations and metabolic flux in [U-¹³C]glucose-labeled tumors highlighted the distinctive phenotypes of two PDX with elevated levels of numerous metabolites and increased fractional enrichment of lactate and/or glutamate, capturing the metabolic heterogeneity of glycolysis and the TCA cycle in clinical ccRCC. Culturing PDX cells and reimplanting to generate xenografts (XEN), or passaging PDX in vivo, altered some imaging and metabolic characteristics while transcription remained like that of the original PDX. These findings show that PDX are realistic models of ccRCC for imaging and metabolic studies but that the plasticity of metabolism must be considered when manipulating PDX for preclinical studies. Full article

(This article belongs to the Special Issue Imaging and Spectroscopic Based Methods to Understand Cancer Metabolism and Biology)

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15 pages, 2939 KiB

Open AccessEditor’s ChoiceArticle

Effects of Proteases from Pineapple and Papaya on Protein Digestive Capacity and Gut Microbiota in Healthy C57BL/6 Mice and Dose-Manner Response on Mucosal Permeability in Human Reconstructed Intestinal 3D Tissue Model

by Olha Kostiuchenko, Nadiia Kravchenko, Jan Markus, Stephen Burleigh, Olexandr Fedkiv, Ling Cao, Silvia Letasiova, Galyna Skibo, Frida Fåk Hållenius and Olena Prykhodko

Metabolites 2022, 12(11), 1027; https://doi.org/10.3390/metabo12111027 - 26 Oct 2022

Cited by 7 | Viewed by 2691

Abstract

Cysteine proteases obtained from the stem of pineapple or papaya latex, bromelain and papain, respectively, exhibit a broad spectrum of beneficial effects on human health. However, their effects on gut microbiota composition or dose-manner effects on the intestinal integrity of healthy tissue have [...] Read more.

Cysteine proteases obtained from the stem of pineapple or papaya latex, bromelain and papain, respectively, exhibit a broad spectrum of beneficial effects on human health. However, their effects on gut microbiota composition or dose-manner effects on the intestinal integrity of healthy tissue have not been evaluated. In this study, C57BL/6 young, healthy mice were fed bromelain or papain in a dose of 1 mg per animal/day for three consecutive days, followed by the assessment of digestive protein capacity, intestinal morphology and gut microbiota composition. Furthermore, a human reconstructed 3D tissue model EpiIntestinal (SMI-100) was used to study the effects of 1, 0.1 and 10 mg/mL doses of each enzyme on tissue integrity and mucosal permeability using TEER measurements and passage of Lucifer Yellow marker from the apical to the basolateral side of the mucosa. The results indicated that fruit proteases have the potential to modulate gut microbiota with decreasing abundance of Proteobacteria and increasing beneficial Akkermansia muciniphila. The enhancement of pancreatic trypsin was observed in bromelain and papain supplementation, while bromelain also increased the thickness of the ileal mucosa. Furthermore, an in vitro study showed a dose-dependent interruption in epithelial integrity, which resulted in increased paracellular permeability by the highest doses of enzymes. These findings define bromelain and papain as promising enzymatic supplementation for controlled enhancement of paracellular uptake when needed, together with beneficial effects on the gut microbiota. Full article

(This article belongs to the Special Issue Dietary Effects on Gut Microbial Metabolism and Intestinal Inflammation in Mammals)

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18 pages, 1500 KiB

Open AccessEditor’s ChoiceArticle

A Novel Ketone-Supplemented Diet Improves Recognition Memory and Hippocampal Mitochondrial Efficiency in Healthy Adult Mice

by Erin R. Saito, Cali E. Warren, Cameron M. Hanegan, John G. Larsen, Johannes D. du Randt, Mio Cannon, Jeremy Y. Saito, Rachel J. Campbell, Colin M. Kemberling, Gavin S. Miller, Jeffrey G. Edwards and Benjamin T. Bikman

Metabolites 2022, 12(11), 1019; https://doi.org/10.3390/metabo12111019 - 25 Oct 2022

Cited by 8 | Viewed by 7387

Abstract

Mitochondrial dysfunction and cognitive impairment are common symptoms in many neurologic and psychiatric disorders, as well as nonpathological aging. Ketones have been suggested as therapeutic for their efficacy in epilepsy and other brain pathologies such as Alzheimer’s disease and major depressive disorder. However, [...] Read more.

Mitochondrial dysfunction and cognitive impairment are common symptoms in many neurologic and psychiatric disorders, as well as nonpathological aging. Ketones have been suggested as therapeutic for their efficacy in epilepsy and other brain pathologies such as Alzheimer’s disease and major depressive disorder. However, their effects on cognitive function in healthy individuals is less established. Here, we explored the mitochondrial and performative outcomes of a novel eight-week ketone-supplemented ketogenic (KETO) diet in healthy adult male and female mice. In a novel object recognition test, KETO mice spent more time with the novel, compared to familiar, object, indicating an improvement in recognition memory. High-resolution respirometry on permeabilized hippocampal tissue returned significant reductions in mitochondrial O₂ consumption. No changes in ATP production were observed, yielding a significantly higher ATP:O₂ ratio, a measure of mitochondrial efficiency. Together, these findings demonstrate the KETO diet improves hippocampal mitochondrial efficiency. They add to a growing body of evidence that suggests ketones and ketogenic diets are neuroprotective and metabolically and cognitively relevant, even in healthy adults. They also suggest that ketogenic lifestyle changes may be effective strategies for protecting against cognitive decline associated with aging and disease. Full article

(This article belongs to the Special Issue The Metabolomic Landscape of Carbohydrate Restriction)

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10 pages, 1522 KiB

Open AccessEditor’s ChoiceArticle

Liver Fetuin-A at Initiation of Insulin Resistance

by Nicolas Lanthier, Valérie Lebrun, Olivier Molendi-Coste, Nico van Rooijen and Isabelle A. Leclercq

Metabolites 2022, 12(11), 1023; https://doi.org/10.3390/metabo12111023 - 25 Oct 2022

Cited by 9 | Viewed by 1727

Abstract

Hepatokines (liver secreted proteins with possible distant action) are emerging potential players in insulin resistance in type 2 diabetic patients. Here, we explored the effect of a high-fat diet on the expression of fetuin-A, one of those candidate liver proteins, and its relationship [...] Read more.

Hepatokines (liver secreted proteins with possible distant action) are emerging potential players in insulin resistance in type 2 diabetic patients. Here, we explored the effect of a high-fat diet on the expression of fetuin-A, one of those candidate liver proteins, and its relationship with liver macrophage activation. Mice were fed a normal diet or a high-fat diet for 3 days, known to initiate steatosis and liver insulin resistance. A preventive liver macrophage depletion was obtained by intravenous injection of clodronate-loaded liposomes. The mRNA and protein expression of fetuin-A was evaluated by qPCR, Western blot and immunofluorescence on different insulin-sensitive tissues (liver, adipose tissue, and muscle). Short-term high-fat diet-induced steatosis, liver macrophage activation, and hepatic insulin resistance together with a significantly increased expression of liver AHSG (α2-HS glycoprotein/fetuin-A) mRNA and serum fetuin-A concentration. On immunofluorescence, fetuin-A was mostly expressed in centrilobular hepatocytes. This increase in fetuin-A under high-fat diet was not evidenced in other peripheral insulin-sensitive tissues (skeletal muscle and adipose tissue). The mRNA expression of α2-HS glycoprotein was 800 times higher within the liver compared with the adipose tissue or the muscle. Liver macrophage depletion that significantly ameliorated insulin sensitivity was associated with a significant decrease in α2-HS glycoprotein mRNA expression. In conclusion, this study demonstrated liver fetuin-A overexpression at the initiation of high-fat diet feeding, concurrent with hepatic steatosis and insulin resistance. Targeting liver macrophages in this setting reduced liver α2-HS glycoprotein expression suggesting that fetuin-A acts as an hepatokine with proinsulin resistance effects. Full article

(This article belongs to the Special Issue Fatty Liver Index and Progression to Diabetes in Patients with Metabolic Syndrome)

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14 pages, 2145 KiB

Open AccessEditor’s ChoiceArticle

Identification of Metabolic Signature Associated with Idiopathic Inflammatory Myopathy Reveals Polyamine Pathway Alteration in Muscle Tissue

by Jihyun Kang, Jeong Yeon Kim, Youjin Jung, Seon Uk Kim, Eun Young Lee and Joo-Youn Cho

Metabolites 2022, 12(10), 1004; https://doi.org/10.3390/metabo12101004 - 21 Oct 2022

Cited by 3 | Viewed by 1532

Abstract

Idiopathic inflammatory myopathy (IIM) is hard to diagnose without a muscle biopsy. We aimed to identify a metabolite panel for IIM detection by metabolomics approach in serum samples and to explore the metabolomic signature in tissue samples from a mouse model. We obtained [...] Read more.

Idiopathic inflammatory myopathy (IIM) is hard to diagnose without a muscle biopsy. We aimed to identify a metabolite panel for IIM detection by metabolomics approach in serum samples and to explore the metabolomic signature in tissue samples from a mouse model. We obtained serum samples from IIM patients, ankylosing spondylitis (AS) patients, healthy volunteers and muscle tissue samples from IIM murine model. All samples were subjected to a targeted metabolomic approach with various statistical analyses on serum and tissue samples to identify metabolic alterations. Three machine learning methods, such as logistic regression (LR), support vector machine (SVM), and random forest (RF), were applied to build prediction models. A set of 7 predictive metabolites was calculated using backward stepwise selection, and the model was evaluated within 5-fold cross-validation by using three machine algorithms. The model produced an area under the receiver operating characteristic curve values of 0.955 (LR), 0.908 (RF) and 0.918 (SVM). A total of 68 metabolites were significantly changed in mouse tissue. Notably, the most influential pathways contributing to the inflammation of muscle were the polyamine pathway and the beta-alanine pathway. Our metabolomic approach offers the potential biomarkers of IIM and reveals pathologically relevant metabolic pathways that are associated with IIM. Full article

(This article belongs to the Section Endocrinology and Clinical Metabolic Research)

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17 pages, 2720 KiB

Open AccessEditor’s ChoiceArticle

Combining Feature-Based Molecular Networking and Contextual Mass Spectral Libraries to Decipher Nutrimetabolomics Profiles

by Lapo Renai, Marynka Ulaszewska, Fulvio Mattivi, Riccardo Bartoletti, Massimo Del Bubba and Justin J. J. van der Hooft

Metabolites 2022, 12(10), 1005; https://doi.org/10.3390/metabo12101005 - 21 Oct 2022

Cited by 4 | Viewed by 2328

Abstract

Untargeted metabolomics approaches deal with complex data hindering structural information for the comprehensive analysis of unknown metabolite features. We investigated the metabolite discovery capacity and the possible extension of the annotation coverage of the Feature-Based Molecular Networking (FBMN) approach by adding two novel [...] Read more.

Untargeted metabolomics approaches deal with complex data hindering structural information for the comprehensive analysis of unknown metabolite features. We investigated the metabolite discovery capacity and the possible extension of the annotation coverage of the Feature-Based Molecular Networking (FBMN) approach by adding two novel nutritionally-relevant (contextual) mass spectral libraries to the existing public ones, as compared to widely-used open-source annotation protocols. Two contextual mass spectral libraries in positive and negative ionization mode of ~300 reference molecules relevant for plant-based nutrikinetic studies were created and made publicly available through the GNPS platform. The postprandial urinary metabolome analysis within the intervention of Vaccinium supplements was selected as a case study. Following the FBMN approach in combination with the added contextual mass spectral libraries, 67 berry-related and human endogenous metabolites were annotated, achieving a structural annotation coverage comparable to or higher than existing non-commercial annotation workflows. To further exploit the quantitative data obtained within the FBMN environment, the postprandial behavior of the annotated metabolites was analyzed with Pearson product-moment correlation. This simple chemometric tool linked several molecular families with phase II and phase I metabolism. The proposed approach is a powerful strategy to employ in longitudinal studies since it reduces the unknown chemical space by boosting the annotation power to characterize biochemically relevant metabolites in human biofluids. Full article

(This article belongs to the Special Issue Advances in Metabolic Profiling of Biological Samples)

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20 pages, 1294 KiB

Open AccessEditor’s ChoiceArticle

A Marked Low-Grade Inflammation and a Significant Deterioration in Metabolic Status in First-Episode Schizophrenia: A Five-Year Follow-Up Study

by Madis Parksepp, Liina Haring, Kalle Kilk, Egon Taalberg, Raul Kangro, Mihkel Zilmer and Eero Vasar

Metabolites 2022, 12(10), 983; https://doi.org/10.3390/metabo12100983 - 17 Oct 2022

Cited by 4 | Viewed by 1654

Abstract

The objective of this study was to evaluate how schizophrenia spectrum disorders and applied long-term (5.1 years) antipsychotic (AP) treatment affect the serum level of acylcarnitines (ACs), cytokines and metabolic biomarkers and to characterize the dynamics of inflammatory and metabolic changes in the [...] Read more.

The objective of this study was to evaluate how schizophrenia spectrum disorders and applied long-term (5.1 years) antipsychotic (AP) treatment affect the serum level of acylcarnitines (ACs), cytokines and metabolic biomarkers and to characterize the dynamics of inflammatory and metabolic changes in the early course of the disorder. A total of 112 adults participated in the study (54 patients with first-episode psychosis (FEP) and 58 control subjects). Biomolecule profiles were measured at the onset of first-episode psychosis and 0.6 years and 5.1 years after the initiation of APs. The results of the present study confirmed that specific metabolic–inflammatory imbalance characterizes AP-naïve patients. Short-term (0.6-years) AP treatment has a favourable effect on psychotic symptoms, as well as the recovery of metabolic flexibility and resolution of low-level inflammation. However, 5.1 years of AP treatment resulted in weight gain and increased serum levels of interleukin (IL)-2, IL-4, IL-6, IL-10, interferon-γ, hexoses, acetylcarnitine, short-chain ACs (C3, C4) and long-chain ACs (C16:2, C18:1, C18:2). In conclusion, despite the improvement in psychotic symptoms, 5.1 years of AP treatment was accompanied by a pronounced metabolic–inflammatory imbalance, which was confirmed by the presence of enhanced pro-inflammatory activity and increased obesity with changes in the metabolism of carbohydrates, lipids, and their metabolites. Full article

(This article belongs to the Section Endocrinology and Clinical Metabolic Research)

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17 pages, 678 KiB

Open AccessEditor’s ChoiceReview

Targeting Both Autophagy and Immunotherapy in Breast Cancer Treatment

by Spyridon Giannopoulos, Cansu Cimen Bozkus, Eleni Zografos, Aikaterini Athanasiou, Ann Marie Bongiovanni, Georgios Doulaveris, Chris N. Bakoyiannis, Georgios E. Theodoropoulos, Georgios C. Zografos, Steven S. Witkin and Theofano Orfanelli

Metabolites 2022, 12(10), 966; https://doi.org/10.3390/metabo12100966 - 12 Oct 2022

Cited by 3 | Viewed by 2275

Abstract

As clinical efforts towards breast-conserving therapy and prolonging survival of those with metastatic breast cancer increase, innovative approaches with the use of biologics are on the rise. Two areas of current focus are cancer immunotherapy and autophagy, both of which have been well-studied [...] Read more.

As clinical efforts towards breast-conserving therapy and prolonging survival of those with metastatic breast cancer increase, innovative approaches with the use of biologics are on the rise. Two areas of current focus are cancer immunotherapy and autophagy, both of which have been well-studied independently but have recently been shown to have intertwining roles in cancer. An increased understanding of their interactions could provide new insights that result in novel diagnostic, prognostic, and therapeutic strategies. In this breast cancer-focused review, we explore the interactions between autophagy and two clinically relevant immune checkpoint pathways; the programmed cell death-1 receptor with its ligand (PD-L1)/PD-1 and the cytotoxic T-lymphocyte-associated protein 4 (CTLA-4)/CD80 and CD86 (B7-1 and B7-2). Furthermore, we discuss emerging preclinical and clinical data supporting targeting both immunotherapy and autophagy pathway manipulation as a promising approach in the treatment of breast cancer. Full article

(This article belongs to the Special Issue DNA Damage and Cancer Metabolism: Basic Research to Clinical Translation)

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16 pages, 1635 KiB

Open AccessEditor’s ChoiceArticle

Serum Bile Acid Profiling and Mixed Model Analysis Reveal Biomarkers Associated with Pruritus Reduction in Maralixibat-Treated Patients with BSEP Deficiency

by Xueheng Zhao, Wujuan Zhang, Pamela Vig, Cory Kostrub and Kenneth D. R. Setchell

Metabolites 2022, 12(10), 952; https://doi.org/10.3390/metabo12100952 - 06 Oct 2022

Cited by 2 | Viewed by 1744

Abstract

Progressive familial intrahepatic cholestasis (PFIC) is a debilitating disease manifest by severe cholestasis, intractable pruritus and growth delay that ultimately leads to liver failure or transplantation. Maralixibat (MRX) was recently approved for the treatment of cholestatic pruritus in patients with Alagille syndrome. The [...] Read more.

Progressive familial intrahepatic cholestasis (PFIC) is a debilitating disease manifest by severe cholestasis, intractable pruritus and growth delay that ultimately leads to liver failure or transplantation. Maralixibat (MRX) was recently approved for the treatment of cholestatic pruritus in patients with Alagille syndrome. The aim of this study was to determine whether specific changes in the composition of the serum bile acid metabolome could predict pruritus response to treatment. Serum BAs (sBA) and 7α-hydroxy-4-cholesten-3-one (7α-C4), a surrogate marker of BA synthesis, were monitored by ultrahigh-performance liquid chromatography coupled with tandem mass spectrometry over 72 weeks in PFIC patients with mild to moderate non-truncating bile salt export pump (BSEP) mutations (n = 19) treated with MRX. The weekly itch reported outcome observer (ItchRO[Obs]) score measured pruritus severity. Linear mixed models (LMM) were applied to explore the effects of individual sBA profiles and their relationship to pruritus response. Changes in the composition of sBA correlated with pruritus improvement. Notably, the trajectory of serum total and individual BA species and 7α-C4 were significantly associated with ItchRO[Obs] score (p < 0.05). These results reveal that beyond simple total sBA concentrations, specific changes to the BA metabolome are associated with pruritus reduction in patients with BSEP deficiency, thus providing further insight into causal relationship of bile acids and pruritus. Full article

(This article belongs to the Section Endocrinology and Clinical Metabolic Research)

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19 pages, 3397 KiB

Open AccessEditor’s ChoiceArticle

Multi-Omics, an Integrated Approach to Identify Novel Blood Biomarkers of Alzheimer’s Disease

by Maxime François, Avinash V. Karpe, Jian-Wei Liu, David J. Beale, Maryam Hor, Jane Hecker, Jeff Faunt, John Maddison, Sally Johns, James D. Doecke, Stephen Rose and Wayne R. Leifert

Metabolites 2022, 12(10), 949; https://doi.org/10.3390/metabo12100949 - 06 Oct 2022

Cited by 6 | Viewed by 2350

Abstract

The metabolomic and proteomic basis of mild cognitive impairment (MCI) and Alzheimer’s disease (AD) is poorly understood, and the relationships between systemic abnormalities in metabolism and AD/MCI pathogenesis is unclear. This study compared the metabolomic and proteomic signature of plasma from cognitively normal [...] Read more.

The metabolomic and proteomic basis of mild cognitive impairment (MCI) and Alzheimer’s disease (AD) is poorly understood, and the relationships between systemic abnormalities in metabolism and AD/MCI pathogenesis is unclear. This study compared the metabolomic and proteomic signature of plasma from cognitively normal (CN) and dementia patients diagnosed with MCI or AD, to identify specific cellular pathways and new biomarkers altered with the progression of the disease. We analysed 80 plasma samples from individuals with MCI or AD, as well as age- and gender-matched CN individuals, by utilising mass spectrometry methods and data analyses that included combined pathway analysis and model predictions. Several proteins clearly identified AD from the MCI and CN groups and included plasma actins, mannan-binding lectin serine protease 1, serum amyloid A2, fibronectin and extracellular matrix protein 1 and Keratin 9. The integrated pathway analysis showed various metabolic pathways were affected in AD, such as the arginine, alanine, aspartate, glutamate and pyruvate metabolism pathways. Therefore, our multi-omics approach identified novel plasma biomarkers for the MCI and AD groups, identified changes in metabolic processes, and may form the basis of a biomarker panel for stratifying dementia participants in future clinical trials. Full article

(This article belongs to the Special Issue Integrated Systems Biology: Challenges and Future Perspectives)

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23 pages, 1746 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Substantial Fat Loss in Physique Competitors Is Characterized by Increased Levels of Bile Acids, Very-Long Chain Fatty Acids, and Oxylipins

by Heikki V. Sarin, Juha J. Hulmi, Youwen Qin, Michael Inouye, Scott C. Ritchie, Susan Cheng, Jeramie D. Watrous, Thien-Tu C. Nguyen, Joseph H. Lee, Zhezhen Jin, Joseph D. Terwilliger, Teemu Niiranen, Aki Havulinna, Veikko Salomaa, Kirsi H. Pietiläinen, Ville Isola, Juha P. Ahtiainen, Keijo Häkkinen, Mohit Jain and Markus Perola

Metabolites 2022, 12(10), 928; https://doi.org/10.3390/metabo12100928 - 30 Sep 2022

Cited by 2 | Viewed by 3025

Abstract

Weight loss and increased physical activity may promote beneficial modulation of the metabolome, but limited evidence exists about how very low-level weight loss affects the metabolome in previously non-obese active individuals. Following a weight loss period (21.1 ± 3.1 weeks) leading to substantial [...] Read more.

Weight loss and increased physical activity may promote beneficial modulation of the metabolome, but limited evidence exists about how very low-level weight loss affects the metabolome in previously non-obese active individuals. Following a weight loss period (21.1 ± 3.1 weeks) leading to substantial fat mass loss of 52% (−7.9 ± 1.5 kg) and low body fat (12.7 ± 4.1%), the liquid chromatography-mass spectrometry-based metabolic signature of 24 previously young, healthy, and normal weight female physique athletes was investigated. We observed uniform increases (FDR < 0.05) in bile acids, very-long-chain free fatty acids (FFA), and oxylipins, together with reductions in unsaturated FFAs after weight loss. These widespread changes, especially in the bile acid profile, were most strongly explained (FDR < 0.05) by changes in android (visceral) fat mass. The reported changes did not persist, as all of them were reversed after the subsequent voluntary weight regain period (18.4 ± 2.9 weeks) and were unchanged in non-dieting controls (n = 16). Overall, we suggest that the reported changes in FFA, bile acid, and oxylipin profiles reflect metabolic adaptation to very low levels of fat mass after prolonged periods of intense exercise and low-energy availability. However, the effects of the aforementioned metabolome subclass alteration on metabolic homeostasis remain controversial, and more studies are warranted to unravel the complex physiology and potentially associated health implications. In the end, our study reinforced the view that transient weight loss seems to have little to no long-lasting molecular and physiological effects. Full article

(This article belongs to the Special Issue Effects of Exercise and Nutritional Interventions on Metabolic Health)

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16 pages, 2237 KiB

Open AccessEditor’s ChoiceArticle

Association of Metabolic Signatures with Nonalcoholic Fatty Liver Disease in Pediatric Population

by Woori Chae, Kyung Jae Lee, Ki Young Huh, Jin Soo Moon, Jae Sung Ko and Joo-Youn Cho

Metabolites 2022, 12(9), 881; https://doi.org/10.3390/metabo12090881 - 19 Sep 2022

Cited by 4 | Viewed by 2277

Abstract

Several adult omics studies have been conducted to understand the pathophysiology of nonalcoholic fatty liver disease (NAFLD). However, the histological features of children are different from those of adults, and the onset and progression of pediatric NAFLD are not fully understood. In this [...] Read more.

Several adult omics studies have been conducted to understand the pathophysiology of nonalcoholic fatty liver disease (NAFLD). However, the histological features of children are different from those of adults, and the onset and progression of pediatric NAFLD are not fully understood. In this study, we aimed to evaluate the metabolome profile and metabolic pathway changes associated with pediatric NAFLD to elucidate its pathophysiology and to develop machine learning-based NAFLD diagnostic models. We analyzed the metabolic profiles of healthy control, lean NAFLD, overweight control, and overweight NAFLD groups of children and adolescent participants (N = 165) by assessing plasma samples. Additionally, we constructed diagnostic models by applying three machine learning methods (ElasticNet, random forest, and XGBoost) and multiple logistic regression by using NAFLD-specific metabolic features, genetic variants, and clinical data. We identified 18 NAFLD-specific metabolic features and metabolic changes in lipid, glutathione-related amino acid, and branched-chain amino acid metabolism by comparing the control and NAFLD groups in the overweight pediatric population. Additionally, we successfully developed and cross-validated diagnostic models that showed excellent diagnostic performance (ElasticNet and random forest model: area under the receiver operating characteristic curve, 0.95). Metabolome changes in the plasma of pediatric patients with NAFLD are associated with the pathophysiology of the disease and can be utilized as a less-invasive approach to diagnosing the disease. Full article

(This article belongs to the Special Issue Metabolic Profiles and Fibrosis of Nonalcoholic Fatty Liver Disease)

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13 pages, 596 KiB

Open AccessEditor’s ChoiceArticle

Fecal Bile Acids and Neutral Sterols Are Associated with Latent Microbial Subgroups in the Human Gut

by Taylor A. Breuninger, Nina Wawro, Dennis Freuer, Sandra Reitmeier, Anna Artati, Harald Grallert, Jerzy Adamski, Christa Meisinger, Annette Peters, Dirk Haller and Jakob Linseisen

Metabolites 2022, 12(9), 846; https://doi.org/10.3390/metabo12090846 - 08 Sep 2022

Cited by 2 | Viewed by 1619

Abstract

Bile acids, neutral sterols, and the gut microbiome are intricately intertwined and each affects human health and metabolism. However, much is still unknown about this relationship. This analysis included 1280 participants of the KORA FF4 study. Fecal metabolites (primary and secondary bile acids, [...] Read more.

Bile acids, neutral sterols, and the gut microbiome are intricately intertwined and each affects human health and metabolism. However, much is still unknown about this relationship. This analysis included 1280 participants of the KORA FF4 study. Fecal metabolites (primary and secondary bile acids, plant and animal sterols) were analyzed using a metabolomics approach. Dirichlet regression models were used to evaluate associations between the metabolites and twenty microbial subgroups that were previously identified using latent Dirichlet allocation. Significant associations were identified between 12 of 17 primary and secondary bile acids and several of the microbial subgroups. Three subgroups showed largely positive significant associations with bile acids, and six subgroups showed mostly inverse associations with fecal bile acids. We identified a trend where microbial subgroups that were previously associated with “healthy” factors were here inversely associated with fecal bile acid levels. Conversely, subgroups that were previously associated with “unhealthy” factors were positively associated with fecal bile acid levels. These results indicate that further research is necessary regarding bile acids and microbiota composition, particularly in relation to metabolic health. Full article

(This article belongs to the Special Issue Diet, Drugs and the Gut Microbiome on the Metabolic Phenotype)

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21 pages, 803 KiB

Open AccessEditor’s ChoiceArticle

Maternal Serum and Placental Metabolomes in Association with Prenatal Phthalate Exposure and Neurodevelopmental Outcomes in the MARBLES Cohort

by Mariana Parenti, Rebecca J. Schmidt, Sally Ozonoff, Hyeong-Moo Shin, Daniel J. Tancredi, Paula Krakowiak, Irva Hertz-Picciotto, Cheryl K. Walker and Carolyn M. Slupsky

Metabolites 2022, 12(9), 829; https://doi.org/10.3390/metabo12090829 - 02 Sep 2022

Cited by 8 | Viewed by 2342

Abstract

Prenatal exposure to phthalates, a family of endocrine-disrupting plasticizers, is associated with disruption of maternal metabolism and impaired neurodevelopment. We investigated associations between prenatal phthalate exposure and alterations of both the maternal third trimester serum metabolome and the placental metabolome at birth, and [...] Read more.

Prenatal exposure to phthalates, a family of endocrine-disrupting plasticizers, is associated with disruption of maternal metabolism and impaired neurodevelopment. We investigated associations between prenatal phthalate exposure and alterations of both the maternal third trimester serum metabolome and the placental metabolome at birth, and associations of these with child neurodevelopmental outcomes using data and samples from the Markers of Autism Risk in Babies Learning Early Signs (MARBLES) cohort. The third trimester serum (n = 106) and placental (n = 132) metabolomes were investigated using ¹H nuclear magnetic resonance spectroscopy. Children were assessed clinically for autism spectrum disorder (ASD) and cognitive development. Although none of the urinary phthalate metabolite concentrations were associated with maternal serum metabolites after adjustment for covariates, mixture analysis using quantile g-computation revealed alterations in placental metabolites with increasing concentrations of phthalate metabolites that included reduced concentrations of 2-hydoxybutyrate, carnitine, O-acetylcarnitine, glucitol, and N-acetylneuraminate. Child neurodevelopmental outcome was not associated with the third trimester serum metabolome, but it was correlated with the placental metabolome in male children only. Maternal phthalate exposure during pregnancy is associated with differences in the placental metabolome at delivery, and the placental metabolome is associated with neurodevelopmental outcomes in males in a cohort with high familial ASD risk. Full article

(This article belongs to the Special Issue Metabolomics of Autism Spectrum Disorder)

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14 pages, 2635 KiB

Open AccessEditor’s ChoiceArticle

Site-Differentiated Iron–Sulfur Cluster Ligation Affects Flavin-Based Electron Bifurcation Activity

by Courtney E. Wise, Anastasia E. Ledinina and Carolyn E. Lubner

Metabolites 2022, 12(9), 823; https://doi.org/10.3390/metabo12090823 - 01 Sep 2022

Cited by 2 | Viewed by 1764

Abstract

Electron bifurcation is an elegant mechanism of biological energy conversion that effectively couples three different physiologically relevant substrates. As such, enzymes that perform this function often play critical roles in modulating cellular redox metabolism. One such enzyme is NADH-dependent reduced-ferredoxin: NADP⁺ oxidoreductase [...] Read more.

Electron bifurcation is an elegant mechanism of biological energy conversion that effectively couples three different physiologically relevant substrates. As such, enzymes that perform this function often play critical roles in modulating cellular redox metabolism. One such enzyme is NADH-dependent reduced-ferredoxin: NADP⁺ oxidoreductase (NfnSL), which couples the thermodynamically favorable reduction of NAD⁺ to drive the unfavorable reduction of ferredoxin from NADPH. The interaction of NfnSL with its substrates is constrained to strict stoichiometric conditions, which ensures minimal energy losses from non-productive intramolecular electron transfer reactions. However, the determinants for this are not well understood. One curious feature of NfnSL is that both initial acceptors of bifurcated electrons are unique iron–sulfur (FeS) clusters containing one non-cysteinyl ligand each. The biochemical impact and mechanistic roles of site-differentiated FeS ligands are enigmatic, despite their incidence in many redox active enzymes. Herein, we describe the biochemical study of wild-type NfnSL and a variant in which one of the site-differentiated ligands has been replaced with a cysteine. Results of dye-based steady-state kinetics experiments, substrate-binding measurements, biochemical activity assays, and assessments of electron distribution across the enzyme indicate that this site-differentiated ligand in NfnSL plays a role in maintaining fidelity of the coordinated reactions performed by the two electron transfer pathways. Given the commonality of these cofactors, our findings have broad implications beyond electron bifurcation and mechanistic biochemistry and may inform on means of modulating the redox balance of the cell for targeted metabolic engineering approaches. Full article

(This article belongs to the Special Issue The Thermodynamic Regulation of Microbial Metabolisms by Environmental Factors)

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28 pages, 3005 KiB

Open AccessEditor’s ChoiceArticle

A Multi-Matrix Metabolomic Approach in Ringed Seals and Beluga Whales to Evaluate Contaminant and Climate-Related Stressors

by Antoine É. Simond, Marie Noël, Lisa Loseto, Magali Houde, Jane Kirk, Ashley Elliott and Tanya M. Brown

Metabolites 2022, 12(9), 813; https://doi.org/10.3390/metabo12090813 - 30 Aug 2022

Cited by 1 | Viewed by 2584

Abstract

As a high trophic-level species, ringed seals (Pusa hispida) and beluga whales (Delphinapterus leucas) are particularly vulnerable to elevated concentrations of biomagnifying contaminants, such as polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs) and mercury (Hg). These species also face [...] Read more.

As a high trophic-level species, ringed seals (Pusa hispida) and beluga whales (Delphinapterus leucas) are particularly vulnerable to elevated concentrations of biomagnifying contaminants, such as polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs) and mercury (Hg). These species also face climate-change-related impacts which are leading to alterations in their diet and associated contaminant exposure. The metabolomic profile of marine mammal tissues and how it changes to environmental stressors is poorly understood. This study characterizes the profiles of 235 metabolites across plasma, liver, and inner and outer blubber in adult ringed seals and beluga whales and assesses how these profiles change as a consequence of contaminants and dietary changes. In both species, inner and outer blubber were characterized by a greater proportion of lipid classes, whereas the dominant metabolites in liver and plasma were amino acids, carbohydrates, biogenic amines and lysophosphatidylcholines. Several metabolite profiles in ringed seal plasma correlated with δ¹³C, while metabolite profiles in blubber were affected by hexabromobenzene in ringed seals and PBDEs and Hg in belugas. This study provides insight into inter-matrix similarities and differences across tissues and suggests that plasma and liver are more suitable for studying changes in diet, whereas liver and blubber are more suitable for studying the impacts of contaminants. Full article

(This article belongs to the Special Issue Application of Metabolomic in Ecotoxicology)

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15 pages, 1280 KiB

Open AccessEditor’s ChoiceArticle

Bucket Fuser: Statistical Signal Extraction for 1D ¹H NMR Metabolomic Data

by Michael Altenbuchinger, Henry Berndt, Robin Kosch, Iris Lang, Jürgen Dönitz, Peter J. Oefner, Wolfram Gronwald, Helena U. Zacharias and Investigators GCKD Study

Metabolites 2022, 12(9), 812; https://doi.org/10.3390/metabo12090812 - 29 Aug 2022

Viewed by 1799

Abstract

Untargeted metabolomics is a promising tool for identifying novel disease biomarkers and unraveling underlying pathomechanisms. Nuclear magnetic resonance (NMR) spectroscopy is particularly suited for large-scale untargeted metabolomics studies due to its high reproducibility and cost effectiveness. Here, one-dimensional (1D) ¹H NMR experiments [...] Read more.

Untargeted metabolomics is a promising tool for identifying novel disease biomarkers and unraveling underlying pathomechanisms. Nuclear magnetic resonance (NMR) spectroscopy is particularly suited for large-scale untargeted metabolomics studies due to its high reproducibility and cost effectiveness. Here, one-dimensional (1D) ¹H NMR experiments offer good sensitivity at reasonable measurement times. Their subsequent data analysis requires sophisticated data preprocessing steps, including the extraction of NMR features corresponding to specific metabolites. We developed a novel 1D NMR feature extraction procedure, called Bucket Fuser (BF), which is based on a regularized regression framework with fused group LASSO terms. The performance of the BF procedure was demonstrated using three independent NMR datasets and was benchmarked against existing state-of-the-art NMR feature extraction methods. BF dynamically constructs NMR metabolite features, the widths of which can be adjusted via a regularization parameter. BF consistently improved metabolite signal extraction, as demonstrated by our correlation analyses with absolutely quantified metabolites. It also yielded a higher proportion of statistically significant metabolite features in our differential metabolite analyses. The BF algorithm is computationally efficient and it can deal with small sample sizes. In summary, the Bucket Fuser algorithm, which is available as a supplementary python code, facilitates the fast and dynamic extraction of 1D NMR signals for the improved detection of metabolic biomarkers. Full article

(This article belongs to the Special Issue Development and Application of Statistical Methods for Analyzing Metabolomics Data Volume 2)

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16 pages, 2248 KiB

Open AccessEditor’s ChoiceArticle

Multi-Omic Admission-Based Prognostic Biomarkers Identified by Machine Learning Algorithms Predict Patient Recovery and 30-Day Survival in Trauma Patients

by Sultan S. Abdelhamid, Jacob Scioscia, Yoram Vodovotz, Junru Wu, Anna Rosengart, Eunseo Sung, Syed Rahman, Robert Voinchet, Jillian Bonaroti, Shimena Li, Jennifer L. Darby, Upendra K. Kar, Matthew D. Neal, Jason Sperry, Jishnu Das and Timothy R. Billiar

Metabolites 2022, 12(9), 774; https://doi.org/10.3390/metabo12090774 - 23 Aug 2022

Cited by 4 | Viewed by 2832

Abstract

Admission-based circulating biomarkers for the prediction of outcomes in trauma patients could be useful for clinical decision support. It is unknown which molecular classes of biomolecules can contribute biomarkers to predictive modeling. Here, we analyzed a large multi-omic database of over 8500 markers [...] Read more.

Admission-based circulating biomarkers for the prediction of outcomes in trauma patients could be useful for clinical decision support. It is unknown which molecular classes of biomolecules can contribute biomarkers to predictive modeling. Here, we analyzed a large multi-omic database of over 8500 markers (proteomics, metabolomics, and lipidomics) to identify prognostic biomarkers in the circulating compartment for adverse outcomes, including mortality and slow recovery, in severely injured trauma patients. Admission plasma samples from patients (n = 129) enrolled in the Prehospital Air Medical Plasma (PAMPer) trial were analyzed using mass spectrometry (metabolomics and lipidomics) and aptamer-based (proteomics) assays. Biomarkers were selected via Least Absolute Shrinkage and Selection Operator (LASSO) regression modeling and machine learning analysis. A combination of five proteins from the proteomic layer was best at discriminating resolvers from non-resolvers from critical illness with an Area Under the Receiver Operating Characteristic curve (AUC) of 0.74, while 26 multi-omic features predicted 30-day survival with an AUC of 0.77. Patients with traumatic brain injury as part of their injury complex had a unique subset of features that predicted 30-day survival. Our findings indicate that multi-omic analyses can identify novel admission-based prognostic biomarkers for outcomes in trauma patients. Unique biomarker discovery also has the potential to provide biologic insights. Full article

(This article belongs to the Special Issue Metabolomics: An Emerging Potential Approach to Study Critical Illnesses)

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16 pages, 1481 KiB

Open AccessEditor’s ChoiceArticle

A Sample Preparation Method for the Simultaneous Profiling of Signaling Lipids and Polar Metabolites in Small Quantities of Muscle Tissues from a Mouse Model for Sarcopenia

by Yupeng He, Marlien van Mever, Wei Yang, Luojiao Huang, Rawi Ramautar, Yvonne Rijksen, Wilbert P. Vermeij, Jan H. J. Hoeijmakers, Amy C. Harms, Peter W. Lindenburg and Thomas Hankemeier

Metabolites 2022, 12(8), 742; https://doi.org/10.3390/metabo12080742 - 12 Aug 2022

Cited by 1 | Viewed by 2203

Abstract

The metabolic profiling of a wide range of chemical classes relevant to understanding sarcopenia under conditions in which sample availability is limited, e.g., from mouse models, small muscles, or muscle biopsies, is desired. Several existing metabolomics platforms that include diverse classes of signaling [...] Read more.

The metabolic profiling of a wide range of chemical classes relevant to understanding sarcopenia under conditions in which sample availability is limited, e.g., from mouse models, small muscles, or muscle biopsies, is desired. Several existing metabolomics platforms that include diverse classes of signaling lipids, energy metabolites, and amino acids and amines would be informative for suspected biochemical pathways involved in sarcopenia. The sample limitation requires an optimized sample preparation method with minimal losses during isolation and handling and maximal accuracy and reproducibility. Here, two developed sample preparation methods, BuOH-MTBE-Water (BMW) and BuOH-MTBE-More-Water (BMMW), were evaluated and compared with previously reported methods, Bligh-Dyer (BD) and BuOH-MTBE-Citrate (BMC), for their suitability for these classes. The most optimal extraction was found to be the BMMW method, with the highest extraction recovery of 63% for the signaling lipids and 81% for polar metabolites, and an acceptable matrix effect (close to 1.0) for all metabolites of interest. The BMMW method was applied on muscle tissues as small as 5 mg (dry weight) from the well-characterized, prematurely aging, DNA repair-deficient Ercc1^∆/− mouse mutant exhibiting multiple–morbidities, including sarcopenia. We successfully detected 109 lipids and 62 polar targeted metabolites. We further investigated whether fast muscle tissue isolation is necessary for mouse sarcopenia studies. A muscle isolation procedure involving 15 min at room temperature revealed a subset of metabolites to be unstable; hence, fast sample isolation is critical, especially for more oxidative muscles. Therefore, BMMW and fast muscle tissue isolation are recommended for future sarcopenia studies. This research provides a sensitive sample preparation method for the simultaneous extraction of non-polar and polar metabolites from limited amounts of muscle tissue, supplies a stable mouse muscle tissue collection method, and methodologically supports future metabolomic mechanistic studies of sarcopenia. Full article

(This article belongs to the Special Issue Advances in Metabolic Profiling of Biological Samples)

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15 pages, 1952 KiB

Open AccessEditor’s ChoiceArticle

Tissue-Wide Expression of Genes Related to Vitamin D Metabolism and FGF23 Signaling following Variable Phosphorus Intake in Pigs

by Maruf Hasan, Michael Oster, Henry Reyer, Siriluck Ponsuksili, Eduard Murani, Petra Wolf, Dagmar-Christiane Fischer and Klaus Wimmers

Metabolites 2022, 12(8), 729; https://doi.org/10.3390/metabo12080729 - 06 Aug 2022

Cited by 5 | Viewed by 3226

Abstract

Calcium (Ca) and phosphorus (P) homeostasis is maintained by several regulators, including vitamin D and fibroblast growth factor 23 (FGF23), and their tissue-specific activation and signaling cascades. In this study, the tissue-wide expression of key genes linked to vitamin D metabolism (CYP2R1 [...] Read more.

Calcium (Ca) and phosphorus (P) homeostasis is maintained by several regulators, including vitamin D and fibroblast growth factor 23 (FGF23), and their tissue-specific activation and signaling cascades. In this study, the tissue-wide expression of key genes linked to vitamin D metabolism (CYP2R1, CYP27A1, CYP27B1, CYP24A1, GC, VDR) and FGF23 signaling (FGF23, FGFR1-4, KL) were investigated in pigs fed conventional (trial 1) and divergent P diets (trial 2). The tissue set comprised kidney, liver, bone, lung, aorta, and gastrointestinal tract sections. Expression patterns revealed that non-renal tissues and cells (NRTC) express genes to form active vitamin D [1,25(OH)₂D₃] according to site-specific requirements. A low P diet resulted in higher serum calcitriol and increased CYP24A1 expression in the small intestine, indicating local suppression of vitamin D signaling. A high P diet prompted increased mRNA abundances of CYP27B1 for local vitamin D synthesis, specifically in bone. For FGF23 signaling, analyses revealed ubiquitous expression of FGFR1-4, whereas KL was expressed in a tissue-specific manner. Dietary P supply did not affect skeletal FGF23; however, FGFR4 and KL showed increased expression in bone at high P supply, suggesting regulation to balance mineralization. Specific NRTC responses influence vitamin D metabolism and P homeostasis, which should be considered for a thrifty but healthy P supply. Full article

(This article belongs to the Special Issue Effect of Diet on Vitamin D Metabolism: Implications in Health and Disease)

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11 pages, 430 KiB

Open AccessEditor’s ChoiceArticle

Relationship between Fasting and Postprandial Glucose Levels and the Gut Microbiota

by Yui Mineshita, Hiroyuki Sasaki, Hyeon-ki Kim and Shigenobu Shibata

Metabolites 2022, 12(7), 669; https://doi.org/10.3390/metabo12070669 - 20 Jul 2022

Cited by 3 | Viewed by 1671

Abstract

Postprandial hyperglycemia increases the risk of mortality among patients with type 2 diabetes and cardiovascular diseases. Additionally, the gut microbiota and type 2 diabetes and cardio-vascular disease are known to be correlated. Currently, fasting blood glucose is the primary in-dex for the clinical [...] Read more.

Postprandial hyperglycemia increases the risk of mortality among patients with type 2 diabetes and cardiovascular diseases. Additionally, the gut microbiota and type 2 diabetes and cardio-vascular disease are known to be correlated. Currently, fasting blood glucose is the primary in-dex for the clinical diagnosis of diabetes; however, postprandial blood glucose is associated with the risk of developing type 2 diabetes and cardiovascular disease and mortality. Therefore, the dynamic change in blood glucose levels under free-living conditions is considered an important and better marker than fasting glucose levels to study the relationship between glucose levels and microbiota. Here, we investigated the relationship between fasting and postprandial glucose levels and microbiota under free-living conditions for one week in older adults. In addition, in order to clarify the relationship between blood glucose level and intestinal bacteria, postprandial 4-h AUC was calculated and the correlation with gut bacteria was investigated. As a result of the present study, we observed many of the most significant correlations between the gut bacteria and the peak glucose levels after dinner and the 4-h AUC after dinner. Together, these findings suggest that the individual pattern of microbiota may help to predict post-dinner hyperglycemia and the risk of abnormal glucose metabolism, such as diabetes. Full article

(This article belongs to the Section Nutrition and Metabolism)

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15 pages, 3008 KiB

Open AccessEditor’s ChoiceArticle

Molecular Network-Based Identification of Tramadol Metabolites in a Fatal Tramadol Poisoning

by Romain Magny, Nicolas Auzeil, Bertrand Lefrère, Bruno Mégarbane, Pascal Houzé and Laurence Labat

Metabolites 2022, 12(7), 665; https://doi.org/10.3390/metabo12070665 - 19 Jul 2022

Cited by 13 | Viewed by 1937

Abstract

Identification of xenobiotics and their phase I/II metabolites in poisoned patients remains challenging. Systematic approaches using bioinformatic tools are needed to detect all compounds as exhaustively as possible. Here, we aimed to assess an analytical workflow using liquid chromatography coupled to high-resolution mass [...] Read more.

Identification of xenobiotics and their phase I/II metabolites in poisoned patients remains challenging. Systematic approaches using bioinformatic tools are needed to detect all compounds as exhaustively as possible. Here, we aimed to assess an analytical workflow using liquid chromatography coupled to high-resolution mass spectrometry with data processing based on a molecular network to identify tramadol metabolites in urine and plasma in poisoned patients. The generated molecular network from liquid chromatography coupled to high-resolution tandem mass spectrometry data acquired in both positive and negative ion modes allowed for the identification of 25 tramadol metabolites in urine and plasma, including four methylated metabolites that have not been previously reported in humans or in vitro models. While positive ion mode is reliable for generating a network of tramadol metabolites displaying a dimethylamino radical in their structure, negative ion mode was useful to cluster phase II metabolites. In conclusion, the combined use of molecular networks in positive and negative ion modes is a suitable and robust tool to identify a broad range of metabolites in poisoned patients, as shown in a fatal tramadol-poisoned patient. Full article

(This article belongs to the Special Issue Mass Spectrometry-Based Metabolomics as Tools in Pharmaceutical and Biological Analysis)

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13 pages, 9965 KiB

Open AccessEditor’s ChoiceArticle

Discovery of Synergistic Drug Combinations for Colorectal Cancer Driven by Tumor Barcode Derived from Metabolomics “Big Data”

by Bo Lv, Ruijie Xu, Xinrui Xing, Chuyao Liao, Zunjian Zhang, Pei Zhang and Fengguo Xu

Metabolites 2022, 12(6), 494; https://doi.org/10.3390/metabo12060494 - 30 May 2022

Cited by 1 | Viewed by 3116

Abstract

The accumulation of cancer metabolomics data in the past decade provides exceptional opportunities for deeper investigations into cancer metabolism. However, integrating a large amount of heterogeneous metabolomics data to draw a full picture of the metabolic reprogramming and to discover oncometabolites of certain [...] Read more.

The accumulation of cancer metabolomics data in the past decade provides exceptional opportunities for deeper investigations into cancer metabolism. However, integrating a large amount of heterogeneous metabolomics data to draw a full picture of the metabolic reprogramming and to discover oncometabolites of certain cancers remains challenging. In this study, a tumor barcode constructed based upon existing metabolomics “big data” using the Bayesian vote-counting method is proposed to identify oncometabolites in colorectal cancer (CRC). Specifically, a panel of oncometabolites of CRC was generated from 39 clinical studies with 3202 blood samples (1332 CRC vs. 1870 controls) and 990 tissue samples (495 CRC vs. 495 controls). Next, an oncometabolite-protein network was constructed by combining the tumor barcode and its involved proteins/enzymes. The effect of anti-cancer drugs or drug combinations was then mapped into this network by the random walk with restart process. Utilizing this network, potential Irinotecan (CPT-11)-sensitizing agents for CRC treatment were discovered by random forest and Xgboost. Finally, a compound named MK-2206 was highlighted and its synergy with CPT-11 was validated on two CRC cell lines. To summarize, we demonstrate in the present study that the metabolomics “big data”-based tumor barcodes and the subsequent network analyses are potentially useful for drug combination discovery or drug repositioning. Full article

(This article belongs to the Special Issue Advanced Strategies and Tools for Metabolomics Data Analysis, Metabolite Annotation and Identification)

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29 pages, 934 KiB

Open AccessEditor’s ChoiceArticle

Structural Thermokinetic Modelling

by Wolfram Liebermeister

Metabolites 2022, 12(5), 434; https://doi.org/10.3390/metabo12050434 - 11 May 2022

Cited by 2 | Viewed by 2310

Abstract

To translate metabolic networks into dynamic models, the Structural Kinetic Modelling framework (SKM) assumes a given reference state and replaces the reaction elasticities in this state by random numbers. A new variant, called Structural Thermokinetic Modelling (STM), accounts for reversible reactions and thermodynamics. [...] Read more.

To translate metabolic networks into dynamic models, the Structural Kinetic Modelling framework (SKM) assumes a given reference state and replaces the reaction elasticities in this state by random numbers. A new variant, called Structural Thermokinetic Modelling (STM), accounts for reversible reactions and thermodynamics. STM relies on a dependence schema in which some basic variables are sampled, fitted to data, or optimised, while all other variables can be easily computed. Correlated elasticities follow from enzyme saturation values and thermodynamic forces, which are physically independent. Probability distributions in the dependence schema define a model ensemble, which allows for probabilistic predictions even if data are scarce. STM highlights the importance of variabilities, dependencies, and covariances of biological variables. By varying network structure, fluxes, thermodynamic forces, regulation, or types of rate laws, the effects of these model features can be assessed. By choosing the basic variables, metabolic networks can be converted into kinetic models with consistent reversible rate laws. Metabolic control coefficients obtained from these models can tell us about metabolic dynamics, including responses and optimal adaptations to perturbations, enzyme synergies and metabolite correlations, as well as metabolic fluctuations arising from chemical noise. To showcase STM, I study metabolic control, metabolic fluctuations, and enzyme synergies, and how they are shaped by thermodynamic forces. Considering thermodynamics can improve predictions of flux control, enzyme synergies, correlated flux and metabolite variations, and the emergence and propagation of metabolic noise. Full article

(This article belongs to the Section Bioinformatics and Data Analysis)

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42 pages, 823 KiB

Open AccessEditor’s ChoiceReview

Patient Stratification in Sepsis: Using Metabolomics to Detect Clinical Phenotypes, Sub-Phenotypes and Therapeutic Response

by Humma Hussain, Kritchai Vutipongsatorn, Beatriz Jiménez and David B. Antcliffe

Metabolites 2022, 12(5), 376; https://doi.org/10.3390/metabo12050376 - 21 Apr 2022

Cited by 14 | Viewed by 4025

Abstract

Infections are common and need minimal treatment; however, occasionally, due to inappropriate immune response, they can develop into a life-threatening condition known as sepsis. Sepsis is a global concern with high morbidity and mortality. There has been little advancement in the treatment of [...] Read more.

Infections are common and need minimal treatment; however, occasionally, due to inappropriate immune response, they can develop into a life-threatening condition known as sepsis. Sepsis is a global concern with high morbidity and mortality. There has been little advancement in the treatment of sepsis, outside of antibiotics and supportive measures. Some of the difficulty in identifying novel therapies is the heterogeneity of the condition. Metabolic phenotyping has great potential for gaining understanding of this heterogeneity and how the metabolic fingerprints of patients with sepsis differ based on survival, organ dysfunction, disease severity, type of infection, treatment or causative organism. Moreover, metabolomics offers potential for patient stratification as metabolic profiles obtained from analytical platforms can reflect human individuality and phenotypic variation. This article reviews the most relevant metabolomic studies in sepsis and aims to provide an overview of the metabolic derangements in sepsis and how metabolic phenotyping has been used to identify sub-groups of patients with this condition. Finally, we consider the new avenues that metabolomics could open, exploring novel phenotypes and untangling the heterogeneity of sepsis, by looking at advances made in the field with other -omics technologies. Full article

(This article belongs to the Special Issue Using Metabolomics to Subphenotype Disease and Therapeutic Response)

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19 pages, 3218 KiB

Open AccessEditor’s ChoiceArticle

Matching Drug Metabolites from Non-Targeted Metabolomics to Self-Reported Medication in the Qatar Biobank Study

by Karsten Suhre, Nisha Stephan, Shaza Zaghlool, Chris R. Triggle, Richard J. Robinson, Anne M. Evans and Anna Halama

Metabolites 2022, 12(3), 249; https://doi.org/10.3390/metabo12030249 - 16 Mar 2022

Cited by 6 | Viewed by 3202

Abstract

Modern metabolomics platforms are able to identify many drug-related metabolites in blood samples. Applied to population-based biobank studies, the detection of drug metabolites can then be used as a proxy for medication use or serve as a validation tool for questionnaire-based health assessments. [...] Read more.

Modern metabolomics platforms are able to identify many drug-related metabolites in blood samples. Applied to population-based biobank studies, the detection of drug metabolites can then be used as a proxy for medication use or serve as a validation tool for questionnaire-based health assessments. However, it is not clear how well detection of drug metabolites in blood samples matches information on self-reported medication provided by study participants. Here, we curate free-text responses to a drug-usage questionnaire from 6000 participants of the Qatar Biobank (QBB) using standardized WHO Anatomical Therapeutic Chemical (ATC) Classification System codes and compare the occurrence of these ATC terms to the detection of drug-related metabolites in matching blood plasma samples from 2807 QBB participants for which we collected non-targeted metabolomics data. We found that the detection of 22 drug-related metabolites significantly associated with the self-reported use of the corresponding medication. Good agreement of self-reported medication with non-targeted metabolomics was observed, with self-reported drugs and their metabolites being detected in a same blood sample in 79.4% of the cases. On the other hand, only 29.5% of detected drug metabolites matched to self-reported medication. Possible explanations for differences include under-reporting of over-the-counter medications from the study participants, such as paracetamol, misannotation of low abundance metabolites, such as metformin, and inability of the current methods to detect them. Taken together, our study provides a broad real-world view of what to expect from large non-targeted metabolomics measurements in population-based biobank studies and indicates areas where further improvements can be made. Full article

(This article belongs to the Special Issue Metabolomics Data Analysis and Quality Assessment)

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27 pages, 6569 KiB

Open AccessEditor’s ChoiceArticle

Impact of Influenza A Virus Infection on Growth and Metabolism of Suspension MDCK Cells Using a Dynamic Model

by João Rodrigues Correia Ramos, Thomas Bissinger, Yvonne Genzel and Udo Reichl

Metabolites 2022, 12(3), 239; https://doi.org/10.3390/metabo12030239 - 12 Mar 2022

Cited by 3 | Viewed by 3293

Abstract

Cell cultured-based influenza virus production is a viable option for vaccine manufacturing. In order to achieve a high concentration of viable cells, is requirement to have not only optimal process conditions, but also an active metabolism capable of intracellular synthesis of viral components. [...] Read more.

Cell cultured-based influenza virus production is a viable option for vaccine manufacturing. In order to achieve a high concentration of viable cells, is requirement to have not only optimal process conditions, but also an active metabolism capable of intracellular synthesis of viral components. Experimental metabolic data collected in such processes are complex and difficult to interpret, for which mathematical models are an appropriate way to simulate and analyze the complex and dynamic interaction between the virus and its host cell. A dynamic model with 35 states was developed in this study to describe growth, metabolism, and influenza A virus production in shake flask cultivations of suspension Madin-Darby Canine Kidney (MDCK) cells. It considers cell growth (concentration of viable cells, mean cell diameters, volume of viable cells), concentrations of key metabolites both at the intracellular and extracellular level and virus titers. Using one set of parameters, the model accurately simulates the dynamics of mock-infected cells and correctly predicts the overall dynamics of virus-infected cells for up to 60 h post infection (hpi). The model clearly suggests that most changes observed after infection are related to cessation of cell growth and the subsequent transition to apoptosis and cell death. However, predictions do not cover late phases of infection, particularly for the extracellular concentrations of glutamate and ammonium after about 12 hpi. Results obtained from additional in silico studies performed indicated that amino acid degradation by extracellular enzymes resulting from cell lysis during late infection stages may contribute to this observed discrepancy. Full article

(This article belongs to the Section Bioinformatics and Data Analysis)

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16 pages, 2108 KiB

Open AccessEditor’s ChoiceArticle

Systematic Evaluation of HILIC Stationary Phases for Global Metabolomics of Human Plasma

by Farideh Hosseinkhani, Luojiao Huang, Anne-Charlotte Dubbelman, Faisa Guled, Amy C. Harms and Thomas Hankemeier

Metabolites 2022, 12(2), 165; https://doi.org/10.3390/metabo12020165 - 09 Feb 2022

Cited by 13 | Viewed by 4216

Abstract

Polar hydrophilic metabolites have been identified as important actors in many biochemical pathways. Despite continuous improvement and refinement of hydrophilic interaction liquid chromatography (HILIC) platforms, its application in global polar metabolomics has been underutilized. In this study, we aimed to systematically evaluate polar [...] Read more.

Polar hydrophilic metabolites have been identified as important actors in many biochemical pathways. Despite continuous improvement and refinement of hydrophilic interaction liquid chromatography (HILIC) platforms, its application in global polar metabolomics has been underutilized. In this study, we aimed to systematically evaluate polar stationary phases for untargeted metabolomics by using HILIC columns (neutral and zwitterionic) that have been exploited widely in targeted approaches. To do so, high-resolution mass spectrometry was applied to thoroughly investigate selectivity, repeatability and matrix effect at three pH conditions for 9 classes of polar compounds using 54 authentic standards and plasma matrix. The column performance for utilization in untargeted metabolomics was assessed using plasma samples with diverse phenotypes. Our results indicate that the ZIC-c HILIC column operated at neutral pH exhibited several advantages, including superior performance for different classes of compounds, better isomer separation, repeatability and high metabolic coverage. Regardless of the column type, the retention of inorganic ions in plasma leads to extensive adduct formation and co-elution with analytes, which results in ion-suppression as part of the overall plasma matrix effect. In ZIC-c HILIC, the sodium chloride ion effect was particularly observed for amino acids and amine classes. Successful performance of HILIC for separation of plasma samples with different phenotypes highlights this mode of separation as a valuable approach in global profiling of plasma sample and discovering the metabolic changes associated with health and disease. Full article

(This article belongs to the Special Issue Metabolic Pathway Profiling and Untargeted/Targeted Analysis of Metabolites)

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16 pages, 3240 KiB

Open AccessEditor’s ChoiceArticle

Comparative Evaluation of Plasma Metabolomic Data from Multiple Laboratories

by Shin Nishiumi, Yoshihiro Izumi, Akiyoshi Hirayama, Masatomo Takahashi, Motonao Nakao, Kosuke Hata, Daisuke Saigusa, Eiji Hishinuma, Naomi Matsukawa, Suzumi M. Tokuoka, Yoshihiro Kita, Fumie Hamano, Nobuyuki Okahashi, Kazutaka Ikeda, Hiroki Nakanishi, Kosuke Saito, Masami Yokota Hirai, Masaru Yoshida, Yoshiya Oda, Fumio Matsuda and Takeshi Bamba Show full author list Hide full author list

Metabolites 2022, 12(2), 135; https://doi.org/10.3390/metabo12020135 - 01 Feb 2022

Viewed by 2616

Abstract

In mass spectrometry-based metabolomics, the differences in the analytical results from different laboratories/machines are an issue to be considered because various types of machines are used in each laboratory. Moreover, the analytical methods are unique to each laboratory. It is important to understand [...] Read more.

In mass spectrometry-based metabolomics, the differences in the analytical results from different laboratories/machines are an issue to be considered because various types of machines are used in each laboratory. Moreover, the analytical methods are unique to each laboratory. It is important to understand the reality of inter-laboratory differences in metabolomics. Therefore, we have evaluated whether the differences in analytical methods, with the exception sample pretreatment and including metabolite extraction, are involved in the inter-laboratory differences or not. In this study, nine facilities are evaluated for inter-laboratory comparisons of metabolomic analysis. Identical dried samples prepared from human and mouse plasma are distributed to each laboratory, and the metabolites are measured without the pretreatment that is unique to each laboratory. In these measurements, hydrophilic and hydrophobic metabolites are analyzed using 11 and 7 analytical methods, respectively. The metabolomic data acquired at each laboratory are integrated, and the differences in the metabolomic data from the laboratories are evaluated. No substantial difference in the relative quantitative data (human/mouse) for a little less than 50% of the detected metabolites is observed, and the hydrophilic metabolites have fewer differences between the laboratories compared with hydrophobic metabolites. From evaluating selected quantitatively guaranteed metabolites, the proportion of metabolites without the inter-laboratory differences is observed to be slightly high. It is difficult to resolve the inter-laboratory differences in metabolomics because all laboratories cannot prepare the same analytical environments. However, the results from this study indicate that the inter-laboratory differences in metabolomic data are due to measurement and data analysis rather than sample preparation, which will facilitate the understanding of the problems in metabolomics studies involving multiple laboratories. Full article

(This article belongs to the Special Issue Metabolic Profiling of Biofluids and Tissues Using Multiplatform Approaches)

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19 pages, 1922 KiB

Open AccessEditor’s ChoiceArticle

Automated Sample Preparation and Data Collection Workflow for High-Throughput In Vitro Metabolomics

by Julia M. Malinowska, Taina Palosaari, Jukka Sund, Donatella Carpi, Gavin R. Lloyd, Ralf J. M. Weber, Maurice Whelan and Mark R. Viant

Metabolites 2022, 12(1), 52; https://doi.org/10.3390/metabo12010052 - 08 Jan 2022

Cited by 4 | Viewed by 3526

Abstract

Regulatory bodies have started to recognise the value of in vitro screening and metabolomics as two types of new approach methodologies (NAMs) for chemical risk assessments, yet few high-throughput in vitro toxicometabolomics studies have been reported. A significant challenge is to implement automated [...] Read more.

Regulatory bodies have started to recognise the value of in vitro screening and metabolomics as two types of new approach methodologies (NAMs) for chemical risk assessments, yet few high-throughput in vitro toxicometabolomics studies have been reported. A significant challenge is to implement automated sample preparation of the low biomass samples typically used for in vitro screening. Building on previous work, we have developed, characterised and demonstrated an automated sample preparation and analysis workflow for in vitro metabolomics of HepaRG cells in 96-well microplates using a Biomek i7 Hybrid Workstation (Beckman Coulter) and Orbitrap Elite (Thermo Scientific) high-resolution nanoelectrospray direct infusion mass spectrometry (nESI-DIMS), across polar metabolites and lipids. The experimental conditions evaluated included the day of metabolite extraction, order of extraction of samples in 96-well microplates, position of the 96-well microplate on the instrument’s deck and well location within a microplate. By using the median relative standard deviation (mRSD (%)) of spectral features, we have demonstrated good repeatability of the workflow (final mRSD < 30%) with a low percentage of features outside the threshold applied for statistical analysis. To improve the quality of the automated workflow further, small method modifications were made and then applied to a large cohort study (4860 sample infusions across three nESI-DIMS assays), which confirmed very high repeatability of the whole workflow from cell culturing to metabolite measurements, whilst providing a significant improvement in sample throughput. It is envisioned that the automated in vitro metabolomics workflow will help to advance the application of metabolomics (as a part of NAMs) in chemical safety, primarily as an approach for high throughput screening and prioritisation. Full article

(This article belongs to the Special Issue Sample Preparation in Metabolomics Volume II)

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18 pages, 1374 KiB

Open AccessEditor’s ChoiceArticle

Untargeted Metabolomics Reveals a Complex Impact on Different Metabolic Pathways in Scallop Mimachlamys varia (Linnaeus, 1758) after Short-Term Exposure to Copper at Environmental Dose

by Vincent Hamani, Pascaline Ory, Pierre-Edouard Bodet, Laurence Murillo and Marianne Graber

Metabolites 2021, 11(12), 862; https://doi.org/10.3390/metabo11120862 - 11 Dec 2021

Cited by 7 | Viewed by 2693

Abstract

Ports are a good example of how coastal environments, gathering a set of diverse ecosystems, are subjected to pollution factors coming from human activities both on land and at sea. Among them, trace element as copper represents a major factor. Abundant in port [...] Read more.

Ports are a good example of how coastal environments, gathering a set of diverse ecosystems, are subjected to pollution factors coming from human activities both on land and at sea. Among them, trace element as copper represents a major factor. Abundant in port ecosystem, copper is transported by runoff water and results from diverse port features (corrosion of structures, fuel, anti-fouling products, etc.). The variegated scallop Mimachlamys varia is common in the Atlantic port areas and is likely to be directly influenced by copper pollution, due to its sessile and filtering lifestyle. Thus, the aim of the present study is to investigate the disruption of the variegated scallop metabolism, under a short exposure (48 h) to a copper concentration frequently encountered in the waters of the largest marina in Europe (82 μg/L). For this, we chose a non-targeted metabolomic approach using ultra-high performance liquid chromatography coupled to high resolution mass spectrometry (UHPLC-HRMS), offering a high level of sensitivity and allowing the study without a priori of the entire metabolome. We described 28 metabolites clearly modulated by copper. They reflected the action of copper on several biological functions such as osmoregulation, oxidative stress, reproduction and energy metabolism. Full article

(This article belongs to the Special Issue Application of Metabolomic in Ecotoxicology)

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23 pages, 2685 KiB

Open AccessEditor’s ChoiceArticle

Cascading Effects of Root Microbial Symbiosis on the Development and Metabolome of the Insect Herbivore Manduca sexta L.

by Dimitra Papantoniou, Fredd Vergara, Alexander Weinhold, Teresa Quijano, Bekzod Khakimov, David I. Pattison, Søren Bak, Nicole M. van Dam and Ainhoa Martínez-Medina

Metabolites 2021, 11(11), 731; https://doi.org/10.3390/metabo11110731 - 25 Oct 2021

Cited by 12 | Viewed by 4193

Abstract

Root mutualistic microbes can modulate the production of plant secondary metabolites affecting plant–herbivore interactions. Still, the main mechanisms underlying the impact of root mutualists on herbivore performance remain ambiguous. In particular, little is known about how changes in the plant metabolome induced by [...] Read more.

Root mutualistic microbes can modulate the production of plant secondary metabolites affecting plant–herbivore interactions. Still, the main mechanisms underlying the impact of root mutualists on herbivore performance remain ambiguous. In particular, little is known about how changes in the plant metabolome induced by root mutualists affect the insect metabolome and post-larval development. By using bioassays with tomato plants (Solanum lycopersicum), we analyzed the impact of the arbuscular mycorrhizal fungus Rhizophagus irregularis and the growth-promoting fungus Trichoderma harzianum on the plant interaction with the specialist insect herbivore Manduca sexta. We found that root colonization by the mutualistic microbes impaired insect development, including metamorphosis. By using untargeted metabolomics, we found that root colonization by the mutualistic microbes altered the secondary metabolism of tomato shoots, leading to enhanced levels of steroidal glycoalkaloids. Untargeted metabolomics further revealed that root colonization by the mutualists affected the metabolome of the herbivore, leading to an enhanced accumulation of steroidal glycoalkaloids and altered patterns of fatty acid amides and carnitine-derived metabolites. Our results indicate that the changes in the shoot metabolome triggered by root mutualistic microbes can cascade up altering the metabolome of the insects feeding on the colonized plants, thus affecting the insect development. Full article

(This article belongs to the Special Issue Metabolomics in Chemical Ecology)

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13 pages, 5248 KiB

Open AccessEditor’s ChoiceArticle

Analytical Methodology for a Metabolome Atlas of Goat’s Plasma, Milk and Feces Using ¹H-NMR and UHPLC-HRMS

by Cécile Martias, Julie Gatien, Léa Roch, Nadine Baroukh, Sylvie Mavel, Antoine Lefèvre, Frédéric Montigny, Laurent Schibler, Patrick Emond and Lydie Nadal-Desbarats

Metabolites 2021, 11(10), 681; https://doi.org/10.3390/metabo11100681 - 04 Oct 2021

Viewed by 2026

Abstract

Metabolomics has been increasingly used in animal and food sciences. Animal health is one of the most important factor that can also alter animal integrity and welfare. Some studies have already investigated the link between health and metabolic profile of dairy animals. These [...] Read more.

Metabolomics has been increasingly used in animal and food sciences. Animal health is one of the most important factor that can also alter animal integrity and welfare. Some studies have already investigated the link between health and metabolic profile of dairy animals. These studies in metabolomics often consider a single type of sample using a single analytical platform (nuclear magnetic resonance or mass spectrometry). Only few studies with multi-platform approaches are also used with a single or a multi type of sample, but they mainly consider dairy cows’ metabolome although dairy goats present similar diseases, that it could be interesting to detect early to preserve animal health and milk production. This study aims to create a metabolic atlas of goat plasma, milk and feces, based on healthy animals. Our study describes a standard operating procedure for three goat matrices: blood plasma, milk, and feces using multiple platforms (NMR (¹H), UHPLC (RP)-MS and UHPLC (HILIC)-MS) that follows a unique sample preparation procedure for each sample type to be analyzed on multi-platforms basis. Our method was evaluated for its robustness and allowed a better characterization of goat metabolic profile in healthy conditions. Full article

(This article belongs to the Special Issue Metabolomic Applications in Animal Science Volume 2)

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20 pages, 2247 KiB

Open AccessEditor’s ChoiceArticle

An Extensive Metabolomics Workflow to Discover Cardiotoxin-Induced Molecular Perturbations in Microtissues

by Tara J. Bowen, Andrew R. Hall, Gavin R. Lloyd, Ralf J. M. Weber, Amanda Wilson, Amy Pointon and Mark R. Viant

Metabolites 2021, 11(9), 644; https://doi.org/10.3390/metabo11090644 - 21 Sep 2021

Cited by 3 | Viewed by 2685

Abstract

Discovering modes of action and predictive biomarkers of drug-induced structural cardiotoxicity offers the potential to improve cardiac safety assessment of lead compounds and enhance preclinical to clinical translation during drug development. Cardiac microtissues are a promising, physiologically relevant, in vitro model, each composed [...] Read more.

Discovering modes of action and predictive biomarkers of drug-induced structural cardiotoxicity offers the potential to improve cardiac safety assessment of lead compounds and enhance preclinical to clinical translation during drug development. Cardiac microtissues are a promising, physiologically relevant, in vitro model, each composed of ca. 500 cells. While untargeted metabolomics is capable of generating hypotheses on toxicological modes of action and discovering metabolic biomarkers, applying this technology to low-biomass microtissues in suspension is experimentally challenging. Thus, we first evaluated a filtration-based approach for harvesting microtissues and assessed the sensitivity and reproducibility of nanoelectrospray direct infusion mass spectrometry (nESI-DIMS) measurements of intracellular extracts, revealing samples consisting of 28 pooled microtissues, harvested by filtration, are suitable for profiling the intracellular metabolome and lipidome. Subsequently, an extensive workflow combining nESI-DIMS untargeted metabolomics and lipidomics of intracellular extracts with ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS/MS) analysis of spent culture medium, to profile the metabolic footprint and quantify drug exposure concentrations, was implemented. Using the synthetic drug and model cardiotoxin sunitinib, time-resolved metabolic and lipid perturbations in cardiac microtissues were investigated, providing valuable data for generating hypotheses on toxicological modes of action and identifying putative biomarkers such as disruption of purine metabolism and perturbation of polyunsaturated fatty acid levels. Full article

(This article belongs to the Special Issue Toxicometabolomics)

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12 pages, 706 KiB

Open AccessEditor’s ChoiceArticle

Significance of Metabolite Ratios in the Interpretation of Segmental Hair Testing Results—Differentiation of Single from Chronic Morphine Use in a Case Series

by Milena M. Madry, Sandra N. Poetzsch, Andrea E. Steuer, Thomas Kraemer and Markus R. Baumgartner

Metabolites 2021, 11(8), 557; https://doi.org/10.3390/metabo11080557 - 22 Aug 2021

Cited by 3 | Viewed by 2282

Abstract

In morphine intoxication cases, forensic toxicologists are frequently confronted with the question of if the individual was opioid-tolerant or opioid-naïve, which can be investigated by hair analysis. However, interpretation of results can be challenging. Here, we report on hair testing for morphine and [...] Read more.

In morphine intoxication cases, forensic toxicologists are frequently confronted with the question of if the individual was opioid-tolerant or opioid-naïve, which can be investigated by hair analysis. However, interpretation of results can be challenging. Here, we report on hair testing for morphine and its metabolite hydromorphone following morphine intoxication without tolerance and upon chronic use. Two consecutive hair samples were collected after a non-fatal intoxication. Analysis comprised short hair segments and their initial wash water solutions. In the intoxications, morphine and hydromorphone levels were 3.3 to 56 pg/mg and at maximum 9.8 pg/mg, respectively. Both levels and hydromorphone to morphine ratios were significantly lower compared to chronic morphine use. In the non-fatal intoxication, the highest hydromorphone to morphine ratio was obtained in the segment corresponding to the time of intoxication. Morphine ratios of wash to hair were significantly higher in the intoxications compared to chronic use, being indicative of sweat/sebum contamination. We recommend including the analysis of hydromorphone and the initial wash solution in cases of morphine intoxications. Our study demonstrates that hydromorphone to morphine ratios can help in distinguishing single from chronic morphine use and in estimating the period of exposure when a consecutive hair sample can be collected in survived intoxications. Full article

(This article belongs to the Special Issue Metabolite Analysis in Forensic Toxicology)

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13 pages, 1506 KiB

Open AccessEditor’s ChoiceArticle

Acute Administration of Exogenous Lactate Increases Carbohydrate Metabolism during Exercise in Mice

by Inkwon Jang, Jisu Kim, Sunghwan Kyun, Deunsol Hwang and Kiwon Lim

Metabolites 2021, 11(8), 553; https://doi.org/10.3390/metabo11080553 - 21 Aug 2021

Cited by 6 | Viewed by 2870

Abstract

In this study, we investigated the effects of exogenous lactate administration before exercise on energy substrate utilization during exercise. Mice were divided into exercise control (EX) and exercise with lactate intake (EXLA) groups; saline/lactate was administered 30 min before exercise. Respiratory gas was [...] Read more.

In this study, we investigated the effects of exogenous lactate administration before exercise on energy substrate utilization during exercise. Mice were divided into exercise control (EX) and exercise with lactate intake (EXLA) groups; saline/lactate was administered 30 min before exercise. Respiratory gas was measured during moderate intensity treadmill exercise (30 min). Immediately after exercise, blood, liver, and skeletal muscle samples were collected and mRNA levels of energy metabolism-related and metabolic factors were analyzed. At 16–30 min of exercise, the respiratory exchange ratio (p = 0.045) and carbohydrate oxidation level (p = 0.014) were significantly higher in the EXLA than in the EX group. Immediately after exercise, the muscle and liver glycogen content and blood glucose level of the EXLA group were lower than those of the EX group. In addition, muscle mRNA levels of HK2 (hexokinase 2; p = 0.009), a carbohydrate oxidation-related factor, were higher in the EXLA than in the EX group, whereas the expression of PDK4 (pyruvate dehydrogenase kinase 4; p = 0.001), CS (citrate synthase; p = 0.045), and CD36 (cluster of differentiation 36; p = 0.002), factors related to oxidative metabolism, was higher in the EX than in the EXLA group. These results suggest that lactate can be used in various research fields to promote carbohydrate metabolism. Full article

(This article belongs to the Section Animal Metabolism)

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17 pages, 2265 KiB

Open AccessEditor’s ChoiceArticle

Enantioselective Quantification of Amphetamine and Metabolites in Serum Samples: Forensic Evaluation and Estimation of Consumption Time

by Moritz Losacker, Michael Kraemer, Alexandra Philipsen, Kristina Duecker, Nadine Dreimueller, Jan Engelmann, Joerg Roehrich and Cornelius Hess

Metabolites 2021, 11(8), 521; https://doi.org/10.3390/metabo11080521 - 06 Aug 2021

Cited by 9 | Viewed by 3114

Abstract

In forensic toxicology, amphetamine intoxications represent one of the most common case groups and present difficult questions for toxicologists. Estimating the time of consumption and the current influence of the stimulant is particularly difficult when only total amphetamine concentrations are considered. Stereoselective analysis [...] Read more.

In forensic toxicology, amphetamine intoxications represent one of the most common case groups and present difficult questions for toxicologists. Estimating the time of consumption and the current influence of the stimulant is particularly difficult when only total amphetamine concentrations are considered. Stereoselective analysis and the consideration of metabolites can provide valuable information to facilitate interpretation. An enantioselective liquid chromatography−tandem mass spectrometry (LC-MS/MS) method for detection of amphetamine, norephedrine and 4-hydroxyamphetamine was developed. Validation showed satisfactory selectivity, sensitivity, linearity (0.5–250 ng/mL), precision and accuracy for all enantiomers. The method was applied to a collective of 425 forensic serum samples and 30 serum samples from psychiatric inpatients stating their last time of amphetamine consumption. Norephedrine and 4-hydroxyamphetamine were detected more frequently at higher amphetamine concentrations and at lower amphetamine (R)/(S) concentration ratios, possibly indicating recent consumption. Mean (R)/(S) ratio of amphetamine was 1.14, whereas higher ratios (mean 1.36) were found for amphetamine concentrations below 100 ng/mL. The (R)/(S) ratios of psychiatric inpatients significantly correlated with the reported time intervals to last consumption. The use of amphetamine (R)/(S) ratios and the simultaneous detection of metabolites are promising factors that can facilitate estimation of consumption time and current impairment. Full article

(This article belongs to the Special Issue Metabolite Analysis in Forensic Toxicology)

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13 pages, 1542 KiB

Open AccessEditor’s ChoiceArticle

Proline as a Sparker Metabolite of Oxidative Metabolism during the Flight of the Bumblebee, Bombus impatiens

by Nadia Stec, Ammar Saleem and Charles-A. Darveau

Metabolites 2021, 11(8), 511; https://doi.org/10.3390/metabo11080511 - 04 Aug 2021

Cited by 10 | Viewed by 2548

Abstract

Several insect species use the amino acid proline as a major energy substrate. Although initially thought to be limited to blood-feeding dipterans, studies have revealed this capability is more widespread. Recent work with isolated flight muscle showed that the bumblebee Bombus impatiens can [...] Read more.

Several insect species use the amino acid proline as a major energy substrate. Although initially thought to be limited to blood-feeding dipterans, studies have revealed this capability is more widespread. Recent work with isolated flight muscle showed that the bumblebee Bombus impatiens can oxidize proline at a high rate. However, its role as a metabolic fuel to power flight is unclear. To elucidate the extent to which proline is oxidized to power flight and how its contribution changes during flight, we profiled 14 metabolites central to energy and proline metabolism at key time points in flight muscle and abdominal tissues. Ultra-high performance liquid chromatography-electrospray ionization-quadrupole time of flight mass spectrometry (UPLC-ESI-QTOF MS) analysis revealed that proline is likely used as a sparker metabolite of the tricarboxylic acid cycle at the onset of flight, whereby it supplements the intermediates of the cycle. Carbohydrates are the major energy substrates, which is evidenced by marked decreases in abdominal glycogen stores and a lack of alanine accumulation to replenish flight muscle proline. The time course of fuel stores and metabolites changes during flight highlights homeostatic regulation of energy substrates and patterns of changes in metabolic intermediates within pathways. This study clarifies the role of proline and carbohydrate metabolism during flight in hymenopterans, such as B. impatiens. Full article

(This article belongs to the Special Issue Ectotherms Metabolism: Plasticity and Adaptation)

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14 pages, 3236 KiB

Open AccessEditor’s ChoiceArticle

In Vitro Metabolic Fate of the Synthetic Cannabinoid Receptor Agonists QMPSB and QMPCB (SGT-11) Including Isozyme Mapping and Esterase Activity

by Matthias J. Richter, Lea Wagmann, Tanja M. Gampfer, Simon D. Brandt and Markus R. Meyer

Metabolites 2021, 11(8), 509; https://doi.org/10.3390/metabo11080509 - 03 Aug 2021

Cited by 7 | Viewed by 2226

Abstract

Quinolin-8-yl 4-methyl-3-(piperidine-1-sulfonyl)benzoate (QMPSB) and quinolin-8-yl 4-methyl-3-(piperidine-1-carbonyl)benzoate (QMPCB, SGT-11) are synthetic cannabinoid receptor agonists (SCRAs). Knowing their metabolic fate is crucial for the identification of toxicological screening targets and to predict possible drug interactions. The presented study aimed to identify the in vitro phase [...] Read more.

Quinolin-8-yl 4-methyl-3-(piperidine-1-sulfonyl)benzoate (QMPSB) and quinolin-8-yl 4-methyl-3-(piperidine-1-carbonyl)benzoate (QMPCB, SGT-11) are synthetic cannabinoid receptor agonists (SCRAs). Knowing their metabolic fate is crucial for the identification of toxicological screening targets and to predict possible drug interactions. The presented study aimed to identify the in vitro phase I/II metabolites of QMPSB and QMPCB and to study the contribution of different monooxygenases and human carboxylesterases by using pooled human liver S9 fraction (pHLS9), recombinant human monooxygenases, three recombinant human carboxylesterases, and pooled human liver microsomes. Analyses were carried out by liquid chromatography high-resolution tandem mass spectrometry. QMPSB and QMPCB showed ester hydrolysis, and hydroxy and carboxylic acid products were detected in both cases. Mono/dihydroxy metabolites were formed, as were corresponding glucuronides and sulfates. Most of the metabolites could be detected in positive ionization mode with the exception of some QMPSB metabolites, which could only be found in negative mode. Monooxygenase activity screening revealed that CYP2B6/CYP2C8/CYP2C9/CYP2C19/CYP3A4/CYP3A5 were involved in hydroxylations. Esterase screening showed the involvement of all investigated isoforms. Additionally, extensive non-enzymatic ester hydrolysis was observed. Considering the results of the in vitro experiments, inclusion of the ester hydrolysis products and their glucuronides and monohydroxy metabolites into toxicological screening procedures is recommended. Full article

(This article belongs to the Special Issue Metabolite Analysis in Forensic Toxicology)

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16 pages, 3065 KiB

Open AccessEditor’s ChoiceArticle

High Throughput Procedure for Comparative Analysis of In Vivo Cardiac Glucose or Amino Acids Use in Cardiovascular Pathologies and Pharmacological Treatments

by Marta Tomczyk, Mariola Olkowicz, Ewa M. Slominska and Ryszard T. Smolenski

Metabolites 2021, 11(8), 497; https://doi.org/10.3390/metabo11080497 - 30 Jul 2021

Cited by 3 | Viewed by 2725

Abstract

The heart is characterized by the prominent flexibility of its energy metabolism and is able to use diverse carbon substrates, including carbohydrates and amino acids. Cardiac substrate preference could have a major impact on the progress of cardiac pathologies. However, the majority of [...] Read more.

The heart is characterized by the prominent flexibility of its energy metabolism and is able to use diverse carbon substrates, including carbohydrates and amino acids. Cardiac substrate preference could have a major impact on the progress of cardiac pathologies. However, the majority of methods to investigate changes in substrates’ use in cardiac metabolism in vivo are complex and not suitable for high throughput testing necessary to understand and reverse these pathologies. Thus, this study aimed to develop a simple method that would allow for the analysis of cardiac metabolic substrate use. The developed methods involved the subcutaneous injection of stable ¹³C isotopomers of glucose, valine, or leucine with mass spectrometric analysis for the investigation of its entry into cardiac metabolic pathways that were deducted from ¹³C alanine and glutamate enrichments in heart extracts. The procedures were validated by confirming the known effects of treatments that modify glucose, free fatty acids, and amino acid metabolism. Furthermore, we studied changes in the energy metabolism of CD73 knock-out mice to demonstrate the potential of our methods in experimental research. The methods created allowed for fast estimation of cardiac glucose and amino acid use in mice and had the potential for high-throughput analysis of changes in pathology and after pharmacological treatments. Full article

(This article belongs to the Special Issue Insights into the Bioenergetics and Metabolism in Normal and Failing Heart)

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21 pages, 5054 KiB

Open AccessEditor’s ChoiceArticle

Short Duration Alagebrium Chloride Therapy Prediabetes Does Not Inhibit Progression to Autoimmune Diabetes in an Experimental Model

by Danielle J. Borg, Pouya Faridi, Kai Lin Giam, Peta Reeves, Amelia K. Fotheringham, Domenica A. McCarthy, Sherman Leung, Micheal S. Ward, Brooke E. Harcourt, Rochelle Ayala, Jean L. Scheijen, David Briskey, Nadine L. Dudek, Casper G. Schalkwijk, Raymond Steptoe, Anthony W. Purcell and Josephine M. Forbes

Metabolites 2021, 11(7), 426; https://doi.org/10.3390/metabo11070426 - 28 Jun 2021

Cited by 2 | Viewed by 3049

Abstract

Mechanisms by which advanced glycation end products (AGEs) contribute to type 1 diabetes (T1D) pathogenesis are poorly understood. Since life-long pharmacotherapy with alagebrium chloride (ALT) slows progression to experimental T1D, we hypothesized that acute ALT therapy delivered prediabetes, may be effective. However, in [...] Read more.

Mechanisms by which advanced glycation end products (AGEs) contribute to type 1 diabetes (T1D) pathogenesis are poorly understood. Since life-long pharmacotherapy with alagebrium chloride (ALT) slows progression to experimental T1D, we hypothesized that acute ALT therapy delivered prediabetes, may be effective. However, in female, non-obese diabetic (NODShiLt) mice, ALT administered prediabetes (day 50–100) did not protect against experimental T1D. ALT did not decrease circulating AGEs or their precursors. Despite this, pancreatic β-cell function was improved, and insulitis and pancreatic CD45.1⁺ cell infiltration was reduced. Lymphoid tissues were unaffected. ALT pre-treatment, prior to transfer of primed GC98 CD8⁺ T cell receptor transgenic T cells, reduced blood glucose concentrations and delayed diabetes, suggesting islet effects rather than immune modulation by ALT. Indeed, ALT did not reduce interferon-γ production by leukocytes from ovalbumin-pre-immunised NODShiLt mice and NODscid recipients given diabetogenic ALT treated NOD splenocytes were not protected against T1D. To elucidate β-cell effects, NOD-derived MIN6N8 β-cell major histocompatibility complex (MHC) Class Ia surface antigens were examined using immunopeptidomics. Overall, no major changes in the immunopeptidome were observed during the various treatments with all peptides exhibiting allele specific consensus binding motifs. As expected, longer MHC Class Ia peptides were captured bound to H-2D^b than H-2K^b under all conditions. Moreover, more 10–12 mer peptides were isolated from H-2D^b after AGE modified bovine serum albumin (AGE-BSA) treatment, compared with bovine serum albumin (BSA) or AGE-BSA+ALT treatment. Proteomics of MIN6N8 cells showed enrichment of processes associated with catabolism, the immune system, cell cycling and presynaptic endocytosis with AGE-BSA compared with BSA treatments. These data show that short-term ALT intervention, given prediabetes, does not arrest experimental T1D but transiently impacts β-cell function. Full article

(This article belongs to the Special Issue Islet Biology and Metabolism)

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14 pages, 4165 KiB

Open AccessEditor’s ChoiceArticle

Lipidomic Analysis to Assess Oxidative Stress in Acute Coronary Syndrome and Acute Stroke Patients

by Martin Malý, Martin Hajšl, Kamila Bechyňská, Ondřej Kučerka, Martin Šrámek, Jiří Suttnar, Alžběta Hlaváčková, Jana Hajšlová and Vít Kosek

Metabolites 2021, 11(7), 412; https://doi.org/10.3390/metabo11070412 - 23 Jun 2021

Cited by 11 | Viewed by 2830

Abstract

Alterations in lipid metabolism mediated by oxidative stress play a key role in the process of atherosclerosis and superimposed thrombosis; these can lead to acute coronary syndrome (ACS) and acute ischemic stroke (AIS). Multiple studies have shown that the formation of atheromatous lesions [...] Read more.

Alterations in lipid metabolism mediated by oxidative stress play a key role in the process of atherosclerosis and superimposed thrombosis; these can lead to acute coronary syndrome (ACS) and acute ischemic stroke (AIS). Multiple studies have shown that the formation of atheromatous lesions is initiated by oxidation of low-density lipoproteins incorporated into the intima of the vessel wall. Here, we studied lipids in plasma samples from three cohorts: 61 patients with ACS (group A), 49 patients with AIS (group D), and 82 controls (group K). Untargeted lipidomics based on high-performance liquid chromatography coupled to mass spectrometry (UHPLC-HRMS) was employed to obtain comprehensive information on whether relationships exist between these patient categories based on lipid patterns. In addition, malondialdehyde (MDA) as a standard marker of oxidative stress was monitored. The most characteristic lipids in group K were fatty acyls of hydroxyfatty acids (FAHFAs). As expected, MDA concentrations were the lowest in group K. Our findings can better explain ongoing pathologies, both acute and chronic, with the potential for future diagnosis and treatment. Full article

(This article belongs to the Special Issue Thrombosis and Metabolism)

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13 pages, 779 KiB

Open AccessEditor’s ChoiceReview

Measurement of Pulsatile Insulin Secretion: Rationale and Methodology

by Marcello C. Laurenti, Aleksey Matveyenko and Adrian Vella

Metabolites 2021, 11(7), 409; https://doi.org/10.3390/metabo11070409 - 22 Jun 2021

Cited by 12 | Viewed by 2785

Abstract

Pancreatic β-cells are responsible for the synthesis and exocytosis of insulin in response to an increase in circulating glucose. Insulin secretion occurs in a pulsatile manner, with oscillatory pulses superimposed on a basal secretion rate. Insulin pulses are a marker of β-cell health, [...] Read more.

Pancreatic β-cells are responsible for the synthesis and exocytosis of insulin in response to an increase in circulating glucose. Insulin secretion occurs in a pulsatile manner, with oscillatory pulses superimposed on a basal secretion rate. Insulin pulses are a marker of β-cell health, and secretory parameters, such as pulse amplitude, time interval and frequency distribution, are impaired in obesity, aging and type 2 diabetes. In this review, we detail the mechanisms of insulin production and β-cell synchronization that regulate pulsatile insulin secretion, and we discuss the challenges to consider when measuring fast oscillatory secretion in vivo. These include the anatomical difficulties of measuring portal vein insulin noninvasively in humans before the hormone is extracted by the liver and quickly removed from the circulation. Peripheral concentrations of insulin or C-peptide, a peptide cosecreted with insulin, can be used to estimate their secretion profile, but mathematical deconvolution is required. Parametric and nonparametric approaches to the deconvolution problem are evaluated, alongside the assumptions and trade-offs required for their application in the quantification of unknown insulin secretory rates from known peripheral concentrations. Finally, we discuss the therapeutical implication of targeting impaired pulsatile secretion and its diagnostic value as an early indicator of β-cell stress. Full article

(This article belongs to the Special Issue Insulin: A Life-Saving Hormone and Key Regulator of Metabolism)

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37 pages, 1443 KiB

Open AccessEditor’s ChoiceReview

What We Know So Far about the Metabolite-Mediated Microbiota-Intestinal Immunity Dialogue and How to Hear the Sound of This Crosstalk

by Clément Caffaratti, Caroline Plazy, Geoffroy Mery, Abdoul-Razak Tidjani, Federica Fiorini, Sarah Thiroux, Bertrand Toussaint, Dalil Hannani and Audrey Le Gouellec

Metabolites 2021, 11(6), 406; https://doi.org/10.3390/metabo11060406 - 21 Jun 2021

Cited by 16 | Viewed by 7323

Abstract

Trillions of microorganisms, termed the “microbiota”, reside in the mammalian gastrointestinal tract, and collectively participate in regulating the host phenotype. It is now clear that the gut microbiota, metabolites, and intestinal immune function are correlated, and that alterations of the complex and dynamic [...] Read more.

Trillions of microorganisms, termed the “microbiota”, reside in the mammalian gastrointestinal tract, and collectively participate in regulating the host phenotype. It is now clear that the gut microbiota, metabolites, and intestinal immune function are correlated, and that alterations of the complex and dynamic host-microbiota interactions can have deep consequences for host health. However, the mechanisms by which the immune system regulates the microbiota and by which the microbiota shapes host immunity are still not fully understood. This article discusses the contribution of metabolites in the crosstalk between gut microbiota and immune cells. The identification of key metabolites having a causal effect on immune responses and of the mechanisms involved can contribute to a deeper insight into host-microorganism relationships. This will allow a better understanding of the correlation between dysbiosis, microbial-based dysmetabolism, and pathogenesis, thus creating opportunities to develop microbiota-based therapeutics to improve human health. In particular, we systematically review the role of soluble and membrane-bound microbial metabolites in modulating host immunity in the gut, and of immune cells-derived metabolites affecting the microbiota, while discussing evidence of the bidirectional impact of this crosstalk. Furthermore, we discuss the potential strategies to hear the sound of such metabolite-mediated crosstalk. Full article

(This article belongs to the Special Issue Reviews and Advances in Microbial Metabolomics)

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19 pages, 9214 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Metabolomic Study of High-Fat Diet-Induced Obese (DIO) and DIO Plus CCl₄-Induced NASH Mice and the Effect of Obeticholic Acid

by Nanlin Zhu, Suling Huang, Qingli Zhang, Zhuohui Zhao, Hui Qu, Mengmeng Ning, Ying Leng and Jia Liu

Metabolites 2021, 11(6), 374; https://doi.org/10.3390/metabo11060374 - 10 Jun 2021

Cited by 6 | Viewed by 3991

Abstract

The pathophysiology of nonalcoholic fatty liver disease (NAFLD) is a complex process involving metabolic and inflammatory changes in livers and other organs, but the pathogenesis is still not well clarified. Two mouse models were established to study metabolic alteration of nonalcoholic fatty liver [...] Read more.

The pathophysiology of nonalcoholic fatty liver disease (NAFLD) is a complex process involving metabolic and inflammatory changes in livers and other organs, but the pathogenesis is still not well clarified. Two mouse models were established to study metabolic alteration of nonalcoholic fatty liver and nonalcoholic steatohepatitis, respectively. The concentrations of metabolites in serum, liver and intestine content were measured by the AbsoluteIDQ^® p180 Kit (Biocrates Life Sciences, Innsbruck, Austria). Multivariate statistical methods, pathway analysis, enrichment analysis and correlation analysis were performed to analyze metabolomic data. The metabolic characteristics of liver, serum and intestine content could be distinctly distinguished from each group, indicating the occurrence of metabolic disturbance. Among them, metabolic alteration of liver and intestine content was more significant. Based on the metabolic data of liver, 19 differential metabolites were discovered between DIO and control, 12 between DIO-CCl₄ and DIO, and 47 between DIO-CCl₄ and normal. These metabolites were mainly associated with aminoacyl-tRNA biosynthesis, nitrogen metabolism, lipid metabolism, glyoxylate and dicarboxylate metabolism, and amino metabolism. Further study revealed that the intervention of obeticholic acid (OCA) could partly reverse the damage of CCl₄. The correlation analysis of metabolite levels and clinical parameters showed that phosphatidylcholines were negatively associated with serum alanine aminotransferase, aspartate aminotransferase, NAFLD activity score, and fibrosis score, while lysophosphatidylcholines, sphingomyelins, amino acids, and acylcarnitines shared the reverse pattern. Our study investigated metabolic alteration among control, NAFLD model, and OCA treatment groups, providing preclinical information to understand the mechanism of NAFLD and amelioration of OCA. Full article

(This article belongs to the Section Endocrinology and Clinical Metabolic Research)

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15 pages, 3480 KiB

Open AccessEditor’s ChoiceArticle

Hypothalamic Expression of Neuropeptide Y (NPY) and Pro-OpioMelanoCortin (POMC) in Adult Male Mice Is Affected by Chronic Exposure to Endocrine Disruptors

by Marilena Marraudino, Elisabetta Bo, Elisabetta Carlini, Alice Farinetti, Giovanna Ponti, Isabella Zanella, Diego Di Lorenzo, Gian Carlo Panzica and Stefano Gotti

Metabolites 2021, 11(6), 368; https://doi.org/10.3390/metabo11060368 - 09 Jun 2021

Cited by 10 | Viewed by 3412

Abstract

In the arcuate nucleus, neuropeptide Y (NPY) neurons, increase food intake and decrease energy expenditure, and control the activity of pro-opiomelanocortin (POMC) neurons, that decrease food intake and increase energy expenditure. Both systems project to other hypothalamic nuclei such as the paraventricular and [...] Read more.

In the arcuate nucleus, neuropeptide Y (NPY) neurons, increase food intake and decrease energy expenditure, and control the activity of pro-opiomelanocortin (POMC) neurons, that decrease food intake and increase energy expenditure. Both systems project to other hypothalamic nuclei such as the paraventricular and dorsomedial hypothalamic nuclei. Endocrine disrupting chemicals (EDCs) are environmental contaminants that alter the endocrine system causing adverse health effects in an intact organism or its progeny. We investigated the effects of long-term exposure to some EDCs on the hypothalamic NPY and POMC systems of adult male mice that had been previously demonstrated to be a target of some of these EDCs after short-term exposure. Animals were chronically fed for four months with a phytoestrogen-free diet containing two different concentrations of bisphenol A, diethylstilbestrol, tributyltin, or E₂. At the end, brains were processed for NPY and POMC immunohistochemistry and quantitatively analyzed. In the arcuate and dorsomedial nuclei, both NPY and POMC immunoreactivity showed a statistically significant decrease. In the paraventricular nucleus, only the NPY system was affected, while the POMC system was not affected. Finally, in the VMH the NPY system was affected whereas no POMC immunoreactive material was observed. These results indicate that adult exposure to different EDCs may alter the hypothalamic circuits that control food intake and energy metabolism. Full article

(This article belongs to the Special Issue Neuroendocrine Control of Energy Metabolism)

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13 pages, 1792 KiB

Open AccessEditor’s ChoiceArticle

Identification of Circulating Diagnostic Biomarkers for Coronary Microvascular Disease in Postmenopausal Women Using Machine-Learning Techniques

by Alicia Arredondo Eve, Elif Tunc, Yu-Jeh Liu, Saumya Agrawal, Huriye Erbak Yilmaz, Sadık Volkan Emren, Filiz Akyıldız Akçay, Luidmila Mainzer, Justina Žurauskienė and Zeynep Madak Erdogan

Metabolites 2021, 11(6), 339; https://doi.org/10.3390/metabo11060339 - 25 May 2021

Cited by 3 | Viewed by 4074

Abstract

Coronary microvascular disease (CMD) is a common form of heart disease in postmenopausal women. It is not due to plaque formation but dysfunction of microvessels that feed the heart muscle. The majority of the patients do not receive a proper diagnosis, are discharged [...] Read more.

Coronary microvascular disease (CMD) is a common form of heart disease in postmenopausal women. It is not due to plaque formation but dysfunction of microvessels that feed the heart muscle. The majority of the patients do not receive a proper diagnosis, are discharged prematurely and must go back to the hospital with persistent symptoms. Because of the lack of diagnostic biomarkers, in the current study, we focused on identifying novel circulating biomarkers of CMV that could potentially be used for developing a diagnostic test. We hypothesized that plasma metabolite composition is different for postmenopausal women with no heart disease, CAD, or CMD. A total of 70 postmenopausal women, 26 healthy individuals, 23 individuals with CMD and 21 individuals with CAD were recruited. Their full health screening and tests were completed. Basic cardiac examination, including detailed clinical history, additional disease and prescribed drugs, were noted. Electrocardiograph, transthoracic echocardiography and laboratory analysis were also obtained. Additionally, we performed full metabolite profiling of plasma samples from these individuals using gas chromatography-mass spectrometry (GC–MS) analysis, identified and classified circulating biomarkers using machine learning approaches. Stearic acid and ornithine levels were significantly higher in postmenopausal women with CMD. In contrast, valine levels were higher for women with CAD. Our research identified potential circulating plasma biomarkers of this debilitating heart disease in postmenopausal women, which will have a clinical impact on diagnostic test design in the future. Full article

(This article belongs to the Special Issue Biomarkers for Metabolism and Cardiometabolic Diseases)

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26 pages, 1764 KiB

Open AccessEditor’s ChoiceReview

Thromboembolic Complications of SARS-CoV-2 and Metabolic Derangements: Suggestions from Clinical Practice Evidence to Causative Agents

by Francesco Nappi, Adelaide Iervolino and Sanjeet Singh Avtaar Singh

Metabolites 2021, 11(6), 341; https://doi.org/10.3390/metabo11060341 - 25 May 2021

Cited by 11 | Viewed by 3806

Abstract

Severe Acute Respiratory Syndrome (SARS) Coronavirus (CoV)-2 is a recently identified positive sense single-strand RNA (ssRNA) β-coronavirus. The viral spike proteins infect human hosts by binding to the cellular receptor angiotensin-converting enzyme 2 (ACE2). The infection causes a systemic illness involving cell metabolism. [...] Read more.

Severe Acute Respiratory Syndrome (SARS) Coronavirus (CoV)-2 is a recently identified positive sense single-strand RNA (ssRNA) β-coronavirus. The viral spike proteins infect human hosts by binding to the cellular receptor angiotensin-converting enzyme 2 (ACE2). The infection causes a systemic illness involving cell metabolism. This widespread involvement is implicated in the pathophysiology of the illness which ranges from mild to severe, requiring multi organ support, ranging from oxygen supplementation to full cardiovascular and respiratory support. Patients with multiple co-existing comorbidities are also at a higher risk. The aim of this review is to explore the exact mechanisms by which COVID-19 affects patients systemically with a primary focus on the bleeding and thrombotic complications linked with the disease. Issues surrounding the thrombotic complications following administration of the ChAdOx1 nCoV-19 (Astra-Zeneca-Oxford) vaccine have also been illustrated. Risk stratification and treatment options in these patients should be tailored according to clinical severity with input from a multidisciplinary team. Full article

(This article belongs to the Special Issue Thrombosis and Metabolism)

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