1
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Faulhammer F, van Ravenzwaay B, Schnatter AR, Rooseboom M, Kamp H, Flick B, Giri V, Sperber S, Higgins LG, Penman MG, Kocabas NA. The short-term toxicity and metabolome of Benzene. Toxicol Lett 2024; 400:58-70. [PMID: 39094914 DOI: 10.1016/j.toxlet.2024.07.913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Revised: 07/18/2024] [Accepted: 07/22/2024] [Indexed: 08/04/2024]
Abstract
A 14-day rat study with plasma metabolomics was conducted to evaluate the toxicity of Benzene. Wistar rats were orally administered Benzene daily at doses of 0, 300 and 1000 mg/kg bw. The study identified liver and kidneys as target organs of Benzene toxicity and found reductions in total white blood cells, absolute lymphocyte and eosinophil cell counts, and increased relative monocyte counts suggesting bone marrow as a target organ. The study also confirmed liver as a target organ using metabolomics, which showed indications of a stress reaction in rats and changes in metabolites suggestive of a metabolic disorder. The metabolomics investigations did not find any other toxicologically relevant modes of action, and the observed metabolite changes were not associated with markers for mitochondrial dysfunction. The study concludes that integration of omics technologies, such as metabolomics, in regulatory toxicity studies is possible, confirms existing knowledge and adds additional information that can be used for mechanistic understanding of observed toxicity.
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Affiliation(s)
| | | | | | - Martijn Rooseboom
- Shell Global Solution International B.V., The Hague, the Netherlands
| | | | | | | | | | - Larry G Higgins
- Lower Olefins and Aromatics Consortium Services Team, Penman Consulting bvba, Brussels, Belgium.
| | - Michael G Penman
- Lower Olefins and Aromatics Consortium Services Team, Penman Consulting bvba, Brussels, Belgium
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2
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van Ravenzwaay B, Kocabas NA, Faulhammer F, Flick B, Giri V, Sperber S, Penman MG, Higgins LG, Kamp H, Rooseboom M. The short-term toxicity and metabolome of dicyclopentadiene. Toxicol Lett 2024; 393:57-68. [PMID: 38219808 DOI: 10.1016/j.toxlet.2024.01.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 12/25/2023] [Accepted: 01/06/2024] [Indexed: 01/16/2024]
Abstract
Dicyclopentadiene (DCPD) was investigated in a 14-day oral rat toxicity study based on the OECD 407 guideline in combination with plasma metabolomics. Wistar rats received the compound daily via gavage at dose levels of 0, 50 and 150 mg/kg bw. The high dose induced transient clinical signs of toxicity and in males only reduced body weight gain. High dose liver changes were characterized by altered clinical chemistry parameters in both sexes and pathological changes in females. In high dose males an accumulation of alpha-2 u-globulin in the kidney was noted. Comparing the DCPD metabolome with previously established specific metabolome patterns in the MetaMap® Tox data base suggested that the high dose would result in liver enzyme induction leading to increased breakdown of thyroid hormones for males and females. An indication for liver toxicity in males was also noted. Metabolomics also suggested an effect on the functionality of the adrenals in high dose males, which together with published data, is suggestive of a stress related effect in this organ. The results of the present 14-day combined toxicity and metabolome investigations were qualitatively in line with literature data from subchronic oral studies in rats with DCPD. Importantly no other types of organ toxicity, or hormone dysregulation beyond the ones associated with liver enzyme induction and stress were indicated, again in line with results of published 90-day studies. It is therefore suggested that short term "smart" studies, combining classical toxicity with 'omics technologies, could be a 2 R (refine and reduce) new approach method allowing for the reduction of in vivo toxicity testing.
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Affiliation(s)
| | | | | | | | | | | | - Michael G Penman
- Lower Olefins and Aromatics Consortium Services Team, Penman Consulting bvba, Brussels, Belgium
| | - Larry G Higgins
- Lower Olefins and Aromatics Consortium Services Team, Penman Consulting bvba, Brussels, Belgium.
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3
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Vazquez-Aguilar A, Sanchez-Rodriguez E, Rodriguez-Perez C, Rangel-Huerta OD, Mesa MD. Metabolomic-Based Studies of the Intake of Virgin Olive Oil: A Comprehensive Review. Metabolites 2023; 13:metabo13040472. [PMID: 37110130 PMCID: PMC10142154 DOI: 10.3390/metabo13040472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 03/22/2023] [Accepted: 03/23/2023] [Indexed: 03/29/2023] Open
Abstract
Virgin olive oil (VOO) is a high-value product from the Mediterranean diet. Some health and nutritional benefits have been associated with its consumption, not only because of its monounsaturated-rich triacylglycerols but also due to its minor bioactive components. The search for specific metabolites related to VOO consumption may provide valuable information to identify the specific bioactive components and to understand possible molecular and metabolic mechanisms implicated in those health effects. In this regard, metabolomics, considered a key analytical tool in nutritional studies, offers a better understanding of the regulatory functions of food components on human nutrition, well-being, and health. For that reason, the aim of the present review is to summarize the available scientific evidence related to the metabolic effects of VOO or its minor bioactive compounds in human, animal, and in vitro studies using metabolomics approaches.
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Affiliation(s)
- Alejandra Vazquez-Aguilar
- Department of Biochemistry and Molecular Biology II, University of Granada, Campus Cartuja s/n, 18071 Granada, Spain
- Institute of Nutrition and Food Technology “José Mataix”, Biomedical Research Center, University of Granada, Parque Tecnológico de la Salud, Avenida del Conocimiento s/n, 18016 Granada, Spain
| | - Estefania Sanchez-Rodriguez
- Department of Biochemistry and Molecular Biology II, University of Granada, Campus Cartuja s/n, 18071 Granada, Spain
- Institute of Nutrition and Food Technology “José Mataix”, Biomedical Research Center, University of Granada, Parque Tecnológico de la Salud, Avenida del Conocimiento s/n, 18016 Granada, Spain
- Instituto de Investigación Biosanitaria de Granada ibs, 18012 Granada, Spain
- Correspondence:
| | - Celia Rodriguez-Perez
- Institute of Nutrition and Food Technology “José Mataix”, Biomedical Research Center, University of Granada, Parque Tecnológico de la Salud, Avenida del Conocimiento s/n, 18016 Granada, Spain
- Instituto de Investigación Biosanitaria de Granada ibs, 18012 Granada, Spain
- Department of Nutrition and Food Science, University of Granada, Campus Melilla C/Santander, 52005 Melilla, Spain
| | | | - Maria D. Mesa
- Department of Biochemistry and Molecular Biology II, University of Granada, Campus Cartuja s/n, 18071 Granada, Spain
- Institute of Nutrition and Food Technology “José Mataix”, Biomedical Research Center, University of Granada, Parque Tecnológico de la Salud, Avenida del Conocimiento s/n, 18016 Granada, Spain
- Instituto de Investigación Biosanitaria de Granada ibs, 18012 Granada, Spain
- Primary Care Promotion of Maternal, Child and Women’s Health for Prevention of Adult Chronic Diseases Network (RD21/0012/0008), Institute of Health Carlos III, 28029 Madrid, Spain
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4
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Motohira K, Yohannes YB, Ikenaka Y, Eguchi A, Nakayama SM, Wepener V, Smit NJ, VAN Vuren JH, Ishizuka M. Investigation of dichlorodiphenyltrichloroethane (DDT) on xenobiotic enzyme disruption and metabolomic bile acid biosynthesis in DDT-sprayed areas using wild rats. J Vet Med Sci 2023; 85:236-243. [PMID: 36596564 PMCID: PMC10017292 DOI: 10.1292/jvms.22-0490] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
Dichlorodiphenyltrichloroethane (DDT) is an organochlorine insecticide used worldwide. Several studies have reported the toxic effects of DDT and its metabolites on steroid hormone biosynthesis; however, its environmental effects are not well understood. This study examined wild rats collected in DDT-sprayed areas of South Africa and quantified plasma metabolites using liquid chromatography quadrupole time-of-flight mass spectrometry (LC-Q-TOF-MS). Fold change analysis of the metabolome revealed the effect of DDT on bile acid biosynthesis. Gene expression of the related enzyme in rat liver samples was also quantified. Significant association was found between DDT and gene expression levels related to constitutive androstane receptor mediated enzymes, such as Cyp2b1 in rat livers. However, our results could not fully demonstrate that enzymes related to bile acid biosynthesis were strongly affected by DDT. The correlation between DDT concentration and gene expression involved in steroid hormone synthesis in testis was also evaluated; however, no significant correlation was found. The disturbance of metabolic enzymes occurred in rat liver in the target area. Our results suggest that DDT exposure affects gene expression in wild rats living in DDT-sprayed areas. Therefore, there is a need for DDT toxicity evaluation in mammals living in DDT-sprayed areas. We could not find an effective biomarker that could reflect the mechanism of DDT exposure; however, this approach can provide new insights for future research to evaluate DDT effects in sprayed areas.
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Affiliation(s)
- Kodai Motohira
- Laboratory of Toxicology, Department of Environmental Veterinary Sciences, Laboratory of Toxicology, Hokkaido University, Hokkaido, Japan
| | - Yared Beyene Yohannes
- Laboratory of Toxicology, Department of Environmental Veterinary Sciences, Laboratory of Toxicology, Hokkaido University, Hokkaido, Japan.,Department of Chemistry, College of Natural and Computational Science, University of Gondar, Gondar, Ethiopia
| | - Yoshinori Ikenaka
- Laboratory of Toxicology, Department of Environmental Veterinary Sciences, Laboratory of Toxicology, Hokkaido University, Hokkaido, Japan.,Water Research Group, Unit for Environmental Sciences and Management, Potchefstroom Campus, North-West University, Potchefstroom, South Africa.,Translational Research Unit, Veterinary Teaching Hospital, Faculty of Veterinary Medicine, Hokkaido University, Hokkaido, Japan.,One Health Research Center, Hokkaido University, Hokkaido, Japan
| | - Akifumi Eguchi
- Center for Preventive Medical Sciences, Chiba University, Chiba, Japan
| | - Shouta Mm Nakayama
- Laboratory of Toxicology, Department of Environmental Veterinary Sciences, Laboratory of Toxicology, Hokkaido University, Hokkaido, Japan.,Biomedical Sciences Department, School of Veterinary Medicine, The University of Zambia, Lusaka, Zambia
| | - Victor Wepener
- Water Research Group, Unit for Environmental Sciences and Management, Potchefstroom Campus, North-West University, Potchefstroom, South Africa
| | - Nico J Smit
- Water Research Group, Unit for Environmental Sciences and Management, Potchefstroom Campus, North-West University, Potchefstroom, South Africa
| | - Johan Hj VAN Vuren
- Water Research Group, Unit for Environmental Sciences and Management, Potchefstroom Campus, North-West University, Potchefstroom, South Africa
| | - Mayumi Ishizuka
- Laboratory of Toxicology, Department of Environmental Veterinary Sciences, Laboratory of Toxicology, Hokkaido University, Hokkaido, Japan
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5
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Gegner HM, Mechtel N, Heidenreich E, Wirth A, Cortizo FG, Bennewitz K, Fleming T, Andresen C, Freichel M, Teleman AA, Kroll J, Hell R, Poschet G. Deep Metabolic Profiling Assessment of Tissue Extraction Protocols for Three Model Organisms. Front Chem 2022; 10:869732. [PMID: 35548679 PMCID: PMC9083328 DOI: 10.3389/fchem.2022.869732] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Accepted: 04/05/2022] [Indexed: 12/12/2022] Open
Abstract
Metabolic profiling harbors the potential to better understand various disease entities such as cancer, diabetes, Alzheimer's, Parkinson's disease or COVID-19. To better understand such diseases and their intricate metabolic pathways in human studies, model animals are regularly used. There, standardized rearing conditions and uniform sampling strategies are prerequisites towards a successful metabolomic study that can be achieved through model organisms. Although metabolomic approaches have been employed on model organisms before, no systematic assessment of different conditions to optimize metabolite extraction across several organisms and sample types has been conducted. We address this issue using a highly standardized metabolic profiling assay analyzing 630 metabolites across three commonly used model organisms (Drosophila, mouse, and zebrafish) to find an optimal extraction protocol for various matrices. Focusing on parameters such as metabolite coverage, concentration and variance between replicates we compared seven extraction protocols. We found that the application of a combination of 75% ethanol and methyl tertiary-butyl ether (MTBE), while not producing the broadest coverage and highest concentrations, was the most reproducible extraction protocol. We were able to determine up to 530 metabolites in mouse kidney samples, 509 in mouse liver, 422 in zebrafish and 388 in Drosophila and discovered a core overlap of 261 metabolites in these four matrices. To enable other scientists to search for the most suitable extraction protocol in their experimental context and interact with this comprehensive data, we have integrated our data set in the open-source shiny app "MetaboExtract". Hereby, scientists can search for metabolites or compound classes of interest, compare them across the different tested extraction protocols and sample types as well as find reference concentration values.
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Affiliation(s)
- Hagen M. Gegner
- Metabolomics Core Technology Platform, Centre for Organismal Studies (COS), Heidelberg University, Heidelberg, Germany
| | - Nils Mechtel
- Metabolomics Core Technology Platform, Centre for Organismal Studies (COS), Heidelberg University, Heidelberg, Germany
| | - Elena Heidenreich
- Metabolomics Core Technology Platform, Centre for Organismal Studies (COS), Heidelberg University, Heidelberg, Germany
| | - Angela Wirth
- Institute of Pharmacology, Heidelberg University, Heidelberg, Germany
| | - Fabiola Garcia Cortizo
- Division of Signal Transduction in Cancer and Metabolism, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Katrin Bennewitz
- European Center for Angioscience (ECAS), Department of Vascular Biology and Tumor Angiogenesis, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Thomas Fleming
- Department of Internal Medicine I and Clinical Chemistry, Heidelberg University Hospital, Heidelberg, Germany
| | - Carolin Andresen
- Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM GGmbH), Heidelberg, Germany
- Division of Stem Cells and Cancer, Deutsches Krebsforschungszentrum (DKFZ) and DKFZ-ZMBH Alliance, Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
| | - Marc Freichel
- Institute of Pharmacology, Heidelberg University, Heidelberg, Germany
| | - Aurelio A. Teleman
- Division of Signal Transduction in Cancer and Metabolism, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jens Kroll
- European Center for Angioscience (ECAS), Department of Vascular Biology and Tumor Angiogenesis, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Rüdiger Hell
- Metabolomics Core Technology Platform, Centre for Organismal Studies (COS), Heidelberg University, Heidelberg, Germany
| | - Gernot Poschet
- Metabolomics Core Technology Platform, Centre for Organismal Studies (COS), Heidelberg University, Heidelberg, Germany
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6
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Ramirez-Hincapie S, Giri V, Keller J, Kamp H, Haake V, Richling E, van Ravenzwaay B. Influence of pregnancy and non-fasting conditions on the plasma metabolome in a rat prenatal toxicity study. Arch Toxicol 2021; 95:2941-2959. [PMID: 34327559 DOI: 10.1007/s00204-021-03105-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Accepted: 06/17/2021] [Indexed: 11/25/2022]
Abstract
The current parameters for determining maternal toxicity (e.g. clinical signs, food consumption, body weight development) lack specificity and may underestimate the extent of effects of test compounds on the dams. Previous reports have highlighted the use of plasma metabolomics for an improved and mechanism-based identification of maternal toxicity. To establish metabolite profiles of healthy pregnancies and evaluate the influence of food consumption as a confounding factor, metabolite profiling of rat plasma was performed by gas- and liquid-chromatography-tandem mass spectrometry techniques. Metabolite changes in response to pregnancy, food consumption prior to blood sampling (non-fasting) as well as the interaction of both conditions were studied. In dams, both conditions, non-fasting and pregnancy, had a marked influence on the plasma metabolome and resulted in distinct individual patterns of changed metabolites. Non-fasting was characterized by increased plasma concentrations of amino acids and diet related compounds and lower levels of ketone bodies. The metabolic profile of pregnant rats was characterized by lower amino acids and glucose levels and higher concentrations of plasma fatty acids, triglycerides and hormones, capturing the normal biochemical changes undergone during pregnancy. The establishment of metabolic profiles of pregnant non-fasted rats serves as a baseline to create metabolic fingerprints for prenatal and maternal toxicity studies.
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Affiliation(s)
- S Ramirez-Hincapie
- Experimental Toxicology and Ecology, BASF SE, 67056, Ludwigshafen, Germany
| | - V Giri
- Experimental Toxicology and Ecology, BASF SE, 67056, Ludwigshafen, Germany
| | - J Keller
- Experimental Toxicology and Ecology, BASF SE, 67056, Ludwigshafen, Germany
| | - H Kamp
- Experimental Toxicology and Ecology, BASF SE, 67056, Ludwigshafen, Germany
| | - V Haake
- BASF Metabolome Solution GmbH, Berlin, Germany
| | - E Richling
- Food Chemistry and Toxicology, Department of Chemistry, University of Kaiserslautern, Kaiserslautern, Germany
| | - B van Ravenzwaay
- Experimental Toxicology and Ecology, BASF SE, 67056, Ludwigshafen, Germany.
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7
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Kamp H, Wahrheit J, Stinchcombe S, Walk T, Stauber F, Ravenzwaay BV. Succinate dehydrogenase inhibitors: in silico flux analysis and in vivo metabolomics investigations show no severe metabolic consequences for rats and humans. Food Chem Toxicol 2021; 150:112085. [PMID: 33636213 DOI: 10.1016/j.fct.2021.112085] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 02/05/2021] [Accepted: 02/16/2021] [Indexed: 12/26/2022]
Abstract
Succinate dehydrogenase complex II inhibitors (SDHIs) are widely used fungicides since the 1960s. Recently, based on published in vitro cell viability data, potential health effects via disruption of the mitochondrial respiratory chain and tricarboxylic acid cycle have been postulated in mammalian species. As primary metabolic impact of SDH inhibition, an increase in succinate, and compensatory ATP production via glycolysis resulting in excess lactate levels was hypothesized. To investigate these hypotheses, genome-scale metabolic models of Rattus norvegicus and Homo sapiens were used for an in silico analysis of mammalian metabolism. Moreover, plasma samples from 28-day studies with the SDHIs boscalid and fluxapyroxad were subjected to metabolome analyses, to assess in vivo metabolite changes induced by SDHIs. The outcome of in silico analyses indicated that mammalian metabolic networks are robust and able to compensate different types of metabolic perturbation, e.g., partial or complete SDH inhibition. Additionally, the in silico comparison of rat and human responses suggested no noticeable differences between both species, evidencing that the rat is an appropriate testing organism for toxicity of SDHIs. Since no succinate or lactate accumulation were found in rats, such an accumulation is also not expected in humans as a result of SDHI exposure.
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Affiliation(s)
- H Kamp
- BASF SE, Ludwigshafen, Germany
| | | | | | - T Walk
- BASF Metabolome Solutions GmbH, Berlin, Germany
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8
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Patel DP, Pauly GT, Tada T, Parker AL, Toulabi L, Kanke Y, Oike T, Krausz KW, Gonzalez FJ, Harris CC. Improved detection and precise relative quantification of the urinary cancer metabolite biomarkers - Creatine riboside, creatinine riboside, creatine and creatinine by UPLC-ESI-MS/MS: Application to the NCI-Maryland cohort population controls and lung cancer cases. J Pharm Biomed Anal 2020; 191:113596. [PMID: 32937240 PMCID: PMC7756200 DOI: 10.1016/j.jpba.2020.113596] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Revised: 08/11/2020] [Accepted: 08/12/2020] [Indexed: 01/21/2023]
Abstract
Creatine riboside (CR) is a novel metabolite of cancer metabolism. It is a urinary diagnostic biomarker of lung and liver cancer risk and prognosis. The level of CR is highly positive correlated in tumor and urine indicating that it is derived from human lung and liver cancers. A precise and sensitive ultra-pressure liquid chromatography-tandem mass spectrometry (UPLC-ESI-MS/MS) method was developed and validated for simultaneous quantification of the noninvasive biomarker CR, along with creatinine riboside (CNR), and their precursors creatine and creatinine, utilizing the labeled internal standard creatine riboside-13C,15N2 (CR-13C,15N2). Chromatography was carried out on a hydrophilic interaction chromatography column under a gradient mobile phase condition. MRM transitions were monitored for CR (264.1 > 132.1, m/z), CNR (246.1 > 113.9, m/z), creatine (132.0 > 72.0, m/z), creatinine (114.0 > 85.8, m/z) and CR-13C,15N2 (267.1 > 134.9, m/z) with a 11.0 min run time in the positive mode ionization. The calibration plot of the method was linear over the concentration range of 4.50-10,000 nM. Method validation was performed according to regulatory guidelines established for sensitivity, selectivity, calibration curve, stability at different storage conditions, reinjection reproducibility, ruggedness with acceptable accuracy, and precision. This assay was applied for the quantification of CR along with CNR, creatine and creatinine in a subset of urine and serum samples from the National Cancer Institute - Maryland (NCI-MD) cohort population controls and lung cancer cases. It can be standardized and used in multiple laboratories for cancer diagnosis and determining the efficacy of cancer therapy and monitoring cancer recurrence.
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Affiliation(s)
- Daxesh P Patel
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | - Gary T Pauly
- Chemical Biology Laboratory, Center for Cancer Research, National Cancer Institute, Fredrick, MD, USA
| | - Takeshi Tada
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | - Amelia L Parker
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | - Leila Toulabi
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | - Yasuyuki Kanke
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | - Takahiro Oike
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | - Kristopher W Krausz
- Laboratory of Metabolism, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | - Frank J Gonzalez
- Laboratory of Metabolism, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | - Curtis C Harris
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA.
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9
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Gao X, Randell E, Tian Y, Zhou H, Sun G. Low serum choline and high serum betaine levels are associated with favorable components of metabolic syndrome in Newfoundland population. J Diabetes Complications 2019; 33:107398. [PMID: 31320248 DOI: 10.1016/j.jdiacomp.2019.06.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/22/2019] [Revised: 05/26/2019] [Accepted: 06/11/2019] [Indexed: 12/29/2022]
Abstract
BACKGROUND We investigated the relationships between serum choline and betaine levels with metabolic syndrome-related indices in the general population of Newfoundland. METHODS 1081 adults were selected from the CODING study. Serum choline and betaine levels were measured. Major confounding factors were controlled in all analyses. RESULTS Partial correlation and linear regression analysis showed that serum choline levels were positively associated with systolic blood pressure (r: 0.124), serum TG levels (r: 0.132) and negatively correlated with serum glucose levels (r: -0.121) in males (p < 0.01 for all). In females, serum choline levels were positively correlated with serum TG, TC and HDL levels (r: 0.104 to 0.148, p < 0.05 for all). Serum betaine levels were negatively associated with serum TG, TC, LDL and insulin levels, and with atherogenic index and HOMA-IR index in males (r: -0.081 to -0.179, p < 0.05 for all). In females, serum betaine levels were negatively associated with serum TG, hsCRP and insulin levels, and with HOMA-IR index (r: -0.092 to -0.213, p < 0.05 for all). Moreover, subjects with serum choline levels in the highest tertile showed highest serum TG levels and systolic blood pressure in males, and highest serum lipids levels in females. Subjects with the highest serum betaine levels had the lowest serum lipids levels, atherogenic index, IR severity in males, and the lowest serum TG and hsCRP levels, and IR severity in females. CONCLUSION Low serum choline and high serum betaine levels are associated with favorable components of metabolic syndrome in general adults.
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Affiliation(s)
- Xiang Gao
- College of Life Sciences, Qingdao University, No.308,Ningxia Road, Qingdao, Shandong, China
| | - Edward Randell
- Faculty of Medicine, Memorial University, 300 Prince Philip Drive, St. John's, NL, Canada
| | - Yuan Tian
- Faculty of Medicine, Memorial University, 300 Prince Philip Drive, St. John's, NL, Canada; Xiangyang Central Hospital, Affiliated Hospital Of Hubei University of Arts and Science, Xiangyang, Hubei Province 441021, China
| | - Haicheng Zhou
- Faculty of Medicine, Memorial University, 300 Prince Philip Drive, St. John's, NL, Canada; The Department of Endocrinology, the First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Guang Sun
- Faculty of Medicine, Memorial University, 300 Prince Philip Drive, St. John's, NL, Canada.
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10
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Vinnakota KC, Pannala VR, Wall ML, Rahim M, Estes SK, Trenary I, O'Brien TP, Printz RL, Reifman J, Shiota M, Young JD, Wallqvist A. Network Modeling of Liver Metabolism to Predict Plasma Metabolite Changes During Short-Term Fasting in the Laboratory Rat. Front Physiol 2019; 10:161. [PMID: 30881311 PMCID: PMC6405515 DOI: 10.3389/fphys.2019.00161] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2018] [Accepted: 02/11/2019] [Indexed: 12/20/2022] Open
Abstract
The liver—a central metabolic organ that integrates whole-body metabolism to maintain glucose and fatty-acid regulation, and detoxify ammonia—is susceptible to injuries induced by drugs and toxic substances. Although plasma metabolite profiles are increasingly investigated for their potential to detect liver injury earlier than current clinical markers, their utility may be compromised because such profiles are affected by the nutritional state and the physiological state of the animal, and by contributions from extrahepatic sources. To tease apart the contributions of liver and non-liver sources to alterations in plasma metabolite profiles, here we sought to computationally isolate the plasma metabolite changes originating in the liver during short-term fasting. We used a constraint-based metabolic modeling approach to integrate central carbon fluxes measured in our study, and physiological flux boundary conditions gathered from the literature, into a genome-scale model of rat liver metabolism. We then measured plasma metabolite profiles in rats fasted for 5–7 or 10–13 h to test our model predictions. Our computational model accounted for two-thirds of the observed directions of change (an increase or decrease) in plasma metabolites, indicating their origin in the liver. Specifically, our work suggests that changes in plasma lipid metabolites, which are reliably predicted by our liver metabolism model, are key features of short-term fasting. Our approach provides a mechanistic model for identifying plasma metabolite changes originating in the liver.
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Affiliation(s)
- Kalyan C Vinnakota
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, United States.,Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, United States Army Medical Research and Materiel Command, Fort Detrick, MD, United States
| | - Venkat R Pannala
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, United States.,Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, United States Army Medical Research and Materiel Command, Fort Detrick, MD, United States
| | - Martha L Wall
- Department of Chemical and Biomolecular Engineering, Vanderbilt University School of Engineering, Nashville, TN, United States
| | - Mohsin Rahim
- Department of Chemical and Biomolecular Engineering, Vanderbilt University School of Engineering, Nashville, TN, United States
| | - Shanea K Estes
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN, United States
| | - Irina Trenary
- Department of Chemical and Biomolecular Engineering, Vanderbilt University School of Engineering, Nashville, TN, United States
| | - Tracy P O'Brien
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN, United States
| | - Richard L Printz
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN, United States
| | - Jaques Reifman
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, United States Army Medical Research and Materiel Command, Fort Detrick, MD, United States
| | - Masakazu Shiota
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN, United States
| | - Jamey D Young
- Department of Chemical and Biomolecular Engineering, Vanderbilt University School of Engineering, Nashville, TN, United States.,Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN, United States
| | - Anders Wallqvist
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, United States Army Medical Research and Materiel Command, Fort Detrick, MD, United States
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11
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Added value of plasma metabolomics to describe maternal effects in rat maternal and prenatal toxicity studies. Toxicol Lett 2019; 301:42-52. [DOI: 10.1016/j.toxlet.2018.10.032] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2018] [Revised: 09/14/2018] [Accepted: 10/29/2018] [Indexed: 12/14/2022]
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12
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Calorie restriction and its impact on gut microbial composition and global metabolism. Front Med 2018; 12:634-644. [PMID: 30446879 DOI: 10.1007/s11684-018-0670-8] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2017] [Accepted: 09/27/2018] [Indexed: 02/08/2023]
Abstract
Calorie restriction (CR) is a dietary regimen that reduces calorie intake without incurring malnutrition or a reduction in essential nutrients. It has long been recognized as a natural strategy for promoting health, extending longevity, and prevents the development of metabolic and age-related diseases. In the present review, we focus on the general effect of CR on gut microbiota composition and global metabolism. We also propose mechanisms for its beneficial effect. Results showed that probiotic and butyrate-producing microbes increased their relative abundance, whereas proinflammatory strains exhibited suppressed relative abundance following CR. Analyses of the gut microbial and host metabolisms revealed that most host microbial co-metabolites were changed due to CR. Examples of dramatic CR-induced changes in host metabolism included a decrease in the rate of lipid biosynthesis and an increase in the rates of fatty acid catabolism, β-oxidation, glycogenolysis, and gluconeogenesis. The observed phenotypes and the further verification of the direct link between gut microbiota and metabolome may benefit patients that are at risk for developing metabolic disease. Thus, improved gut microbiota composition and metabolome are potential biomarkers for determining the effectiveness of dietary interventions for age-related and metabolic diseases.
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13
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Higher serum choline and betaine levels are associated with better body composition in male but not female population. PLoS One 2018; 13:e0193114. [PMID: 29462191 PMCID: PMC5819804 DOI: 10.1371/journal.pone.0193114] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2017] [Accepted: 02/05/2018] [Indexed: 02/08/2023] Open
Abstract
Background Animal studies proved that choline and betaine have beneficial effect on reducing body fat. However, evidence in humans is scarce. We aim to investigate the association between serum choline and betaine levels with body composition in general population. Methods This is an observational cross-sectional study performed in 1081 subjects from the CODING (Complex Disease in Newfoundland population: Environment and Genetics) study. Serum choline and betaine levels were measured based on liquid chromatography coupled with tandem mass spectrometry technology. Body composition was measured using dual-energy X-ray absorptiometry following a 12-hour fast. Major confounding factors including age, sex, total calorie intake and physical activity level were controlled in all analyses. Results Significantly inverse correlations were found between serum betaine levels and all obesity measurements in males (r ranged from -0.12 to -0.23, and p<0.01 for all) but not in females. Serum choline was negatively associated with total percent body fat (%BF), percent trunk fat (%TF), weight, body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (r ranged from -0.11 to -0.19, and p<0.05 for all) in males and positively associated with weight, BMI and WC (r ranged from 0.09 to 0.10, and p<0.05 for all) in females. The negative associations between serum choline and betaine levels with obesity in males were more profound in those not on any medication than those taking medications. Moreover, obese males had the lowest serum choline and betaine levels, followed by overweight males, and normal weight males having the highest serum choline and betaine levels, especially in those not taking medications (p<0.05). Likewise, subjects with the highest serum levels of both had the lowest obesity indexes, especially those not taking medications. Conclusions Higher serum choline and betaine levels were associated with a more favorable body composition (lower body fat and higher lean body mass) in males and the favorable association was more pronounced in non-medication users.
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Behr C, Kamp H, Fabian E, Krennrich G, Mellert W, Peter E, Strauss V, Walk T, Rietjens IMCM, van Ravenzwaay B. Gut microbiome-related metabolic changes in plasma of antibiotic-treated rats. Arch Toxicol 2017; 91:3439-3454. [PMID: 28337503 DOI: 10.1007/s00204-017-1949-2] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2016] [Accepted: 02/23/2017] [Indexed: 12/13/2022]
Abstract
The intestinal microbiota contributes to the metabolism of its host. Adequate identification of the microbiota's impact on the host plasma metabolites is lacking. As antibiotics have a profound effect on the microbial composition and hence on the mammalian-microbiota co-metabolism, we studied the effects of antibiotics on the "functionality of the microbiome"-defined as the production of metabolites absorbed by the host. This metabolomics study presents insights into the mammalian-microbiome co-metabolism of endogenous metabolites. To identify plasma metabolites related to microbiome changes due to antibiotic treatment, we have applied broad-spectrum antibiotics belonging to the class of aminoglycosides (neomycin, gentamicin), fluoroquinolones (moxifloxacin, levofloxacin) and tetracyclines (doxycycline, tetracycline). These were administered orally for 28 days to male rats including blood sampling for metabolic profiling after 7, 14 and 28 days. Fluoroquinolones and tetracyclines can be absorbed from the gut; whereas, aminoglycosides are poorly absorbed. Hippuric acid, indole-3-acetic acid and glycerol were identified as key metabolites affected by antibiotic treatment, beside changes mainly concerning amino acids and carbohydrates. Inter alia, effects on indole-3-propionic acid were found to be unique for aminoglycosides, and on 3-indoxylsulfate for tetracyclines. For each class of antibiotics, specific metabolome patterns could be established in the MetaMap®Tox data base, which contains metabolome data for more than 550 reference compounds. The results suggest that plasma-based metabolic profiling (metabolomics) could be a suitable tool to investigate the effect of antibiotics on the functionality of the microbiome and to obtain insight into the mammalian-microbiome co-metabolism.
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Affiliation(s)
- C Behr
- BASF SE, 67056, Ludwigshafen, Germany
| | - H Kamp
- BASF SE, 67056, Ludwigshafen, Germany
| | - E Fabian
- BASF SE, 67056, Ludwigshafen, Germany
| | | | - W Mellert
- BASF SE, 67056, Ludwigshafen, Germany
| | - E Peter
- Metanomics GmbH, 10589, Berlin, Germany
| | - V Strauss
- BASF SE, 67056, Ludwigshafen, Germany
| | - T Walk
- Metanomics GmbH, 10589, Berlin, Germany
| | - I M C M Rietjens
- Division of Toxicology, Wageningen University, 6700 EA, Wageningen, The Netherlands
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15
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Hu L, Gao Y, Cao Y, Zhang Y, Xu M, Wang Y, Jing Y, Guo S, Jing F, Hu X, Zhu Z. Association of plasma arginine with breast cancer molecular subtypes in women of Liaoning province. IUBMB Life 2016; 68:980-984. [PMID: 27797142 DOI: 10.1002/iub.1581] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2016] [Accepted: 10/06/2016] [Indexed: 12/20/2022]
Affiliation(s)
- Lu Hu
- Cancer Center; The First Affiliated Hospital of Jinzhou Medical University; Jinzhou People's Republic of China
| | - Yu Gao
- Cancer Center; The First Affiliated Hospital of Jinzhou Medical University; Jinzhou People's Republic of China
| | - Yunfeng Cao
- Dalian Institute of Chemical Physics, Chinese Academy of Sciences; Dalian People's Republic of China
- Runsheng Kangtai Biomedical Technology Co. Ltd; Jinzhou People's Republic of China
| | - Yinxu Zhang
- Cancer Center; The First Affiliated Hospital of Jinzhou Medical University; Jinzhou People's Republic of China
| | - Minghao Xu
- Cancer Center; The First Affiliated Hospital of Jinzhou Medical University; Jinzhou People's Republic of China
| | - Yuanyuan Wang
- Cancer Center; The First Affiliated Hospital of Jinzhou Medical University; Jinzhou People's Republic of China
| | - Yu Jing
- Cancer Center; The First Affiliated Hospital of Jinzhou Medical University; Jinzhou People's Republic of China
| | - Shengnan Guo
- Cancer Center; The First Affiliated Hospital of Jinzhou Medical University; Jinzhou People's Republic of China
| | - Fangyu Jing
- Cancer Center; The First Affiliated Hospital of Jinzhou Medical University; Jinzhou People's Republic of China
| | - Xiaodan Hu
- Cancer Center; The First Affiliated Hospital of Jinzhou Medical University; Jinzhou People's Republic of China
| | - Zhitu Zhu
- Cancer Center; The First Affiliated Hospital of Jinzhou Medical University; Jinzhou People's Republic of China
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16
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Bordag N, Janakiraman V, Nachtigall J, González Maldonado S, Bethan B, Laine JP, Fux E. Fast Filtration of Bacterial or Mammalian Suspension Cell Cultures for Optimal Metabolomics Results. PLoS One 2016; 11:e0159389. [PMID: 27438065 PMCID: PMC4954723 DOI: 10.1371/journal.pone.0159389] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2016] [Accepted: 07/03/2016] [Indexed: 01/08/2023] Open
Abstract
The metabolome offers real time detection of the adaptive, multi-parametric response of the organisms to environmental changes, pathophysiological stimuli or genetic modifications and thus rationalizes the optimization of cell cultures in bioprocessing. In bioprocessing the measurement of physiological intracellular metabolite levels is imperative for successful applications. However, a sampling method applicable to all cell types with little to no validation effort which simultaneously offers high recovery rates, high metabolite coverage and sufficient removal of extracellular contaminations is still missing. Here, quenching, centrifugation and fast filtration were compared and fast filtration in combination with a stabilizing washing solution was identified as the most promising sampling method. Different influencing factors such as filter type, vacuum pressure, washing solutions were comprehensively tested. The improved fast filtration method (MxP® FastQuench) followed by routine lipid/polar extraction delivers a broad metabolite coverage and recovery reflecting well physiological intracellular metabolite levels for different cell types, such as bacteria (Escherichia coli) as well as mammalian cells chinese hamster ovary (CHO) and mouse myeloma cells (NS0).The proposed MxP® FastQuench allows sampling, i.e. separation of cells from medium with washing and quenching, in less than 30 seconds and is robustly designed to be applicable to all cell types. The washing solution contains the carbon source respectively the 13C-labeled carbon source to avoid nutritional stress during sampling. This method is also compatible with automation which would further reduce sampling times and the variability of metabolite profiling data.
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Affiliation(s)
| | - Vijay Janakiraman
- Biogen Idec Inc., Raleigh-Durham, North Carolina, United States of America
| | | | | | | | | | - Elie Fux
- Metanomics GmbH, Berlin, Germany
- * E-mail:
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17
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Metabolite profiles of rats in repeated dose toxicological studies after oral and inhalative exposure. Toxicol Lett 2016; 255:11-23. [PMID: 27153797 DOI: 10.1016/j.toxlet.2016.05.003] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2015] [Revised: 04/26/2016] [Accepted: 05/02/2016] [Indexed: 11/24/2022]
Abstract
The MetaMap(®)-Tox database contains plasma-metabolome and toxicity data of rats obtained from oral administration of 550 reference compounds following a standardized adapted OECD 407 protocol. Here, metabolic profiles for aniline (A), chloroform (CL), ethylbenzene (EB), 2-methoxyethanol (ME), N,N-dimethylformamide (DMF) and tetrahydrofurane (THF), dosed inhalatively for six hours/day, five days a week for 4 weeks were compared to oral dosing performed daily for 4 weeks. To investigate if the oral and inhalative metabolome would be comparable statistical analyses were performed. Best correlations for metabolome changes via both routes of exposure were observed for toxicants that induced profound metabolome changes. e.g. CL and ME. Liver and testes were correctly identified as target organs. In contrast, route of exposure dependent differences in metabolic profiles were noted for low profile strength e.g. female rats dosed inhalatively with A or THF. Taken together, the current investigations demonstrate that plasma metabolome changes are generally comparable for systemic effects after oral and inhalation exposure. Differences may result from kinetics and first pass effects. For compounds inducing only weak changes, the differences between both routes of exposure are visible in the metabolome.
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18
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Zhu H, Bouhifd M, Kleinstreuer N, Kroese ED, Liu Z, Luechtefeld T, Pamies D, Shen J, Strauss V, Wu S, Hartung T. Supporting read-across using biological data. ALTEX 2016; 33:167-82. [PMID: 26863516 PMCID: PMC4834201 DOI: 10.14573/altex.1601252] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/25/2016] [Accepted: 02/09/2016] [Indexed: 01/08/2023]
Abstract
Read-across, i.e. filling toxicological data gaps by relating to similar chemicals, for which test data are available, is usually done based on chemical similarity. Besides structure and physico-chemical properties, however, biological similarity based on biological data adds extra strength to this process. In the context of developing Good Read-Across Practice guidance, a number of case studies were evaluated to demonstrate the use of biological data to enrich read-across. In the simplest case, chemically similar substances also show similar test results in relevant in vitro assays. This is a well-established method for the read-across of e.g. genotoxicity assays. Larger datasets of biological and toxicological properties of hundreds and thousands of substances become increasingly available enabling big data approaches in read-across studies. Several case studies using various big data sources are described in this paper. An example is given for the US EPA's ToxCast dataset allowing read-across for high quality uterotrophic assays for estrogenic endocrine disruption. Similarly, an example for REACH registration data enhancing read-across for acute toxicity studies is given. A different approach is taken using omics data to establish biological similarity: Examples are given for stem cell models in vitro and short-term repeated dose studies in rats in vivo to support read-across and category formation. These preliminary biological data-driven read-across studies highlight the road to the new generation of read-across approaches that can be applied in chemical safety assessment.
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Affiliation(s)
- Hao Zhu
- Department of Chemistry, Rutgers University, Camden, NJ, USA; Center for Computational and Integrative Biology, Rutgers University, Camden, NJ, USA
| | - Mounir Bouhifd
- Johns Hopkins Bloomberg School of Public Health, Center for Alternatives to Animal Testing (CAAT), Baltimore, MD, USA
| | - Nicole Kleinstreuer
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
| | - E. Dinant Kroese
- Risk Analysis for Products in Development, TNO Zeist, The Netherlands
| | | | - Thomas Luechtefeld
- Johns Hopkins Bloomberg School of Public Health, Center for Alternatives to Animal Testing (CAAT), Baltimore, MD, USA
| | - David Pamies
- Johns Hopkins Bloomberg School of Public Health, Center for Alternatives to Animal Testing (CAAT), Baltimore, MD, USA
| | - Jie Shen
- Research Institute for Fragrance Materials, Inc. Woodcliff Lake, New Jersey, USA
| | - Volker Strauss
- BASF Aktiengesellschaft, Experimental Toxicology and Ecology, Ludwigshafen, Germany
| | | | - Thomas Hartung
- Johns Hopkins Bloomberg School of Public Health, Center for Alternatives to Animal Testing (CAAT), Baltimore, MD, USA
- University of Konstanz, CAAT-Europe, Konstanz, Germany
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19
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Nestor G, Eriksson J, Sandström C, Malmlöf K. Nuclear Magnetic Resonance-Based Blood Metabolic Profiles of Rats Exposed to Short-Term Caloric Restriction. ANAL LETT 2015. [DOI: 10.1080/00032719.2015.1041028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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20
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Mathé EA, Patterson AD, Haznadar M, Manna SK, Krausz KW, Bowman ED, Shields PG, Idle JR, Smith PB, Anami K, Kazandjian DG, Hatzakis E, Gonzalez FJ, Harris CC. Noninvasive urinary metabolomic profiling identifies diagnostic and prognostic markers in lung cancer. Cancer Res 2014; 74:3259-70. [PMID: 24736543 DOI: 10.1158/0008-5472.can-14-0109] [Citation(s) in RCA: 123] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Lung cancer remains the most common cause of cancer deaths worldwide, yet there is currently a lack of diagnostic noninvasive biomarkers that could guide treatment decisions. Small molecules (<1,500 Da) were measured in urine collected from 469 patients with lung cancer and 536 population controls using unbiased liquid chromatography/mass spectrometry. Clinical putative diagnostic and prognostic biomarkers were validated by quantitation and normalized to creatinine levels at two different time points and further confirmed in an independent sample set, which comprises 80 cases and 78 population controls, with similar demographic and clinical characteristics when compared with the training set. Creatine riboside (IUPAC name: 2-{2-[(2R,3R,4S,5R)-3,4-dihydroxy-5-(hydroxymethyl)-oxolan-2-yl]-1-methylcarbamimidamido}acetic acid), a novel molecule identified in this study, and N-acetylneuraminic acid (NANA) were each significantly (P < 0.00001) elevated in non-small cell lung cancer and associated with worse prognosis [HR = 1.81 (P = 0.0002), and 1.54 (P = 0.025), respectively]. Creatine riboside was the strongest classifier of lung cancer status in all and stage I-II cases, important for early detection, and also associated with worse prognosis in stage I-II lung cancer (HR = 1.71, P = 0.048). All measurements were highly reproducible with intraclass correlation coefficients ranging from 0.82 to 0.99. Both metabolites were significantly (P < 0.03) enriched in tumor tissue compared with adjacent nontumor tissue (N = 48), thus revealing their direct association with tumor metabolism. Creatine riboside and NANA may be robust urinary clinical metabolomic markers that are elevated in tumor tissue and associated with early lung cancer diagnosis and worse prognosis.
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Affiliation(s)
- Ewy A Mathé
- Authors' Affiliations: Laboratory of Molecular Immunogenomics, Genomic and Immunity Section, NIAMS/NIH; Laboratories of Human Carcinogenesis, and Metabolism, National Cancer Institute, NIH, Bethesda, Maryland; Department of Veterinary and Biomedical Sciences and Center for Molecular Toxicology and Carcinogenesis; Metabolomics Core Facility; Nuclear Magnetic Resonance Spectroscopy, The Pennsylvania State University, University Park, Pennsylvania; Ohio State University Comprehensive Cancer Center, Columbus, Ohio; and Department of Clinical Research, University of Bern, Bern, SwitzerlandAuthors' Affiliations: Laboratory of Molecular Immunogenomics, Genomic and Immunity Section, NIAMS/NIH; Laboratories of Human Carcinogenesis, and Metabolism, National Cancer Institute, NIH, Bethesda, Maryland; Department of Veterinary and Biomedical Sciences and Center for Molecular Toxicology and Carcinogenesis; Metabolomics Core Facility; Nuclear Magnetic Resonance Spectroscopy, The Pennsylvania State University, University Park, Pennsylvania; Ohio State University Comprehensive Cancer Center, Columbus, Ohio; and Department of Clinical Research, University of Bern, Bern, Switzerland
| | - Andrew D Patterson
- Authors' Affiliations: Laboratory of Molecular Immunogenomics, Genomic and Immunity Section, NIAMS/NIH; Laboratories of Human Carcinogenesis, and Metabolism, National Cancer Institute, NIH, Bethesda, Maryland; Department of Veterinary and Biomedical Sciences and Center for Molecular Toxicology and Carcinogenesis; Metabolomics Core Facility; Nuclear Magnetic Resonance Spectroscopy, The Pennsylvania State University, University Park, Pennsylvania; Ohio State University Comprehensive Cancer Center, Columbus, Ohio; and Department of Clinical Research, University of Bern, Bern, Switzerland
| | - Majda Haznadar
- Authors' Affiliations: Laboratory of Molecular Immunogenomics, Genomic and Immunity Section, NIAMS/NIH; Laboratories of Human Carcinogenesis, and Metabolism, National Cancer Institute, NIH, Bethesda, Maryland; Department of Veterinary and Biomedical Sciences and Center for Molecular Toxicology and Carcinogenesis; Metabolomics Core Facility; Nuclear Magnetic Resonance Spectroscopy, The Pennsylvania State University, University Park, Pennsylvania; Ohio State University Comprehensive Cancer Center, Columbus, Ohio; and Department of Clinical Research, University of Bern, Bern, Switzerland
| | - Soumen K Manna
- Authors' Affiliations: Laboratory of Molecular Immunogenomics, Genomic and Immunity Section, NIAMS/NIH; Laboratories of Human Carcinogenesis, and Metabolism, National Cancer Institute, NIH, Bethesda, Maryland; Department of Veterinary and Biomedical Sciences and Center for Molecular Toxicology and Carcinogenesis; Metabolomics Core Facility; Nuclear Magnetic Resonance Spectroscopy, The Pennsylvania State University, University Park, Pennsylvania; Ohio State University Comprehensive Cancer Center, Columbus, Ohio; and Department of Clinical Research, University of Bern, Bern, Switzerland
| | - Kristopher W Krausz
- Authors' Affiliations: Laboratory of Molecular Immunogenomics, Genomic and Immunity Section, NIAMS/NIH; Laboratories of Human Carcinogenesis, and Metabolism, National Cancer Institute, NIH, Bethesda, Maryland; Department of Veterinary and Biomedical Sciences and Center for Molecular Toxicology and Carcinogenesis; Metabolomics Core Facility; Nuclear Magnetic Resonance Spectroscopy, The Pennsylvania State University, University Park, Pennsylvania; Ohio State University Comprehensive Cancer Center, Columbus, Ohio; and Department of Clinical Research, University of Bern, Bern, Switzerland
| | - Elise D Bowman
- Authors' Affiliations: Laboratory of Molecular Immunogenomics, Genomic and Immunity Section, NIAMS/NIH; Laboratories of Human Carcinogenesis, and Metabolism, National Cancer Institute, NIH, Bethesda, Maryland; Department of Veterinary and Biomedical Sciences and Center for Molecular Toxicology and Carcinogenesis; Metabolomics Core Facility; Nuclear Magnetic Resonance Spectroscopy, The Pennsylvania State University, University Park, Pennsylvania; Ohio State University Comprehensive Cancer Center, Columbus, Ohio; and Department of Clinical Research, University of Bern, Bern, Switzerland
| | - Peter G Shields
- Authors' Affiliations: Laboratory of Molecular Immunogenomics, Genomic and Immunity Section, NIAMS/NIH; Laboratories of Human Carcinogenesis, and Metabolism, National Cancer Institute, NIH, Bethesda, Maryland; Department of Veterinary and Biomedical Sciences and Center for Molecular Toxicology and Carcinogenesis; Metabolomics Core Facility; Nuclear Magnetic Resonance Spectroscopy, The Pennsylvania State University, University Park, Pennsylvania; Ohio State University Comprehensive Cancer Center, Columbus, Ohio; and Department of Clinical Research, University of Bern, Bern, Switzerland
| | - Jeffrey R Idle
- Authors' Affiliations: Laboratory of Molecular Immunogenomics, Genomic and Immunity Section, NIAMS/NIH; Laboratories of Human Carcinogenesis, and Metabolism, National Cancer Institute, NIH, Bethesda, Maryland; Department of Veterinary and Biomedical Sciences and Center for Molecular Toxicology and Carcinogenesis; Metabolomics Core Facility; Nuclear Magnetic Resonance Spectroscopy, The Pennsylvania State University, University Park, Pennsylvania; Ohio State University Comprehensive Cancer Center, Columbus, Ohio; and Department of Clinical Research, University of Bern, Bern, Switzerland
| | - Philip B Smith
- Authors' Affiliations: Laboratory of Molecular Immunogenomics, Genomic and Immunity Section, NIAMS/NIH; Laboratories of Human Carcinogenesis, and Metabolism, National Cancer Institute, NIH, Bethesda, Maryland; Department of Veterinary and Biomedical Sciences and Center for Molecular Toxicology and Carcinogenesis; Metabolomics Core Facility; Nuclear Magnetic Resonance Spectroscopy, The Pennsylvania State University, University Park, Pennsylvania; Ohio State University Comprehensive Cancer Center, Columbus, Ohio; and Department of Clinical Research, University of Bern, Bern, Switzerland
| | - Katsuhiro Anami
- Authors' Affiliations: Laboratory of Molecular Immunogenomics, Genomic and Immunity Section, NIAMS/NIH; Laboratories of Human Carcinogenesis, and Metabolism, National Cancer Institute, NIH, Bethesda, Maryland; Department of Veterinary and Biomedical Sciences and Center for Molecular Toxicology and Carcinogenesis; Metabolomics Core Facility; Nuclear Magnetic Resonance Spectroscopy, The Pennsylvania State University, University Park, Pennsylvania; Ohio State University Comprehensive Cancer Center, Columbus, Ohio; and Department of Clinical Research, University of Bern, Bern, Switzerland
| | - Dickran G Kazandjian
- Authors' Affiliations: Laboratory of Molecular Immunogenomics, Genomic and Immunity Section, NIAMS/NIH; Laboratories of Human Carcinogenesis, and Metabolism, National Cancer Institute, NIH, Bethesda, Maryland; Department of Veterinary and Biomedical Sciences and Center for Molecular Toxicology and Carcinogenesis; Metabolomics Core Facility; Nuclear Magnetic Resonance Spectroscopy, The Pennsylvania State University, University Park, Pennsylvania; Ohio State University Comprehensive Cancer Center, Columbus, Ohio; and Department of Clinical Research, University of Bern, Bern, Switzerland
| | - Emmanuel Hatzakis
- Authors' Affiliations: Laboratory of Molecular Immunogenomics, Genomic and Immunity Section, NIAMS/NIH; Laboratories of Human Carcinogenesis, and Metabolism, National Cancer Institute, NIH, Bethesda, Maryland; Department of Veterinary and Biomedical Sciences and Center for Molecular Toxicology and Carcinogenesis; Metabolomics Core Facility; Nuclear Magnetic Resonance Spectroscopy, The Pennsylvania State University, University Park, Pennsylvania; Ohio State University Comprehensive Cancer Center, Columbus, Ohio; and Department of Clinical Research, University of Bern, Bern, Switzerland
| | - Frank J Gonzalez
- Authors' Affiliations: Laboratory of Molecular Immunogenomics, Genomic and Immunity Section, NIAMS/NIH; Laboratories of Human Carcinogenesis, and Metabolism, National Cancer Institute, NIH, Bethesda, Maryland; Department of Veterinary and Biomedical Sciences and Center for Molecular Toxicology and Carcinogenesis; Metabolomics Core Facility; Nuclear Magnetic Resonance Spectroscopy, The Pennsylvania State University, University Park, Pennsylvania; Ohio State University Comprehensive Cancer Center, Columbus, Ohio; and Department of Clinical Research, University of Bern, Bern, Switzerland
| | - Curtis C Harris
- Authors' Affiliations: Laboratory of Molecular Immunogenomics, Genomic and Immunity Section, NIAMS/NIH; Laboratories of Human Carcinogenesis, and Metabolism, National Cancer Institute, NIH, Bethesda, Maryland; Department of Veterinary and Biomedical Sciences and Center for Molecular Toxicology and Carcinogenesis; Metabolomics Core Facility; Nuclear Magnetic Resonance Spectroscopy, The Pennsylvania State University, University Park, Pennsylvania; Ohio State University Comprehensive Cancer Center, Columbus, Ohio; and Department of Clinical Research, University of Bern, Bern, Switzerland
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Mechanistic analysis of metabolomics patterns in rat plasma during administration of direct thyroid hormone synthesis inhibitors or compounds increasing thyroid hormone clearance. Toxicol Lett 2014; 225:240-51. [DOI: 10.1016/j.toxlet.2013.12.010] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2013] [Revised: 12/12/2013] [Accepted: 12/13/2013] [Indexed: 12/11/2022]
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22
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High-resolution time-of-flight mass spectrometry fingerprinting of metabolites from cecum and distal colon contents of rats fed resistant starch. Anal Bioanal Chem 2013; 406:745-56. [DOI: 10.1007/s00216-013-7523-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2013] [Revised: 11/14/2013] [Accepted: 11/18/2013] [Indexed: 10/25/2022]
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23
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De Guzman JM, Ku G, Fahey R, Youm YH, Kass I, Ingram DK, Dixit VD, Kheterpal I. Chronic caloric restriction partially protects against age-related alteration in serum metabolome. AGE (DORDRECHT, NETHERLANDS) 2013; 35:1091-1104. [PMID: 22661299 PMCID: PMC3705111 DOI: 10.1007/s11357-012-9430-x] [Citation(s) in RCA: 47] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2012] [Accepted: 05/14/2012] [Indexed: 06/01/2023]
Abstract
Calorie restriction (CR) remains the most robust metabolic intervention to extend lifespan and improve healthspan in several species. Using global and targeted mass spectrometry-based metabolomics approaches, here we show that chronic CR prevents age-related changes in specific metabolic signatures. Global metabolomic analysis using ultra-performance liquid chromatography-tandem mass spectrometry detected more than 7,000 metabolites in sera from ad-libitum-fed young, aged, and aged C57BL/6 mice maintained on 40 % CR. Multivariate statistical analysis of mass spectrometry data revealed a clear separation among the young, aged, and aged-CR mice demonstrating the potential of this approach for producing reliable metabolic profiles that discriminate based on age and diet. We have identified 168 discriminating features with high statistical significance (p ≤ 0.001) and validated and quantified three of these metabolites using targeted metabolite analysis. Calorie restriction prevented the age-related alteration in specific metabolites, namely lysophosphatidylcholines (16:1 and 18:4), sphingomyelin (d18:1/12:0), tetracosahexaenoic acid, and 7α-dihydroxy-4-cholesten-3-one, in the serum. Pathway analysis revealed that CR impacted the age-related changes in metabolic byproducts of lipid metabolism, fatty acid metabolism, and bile acid biosynthesis. Our data suggest that metabolomics approach has the potential to elucidate the metabolic mechanism of CR's potential anti-aging effects in larger-scale investigations.
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Affiliation(s)
- Jennifer M. De Guzman
- />Protein Structural Biology and Proteomics and Metabolomics Core, Pennington Biomedical Research Center, Louisiana State University System, 6400 Perkins Road, Baton Rouge, LA 70808 USA
| | - Ginger Ku
- />Protein Structural Biology and Proteomics and Metabolomics Core, Pennington Biomedical Research Center, Louisiana State University System, 6400 Perkins Road, Baton Rouge, LA 70808 USA
| | - Ryan Fahey
- />Protein Structural Biology and Proteomics and Metabolomics Core, Pennington Biomedical Research Center, Louisiana State University System, 6400 Perkins Road, Baton Rouge, LA 70808 USA
| | - Yun-Hee Youm
- />Immunobiology Laboratory, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA USA
| | | | - Donald K. Ingram
- />Nutritional Neuroscience and Aging, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA USA
| | - Vishwa Deep Dixit
- />Immunobiology Laboratory, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA USA
| | - Indu Kheterpal
- />Protein Structural Biology and Proteomics and Metabolomics Core, Pennington Biomedical Research Center, Louisiana State University System, 6400 Perkins Road, Baton Rouge, LA 70808 USA
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24
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Prediction of clinically relevant safety signals of nephrotoxicity through plasma metabolite profiling. BIOMED RESEARCH INTERNATIONAL 2013; 2013:202497. [PMID: 23762827 PMCID: PMC3673329 DOI: 10.1155/2013/202497] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/23/2013] [Revised: 04/23/2013] [Accepted: 04/25/2013] [Indexed: 11/17/2022]
Abstract
Addressing safety concerns such as drug-induced kidney injury (DIKI) early in the drug pharmaceutical development process ensures both patient safety and efficient clinical development. We describe a unique adjunct to standard safety assessment wherein the metabolite profile of treated animals is compared with the MetaMap Tox metabolomics database in order to predict the potential for a wide variety of adverse events, including DIKI. To examine this approach, a study of five compounds (phenytoin, cyclosporin A, doxorubicin, captopril, and lisinopril) was initiated by the Technology Evaluation Consortium under the auspices of the Drug Safety Executive Council (DSEC). The metabolite profiles for rats treated with these compounds matched established reference patterns in the MetaMap Tox metabolomics database indicative of each compound's well-described clinical toxicities. For example, the DIKI associated with cyclosporine A and doxorubicin was correctly predicted by metabolite profiling, while no evidence for DIKI was found for phenytoin, consistent with its clinical picture. In some cases the clinical toxicity (hepatotoxicity), not generally seen in animal studies, was detected with MetaMap Tox. Thus metabolite profiling coupled with the MetaMap Tox metabolomics database offers a unique and powerful approach for augmenting safety assessment and avoiding clinical adverse events such as DIKI.
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25
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van Ravenzwaay B, Kolle SN, Ramirez T, Kamp HG. Vinclozolin: a case study on the identification of endocrine active substances in the past and a future perspective. Toxicol Lett 2013; 223:271-9. [PMID: 23558297 DOI: 10.1016/j.toxlet.2013.03.029] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2012] [Revised: 03/22/2013] [Accepted: 03/24/2013] [Indexed: 10/27/2022]
Abstract
In the late 1980s vinclozolin was tested for prenatal developmental toxicity in rats for registration purposes in USA. At 1000mg/kgbw, 95% of all fetuses were female upon visual inspection (ano-genital distance determination). Anti-androgenic effects (AA) were also noted in a subsequent 2-generation study. These findings triggered mechanistic investigations at BASF and at US-EPA. Results published by the latter were the starting point of the endocrine disruption (ED) discussion in the 1990s. AA effects of vinclozolin are mediated by two metabolites, which have an antagonistic effect on the androgen receptor. Currently, determination of ED has become a major end-point in toxicology testing and the US-EPA has set up an elaborated testing paradigm to fulfill this requirement. Future screening for ED can be improved making use of new technologies. ED modes of action can be determined by three alternative (3R) methods. Steroid synthesis in H295R cells (1), androgen-receptor binding in modified yeast (2) and metabolomics (3). Using vinclozolin as a case study, results indicate: (1) an effect on steroid synthesis in vitro, (2) an antagonistic effect on the androgen receptor and (3) that the metabolome profile of vinclozolin is similar to that of other receptor mediated anti-androgens (e.g. flutamide).
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26
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Ryan EP, Heuberger AL, Broeckling CD, Borresen EC, Tillotson C, Prenni JE. Advances in Nutritional Metabolomics. ACTA ACUST UNITED AC 2013; 1:109-120. [PMID: 29682447 DOI: 10.2174/2213235x11301020001] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Metabolomics is maturing as an experimental approach in nutrition science, and it is a useful analysis for revealing systems biology outcomes associated with changes in diet. A major goal of this review is to present the rapidly evolving body of scientific literature that seeks to reveal connections between an individual's metabolic profile and experimentally manipulated or naturally varied dietary intakes. Metabolite profiles in tissue, serum, urine, or stool reflect changes in metabolic pathways that respond to dietary intervention which makes them accessible samples for revealing metabolic effects of diet. Three broadly defined areas of investigation related to dietary-metabolomic strategies include: (1) describing the metabolite variation within and between dietary exposures or interventions; (2) characterizing the metabolic response to dietary interventions with respect to time; and (3) assessing individual variation in baseline nutritional health and/or disease status. An overview of metabolites that were responsive to dietary interventions as reported from original research in human or animal studies is provided and illustrates the breadth of metabolites affected by dietary intervention. Advantages and drawbacks for assessing metabolic changes are discussed in relation to types of metabolite analysis platforms. A combination of targeted and non-targeted global profiling studies as a component of future dietary intervention trials will increase our understanding of nutrition in a systems context.
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Affiliation(s)
- Elizabeth P Ryan
- Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins CO 80523
| | - Adam L Heuberger
- Proteomics and Metabolomics Facility, Colorado State University, Fort Collins CO 80523
| | - Corey D Broeckling
- Proteomics and Metabolomics Facility, Colorado State University, Fort Collins CO 80523
| | - Erica C Borresen
- Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins CO 80523
| | - Cadie Tillotson
- Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins CO 80523
| | - Jessica E Prenni
- Proteomics and Metabolomics Facility, Colorado State University, Fort Collins CO 80523.,Department of Biochemistry and Molecular Biology, Colorado State University, Fort Collins CO 80523
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Application of in vivo metabolomics to preclinical/toxicological studies: case study on phenytoin-induced systemic toxicity. Bioanalysis 2013; 4:2291-301. [PMID: 23046269 DOI: 10.4155/bio.12.214] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
BASF and Metanomics have built-up the database MetaMap(®)-Tox containing rat plasma metabolome data for more than 500 reference compounds. Phenytoin was administered to five Wistar rats of both sexes at dietary dose levels of 600 and 2400 ppm over 28 days and metabolome analysis was performed on days 7, 14 and 28. Clinical pathology did not indicate clear evidence for liver toxicity, whereas liver histopathology revealed slight centrilobular hepatocellular hypertrophy. The metabolome analysis of phenytoin shows metabolome changes at both dose levels and the comparison with MetaMap-Tox indicated strong evidence for liver enzyme induction, as well as liver toxicity. Moreover, evidence for kidney and indirect thyroid effects were observed. This assessment was based on the metabolite changes induced, similarities to specific toxicity patterns and the whole metabolome correlation within MetaMap-Tox. As compared with the classical read-out, a more comprehensive picture of phenytoin's effects is obtained from the metabolome analysis, demonstrating the added value of metabolome data in preclinical/ toxicological studies.
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Kamp H, Strauss V, Wiemer J, Leibold E, Walk T, Mellert W, Looser R, Prokoudine A, Fabian E, Krennrich G, Herold M, van Ravenzwaay B. Reproducibility and robustness of metabolome analysis in rat plasma of 28-day repeated dose toxicity studies. Toxicol Lett 2012; 215:143-9. [DOI: 10.1016/j.toxlet.2012.09.015] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2012] [Revised: 09/18/2012] [Accepted: 09/24/2012] [Indexed: 11/28/2022]
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Hedemann MS, Damgaard BM. Metabolomic study of plasma from female mink (Neovison vison) with low and high residual feed intake during restrictive and ad libitum feeding. COMPARATIVE BIOCHEMISTRY AND PHYSIOLOGY D-GENOMICS & PROTEOMICS 2012; 7:322-7. [PMID: 23123310 DOI: 10.1016/j.cbd.2012.09.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2012] [Revised: 09/24/2012] [Accepted: 09/24/2012] [Indexed: 11/26/2022]
Abstract
Metabolite profiling may elucidate changes in metabolic pathways under various physiological or nutritional conditions. In the present study two groups of female mink characterised as having a high (16 mink) or low (14 mink) residual feed intake were investigated during restrictive and ad libitum feeding. Blood samples were collected three times during the experimental period; during restrictive feeding, and four days and three weeks after the change to ad libitum feeding. Plasma samples were subjected to liquid chromatography mass spectrometry non-targeted metabolomics. Subjecting data to principal component analysis showed that there was no grouping of the data according to the residual feed intake. In contrast, data were clearly grouped according to feeding level. Identification of the metabolites responsible for this grouping showed that the plasma level of metabolites related to mobilisation of energy was high during restrictive feeding, e.g. betaine, carnitine, and creatine. During ad libitum feeding the plasma level of metabolites that can be characterised as biomarkers of meat intake (creatinine, carnosine, 1- and 3 methylhistidine) was high. The plasma level of lysophosphatidylcholine species was highest after four days of ad libitum feeding suggesting a short term imbalance in the transport or metabolism of these metabolites when changing the feeding level.
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Kolle SN, Ramirez T, Kamp HG, Buesen R, Flick B, Strauss V, van Ravenzwaay B. A testing strategy for the identification of mammalian, systemic endocrine disruptors with particular focus on steroids. Regul Toxicol Pharmacol 2012; 63:259-78. [DOI: 10.1016/j.yrtph.2012.04.004] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2011] [Revised: 04/16/2012] [Accepted: 04/17/2012] [Indexed: 12/12/2022]
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31
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Strauss V, Mellert W, Wiemer J, Leibold E, Kamp H, Walk T, Looser R, Prokoudine A, Fabian E, Krennrich G, Herold M, van Ravenzwaay B. Increased toxicity when fibrates and statins are administered in combination – A metabolomics approach with rats. Toxicol Lett 2012; 211:187-200. [DOI: 10.1016/j.toxlet.2012.03.798] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2011] [Revised: 03/19/2012] [Accepted: 03/21/2012] [Indexed: 10/28/2022]
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