Literature DB >> 26383735

Exploring the Process of Energy Generation in Pathophysiology by Targeted Metabolomics: Performance of a Simple and Quantitative Method.

Marta Riera-Borrull1,2, Esther Rodríguez-Gallego1,2, Anna Hernández-Aguilera1,2, Fedra Luciano1,2, Rosa Ras3, Elisabet Cuyàs4,5, Jordi Camps1,2, Antonio Segura-Carretero6,7, Javier A Menendez4,5, Jorge Joven8,9, Salvador Fernández-Arroyo10,11.   

Abstract

Abnormalities in mitochondrial metabolism and regulation of energy balance contribute to human diseases. The consequences of high fat and other nutrient intake, and the resulting acquired mitochondrial dysfunction, are essential to fully understand common disorders, including obesity, cancer, and atherosclerosis. To simultaneously and noninvasively measure and quantify indirect markers of mitochondrial function, we have developed a method based on gas chromatography coupled to quadrupole-time of flight mass spectrometry and an electron ionization interface, and validated the system using plasma from patients with peripheral artery disease, human cancer cells, and mouse tissues. This approach was used to increase sensibility in the measurement of a wide dynamic range and chemical diversity of multiple intermediate metabolites used in energy metabolism. We demonstrate that our targeted metabolomics method allows for quick and accurate identification and quantification of molecules, including the measurement of small yet significant biological changes in experimental samples. The apparently low process variability required for its performance in plasma, cell lysates, and tissues allowed a rapid identification of correlations between interconnected pathways. Our results suggest that delineating the process of energy generation by targeted metabolomics can be a valid surrogate for predicting mitochondrial dysfunction in biological samples. Importantly, when used in plasma, targeted metabolomics should be viewed as a robust and noninvasive source of biomarkers in specific pathophysiological scenarios.

Entities:  

Keywords:  Arteriosclerosis; Biomarkers; Cancer; Energy metabolism; Gas chromatography; Mitochondrial dysfunction; Targeted metabolomics

Mesh:

Substances:

Year:  2015        PMID: 26383735     DOI: 10.1007/s13361-015-1262-3

Source DB:  PubMed          Journal:  J Am Soc Mass Spectrom        ISSN: 1044-0305            Impact factor:   3.109


  41 in total

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Review 2.  Homeostasis, inflammation, and disease susceptibility.

Authors:  Maya E Kotas; Ruslan Medzhitov
Journal:  Cell       Date:  2015-02-26       Impact factor: 41.582

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Journal:  Atherosclerosis       Date:  2007-07-24       Impact factor: 5.162

Review 4.  Mass spectrometry strategies in metabolomics.

Authors:  Zhentian Lei; David V Huhman; Lloyd W Sumner
Journal:  J Biol Chem       Date:  2011-06-01       Impact factor: 5.157

5.  Mitophagy and mitochondrial balance.

Authors:  Simone Patergnani; Paolo Pinton
Journal:  Methods Mol Biol       Date:  2015

6.  Metabolic footprint of diabetes: a multiplatform metabolomics study in an epidemiological setting.

Authors:  Karsten Suhre; Christa Meisinger; Angela Döring; Elisabeth Altmaier; Petra Belcredi; Christian Gieger; David Chang; Michael V Milburn; Walter E Gall; Klaus M Weinberger; Hans-Werner Mewes; Martin Hrabé de Angelis; H-Erich Wichmann; Florian Kronenberg; Jerzy Adamski; Thomas Illig
Journal:  PLoS One       Date:  2010-11-11       Impact factor: 3.240

Review 7.  MITOCHONDRIA: investigation of in vivo muscle mitochondrial function by 31P magnetic resonance spectroscopy.

Authors:  Jeanine J Prompers; Bart Wessels; Graham J Kemp; Klaas Nicolay
Journal:  Int J Biochem Cell Biol       Date:  2014-02-22       Impact factor: 5.085

8.  Metabonomic, transcriptomic, and genomic variation of a population cohort.

Authors:  Michael Inouye; Johannes Kettunen; Pasi Soininen; Kaisa Silander; Samuli Ripatti; Linda S Kumpula; Eija Hämäläinen; Pekka Jousilahti; Antti J Kangas; Satu Männistö; Markku J Savolainen; Antti Jula; Jaana Leiviskä; Aarno Palotie; Veikko Salomaa; Markus Perola; Mika Ala-Korpela; Leena Peltonen
Journal:  Mol Syst Biol       Date:  2010-12-21       Impact factor: 13.068

Review 9.  Metabolic networks in motion: 13C-based flux analysis.

Authors:  Uwe Sauer
Journal:  Mol Syst Biol       Date:  2006-11-14       Impact factor: 11.429

Review 10.  IDH mutations in tumorigenesis and their potential role as novel therapeutic targets.

Authors:  Daniel Krell; Paul Mulholland; Adam E Frampton; Jonathan Krell; Justin Stebbing; Chiara Bardella
Journal:  Future Oncol       Date:  2013-12       Impact factor: 3.674

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  13 in total

1.  Phenotypic, morphological, and metabolic characterization of vascular-spheres from human vascular mesenchymal stem cells.

Authors:  Sabrina Valente; Carmen Ciavarella; Anna Hernández-Aguilera; Fernández-Arroyo Salvador; Marina Buzzi; Jorge Joven; Gianandrea Pasquinelli
Journal:  Microsc Res Tech       Date:  2021-08-27       Impact factor: 2.893

2.  Oncometabolic Nuclear Reprogramming of Cancer Stemness.

Authors:  Javier A Menendez; Bruna Corominas-Faja; Elisabet Cuyàs; María G García; Salvador Fernández-Arroyo; Agustín F Fernández; Jorge Joven; Mario F Fraga; Tomás Alarcón
Journal:  Stem Cell Reports       Date:  2016-02-11       Impact factor: 7.765

3.  Metformin Potentiates the Benefits of Dietary Restraint: A Metabolomic Study.

Authors:  Marta Riera-Borrull; Anabel García-Heredia; Salvador Fernández-Arroyo; Anna Hernández-Aguilera; Noemí Cabré; Elisabet Cuyàs; Fedra Luciano-Mateo; Jordi Camps; Javier A Menendez; Jorge Joven
Journal:  Int J Mol Sci       Date:  2017-10-28       Impact factor: 5.923

Review 4.  Nutrients in Energy and One-Carbon Metabolism: Learning from Metformin Users.

Authors:  Fedra Luciano-Mateo; Anna Hernández-Aguilera; Noemi Cabre; Jordi Camps; Salvador Fernández-Arroyo; Jose Lopez-Miranda; Javier A Menendez; Jorge Joven
Journal:  Nutrients       Date:  2017-02-10       Impact factor: 5.717

5.  Intestinal SIRT3 overexpression in mice improves whole body glucose homeostasis independent of body weight.

Authors:  Deepti Ramachandran; Rosmarie Clara; Shahana Fedele; Junmin Hu; Endre Lackzo; Jing-Yi Huang; Eric Verdin; Wolfgang Langhans; Abdelhak Mansouri
Journal:  Mol Metab       Date:  2017-07-18       Impact factor: 7.422

6.  Chemokine C-C motif ligand 2 overexpression drives tissue-specific metabolic responses in the liver and muscle of mice.

Authors:  Fedra Luciano-Mateo; Noemí Cabré; Salvador Fernández-Arroyo; Gerard Baiges-Gaya; Anna Hernández-Aguilera; Elisabet Rodríguez-Tomàs; Cristina Muñoz-Pinedo; Javier A Menéndez; Jordi Camps; Jorge Joven
Journal:  Sci Rep       Date:  2020-07-20       Impact factor: 4.379

7.  Plasma Energy-Balance Metabolites Discriminate Asymptomatic Patients with Peripheral Artery Disease.

Authors:  Anna Hernández-Aguilera; Salvador Fernández-Arroyo; Noemí Cabre; Fedra Luciano-Mateo; Gerard Baiges-Gaya; Montserrat Fibla; Vicente Martín-Paredero; Javier A Menendez; Jordi Camps; Jorge Joven
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8.  Mitophagy-driven mitochondrial rejuvenation regulates stem cell fate.

Authors:  Alejandro Vazquez-Martin; Chris Van den Haute; Sílvia Cufí; Bruna Corominas-Faja; Elisabet Cuyàs; Eugeni Lopez-Bonet; Esther Rodriguez-Gallego; Salvador Fernández-Arroyo; Jorge Joven; Veerle Baekelandt; Javier A Menendez
Journal:  Aging (Albany NY)       Date:  2016-07       Impact factor: 5.682

9.  Germline BRCA1 mutation reprograms breast epithelial cell metabolism towards mitochondrial-dependent biosynthesis: evidence for metformin-based "starvation" strategies in BRCA1 carriers.

Authors:  Elisabet Cuyàs; Salvador Fernández-Arroyo; Tomás Alarcón; Ruth Lupu; Jorge Joven; Javier A Menendez
Journal:  Oncotarget       Date:  2016-08-16

10.  Metabolite normalization with local radiotherapy following breast tumor resection.

Authors:  Meritxell Arenas; Elisabet Rodríguez; Anabel García-Heredia; Salvador Fernández-Arroyo; Sebastià Sabater; Rogelio Robaina; Marina Gascón; Maria Rodríguez-Pla; Noemí Cabré; Fedra Luciano-Mateo; Anna Hernández-Aguilera; Isabel Fort-Gallifa; Jordi Camps; Jorge Joven
Journal:  PLoS One       Date:  2018-11-16       Impact factor: 3.240

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