Deep Metabolic Profiling Assessment of Tissue Extraction Protocols for Three Model Organisms

被引:8
作者
Gegner, Hagen M.
Mechtel, Nils
Heidenreich, Elena
Wirth, Angela
Cortizo, Fabiola Garcia
Bennewitz, Katrin
Fleming, Thomas
Andresen, Carolin
Freichel, Marc
Teleman, Aurelio A.
Kroll, Jens
Hell, Ruediger
Poschet, Gernot
机构
[1] Metabolomics Core Technology Platform, Centre for Organismal Studies (COS), Heidelberg University, Heidelberg
[2] Institute of Pharmacology, Heidelberg University, Heidelberg
[3] Division of Signal Transduction in Cancer and Metabolism, German Cancer Research Center (DKFZ), Heidelberg
[4] European Center for Angioscience (ECAS), Department of Vascular Biology and Tumor Angiogenesis, Medical Faculty Mannheim, Heidelberg University, Mannheim
[5] Department of Internal Medicine I and Clinical Chemistry, Heidelberg University Hospital, Heidelberg
[6] Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM GGmbH), Heidelberg
[7] Division of Stem Cells and Cancer, Deutsches Krebsforschungszentrum (DKFZ), DKFZ-ZMBH Alliance, Heidelberg
[8] Faculty of Biosciences, Heidelberg University, Heidelberg
关键词
metabolomics; LC-MS; MS; extraction protocol; model organisms; drosophila; mouse; zebrafish; MxP Quant 500; TARGETED METABOLOMICS; LIPID EXTRACTION; MASS; IMPACT;
D O I
10.3389/fchem.2022.869732
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
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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页数:11
相关论文
共 30 条
[1]   Metabolomics Approaches for the Diagnosis and Understanding of Kidney Diseases [J].
Abbiss, Hayley ;
Maker, Garth L. ;
Trengove, Robert D. .
METABOLITES, 2019, 9 (02)
[2]   Key elements of metabolomics in the study of biomarkers of diabetes [J].
Adamski, Jerzy .
DIABETOLOGIA, 2016, 59 (12) :2497-2502
[3]  
Andresen C, 2021, bioRxiv, DOI [10.1101/2021.12.15.470649, 10.1101/2021.12.15.470649, DOI 10.1101/2021.12.15.470649]
[4]   Metabolomics of Type 1 and Type 2 Diabetes [J].
Arneth, Borros ;
Arneth, Rebekka ;
Shams, Mohamed .
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2019, 20 (10)
[5]   Sex differences in systemic metabolites at four life stages: cohort study with repeated metabolomics [J].
Bell, Joshua A. ;
Santos Ferreira, Diana L. ;
Fraser, Abigail ;
Soares, Ana Luiza G. ;
Howe, Laura D. ;
Lawlor, Deborah A. ;
Carslake, David ;
Davey Smith, George ;
O'Keeffe, Linda M. .
BMC MEDICINE, 2021, 19 (01)
[6]  
BLIGH EG, 1959, CAN J BIOCHEM PHYS, V37, P911
[7]   Sex matters: a focus on the impact of biological sex on metabolomic profiles and dietary interventions [J].
Brennan, Lorraine ;
Gibbons, Helena .
PROCEEDINGS OF THE NUTRITION SOCIETY, 2020, 79 (02) :205-209
[8]   Comparison of simple monophasic versus classical biphasic extraction protocols for comprehensive UHPLC-MS/MS lipidomic analysis of Hela cells [J].
Calderon, Carlos ;
Sanwald, Corinna ;
Schlotterbeck, Joerg ;
Drotleff, Bernhard ;
Laemmerhofer, Michael .
ANALYTICA CHIMICA ACTA, 2019, 1048 :66-74
[9]   The Time Is Right to Focus on Model Organism Metabolomes [J].
Edison, Arthur S. ;
Hall, Robert D. ;
Junot, Christophe ;
Karp, Peter D. ;
Kurland, Irwin J. ;
Mistrik, Robert ;
Reed, Laura K. ;
Saito, Kazuki ;
Salek, Reza M. ;
Steinbeck, Christoph ;
Sumner, Lloyd W. ;
Viant, Mark R. .
METABOLITES, 2016, 6 (01)
[10]   Evaluation of different stool extraction methods for metabolomics measurements in human faecal samples [J].
Erben, Vanessa ;
Poschet, Gernot ;
Schrotz-King, Petra ;
Brenner, Hermann .
BMJ NUTRITION, PREVENTION & HEALTH, 2021, 4 (02) :374-384