Comparison of extraction methods for intracellular metabolomics of human tissues
Analyses of metabolic compounds inside cells or tissues provide high information content since they represent the endpoint of biological information flow and are a snapshot of the integration of many regulatory processes. However, quantification of the abundance of metabolites requires their careful...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2022-08-01
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| Series: | Frontiers in Molecular Biosciences |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fmolb.2022.932261/full |
| _version_ | 1818082669713424384 |
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| author | Carolin Andresen Carolin Andresen Carolin Andresen Tobias Boch Tobias Boch Tobias Boch Tobias Boch Tobias Boch Hagen M. Gegner Nils Mechtel Andreas Narr Andreas Narr Andreas Narr Emrullah Birgin Erik Rasbach Nuh Rahbari Andreas Trumpp Andreas Trumpp Andreas Trumpp Gernot Poschet Daniel Hübschmann Daniel Hübschmann Daniel Hübschmann |
| author_facet | Carolin Andresen Carolin Andresen Carolin Andresen Tobias Boch Tobias Boch Tobias Boch Tobias Boch Tobias Boch Hagen M. Gegner Nils Mechtel Andreas Narr Andreas Narr Andreas Narr Emrullah Birgin Erik Rasbach Nuh Rahbari Andreas Trumpp Andreas Trumpp Andreas Trumpp Gernot Poschet Daniel Hübschmann Daniel Hübschmann Daniel Hübschmann |
| author_sort | Carolin Andresen |
| collection | DOAJ |
| description | Analyses of metabolic compounds inside cells or tissues provide high information content since they represent the endpoint of biological information flow and are a snapshot of the integration of many regulatory processes. However, quantification of the abundance of metabolites requires their careful extraction. We present a comprehensive study comparing ten extraction protocols in four human sample types (liver tissue, bone marrow, HL60, and HEK cells) aiming to detect and quantify up to 630 metabolites of different chemical classes. We show that the extraction efficiency and repeatability are highly variable across protocols, tissues, and chemical classes of metabolites. We used different quality metrics including the limit of detection and variability between replicates as well as the sum of concentrations as a global estimate of analytical repeatability of the extraction. The coverage of extracted metabolites depends on the used solvents, which has implications for the design of measurements of different sample types and metabolic compounds of interest. The benchmark dataset can be explored in an easy-to-use, interactive, and flexible online resource (R/shiny app MetaboExtract: http://www.metaboextract.shiny.dkfz.de) for context-specific selection of the optimal extraction method. Furthermore, data processing and conversion functionality underlying the shiny app are accessible as an R package: https://cran.r-project.org/package=MetAlyzer. |
| first_indexed | 2024-12-10T19:25:47Z |
| format | Article |
| id | doaj.art-62facc52ca3149f7aad06d434be45a5f |
| institution | Directory Open Access Journal |
| issn | 2296-889X |
| language | English |
| last_indexed | 2024-12-10T19:25:47Z |
| publishDate | 2022-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Molecular Biosciences |
| spelling | doaj.art-62facc52ca3149f7aad06d434be45a5f2022-12-22T01:36:22ZengFrontiers Media S.A.Frontiers in Molecular Biosciences2296-889X2022-08-01910.3389/fmolb.2022.932261932261Comparison of extraction methods for intracellular metabolomics of human tissuesCarolin Andresen0Carolin Andresen1Carolin Andresen2Tobias Boch3Tobias Boch4Tobias Boch5Tobias Boch6Tobias Boch7Hagen M. Gegner8Nils Mechtel9Andreas Narr10Andreas Narr11Andreas Narr12Emrullah Birgin13Erik Rasbach14Nuh Rahbari15Andreas Trumpp16Andreas Trumpp17Andreas Trumpp18Gernot Poschet19Daniel Hübschmann20Daniel Hübschmann21Daniel Hübschmann22Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM gGmbH), Heidelberg, GermanyDivision of Stem Cells and Cancer, German Cancer Research Center and DKFZ-ZMBH Alliance, Heidelberg, GermanyFaculty of Biosciences, Heidelberg University, Heidelberg, GermanyHeidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM gGmbH), Heidelberg, GermanyDivision of Stem Cells and Cancer, German Cancer Research Center and DKFZ-ZMBH Alliance, Heidelberg, GermanyDivision of Personalized Medical Oncology, German Cancer Research Center, Heidelberg, GermanyDepartment of Personalized Oncology, University Hospital Mannheim, University of Heidelberg, Mannheim, GermanyDKFZ-Hector Cancer Institute at the University Medical Center Mannheim, Mannheim, GermanyCentre for Organismal Studies (COS), Heidelberg University, Heidelberg, GermanyCentre for Organismal Studies (COS), Heidelberg University, Heidelberg, GermanyHeidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM gGmbH), Heidelberg, GermanyDivision of Stem Cells and Cancer, German Cancer Research Center and DKFZ-ZMBH Alliance, Heidelberg, GermanyFaculty of Biosciences, Heidelberg University, Heidelberg, GermanyDepartment of Surgery, Medical Faculty Mannheim, Universitätsmedizin Mannheim, Heidelberg University, Mannheim, GermanyDepartment of Surgery, Medical Faculty Mannheim, Universitätsmedizin Mannheim, Heidelberg University, Mannheim, GermanyDepartment of Surgery, Medical Faculty Mannheim, Universitätsmedizin Mannheim, Heidelberg University, Mannheim, GermanyHeidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM gGmbH), Heidelberg, GermanyDivision of Stem Cells and Cancer, German Cancer Research Center and DKFZ-ZMBH Alliance, Heidelberg, GermanyGerman Cancer Consortium (DKTK), Heidelberg, GermanyCentre for Organismal Studies (COS), Heidelberg University, Heidelberg, GermanyHeidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM gGmbH), Heidelberg, GermanyGerman Cancer Consortium (DKTK), Heidelberg, Germany0Computational Oncology, Molecular Diagnostics Program, National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ), Heidelberg, GermanyAnalyses of metabolic compounds inside cells or tissues provide high information content since they represent the endpoint of biological information flow and are a snapshot of the integration of many regulatory processes. However, quantification of the abundance of metabolites requires their careful extraction. We present a comprehensive study comparing ten extraction protocols in four human sample types (liver tissue, bone marrow, HL60, and HEK cells) aiming to detect and quantify up to 630 metabolites of different chemical classes. We show that the extraction efficiency and repeatability are highly variable across protocols, tissues, and chemical classes of metabolites. We used different quality metrics including the limit of detection and variability between replicates as well as the sum of concentrations as a global estimate of analytical repeatability of the extraction. The coverage of extracted metabolites depends on the used solvents, which has implications for the design of measurements of different sample types and metabolic compounds of interest. The benchmark dataset can be explored in an easy-to-use, interactive, and flexible online resource (R/shiny app MetaboExtract: http://www.metaboextract.shiny.dkfz.de) for context-specific selection of the optimal extraction method. Furthermore, data processing and conversion functionality underlying the shiny app are accessible as an R package: https://cran.r-project.org/package=MetAlyzer.https://www.frontiersin.org/articles/10.3389/fmolb.2022.932261/fullmetabolismmetabolomicsintra-cellularextraction protocolabsolute quantification |
| spellingShingle | Carolin Andresen Carolin Andresen Carolin Andresen Tobias Boch Tobias Boch Tobias Boch Tobias Boch Tobias Boch Hagen M. Gegner Nils Mechtel Andreas Narr Andreas Narr Andreas Narr Emrullah Birgin Erik Rasbach Nuh Rahbari Andreas Trumpp Andreas Trumpp Andreas Trumpp Gernot Poschet Daniel Hübschmann Daniel Hübschmann Daniel Hübschmann Comparison of extraction methods for intracellular metabolomics of human tissues Frontiers in Molecular Biosciences metabolism metabolomics intra-cellular extraction protocol absolute quantification |
| title | Comparison of extraction methods for intracellular metabolomics of human tissues |
| title_full | Comparison of extraction methods for intracellular metabolomics of human tissues |
| title_fullStr | Comparison of extraction methods for intracellular metabolomics of human tissues |
| title_full_unstemmed | Comparison of extraction methods for intracellular metabolomics of human tissues |
| title_short | Comparison of extraction methods for intracellular metabolomics of human tissues |
| title_sort | comparison of extraction methods for intracellular metabolomics of human tissues |
| topic | metabolism metabolomics intra-cellular extraction protocol absolute quantification |
| url | https://www.frontiersin.org/articles/10.3389/fmolb.2022.932261/full |
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