2.50
Hdl Handle:
http://hdl.handle.net/10033/621096
Title:
Metabolic profiling of body fluids and multivariate data analysis.
Authors:
Trezzi, Jean-Pierre; Jäger, Christian; Galozzi, Sara; Barkovits, Katalin; Marcus, Katrin; Mollenhauer, Brit; Hiller, Karsten
Abstract:
Metabolome analyses of body fluids are challenging due pre-analytical variations, such as pre-processing delay and temperature, and constant dynamical changes of biochemical processes within the samples. Therefore, proper sample handling starting from the time of collection up to the analysis is crucial to obtain high quality samples and reproducible results. A metabolomics analysis is divided into 4 main steps: 1) Sample collection, 2) Metabolite extraction, 3) Data acquisition and 4) Data analysis. Here, we describe a protocol for gas chromatography coupled to mass spectrometry (GC-MS) based metabolic analysis for biological matrices, especially body fluids. This protocol can be applied on blood serum/plasma, saliva and cerebrospinal fluid (CSF) samples of humans and other vertebrates. It covers sample collection, sample pre-processing, metabolite extraction, GC-MS measurement and guidelines for the subsequent data analysis. Advantages of this protocol include: •Robust and reproducible metabolomics results, taking into account pre-analytical variations that may occur during the sampling process•Small sample volume required•Rapid and cost-effective processing of biological samples•Logistic regression based determination of biomarker signatures for in-depth data analysis.
Affiliation:
Helmholtz Centre for infection research, Inhoffenstr. 7, 38124 Braunschweig, Germany.
Citation:
Metabolic profiling of body fluids and multivariate data analysis. 2017, 4:95-103 MethodsX
Journal:
MethodsX
Issue Date:
2017
URI:
http://hdl.handle.net/10033/621096
DOI:
10.1016/j.mex.2017.02.004
PubMed ID:
28275554
Type:
Article
Language:
en
ISSN:
2215-0161
Appears in Collections:
Publications of Scientific Director (GFW)

Full metadata record

DC FieldValue Language
dc.contributor.authorTrezzi, Jean-Pierreen
dc.contributor.authorJäger, Christianen
dc.contributor.authorGalozzi, Saraen
dc.contributor.authorBarkovits, Katalinen
dc.contributor.authorMarcus, Katrinen
dc.contributor.authorMollenhauer, Briten
dc.contributor.authorHiller, Karstenen
dc.date.accessioned2017-09-07T12:55:28Z-
dc.date.available2017-09-07T12:55:28Z-
dc.date.issued2017-
dc.identifier.citationMetabolic profiling of body fluids and multivariate data analysis. 2017, 4:95-103 MethodsXen
dc.identifier.issn2215-0161-
dc.identifier.pmid28275554-
dc.identifier.doi10.1016/j.mex.2017.02.004-
dc.identifier.urihttp://hdl.handle.net/10033/621096-
dc.description.abstractMetabolome analyses of body fluids are challenging due pre-analytical variations, such as pre-processing delay and temperature, and constant dynamical changes of biochemical processes within the samples. Therefore, proper sample handling starting from the time of collection up to the analysis is crucial to obtain high quality samples and reproducible results. A metabolomics analysis is divided into 4 main steps: 1) Sample collection, 2) Metabolite extraction, 3) Data acquisition and 4) Data analysis. Here, we describe a protocol for gas chromatography coupled to mass spectrometry (GC-MS) based metabolic analysis for biological matrices, especially body fluids. This protocol can be applied on blood serum/plasma, saliva and cerebrospinal fluid (CSF) samples of humans and other vertebrates. It covers sample collection, sample pre-processing, metabolite extraction, GC-MS measurement and guidelines for the subsequent data analysis. Advantages of this protocol include: •Robust and reproducible metabolomics results, taking into account pre-analytical variations that may occur during the sampling process•Small sample volume required•Rapid and cost-effective processing of biological samples•Logistic regression based determination of biomarker signatures for in-depth data analysis.en
dc.language.isoenen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.titleMetabolic profiling of body fluids and multivariate data analysis.en
dc.typeArticleen
dc.contributor.departmentHelmholtz Centre for infection research, Inhoffenstr. 7, 38124 Braunschweig, Germany.en
dc.identifier.journalMethodsXen

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