Error Propagation Analysis for Quantitative Intracellular Metabolomics
Model-based analyses have become an integral part of modern metabolic engineering and systems biology in order to gain knowledge about complex and not directly observable cellular processes. For quantitative analyses, not only experimental data, but also measurement errors, play a crucial role. The...
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2012-11-01
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Online Access: | http://www.mdpi.com/2218-1989/2/4/1012 |
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doaj-6095e7c0bd6541498cb9594d9861a10c2020-11-24T20:54:26ZengMDPI AGMetabolites2218-19892012-11-01241012103010.3390/metabo2041012Error Propagation Analysis for Quantitative Intracellular MetabolomicsJana TillackNicole PacziaKatharina NöhWolfgang WiechertStephan NoackModel-based analyses have become an integral part of modern metabolic engineering and systems biology in order to gain knowledge about complex and not directly observable cellular processes. For quantitative analyses, not only experimental data, but also measurement errors, play a crucial role. The total measurement error of any analytical protocol is the result of an accumulation of single errors introduced by several processing steps. Here, we present a framework for the quantification of intracellular metabolites, including error propagation during metabolome sample processing. Focusing on one specific protocol, we comprehensively investigate all currently known and accessible factors that ultimately impact the accuracy of intracellular metabolite concentration data. All intermediate steps are modeled, and their uncertainty with respect to the final concentration data is rigorously quantified. Finally, on the basis of a comprehensive metabolome dataset of Corynebacterium glutamicum, an integrated error propagation analysis for all parts of the model is conducted, and the most critical steps for intracellular metabolite quantification are detected.http://www.mdpi.com/2218-1989/2/4/1012metabolomicsquantificationintracellular metabolitesquenchingmetabolite leakageLC-MS/MSerror propagation analysisCorynebacterium glutamicum |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jana Tillack Nicole Paczia Katharina Nöh Wolfgang Wiechert Stephan Noack |
spellingShingle |
Jana Tillack Nicole Paczia Katharina Nöh Wolfgang Wiechert Stephan Noack Error Propagation Analysis for Quantitative Intracellular Metabolomics Metabolites metabolomics quantification intracellular metabolites quenching metabolite leakage LC-MS/MS error propagation analysis Corynebacterium glutamicum |
author_facet |
Jana Tillack Nicole Paczia Katharina Nöh Wolfgang Wiechert Stephan Noack |
author_sort |
Jana Tillack |
title |
Error Propagation Analysis for Quantitative Intracellular Metabolomics |
title_short |
Error Propagation Analysis for Quantitative Intracellular Metabolomics |
title_full |
Error Propagation Analysis for Quantitative Intracellular Metabolomics |
title_fullStr |
Error Propagation Analysis for Quantitative Intracellular Metabolomics |
title_full_unstemmed |
Error Propagation Analysis for Quantitative Intracellular Metabolomics |
title_sort |
error propagation analysis for quantitative intracellular metabolomics |
publisher |
MDPI AG |
series |
Metabolites |
issn |
2218-1989 |
publishDate |
2012-11-01 |
description |
Model-based analyses have become an integral part of modern metabolic engineering and systems biology in order to gain knowledge about complex and not directly observable cellular processes. For quantitative analyses, not only experimental data, but also measurement errors, play a crucial role. The total measurement error of any analytical protocol is the result of an accumulation of single errors introduced by several processing steps. Here, we present a framework for the quantification of intracellular metabolites, including error propagation during metabolome sample processing. Focusing on one specific protocol, we comprehensively investigate all currently known and accessible factors that ultimately impact the accuracy of intracellular metabolite concentration data. All intermediate steps are modeled, and their uncertainty with respect to the final concentration data is rigorously quantified. Finally, on the basis of a comprehensive metabolome dataset of Corynebacterium glutamicum, an integrated error propagation analysis for all parts of the model is conducted, and the most critical steps for intracellular metabolite quantification are detected. |
topic |
metabolomics quantification intracellular metabolites quenching metabolite leakage LC-MS/MS error propagation analysis Corynebacterium glutamicum |
url |
http://www.mdpi.com/2218-1989/2/4/1012 |
work_keys_str_mv |
AT janatillack errorpropagationanalysisforquantitativeintracellularmetabolomics AT nicolepaczia errorpropagationanalysisforquantitativeintracellularmetabolomics AT katharinanoh errorpropagationanalysisforquantitativeintracellularmetabolomics AT wolfgangwiechert errorpropagationanalysisforquantitativeintracellularmetabolomics AT stephannoack errorpropagationanalysisforquantitativeintracellularmetabolomics |
_version_ |
1716794500080205824 |