Systematic Applications of Metabolomics in Metabolic Engineering

The goals of metabolic engineering are well-served by the biological information provided by metabolomics: information on how the cell is currently using its biochemical resources is perhaps one of the best ways to inform strategies to engineer a cell to produce a target compound. Using the analysis...

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Main Authors: Robert A. Dromms, Mark P. Styczynski
Format: Article
Language:English
Published: MDPI AG 2012-12-01
Series:Metabolites
Subjects:
Online Access:http://www.mdpi.com/2218-1989/2/4/1090
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spelling doaj-1673918c03fc400c8ebe25ecd5bf92a62020-11-25T00:05:36ZengMDPI AGMetabolites2218-19892012-12-01241090112210.3390/metabo2041090Systematic Applications of Metabolomics in Metabolic EngineeringRobert A. DrommsMark P. StyczynskiThe goals of metabolic engineering are well-served by the biological information provided by metabolomics: information on how the cell is currently using its biochemical resources is perhaps one of the best ways to inform strategies to engineer a cell to produce a target compound. Using the analysis of extracellular or intracellular levels of the target compound (or a few closely related molecules) to drive metabolic engineering is quite common. However, there is surprisingly little systematic use of metabolomics datasets, which simultaneously measure hundreds of metabolites rather than just a few, for that same purpose. Here, we review the most common systematic approaches to integrating metabolite data with metabolic engineering, with emphasis on existing efforts to use whole-metabolome datasets. We then review some of the most common approaches for computational modeling of cell-wide metabolism, including constraint-based models, and discuss current computational approaches that explicitly use metabolomics data. We conclude with discussion of the broader potential of computational approaches that systematically use metabolomics data to drive metabolic engineering.http://www.mdpi.com/2218-1989/2/4/1090metabolomicsmetabolic engineeringmass spectrometrymetabolic fluxmetabolic profilingprincipal components analysispartial least squares regressionflux balance analysisconstraint-based modelskinetic ODE models
collection DOAJ
language English
format Article
sources DOAJ
author Robert A. Dromms
Mark P. Styczynski
spellingShingle Robert A. Dromms
Mark P. Styczynski
Systematic Applications of Metabolomics in Metabolic Engineering
Metabolites
metabolomics
metabolic engineering
mass spectrometry
metabolic flux
metabolic profiling
principal components analysis
partial least squares regression
flux balance analysis
constraint-based models
kinetic ODE models
author_facet Robert A. Dromms
Mark P. Styczynski
author_sort Robert A. Dromms
title Systematic Applications of Metabolomics in Metabolic Engineering
title_short Systematic Applications of Metabolomics in Metabolic Engineering
title_full Systematic Applications of Metabolomics in Metabolic Engineering
title_fullStr Systematic Applications of Metabolomics in Metabolic Engineering
title_full_unstemmed Systematic Applications of Metabolomics in Metabolic Engineering
title_sort systematic applications of metabolomics in metabolic engineering
publisher MDPI AG
series Metabolites
issn 2218-1989
publishDate 2012-12-01
description The goals of metabolic engineering are well-served by the biological information provided by metabolomics: information on how the cell is currently using its biochemical resources is perhaps one of the best ways to inform strategies to engineer a cell to produce a target compound. Using the analysis of extracellular or intracellular levels of the target compound (or a few closely related molecules) to drive metabolic engineering is quite common. However, there is surprisingly little systematic use of metabolomics datasets, which simultaneously measure hundreds of metabolites rather than just a few, for that same purpose. Here, we review the most common systematic approaches to integrating metabolite data with metabolic engineering, with emphasis on existing efforts to use whole-metabolome datasets. We then review some of the most common approaches for computational modeling of cell-wide metabolism, including constraint-based models, and discuss current computational approaches that explicitly use metabolomics data. We conclude with discussion of the broader potential of computational approaches that systematically use metabolomics data to drive metabolic engineering.
topic metabolomics
metabolic engineering
mass spectrometry
metabolic flux
metabolic profiling
principal components analysis
partial least squares regression
flux balance analysis
constraint-based models
kinetic ODE models
url http://www.mdpi.com/2218-1989/2/4/1090
work_keys_str_mv AT robertadromms systematicapplicationsofmetabolomicsinmetabolicengineering
AT markpstyczynski systematicapplicationsofmetabolomicsinmetabolicengineering
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