ArticleBMC bioinformatics2012
iMS2Flux--a high-throughput processing tool for stable isotope labeled mass spectrometric data used for metabolic flux analysis.
Article in BMC bioinformatics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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20 citing papers in PubMed, 39 citations in OpenAlex.
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- Improved 13C metabolic flux analysis in Escherichia coli metabolism: application of a high-resolution MS (GC-EI-QTOF) for comprehensive assessment of MS/MS fragments.Journal of industrial microbiology & biotechnology · 2023Article
- Investigating metabolic interactions in a microbial co-culture through integrated modelling and experiments.Computational and structural biotechnology journal · 2020Article
- Integration of flux measurements and pharmacological controls to optimize stable isotope-resolved metabolomics workflows and interpretation.Scientific reports · 2019Article
- Elevated temperatures do not trigger a conserved metabolic network response among thermotolerant yeasts.BMC microbiology · 2019Article
- Multi-Omics Analysis of Fatty Alcohol Production in Engineered YeastsFrontiers in genetics · 2019Article
- The Design of FluxML: A Universal Modeling Language forFrontiers in microbiology · 2019Article
- Comparison of Three Xylose Pathways inFrontiers in bioengineering and biotechnology · 2019Article
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- A comprehensive evaluation of constraining amino acid biosynthesis in compartmented models for metabolic flux analysis.Metabolic engineering communications · 2017Article
- Metabolic response ofEngineering in life sciences · 2017Article
- FluxFix: automatic isotopologue normalization for metabolic tracer analysis.BMC bioinformatics · 2016Article
- WUFlux: an open-source platform forBMC bioinformatics · 2016Article
- Genome-scale metabolic model of Rhodococcus jostii RHA1 (iMT1174) to study the accumulation of storage compounds during nitrogen-limited condition.BMC systems biology · 2015Article
- Stable isotope-labeling studies in metabolomics: new insights into structure and dynamics of metabolic networks.Bioanalysis · 2014Review
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6 authors at 3 institutions in 2 countries.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundMetabolic flux analysis has become an established method in systems biology and functional genomics. The most common approach for determining intracellular metabolic fluxes is to utilize mass spectrometry in combination with stable isotope labeling experiments. However, before the mass spectrometric data can be used it has to be corrected for biases caused by naturally occurring stable isotopes, by the analytical technique(s) employed, or by the biological sample itself. Finally the MS data and the labeling information it contains have to be assembled into a data format usable by flux analysis software (of which several dedicated packages exist). Currently the processing of mass spectrometric data is time-consuming and error-prone requiring peak by peak cut-and-paste analysis and manual curation. In order to facilitate high-throughput metabolic flux analysis, the automation of multiple steps in the analytical workflow is necessary.
resultsHere we describe iMS2Flux, software developed to automate, standardize and connect the data flow between mass spectrometric measurements and flux analysis programs. This tool streamlines the transfer of data from extraction via correction tools to ¹³C-Flux software by processing MS data from stable isotope labeling experiments. It allows the correction of large and heterogeneous MS datasets for the presence of naturally occurring stable isotopes, initial biomass and several mass spectrometry effects. Before and after data correction, several checks can be performed to ensure accurate data. The corrected data may be returned in a variety of formats including those used by metabolic flux analysis software such as 13CFLUX, OpenFLUX and 13CFLUX2.
conclusioniMS2Flux is a versatile, easy to use tool for the automated processing of mass spectrometric data containing isotope labeling information. It represents the core framework for a standardized workflow and data processing. Due to its flexibility it facilitates the inclusion of different experimental datasets and thus can contribute to the expansion of flux analysis applications.
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