Model-independent fluxome profiling from (2)H and (13)C experiments for metabolic variant discrimination

We introduce a conceptually novel method for intracellular fluxome profiling from unsupervised statistical analysis of stable isotope labeling. Without a priori knowledge on the metabolic system, we identified characteristic flux fingerprints in 10 Bacillus subtilis mutants from 132 (2)H and (13)C t...

Descripción completa

Detalles Bibliográficos
Autores principales: Zamboni, Nicola, Sauer, Uwe
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2004
Materias:
Method
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC545802/
https://www.ncbi.nlm.nih.gov/pubmed/15575973
http://dx.doi.org/10.1186/gb-2004-5-12-r99
_version_ 1782122218817323008
author Zamboni, Nicola
Sauer, Uwe
author_facet Zamboni, Nicola
Sauer, Uwe
author_sort Zamboni, Nicola
collection PubMed
description We introduce a conceptually novel method for intracellular fluxome profiling from unsupervised statistical analysis of stable isotope labeling. Without a priori knowledge on the metabolic system, we identified characteristic flux fingerprints in 10 Bacillus subtilis mutants from 132 (2)H and (13)C tracer experiments. Beyond variant discrimination, independent component analysis automatically mapped several fingerprints to their metabolic determinants. The approach is flexible and paves the way to large-scale fluxome profiling of any biological system and condition.
format Text
id pubmed-545802
institution National Center for Biotechnology Information
language English
publishDate 2004
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-5458022005-01-27 Model-independent fluxome profiling from (2)H and (13)C experiments for metabolic variant discrimination Zamboni, Nicola Sauer, Uwe Genome Biol Method We introduce a conceptually novel method for intracellular fluxome profiling from unsupervised statistical analysis of stable isotope labeling. Without a priori knowledge on the metabolic system, we identified characteristic flux fingerprints in 10 Bacillus subtilis mutants from 132 (2)H and (13)C tracer experiments. Beyond variant discrimination, independent component analysis automatically mapped several fingerprints to their metabolic determinants. The approach is flexible and paves the way to large-scale fluxome profiling of any biological system and condition. BioMed Central 2004 2004-11-16 /pmc/articles/PMC545802/ /pubmed/15575973 http://dx.doi.org/10.1186/gb-2004-5-12-r99 Text en Copyright © 2004 Zamboni and Sauer; licensee BioMed Central Ltd.
spellingShingle Method
Zamboni, Nicola
Sauer, Uwe
Model-independent fluxome profiling from (2)H and (13)C experiments for metabolic variant discrimination
title Model-independent fluxome profiling from (2)H and (13)C experiments for metabolic variant discrimination
title_full Model-independent fluxome profiling from (2)H and (13)C experiments for metabolic variant discrimination
title_fullStr Model-independent fluxome profiling from (2)H and (13)C experiments for metabolic variant discrimination
title_full_unstemmed Model-independent fluxome profiling from (2)H and (13)C experiments for metabolic variant discrimination
title_short Model-independent fluxome profiling from (2)H and (13)C experiments for metabolic variant discrimination
title_sort model-independent fluxome profiling from (2)h and (13)c experiments for metabolic variant discrimination
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC545802/
https://www.ncbi.nlm.nih.gov/pubmed/15575973
http://dx.doi.org/10.1186/gb-2004-5-12-r99
work_keys_str_mv AT zamboninicola modelindependentfluxomeprofilingfrom2hand13cexperimentsformetabolicvariantdiscrimination
AT saueruwe modelindependentfluxomeprofilingfrom2hand13cexperimentsformetabolicvariantdiscrimination

Ejemplares similares