ArticlePLoS computational biology2012
System-level insights into yeast metabolism by thermodynamic analysis of elementary flux modes.
Article in PLoS computational biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
27 citing papers in PubMed.
- Elementary vectors and autocatalytic sets for resource allocation in next-generation models of cellular growth.PLoS computational biology · 2022Article
- Unlocking Elementary Conversion Modes: ecmtool Unveils All Capabilities of Metabolic Networks.Patterns (New York, N.Y.) · 2021Article
- Physicochemical and metabolic constraints for thermodynamics-based stoichiometric modelling under mesophilic growth conditions.PLoS computational biology · 2021Article
- Dynamic metabolic resource allocation based on the maximum entropy principle.Journal of mathematical biology · 2020Article
- Thermodynamic Limits and Optimality of Microbial Growth.Entropy (Basel, Switzerland) · 2020Review
- Bayesian inference of metabolic kinetics from genome-scale multiomics data.PLoS computational biology · 2019Article
- Spatial-fluxomics provides a subcellular-compartmentalized view of reductive glutamine metabolism in cancer cells.Nature communications · 2019Article
- OptMDFpathway: Identification of metabolic pathways with maximal thermodynamic driving force and its application for analyzing the endogenous CO2 fixation potential of Escherichia coli.PLoS computational biology · 2018Article
- Metabolic enzyme cost explains variable trade-offs between microbial growth rate and yield.PLoS computational biology · 2018Article
- From elementary flux modes to elementary flux vectors: Metabolic pathway analysis with arbitrary linear flux constraints.PLoS computational biology · 2017Review
- Article
- Quantification of Microbial Phenotypes.Metabolites · 2016Review
- Which sets of elementary flux modes form thermodynamically feasible flux distributions?The FEBS journal · 2016Article
- Redirecting metabolic flux in Saccharomyces cerevisiae through regulation of cofactors in UMP production.Journal of industrial microbiology & biotechnology · 2015Article
- Metabolomics integrated elementary flux mode analysis in large metabolic networks.Scientific reports · 2015Article
- Obstructions to Sampling Qualitative Properties.PloS one · 2015Article
- Article
- Elementary Flux Mode Analysis Revealed Cyclization Pathway as a Powerful Way for NADPH Regeneration of Central Carbon Metabolism.PloS one · 2015Article
- Tailoring strain construction strategies for muconic acid production inMetabolic engineering communications · 2014Article
- Environmental systems biology of cold-tolerant phenotype in Saccharomyces species adapted to grow at different temperatures.Molecular ecology · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
One of the most obvious phenotypes of a cell is its metabolic activity, which is defined by the fluxes in the metabolic network. Although experimental methods to determine intracellular fluxes are well established, only a limited number of fluxes can be resolved. Especially in eukaryotes such as yeast, compartmentalization and the existence of many parallel routes render exact flux analysis impossible using current methods. To gain more insight into the metabolic operation of S. cerevisiae we developed a new computational approach where we characterize the flux solution space by determining elementary flux modes (EFMs) that are subsequently classified as thermodynamically feasible or infeasible on the basis of experimental metabolome data. This allows us to provably rule out the contribution of certain EFMs to the in vivo flux distribution. From the 71 million EFMs in a medium size metabolic network of S. cerevisiae, we classified 54% as thermodynamically feasible. By comparing the thermodynamically feasible and infeasible EFMs, we could identify reaction combinations that span the cytosol and mitochondrion and, as a system, cannot operate under the investigated glucose batch conditions. Besides conclusions on single reactions, we found that thermodynamic constraints prevent the import of redox cofactor equivalents into the mitochondrion due to limits on compartmental cofactor concentrations. Our novel approach of incorporating quantitative metabolite concentrations into the analysis of the space of all stoichiometrically feasible flux distributions allows generating new insights into the system-level operation of the intracellular fluxes without making assumptions on metabolic objectives of the cell.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.