ArticleNature communications2023
Inferring mitochondrial and cytosolic metabolism by coupling isotope tracing and deconvolution.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 10 citations in OpenAlex.
- Stable Isotope-Resolved Metabolomics in Elucidating Mitochondrial Metabolic Reprogramming and Therapeutic Targets.Biomedical chromatography : BMC · 2026Review
- Article
- Atomic elementary flux modes explain the steady state flow of metabolites in large-scale flux networks.Cell reports methods · 2026Article
- dCas9-metabolic enzyme fusions modulate global and locus-specific gene expression.bioRxiv : the preprint server for biology · 2026Article
- Article
- Dynamic single-cell metabolomics reveals cell-cell interaction between tumor cells and macrophages.Nature communications · 2025Article
- The Switching of the Type of a ROS Signal from Mitochondria: The Role of Respiratory Substrates and Permeability Transition.Antioxidants (Basel, Switzerland) · 2024Article
- The bioenergetic landscape of cancer.Molecular metabolism · 2024Review
- Challenges of Spatially Resolved Metabolism in Cancer Research.Metabolites · 2024Review
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The inability to inspect metabolic activities within distinct subcellular compartments has been a major barrier to our understanding of eukaryotic cell metabolism. Previous work addressed this challenge by analyzing metabolism in isolated organelles, which grossly bias metabolic activity. Here, we describe a method for inferring physiological metabolic fluxes and metabolite concentrations in mitochondria and cytosol based on isotope tracing experiments performed with intact cells. This is made possible by computational deconvolution of metabolite isotopic labeling patterns and concentrations into cytosolic and mitochondrial counterparts, coupled with metabolic and thermodynamic modelling. Our approach lowers the uncertainty regarding compartmentalized fluxes and concentrations by one and three orders of magnitude compared to existing modelling approaches, respectively. We derive a quantitative view of mitochondrial and cytosolic metabolic activities in central carbon metabolism across cultured cell lines without performing cell fractionation, finding major variability in compartmentalized malate-aspartate shuttle fluxes. We expect our approach for inferring metabolism at a subcellular resolution to be instrumental for a variety of studies of metabolic dysfunction in human disease and for bioengineering.
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