Global 13C tracing and metabolic flux analysis of intact human liver tissue ex vivo
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PROVIDER: PRJNA1129474 | ENA |
REPOSITORIES: ENA
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Project description:Liver metabolism is central to human physiology and influences the pathogenesis of common metabolic diseases. Yet, our understanding of human liver metabolism remains incomplete, with much of current knowledge based on animal or cell culture models that do not fully recapitulate human physiology. Here, we performed in-depth measurement of metabolism in intact human liver tissue ex vivo using global 13C tracing, non-targeted mass spectrometry and model-based metabolic flux analysis. Cultured liver tissue exhibited normal anatomical structure and retained canonical liver functions such as glucose production, albumin and VLDL synthesis at near-physiological rates. Isotope tracing with a highly 13C-labeled medium generated 13C enrichment in hundreds of compounds, allowing qualitative assessment of a wide range of metabolic pathways within a single experiment. This confirmed well-known features of liver metabolism, but also revealed unexpected metabolic activities such as de novo creatine synthesis and branched-chain amino acid transamination, where human liver appears to differ from rodent models. Metabolic flux analysis identified glycogenolysis as the main source of glucose production, which could be suppressed by pharmacological inhibition of glycogen phosphorylase. Glucose production ex vivo also correlated with donor plasma glucose, suggesting that cultured liver tissue retains individual metabolic phenotypes. Moreover, liver tissue responded to postprandial levels of nutrients and insulin by suppressing glucose production and increasing nutrient uptake. Isotope tracing ex vivo allows measuring human liver metabolism with great depth and resolution in an experimentally tractable system.
2024-07-08 | GSE271041 | GEO
Project description:Liver metabolism is central to human physiology and influences the pathogenesis of common metabolic diseases. Yet, our understanding of human liver metabolism remains incomplete, with much of current knowledge based on animal or cell culture models that do not fully recapitulate human physiology. Here, we performed in-depth measurement of metabolism in intact human liver tissue ex vivo using global 13C tracing, non-targeted mass spectrometry and model-based metabolic flux analysis. Cultured liver tissue exhibited normal anatomical structure and retained canonical liver functions such as glucose production, albumin and VLDL synthesis at near-physiological rates. Isotope tracing with a highly 13C-labeled medium generated 13C enrichment in hundreds of compounds, allowing qualitative assessment of a wide range of metabolic pathways within a single experiment. This confirmed well-known features of liver metabolism, but also revealed unexpected metabolic activities such as de novo creatine synthesis and branched-chain amino acid transamination, where human liver appears to differ from rodent models. Metabolic flux analysis identified glycogenolysis as the main source of glucose production, which could be suppressed by pharmacological inhibition of glycogen phosphorylase. Glucose production ex vivo also correlated with donor plasma glucose, suggesting that cultured liver tissue retains individual metabolic phenotypes. Moreover, liver tissue responded to postprandial levels of nutrients and insulin by suppressing glucose production and increasing nutrient uptake. Isotope tracing ex vivo allows measuring human liver metabolism with great depth and resolution in an experimentally tractable system.
2024-07-23 | MTBLS10481 | MetaboLights
Project description:Recent advancements in metabolic flux estimations in vivo are limited to preclinical models, primarily due to challenges in tissue sampling, tumor microenvironment heterogeneity, and non-steady state conditions. To address these limitations and enable flux estimation in human patients, we developed two machine learning-based frameworks. First, the digital twin framework integrates first-principles stoichiometric and isotopic simulations with convolutional neural networks to estimate fluxes in patient bulk samples. Second, the 13C-scMFA framework combines patient scRNA-seq data with 13C-isotope tracing, allowing single-cell-level flux quantification. These studies allow quantification of metabolic activity in neoplastic glioma cells, revealing frequently elevated purine synthesis and serine uptake compared to non-malignant cells. Our models also identify metabolic heterogeneity among patients and mice with brain cancer, in turn predicting treatment responses to metabolic inhibitors. Our frameworks advance in vivo metabolic flux analysis, may lead to novel metabolic therapies, and identify biomarkers for metabolism-directed therapies in patients.
2025-11-28 | GSE311151 | GEO
Project description:Recent advancements in metabolic flux estimations in vivo are limited to preclinical models, primarily due to challenges in tissue sampling, tumor microenvironment heterogeneity, and non-steady state conditions. To address these limitations and enable flux estimation in human patients, we developed two machine learning-based frameworks. First, the digital twin framework integrates first-principles stoichiometric and isotopic simulations with convolutional neural networks to estimate fluxes in patient bulk samples. Second, the 13C-scMFA framework combines patient scRNA-seq data with 13C-isotope tracing, allowing single-cell-level flux quantification. These studies allow quantification of metabolic activity in neoplastic glioma cells, revealing frequently elevated purine synthesis and serine uptake compared to non-malignant cells. Our models also identify metabolic heterogeneity among patients and mice with brain cancer, in turn predicting treatment responses to metabolic inhibitors. Our frameworks advance in vivo metabolic flux analysis, may lead to novel metabolic therapies, and identify biomarkers for metabolism-directed therapies in patients.
2025-11-29 | GSE311464 | GEO
Project description:Liver metabolism is central to human physiology and influences the pathogenesis of common metabolic diseases. Yet, our understanding of human liver metabolism remains incomplete, with much of current knowledge based on animal or cell culture models that do not fully recapitulate human physiology. Here, we perform in-depth measurement of metabolism in intact human liver tissue ex vivo using global 13C tracing, non-targeted mass spectrometry and model-based metabolic flux analysis. Isotope tracing allowed qualitative assessment of a wide range of metabolic pathways within a single experiment, confirming well-known features of liver metabolism but also revealing unexpected metabolic activities such as de novo creatine synthesis and branched-chain amino acid transamination, where human liver appears to differ from rodent models. Glucose production ex vivo correlated with donor plasma glucose, suggesting that cultured liver tissue retains individual metabolic phenotypes, and could be suppressed by postprandial levels of nutrients and insulin, and also by pharmacological inhibition of glycogen utilization. Isotope tracing ex vivo allows measuring human liver metabolism with great depth and resolution in an experimentally tractable system.
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Project description:Cross-feeding is fundamental to the diversity and function of microbial communities. However, identification of cross-fed metabolites is often challenging due to the universality of metabolic and biosynthetic intermediates. Here, we use 13C isotope tracing in peptides to elucidate cross-fed metabolites in cocultures of Saccharomyces cerevisiae and Lactococcus lactis. The community was grown on lactose as the main carbon source with either glucose or galactose fraction of the molecule labelled with 13C. Data analysis allowing for the possible mass-shifts yielded hundreds of peptides for which we could assign both species identity and labelling degree. The labelling pattern showed that the yeast utilized galactose and, to a lesser extent, lactic acid shared by L. lactis as carbon sources. While the yeast provided essential amino acids to the bacterium as expected, the data also uncovered a complex pattern of amino acid exchange. The identity of the cross-fed metabolites was further supported by metabolite labelling in the co-culture supernatant, and by diminished fitness of a galactose-negative yeast mutant in the community. Together, our results demonstrate the utility of 13C-based proteomics for uncovering microbial interactions.
2023-02-07 | PXD019952 | Pride
Project description:Patients with chronic kidney disease (CKD) face elevated fracture incidences, but mechanisms underlying CKD-related bone loss remain unclear. Using the adenine-induced chronic kidney injury (AdKI) murine model, we identified that AdKI induces dysregulated glucose metabolism in bones and kidneys via in vivo and ex vivo metabolic tracing. Ex vivo 13C-metabolic tracing of osteocyte-enriched femora revealed accelerated citrate production from [1,2-13C]-glucose and [U-13C]-glutamine in AdKI mice. These metabolic changes were observed together with increased circulating citrate and Slc13a5 overexpression in bones from AdKI mice. Thus, to explore the role of citrate in AdKI, we utilized mice harboring a loss of function mutation in the citrate importer SLC13A5 (Slc13a5R337*/R337*). Mutant mice displayed elevated osteocytic citrate production, elevated circulating citrate, without significantly worsened AdKI-related bone loss. Coincident with this, Slc13a5R337*/R337* mutant mice were significantly protected from loss of kidney function with attenuated AdKI-induced nephrolithiasis. We also confirmed that Slc13a5 is highly expressed in cortical bone compared to the kidney, suggesting the effect of the mutation is mediated by SLC13A5’s function outside the kidney. Altogether, this study finds that accelerated osteocytic citrate production in CKD is associated with protection of kidney function, and modulation of citrate handling may be a site for therapeutic intervention in CKD.
2025-11-24 | GSE310794 | GEO
Project description:By fermenting dietary fiber, the gut microbiota supplies carbon to host epithelial cells in the form of short-chain fatty acids and other metabolic byproducts. To track the transfer of carbon from fiber to host tissues via the microbiota and more clearly define the molecules mediating this transfer, we conducted stable isotope tracing in mice with U-13C-labeled inulin followed by untargeted metabolomics by LC-MS. Additionally, we applied this labeling approach to mice with chemically induced colitis to examine how inflammation impacts carbon transfer from the microbiota to host tissues, which may aid in understanding the development of inflammatory bowel diseases.
2021-07-04 | MSV000087752 | MassIVE
Project description:Primary Mouse hepatocytes were introduced to U-13C glucose or U-13C glutamine for 30 min and then analyzed by GC-MS and LC-MS.
2019-06-03 | MSV000083885 | MassIVE
Project description:Deciphering the mechanisms of regulation of metabolic networks subjected to perturbations, including disease states and drug-induced stress, relies on tracing metabolic fluxes. One of the most informative data to predict metabolic fluxes are 13C based metabolomics, which provide information about how carbons are redistributed along central carbon metabolism. Such data can be integrated using 13C Metabolic Flux Analysis (13C MFA) to provide quantitative metabolic maps of flux distributions. However, 13C MFA might be unable to reduce the solution space towards a unique solution either in large metabolic networks or when small sets of measurements are integrated. Here we present parsimonious 13C MFA (p13CMFA), an approach that runs a secondary optimization in the 13C MFA solution space to identify the solution that minimizes the total reaction flux. Furthermore, flux minimization can be weighted by gene expression measurements allowing seamless integration of gene expression data with 13C data. As proof of concept, we demonstrate how p13CMFA can be used to estimate intracellular flux distributions from 13C measurements and transcriptomics data. We have implemented p13CMFA in Iso2Flux, our in-house developed isotopic steady-state 13C MFA software. The source code is freely available on GitHub (https://github.com/cfoguet/iso2flux/releases/tag/0.7.2).
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