Improving genome-scale metabolic model simulations by measuring exchange fluxes during exponential growth phase
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PROVIDER: PRJNA1245327 | ENA |
REPOSITORIES: ENA
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Project description:With the state-of-the-art techniques currently available, measuring all metabolic reactions in a cell remains impossible. Therefore, systems biology approaches such as genome-scale metabolic models (GEMs) should be used to get a holistic view of metabolism. To reduce the solution space in GEM simulations, models are often constrained with exchange fluxes. However, previous literature that used exchange flux constraints violate the steady-state assumption necessary for GEMs, by inferring the flux from a single metabolomic sample. Here, we present the regression during exponential growth phase (REGP) method, which calculates exchange fluxes only during the log phase, thereby assuring measurements are conducted during metabolic steady-state. The REGP method was tested this method using MCF10A breast epithelial cells. We report that exchange fluxes are generally higher using the REGP method, highlighting the importance of measuring exchange fluxes during steady-state. Even changes in flux direction were observed, which indicates a metabolic shift between the lag phase and the exponential growth phase. While models constrained with previously reported exchange fluxes were infeasible or failed to predict the experimental growth rate, the REGP-constrained GEM accurately predicted the correct growth rate. Flux variability analysis revealed that even with constraints on the exchange of metabolites in central carbon metabolism and amino acid metabolism, these pathways still have intermediate variability in reaction flux. The results of this study suggest that future research should use the REGP method to determine exchange fluxes when these are used as constraints for GEMs, this will provide a better understanding of the complex mechanisms involved in metabolism.
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2025-03-18 | PXD053582 | Pride
Project description:Stretched-exponential protein refolding kinetics, first observed decades ago, were attributed to a nonnative ensemble of structures with parallel, non-interconverting folding pathways. However, the structural origin of the large energy barriers preventing interconversion between these folding pathways is unknown. Here, we combine simulations with limited proteolysis (LiP) and cross-linking (XL) mass spectrometry (MS) to study the protein phosphoglycerate kinase (PGK). Simulations recapitulate its stretched-exponential folding kinetics and reveal that misfolded states involving changes of entanglement underlie this behavior: either formation of a nonnative, noncovalent lasso entanglement or failure to form a native entanglement. These misfolded states act as kinetic traps, requiring extensive unfolding to escape, which results in a distribution of free energy barriers and pathway partitioning. Using LiP-MS and XL-MS, we propose heterogeneous structural ensembles consistent with these data that represent the potential long-lived misfolded states PGK populates. This structural and energetic heterogeneity creates a hierarchy of refolding timescales, explaining stretched-exponential kinetics.
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Project description:Targeted protein degradation (TPD) has emerged as a powerful approach for removing (rather than inhibiting) proteins implicated in diseases. A key step in TPD is the formation of an induced proximity complex where a degrader molecule recruits an E3 ligase to the protein of interest (POI), facilitating the transfer of ubiquitin to the POI and initiating the proteasomal degradation process. Here, we address three critical aspects of the TPD process using atomistic simulations: 1) formation of the ternary complex induced by a degrader molecule, 2) conformational heterogeneity of the ternary complex, and 3) degradation efficiency via the full Cullin Ring Ligase (CRL) macromolecular assembly. We combine experimental biophysical data---in this case hydrogen-deuterium exchange mass spectrometry (HDX-MS, which measures the solvent exposure of protein residues)---with molecular dynamics (MD) simulations aided by enhanced sampling techniques to accurately predict ternary complex structures at atomic resolution. We demonstrate improved efficiency, accuracy, and reliability in the ternary structure predictions of the bromodomain of the cancer target SMARCA2 with the E3 ligase VHL mediated by three different degrader molecules. The simulations accurately reproduce X-ray crystal structures -- including a new structure that we determined in this work (PDB ID: 7S4E) -- with root mean square deviations (RMSD) of 1.1 to 1.6 \r{A}. The simulations also reveal a structural ensemble of low-energy conformations of the ternary complex. Snapshots from these simulations are used as seeds for additional simulations, where we perform 7.1 milliseconds of aggregate simulation time using Folding@home. The detailed free energy surface captures the crystal structure conformation within a low-energy basin and is consistent with solution-phase experimental data (HDX-MS and SAXS). Finally, we graft a structural ensemble of the ternary complexes onto the full CRL and perform enhanced sampling simulations, which suggest that differences in degradation efficiency may be related to the proximity distribution of lysine residues on the POI relative to the E2-loaded ubiquitin. Several of the predicted ubiquitinated lysine residues have been validated through a ubiquitin mapping proteomics experiment. DOI 10.1038/s41467-022-33575-4
2022-10-01 | PXD033763 | Pride
Project description:Metabolic fluxes may be regulated "hierarchically," e.g., by changes of gene expression that adjust enzyme capacities (V(max)) and/or "metabolically" by interactions of enzymes with substrates, products, or allosteric effectors. In the present study, a method is developed to dissect the hierarchical regulation into contributions by transcription, translation, protein degradation, and posttranslational modification. The method was applied to the regulation of fluxes through individual glycolytic enzymes when the yeast Saccharomyces cerevisiae was confronted with the absence of oxygen and the presence of benzoic acid depleting its ATP. Metabolic regulation largely contributed to the approximately 10-fold change in flux through the glycolytic enzymes. This contribution varied from 50 to 80%, depending on the glycolytic step and the cultivation condition tested. Within the 50-20% hierarchical regulation of fluxes, transcription played a minor role, whereas regulation of protein synthesis or degradation was the most important. These also contributed to 75-100% of the regulation of protein levels. Keywords: Condition comparison
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Project description:Metabolic fluxes may be regulated "hierarchically," e.g., by changes of gene expression that adjust enzyme capacities (V(max)) and/or "metabolically" by interactions of enzymes with substrates, products, or allosteric effectors. In the present study, a method is developed to dissect the hierarchical regulation into contributions by transcription, translation, protein degradation, and posttranslational modification. The method was applied to the regulation of fluxes through individual glycolytic enzymes when the yeast Saccharomyces cerevisiae was confronted with the absence of oxygen and the presence of benzoic acid depleting its ATP. Metabolic regulation largely contributed to the approximately 10-fold change in flux through the glycolytic enzymes. This contribution varied from 50 to 80%, depending on the glycolytic step and the cultivation condition tested. Within the 50-20% hierarchical regulation of fluxes, transcription played a minor role, whereas regulation of protein synthesis or degradation was the most important. These also contributed to 75-100% of the regulation of protein levels. Experiment Overall Design: To quantify the regulation of the Vmax values and the fluxes at the different levels of gene expression, we measured how the fluxes through the glycolytic enzymes, the Vmax values, and the concentrations of these enzymes and their corresponding mRNA concentrations change when yeast is exposed to aerobic and anaerobic (with and without challenges.
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