Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Haiman2020 - Pyruvate Kinase Regulatory Model of Erythrocyte Glycolysis

ABSTRACT: Dynamic model utilizing mass action kinetics to elucidate network-level effects of allosteric regulation in erythrocyte metabolism. The pyruvate kinase regulatory model includes the glycolytic pathway, the Rapaport Leubering (R.L.) Shunt, hemoglobin-oxygen binding, and elementary reaction steps to represent the enzymatic mechanisms for Pyruvate Kinase (PYK). To demonstrate the sampling and ensemble handling capabilities of MASSpy, an eensemble modeling approach is utilized to assess the dynamics of pyruvate kinase regulation. For the ensemble modeling feature demonstration, a range of parameter sets are generated through Markov-chain Monte Carlo (MCMC) sampling to represent the biological variability across the ensemble of models. Transient dynamic behavior and model steady states are studied through dynamic simulation and analysis. All models associated with the ensemble-modeling example are found in the GitHub repository at (https://github.com/SBRG/MASSpy-publication), including iPython notebooks to construct all model variations presented in the publication.

SUBMITTER: Zack Haiman

PROVIDER: MODEL2012150002 | BioModels | 2024-10-09

REPOSITORIES: BioModels

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	MODEL2012150002?filename=Glycolysis_Hb_PYK.xml	Xml
	MODEL2012150002?filename=all_model_fluxes.csv	Csv
	MODEL2012150002?filename=all_model_init_conds.csv	Csv
	MODEL2012150002?filename=all_model_parameters.csv	Csv

Items per page:

1 - 4 of 4

Similar Datasets

Haiman2020 - Full Kinase Regulatory Model of Erythrocyte Glycolysis

Project description:Dynamic model utilizing mass action kinetics to elucidate network-level effects of allosteric regulation in erythrocyte metabolism. The full kinase regulatory model includes the glycolytic pathway, the Rapaport Leubering (R.L.) Shunt, hemoglobin-oxygen binding, and elementary reaction steps to represent the enzymatic mechanisms for Hexokinase (HEX1), Phosphofructokinase (PFK), and Pyruvate Kinase (PYK). The model and its variations are assembled using the MASSpy software through a module-wise building process outlined in Yurkovich et. al (2018). To validate the MASSpy modeling tool, select results presented in Yurkovich et. al (2018) are reproduced. All models associated with the validation example of the MASSpy publication are additionally hosted at (https://github.com/SBRG/MASSpy-publication), including iPython notebooks to construct all model variations presented in the publication. The MASSpy validation example reproduces models and results from the following publication: Yurkovich JT, Alcantar MA, Haiman ZB, Palsson BO (2018) Network-level allosteric effects are elucidated by detailing how ligand-binding events modulate utilization of catalytic potentials. PLOS Computational Biology 14(8): e1006356. https://doi.org/10.1371/journal.pcbi.1006356

2024-10-09 | MODEL2012150001 | BioModels

Mutations in the Drosophila melanogaster gene pyruvate kinase interfere with larval development

Project description:Pyruvate kinase (Pyk) is a rate-limiting enzyme that catalyzes the final metabolic reaction in glycolysis. The importance of this enzyme, however, extends far beyond ATP production, as Pyk is also known to regulate tissue growth, cell proliferation, and development. Studies of this enzyme in Drosophila melanogaster, however, are complicated by the fact the fly genome encodes six Pyk paralogs and the function of these individual genes remain poorly defined. To address this issue, we used a phylogenetic approach to demonstrate that the gene Pyk encodes the enzyme most similar to the mammalian Pyk orthologs while the other five Drosophila Pyk have significantly diverged from the canonical enzyme. Consistent with this observation, metabolomic studies of two different Pyk mutant backgrounds revealed that larvae lacking Pyk exhibit a severe block in glycolysis, with a buildup of glycolytic intermediates upstream of pyruvate. However, our analysis also unexpectantly reveals that steady state pyruvate levels are unchanged in Pyk mutants, indicating that larval metabolism maintains pyruvate pool size despite severe metabolic limitations. Consistent with our metabolomics findings, a complementary RNAseq analysis revealed that genes involved in lipid metabolism and peptidase activity are elevated in Pyk mutants, again indicating that loss of this glycolytic enzyme induces compensatory changes in other aspects of metabolism. Overall, our study provides both insight towards understanding how Drosophila larval metabolism adapts to disruption of glycolytic metabolism and immediate clinical relevance considering that Pyk deficiency is the most common congenital enzymatic defect in humans.

2023-09-01 | GSE234299 | GEO

Haiman2020 Functional enzyme states in the E.coli glycolytic proteome metabolic model

Project description:Dynamic model utilizing mass action kinetics to compute the functional states of the E.coli glycolytic proteome, providing insight into distribution of catalytic activities of enzymes for different metabolic states. Glycolytic model is derived from the iML1515 E.coli constraint-based reconstruction and contains 17 enzyme modules (12 enzymes plus an additional isozyme for PFK, FBP, FBA, PGM, and PYK). Each enzyme module represents the microscopic steps of the enzymatic mechanism using mass action kinetics and the MASSef package for enzyme fitting (https://github.com/opencobra/MASSef). Two ensembles of 1000 models were parameterized without prior knowledge of enzyme concentrations using E.coli growth data from (DOI:https://doi.org/10.1016/j.cels.2015.09.008). One ensemble representing growth on a glucose carbon source and the other representing growth on a pyruvate carbon source, and the parameterized ensembles were simulated to steady state. The ensembles were used to elucidate thermodynamic shift in the metabolic state, and fractional abundances for individual enzyme states were calculated using the model, providing insight into how catalytic activity is distributed across isozymes. All models associated with the example are found in the GitHub repository at (https://github.com/SBRG/MASSpy-publication/case-study), including iPython notebooks to construct all model variations presented in the publication.

2024-10-09 | MODEL2012150003 | BioModels

Rutkis2013 - Entner-Doudoroff pathway in Z.mobilis

Project description:The model corresponds to the third columns (model simulations) in tables 3 and 5 of publication (PMID: 24085837, DOI: 10.1099/mic.0.071340-0) Mathematical Definition symbol/abbreviation Mathematical symbols Keq Equilibrium constant Ki Inhibition constant Km Affinity constant v Predicted enzyme activities Vf Maximal enzyme activities under saturating substrate and activator conditions, and in the absence of inhibitors h Hill coefficient k Rate constant Abbreviations ACET Acetaldehyde ADH Alcohol dehydrogenase AK Adenylate kinase ATPcons ATP consuming reactions bPG 1,3-bisphosphoglycerate ENO Enolase ETOHcy Cytoplasmic ethanol ETOHex Extracellular ethanol ETOHexp Ethanol transport GAP Glyceraldehyde 3-phosphate GAPD Glyceraldehyde 3-phosphate dehydrogenase GF Glucose facilitator GK Glucokinase GLUCcy Cytoplasmic glucose GLUCex Extracellular glucose GLUC6P Glucose 6-phosphate GPD Glucose 6-phosphate dehydrogenase KDPG 2-keto-3-deoxy-6-phosphogluconate KDPGA 2-keto-3-deoxy-6-phosphogluconate aldolase PDC Pyruvate decarboxylase PEP Phosphoenolpyruvate PGD 6-phosphogluconate dehydratase PGK 3-phosphoglycerate kinase PGL 6-phosphogluconolactonase PGLACTON 6-phosphogluconolactone PGLUCONATE 6-phosphogluconate PGM Phosphoglycerate mutase P3G 3-phosphoglycerate P2G 2-phosphoglycerate PYK Pyruvate kinase PYR Pyruvate

2014-09-15 | MODEL1409050000 | BioModels

Rutkis2013 - Entner-Doudoroff pathway in Z.mobilis (cell-free)

Project description:The model corresponds to the Table 4 and the last column of table 5 of publication (PMID: 24085837, DOI: 10.1099/mic.0.071340-0). Mathematical Definition symbol/abbreviation Mathematical symbols Keq Equilibrium constant Ki Inhibition constant Km Affinity constant v Predicted enzyme activities Vf Maximal enzyme activities under saturating substrate and activator conditions, and in the absence of inhibitors h Hill coefficient k Rate constant Abbreviations ACET Acetaldehyde ADH Alcohol dehydrogenase AK Adenylate kinase ATPcons ATP consuming reactions bPG 1,3-bisphosphoglycerate ENO Enolase ETOHcy Cytoplasmic ethanol ETOHex Extracellular ethanol ETOHexp Ethanol transport GAP Glyceraldehyde 3-phosphate GAPD Glyceraldehyde 3-phosphate dehydrogenase GF Glucose facilitator GK Glucokinase GLUCcy Cytoplasmic glucose GLUCex Extracellular glucose GLUC6P Glucose 6-phosphate GPD Glucose 6-phosphate dehydrogenase KDPG 2-keto-3-deoxy-6-phosphogluconate KDPGA 2-keto-3-deoxy-6-phosphogluconate aldolase PDC Pyruvate decarboxylase PEP Phosphoenolpyruvate PGD 6-phosphogluconate dehydratase PGK 3-phosphoglycerate kinase PGL 6-phosphogluconolactonase PGLACTON 6-phosphogluconolactone PGLUCONATE 6-phosphogluconate PGM Phosphoglycerate mutase P3G 3-phosphoglycerate P2G 2-phosphoglycerate PYK Pyruvate kinase PYR Pyruvate

2014-09-15 | MODEL1409050001 | BioModels

Metabolism of host-derived glycolytic products by Mycobacterium tuberculosis requires five metabolic pathways

Project description:Bacterial nutrition is a key aspect of host-pathogen interaction and bacteria must adapt to use nutrients available in the host. Lipid droplets-derived fatty acids are considered the major intracellular carbon source for Mycobacterium tuberculosis (Mtb), an intracellular pathogen causing Tuberculosis disease. However, many other (and more soluble) substrates are available in vivo and may represent alternative carbon sources. Lactate and pyruvate are rather abundant in human cells and fluids and represent two possible candidates. In this work, we employed a “multi-omics” approach (Transposon Directed Insertion Site Sequencing (TraDIS), RNA-seq transcriptomics, proteomics and stable isotopic labelling coupled with mass spectrometry-based metabolomics) and classic microbial physiology to study Mtb metabolism of lactate and pyruvate. We discovered that Mtb is well adapted to use lactate and pyruvate as sole carbon sources and that it requires gluconeogenesis, Krebs cycle, GABA shunt, glyoxylate shunt and methylcitrate cycle for their metabolism. These latter are traditionally associated with fatty acid metabolism and unexpectedly, we found that methylcitrate cycle operates in reverse. This latter discovery changes the role of this pathway making it a direct route for the biosynthesis of propionyl-CoA, the essential precursor for the biosynthesis of odd-chain fatty acids, abundantly present in Mtb cell envelope.

2020-05-26 | PXD010726 | Pride

Project description:arabidopsis pyruvate kinase

| PRJNA1122224 | ENA

Zymomonas ED Pathway

Project description:Mathematical Definition symbol/abbreviation Mathematical symbols Keq Equilibrium constant Ki Inhibition constant Km Affinity constant v Predicted enzyme activities Vf Maximal enzyme activities under saturating substrate and activator conditions, and in the absence of inhibitors h Hill coefficient k Rate constant Abbreviations ACET Acetaldehyde ADH Alcohol dehydrogenase AK Adenylate kinase ATPcons ATP consuming reactions bPG 1,3-bisphosphoglycerate ENO Enolase ETOHcy Cytoplasmic ethanol ETOHex Extracellular ethanol ETOHexp Ethanol transport GAP Glyceraldehyde 3-phosphate GAPD Glyceraldehyde 3-phosphate dehydrogenase GF Glucose facilitator GK Glucokinase GLUCcy Cytoplasmic glucose GLUCex Extracellular glucose GLUC6P Glucose 6-phosphate GPD Glucose 6-phosphate dehydrogenase KDPG 2-keto-3-deoxy-6-phosphogluconate KDPGA 2-keto-3-deoxy-6-phosphogluconate aldolase PDC Pyruvate decarboxylase PEP Phosphoenolpyruvate PGD 6-phosphogluconate dehydratase PGK 3-phosphoglycerate kinase PGL 6-phosphogluconolactonase PGLACTON 6-phosphogluconolactone PGLUCONATE 6-phosphogluconate PGM Phosphoglycerate mutase P3G 3-phosphoglycerate P2G 2-phosphoglycerate PYK Pyruvate kinase PYR Pyruvate

2020-08-06 | MODEL2008060001 | BioModels

Pyknon siRNA transfection compared with empty vector

Project description:We designed siRNAs against pyk-reg-90 and pyk-reg-10 using the Dharmacon algorithm (Dharmacon siDESIGN http://www.dharmacon.com/sidesign/). Each of four highest-ranking siRNA sequences for pyk-reg-90 and pyk-reg-10 respectively was tested in our and pyk-reg-90, we used a pool of different siRNAs that included the two most effective siRNAs. The cellsperformance was assessed at 24-hr intervals until 96 hrs posttransfection by qRT-PCR. For both pyk-reg-10resuspended in 1X siRNA buffer (Dharmacon, LaFayette CO, USA) to a stock concentration of 50 ?M. Theexperiments. These siRNAs were were transfected with the corresponding siRNA pool at the final concentration of 100nM and 200nM by using Lipofectamine 2000 (Invitrogen) according to the manufacturer's protocol for further analysis. As control, we used a pool of non-targetting siRNAs (Dharmacon).

2014-06-01 | E-MTAB-754 | biostudies-arrayexpress

A3G-Vif-CBFB-CRL5 Cross-Linking with DSSO

Project description:Here we use an optimization cross-linking mass spectrometry (XL-MS) pipeline for the structural characterization of a dynamic HIV-host protein complex. Using DSSO-based XL-MS analysis, residue-protein proximity restraints based on functional genetics, and integrative modeling, we define the structure of the HIV-1 Vif protein bound to restriction factor APOBEC3G (A3G), the Cullin-5 E3 ring ligase (CRL5), and the cellular transcription factor Core Binding Factor Beta (CBFβ). Using a XL-MS3 methodology, we identify 132 inter-linked peptides and integrate the data with atomic structures of the subunits and mutagenesis data, and computed an integrative structure model of the heptameric A3G-CRL5-Vif-CBFβ complex. The resulting model ensemble quantifies the dynamic heterogenity of the A3G C-terminal domain, as well as CUL5 flexibility, and defines the interface between Vif and A3G. Our model can be used to rationalize previous structural, mutatagenesis, and functional data not included in modeling. The experimental and computational approach described here is generally applicable to other challenging host-pathogen protein complexes and provides new visualization tools for characterizing cross-linking data.

2021-11-03 | PXD025391 | Pride