40 samples, OE mutants of glycolysis and pyruvate metabolism enzymes combined with metabolite levels of all 40 samples
Simulation of OE mutants targetting enzymes in the model, combined with metabolite concentrations and enzyme fold change of from the 40 samples. For each second mutant the enzyme concentrations in case of OE and KO mutants in updated and the metabolite concentrations of the second sample are loaded in the model. Using this approach the model approximately predicts combinatorial effects of OE mutations with other mutations, perturbations and time series concentrations.
SEEK ID: https://fairdomhub.org/assays/523
Modelling Analysis
Projects: MycoSynVac - Engineering Mycoplasma pneumoniae as a broad-spectrum anima...
Investigation: Modelling of M. pneumoniae metabolism
Study: Core model predicting combined mutations and perturbations
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Biological problem addressed: Model Analysis Type
Organisms: No organisms
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Created: 1st May 2017 at 12:21
Last updated: 20th Nov 2019 at 00:19
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https://orcid.org/0000-0001-7049-5334I am a researcher (PhD student) working at Wageningen University & Research as bioinformatician and modeller. I am working as part of the MycoSynVac (http://www.mycosynvac.eu/) project on dynamic modelling of central carbon metabolism in M. pneumoniae, to be extended to full dynamic modelling of metabolism to be implemented in a whole cell model. I am also looking into possibilities to improve standards in model generation using semantic technologies, improving automatic generation, annotation ...
Projects that do not fall under current programmes.
Projects: Manchester Institute for Biotechnology, ICYSB 2015 - International Practical Course in Systems Biology, iRhythmics, INBioPharm, EmPowerPutida, Systo models, MycoSynVac - Engineering Mycoplasma pneumoniae as a broad-spectrum animal vaccine, Multiscale modelling of state transitions in the host-microbiome-brain network, Extremophiles metabolsim, NAD COMPARTMENTATION, Agro-ecological modelling, Bergen(Ziegler lab) project AF-NADase, NAMPT affinity, Stress granules, Modelling COVID-19 epidemics, Bio-crop, ORHIZON, Coastal Data, SASKit: Senescence-Associated Systems diagnostics Kit for cancer and stroke, hybrid sequencing, HOST-PAR, BioCreative VII, Boolean modeling of Parkinson disease map, Orphan cytochrome P450 20a1 CRISPR/Cas9 mutants and neurobehavioral phenotypes in zebrafish, Selective Destruction in Ageing, Viral Metagenomic, Synthetic biology in Synechococcus for bioeconomy applications (SynEco), testproject, SDBV ephemeral data exchanges, Test project, The BeeProject, PHENET, LiceVault, EbN1 Systems Biology
Web page: Not specified
The MycoSynVac project AIMS at using cutting-edge synthetic biology methodologies to engineer Mycoplasma pneumoniae as a universal chassis for vaccination. Designing a universal Mycoplasma chassis that can be deployed as single- or multi-vaccine in a range of animal hosts. Annually, infections caused by Mycoplasma species in poultry, cows, and pigs result in multimillion Euro losses in the USA and Europe. There is no effective vaccination against many Mycoplasmas that infect pets, humans and farm ...
Programme: Independent Projects
Public web page: http://www.mycosynvac.eu/
- To develop a whole-cell dynamic model framework of the metabolism of M. pneumoniae
- To build upon M. pneumoniae models to develop a genome-scale, constraint-based model of M. hyopneumoniae for vaccine optimization
- To deploy the metabolic model(s) to: 1) the rational design and optimization of the vaccine chassis; 2) aid the development of a higher-growth rate chassis; 3) assist the development of a nutrient optimized a serum-free growth medium and; 4) assess, at genome scale, the metabolic ...
Submitter: Niels Zondervan
Studies: Core Model predictions, Core Model training, Core model predicting combined mutations and perturbations, Genome-scale, constraint-based metabolic modeling of M. hyopneumonia, Metabolomics measurements, Proteomics analysis, Transcriptomics of M. pneumoniae at different times of growth
Assays: 40 samples data analysis - metabolite correlation, 40 samples, OE mutants of glycolysis and pyruvate metabolism enzymes com..., All samples data, Comparison of Kcat values from the model and values from literature, Construction and training of the core model, Construction of a Genome Scale Metabolitic model of M. hyopneumoniae, Dynamic model simmulation pipeline, Metabolic control analysis (local and global), Metabolomics external metabolites measurements, Metabolomics internal metabolites, time series measurements, Proteomics assay, Transcriptomics assay of M. pneumoniae at diferent times of growth, Validation by simulating independent mutant and perturbation samples
Predictions made using the core model for combinatorial perturbations to the model simulating combined effects from OE, KO mutants, perturbations and time series concentrations.
Submitter: Niels Zondervan
Investigation: Modelling of M. pneumoniae metabolism
Assays: 40 samples, OE mutants of glycolysis and pyruvate metabolism enzymes com...
Simulation of double mutants and perturbations and time series samples using for Sample 1 only OE mutants of which we update the enzyme concentrations. For each second mutant the enzyme concentrations in case of OE and KO mutants in updated and the metabolite concentrations of the second sample are loaded in the model. Using this approach the model approximately predicts combinatorial effects of OE mutations with other mutations, perturbations and time series concentrations.
Contains a Jupyter notebook file that uses libroadrunner and tellurium to run all simmulations and analysis based on the 40 independent samples. The Readme.txt file contains information on how to recreate the complete modelling environment used for all simmulations and analysis using Anaconda.
Dynamic model of glycolysis, pyruvate metabolism and NoxE. The model is parameterized by selecting the best out of 100 parameter set using Copasi's Genetic algorithm with 1000 itterations and 500 simmulatanious models.
Creator: Niels Zondervan
Submitter: Niels Zondervan
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: Not specified
