Contains relative metabolite concentrations for 40 samples based on technical triplicates. Medium and SD values were calculated and used for 1000 sampled simmulations (sampling from the measurement distribution per metabolite) per sample. Also contains annotion to link metabolite concentrations and protein fold change measurements for OE and KO mutants to the model as well as external glucose, acetate and lactate concentrations. A SBtab like format was used to easily load the MEAN and SD metabolite concentration data with metadata for samples and metabolite in a custom simmulation pipeline.
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Created: 7th Jan 2019 at 15:32
Last updated: 14th Jan 2019 at 16:00
Last used: 22nd May 2022 at 20:34

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Version 1 Created 7th Jan 2019 at 15:32 by Niels Zondervan
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Projects: MycoSynVac - Engineering Mycoplasma pneumoniae as a broad-spectrum animal vaccine, WURSynBio
Institutions: Wageningen University & Research

Roles: PhD Student
Expertise: Bioinformatics, Systems Biology, Agent-based modelling, Dynamic modelling, Python, Java, R, pathogen host interaction, Molecular Biology
Tools: Copasi, libRoadrunner, Python, R, semantic web
I 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/
Organisms: Mycoplasma pneumoniae
- 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
Snapshots: Snapshot 1, Snapshot 2, Snapshot 3
Internal metabolites concentrations for time series data (not pulse experiments) and for mutant OE, KO mutants and perturbations External metabolite concentrations for time series data (not pulse experiments) and for mutant OE, KO mutants and perturbations Mutant (OE, KO, perturbation) metabolite measurements
Submitter: Niels Zondervan
Investigation: Modelling of M. pneumoniae metabolism
Assays: 40 samples data analysis - metabolite correlation, All samples data, Metabolomics external metabolites measurements, Metabolomics internal metabolites, time series measurements
Snapshots: No snapshots
Validation of the core model of glycolysis, pyruvate metabolism and ATPase reaction using OE, KO mutant samples and perturbation samples
Submitter: Niels Zondervan
Investigation: Modelling of M. pneumoniae metabolism
Assays: Dynamic model simmulation pipeline, Metabolic control analysis (local and global), Validation by simulating independent mutant and perturbation samples
Snapshots: No snapshots
Validation by simulating independent OE, KO mutant and perturbation samples, using sampling of the gausian distribution based on the mean and SD of measurements per sample. A 1000 samples of the gausian distribution of the mean and SD was performed per sample to show error in the measurements and how it propegates in predicted metabolite concentration in SS
Submitter: Niels Zondervan
Biological problem addressed: Model Analysis Type
Investigation: Modelling of M. pneumoniae metabolism
Study: Core Model predictions
Organisms: No organisms
Models: Dynamic model of glycolysis, pyruvate metabolis...
SOPs: No SOPs
Data files: 40 samples internal metabolite concentrations F..., Comparison of model SS metabolite concentration..., Dynamic modelling pipeline, Internal metabolite concentraitons for mutants,..., Symmetric mean absolute percentage error per sa...
Snapshots: No snapshots
Metabolomics time series measurements for internal metabolites for 6h, 24h and 48h for multiple experiments. Largely based on MAss spectrometry, bioluminescence kits to measure NAD, NADH at 24h, other time points are infered from relative measurements times the absolute measurements at 24h.
Submitter: Niels Zondervan
Assay type: Experimental Assay Type
Technology type: Mass Spectrometry
Investigation: Modelling of M. pneumoniae metabolism
Study: Metabolomics measurements
Organisms: No organisms
SOPs: Metabolomics perturbation samples preparation
Data files: 40 samples internal metabolite concentrations F..., All_samples_mean_meatbolite_concentration&enzym..., Internal metabolite concentraitons for mutants,..., Internal metabolite concentrations time series, Master file, metabolite concentration, protein ..., Metabolites all experiments, relative measurements
Snapshots: No snapshots
Contains the analysis of the internal metabolite concentrations of the 40 independend samples Pearson correlation was used to generate heatmaps Pearson correlation with p-value cutof of 0.001 was used and as input for a correlation network (grouping using H-clust) Principal component analysis was performed on samples, F-ion and H-ion data combined and seperately Zip files contains the data (FC.txt), PCA and heatmap plots and the script to re-generate these plots
Submitter: Niels Zondervan
Biological problem addressed: Model Analysis Type
Investigation: Modelling of M. pneumoniae metabolism
Study: Metabolomics measurements
Organisms: No organisms
Models: No Models
SOPs: No SOPs
Data files: 40 samples internal metabolite concentrations F..., 40 samples metabolite correlation analysis - he...
Snapshots: No snapshots