COSMIC

Automated model building using Taverna workflows from KEGG-Database

methods developed during COSMIC

Despite a long history in using C. acetobutylicum, little is known about the regulation of the metabolic shift, the characteristics of key-regulatory elements as well as bottlenecks of the metabolism. Goal of the collaborative project ´COSMIC-2` (Clostridium acetobutylicum Systems Microbiology 2; part of ‘SysMO’) is to increase the knowledge of this clostridial metabolism and its regulatory patterns. The focus will be on the key regulatory and metabolic events that occur during the shift from the
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Clostridia are very ancient bacteria which evolved before the earth had an oxygen atmosphere. To them the air we breathe is a poison. To survive they produce a spore resting stage, resistant to physical and chemical agents.

Some species cause devastating diseases, such as the superbug Clostridium difficile. On the other hand, most are totally harmless, and make a wide range of chemicals useful to man. The best example is Clostridium acetobutylicum which makes butanol. Butanol is an alcohol, which
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Conversion from KEGG Reactome Information to SBTOOLBOX2 format.

Annotation retrieval

Creation of the KEGG based Reactome

We developed a new metabolomics protocol, which involved a comparison of different harvesting techniques, quenching solutions and extraction methods.

Provided with genomic data over different pH values we have the opportunity to study the similarity of gene expression profiles and cluster groups of very simlar gene expression profiles. Via PCA we can furthermore study dynamic similarity and compe genes that are possible co-regulators or anti-regulators in the clostridial metabolism.

Mathematical modelling of the dynamic shift experiments and the effect of pH upon gene regulation.

test test

We developed a new metabolomics protocol, which involved a comparison of different harvesting techniques, quenching solutions and extraction methods. Cell leakage and metabolite recovery was determined by ATP measurements

Measurements of acetone, butanol, acetate, butyrate and ethanol taken during dynamic shift (pH 5.8, 5.5, 5.3, 5.1, 4.9, 4.7, 4.5) and at steady state (pH 5.7, 5.5, 5.3, 5.1, 4.9, 4.7, 4.5).

Investigation of all steady state pH-values between pH 5.7 and 4.5 (pH 5.5, 5.3, 5.1, 4.9, 4.7).

Comparison of the transcriptome at steady state in acidogenesis and at steady state in solventogenesis.

Investigation of the dynamic switch at pH values between 5.8 and 4.5 (pH 5.5, 5.3, 5.1, 4.9, 4.7 and 4.5).

test

Cytoscape based analysis and yED based representation of clostridial Reactomes

Using Taverna for mining and MATLAB for conversion into specific formats (cytoscape, SBTOOLBOX2)

Using PCA, three components, beam size 8.
Clustering via MCL from Biolayout Express 3D

Data is taken from "Genome-Wide Gene Expression Analysis of the Switch between Acidogenesis and Solventogenesis in Continuous Cultures of Clostridium acetobutylicum." Grimmler et al. 2011
DOI: 10.1159/000320973

Steady state study of the effect of altering gene regulation on yields of end-products, focusing on butanol.

Time-dependent simulations of the dynamic switch between acidogenesis and solventogenesis based on the metabolic network and pH-dependent regulation of the enzymes.

call
ConvertStdModel2SBTtest('Conti_Ferm_Std', 'CD_Transcriptomic.csv', 'glucose.csv', 'OD.csv',0)

transcriptome, glucose, biomass data inside

acetic acid pulse 100mM
acetic acid step 50mM, 70mM

- automated integration of transcriptomic and reactome data to differential equations
- structure of the paths is maintained
- continuous fermentation model in standard format for data integration, two component model (cell and fermenter)

call >> Kegg2SBToolbox2('model_map.txt', 'reactions_compounds_final.csv','extracellular.txt','testmodel.txt') for an example

where
model_map is the desired mapping of species,
reaction_compounds_final.csv is the entire network,
extracellular.txt is a manual
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acetic acid addition

step experiment:
50mM, 70mM, 100mM, 120mM

pulse
200mM

pulse acetic acid: 70mM (2x), 80mM,
shift to 4.5,
pulse acetic acid: 70mM

acetic acid addition 70mM

Basic Graph statistics

RCM: Reaction-Compound Mapping, an edge between nodes means reaction contains metabolite
MMM: Metabolite-Metabolite Mapping, an edge between nodes means these metabolites are reaction partners

_comp: entire network after removal of duplicated edges
_del: taken from the entire network the largest connected subgraph after deletion of a set of nodes

betw: betweeness of nodes
clos: closeness of nodes
neigh: neighbours
node_degree: number of edges per node
path: shortest paths
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RCM: Reaction-Compound Mapping, an edge between nodes means reaction contains metabolite
MMM: Metabolite-Metabolite Mapping, an edge between nodes means these metabolites are reaction partners

_comp: entire network after removal of duplicated edges
_del: taken from the entire network the largest connected subgraph after deletion of a set of nodes
_upload: entire network before removal of duplicated edges

X_depthY: subgraphs where X is a chosen central component and Y is the Yth of neighbour to
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Out

Columnwise datamatrix of reactions, gene identifiers, substrates and products. The direction of reactions is not given.

An ODE model of the gene regulation network governing sporulation initiation in Bacillus subtilis to be run in Matlab.

The network incorporates four sporulation-related signals: nutrient supply, DNA damage, the products of the competence genes and the bacterial population size.

Run execute_bacillus_sporulation_initiation.m to simulate the model. This file also contains the signal-related parameters which can be altered to investigate the effect of competing signals.

Some results for this model
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Here, we use hyperbolic tangents to fit experimental data of AB fermentation in C. acetobutylicum in continous culture at steady state for different external pHs. The estimated parameters are used to define acidogenic and solventogenic phase. Furthermore, an transition phase is identified which cannot be assigned to acidogenesis or solventogenesis.

Several plots compare the fits to the experimental data.

This function estimates the parameters of growth functions of the acid-forming and solvent-forming population observed in 'forward'-shift experiments of phosphate-limited continuous cultures of C. acetobutylicum. The parameters are used in the 'Two-Populations'-Model of the pH-induced metabolic shift.

It assumed that the found behaviour of the optical density during these experiments results from a phenotypic switch caused by the changing pH level.

This model assumes a phenotypic switch between an acid- and solvent-forming population caused by the changing pH levels. The two phenotypes differ in their transcriptomic, proteomic, and ,thus, their metabolomic profile. Because the growth rates of these phenotypes depends on the extracellular pH, the initiation of the pH-shift results in a significant decline of the acidogenic population. Simultaneously, the solvent-forming population rises and establishes an new steady state.

The model is build
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The fitted function describes the pH-drop during 'forward'-shift experiments and the increase of the pH during 'reverse'-shift experiments. The estimated parameters are used to compute the changing pH level in the models of the pH.induced metabolic shift in continuous cultures under phosphate limitation of C. acetobutylicum. Furthermore, the parameters can be applied to join different independent experiments into a single data set.

To fit the changing pH level, an exponential function and a
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input: array of investigated quenching temperatures and volumetric flows
output: quenching time and coil length as function of quenching temperature, and quenching time as function of temperature for varying coil lengths

An ODE model representing the metabolic network governing acid and solvent production by Clostridium acetobutylicum, incorporating the effect of pH upon gene regulation and subsequent end-product levels.

The zip file containes 4 models (in SBML), each representing slightly different experimental conditions.

Protocol for transfer of plasmids into Clostridium
acetobutylicum ATCC 824 by electroporation

ClosTron mutants should always be subjected to Southern blot analysis to ensure that only
one intron insertion has occurred.

A protocol to improve conventional, recombination-based gene knock-out methodologies thtough the provision of negative selection markers, pyrE or codA.

Protocol for transfer of plasmids into
Clostridium spp. by conjugation

A refined and streamlined procedure to generate mutant in a wide range of different clostridial species, using group II intron retargeting methodologies.

This presentation reports about the results from an investigation of a ClosTron-mutant lacking CoA-transferase activity. Using our two-population model developed for the wild type of C. acetobutylicum, we analyse the changes in the formation of products caused by that mutation. In particular, we focus on the investigation of the acid re-assimilation after the initiation of the pH shift. Our comparison of experimental data and simulation unravels that an CoA-independent re-assimilation mechanism
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The acetone-butanol-ethanol (ABE) fermentation of Clostridium acetobutylicum attracts new attention because it provides a potential alternative for the synthesis of value added chemicals to petroleum and other fossil reserves. This fermentative metabolic process comprises two distinct metabolic states that differ in their product spectrum. Growing on starch or sugars the predominant fermentation products are acetate and butyrate during acidogenesis (high pH). In contrast, C. acetobutylicum produces
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April, 5th, 2011

July, 8th, 2011

December, 22th, 2011

September, 13th, 2012

Presentation on project progress - meeting Berlin April 5th 2012

Progress Meeting