SUMO

Cultures grown under standard SUMO conditions were analyzed with respect to heterogeneity in gene expression. To this end GFP reporter strains were constructed and GFP expression at single cell level was monitored by flow cytometry.

The electron transport chain of E. coli is branched. Different NAD Dehydrogenases and terminal oxidases are known to be expressed at different oxygen availabilities. By deleting multiple genes mutant strains were constructed that posses a linear electron transport chain. These mutants were investigated in continous bioreactor experiments with limiting glucose and varying oxygen supply.

A further investigation of the variation of FNR number in E.coli Cyo/Cyd mutants is carrying out at different oxygen supply levels. The agent-based FNR and ArcBA model is going to be used for this prediction. The number of Cyo or Cyd and other unrelated agents would be set as ‘0’ at the initial XML file with which the model starts. According to the restrictions of supercomputer ‘Iceberg’ (serviced provided by the University of Sheffield), certain parameters, such as memory per node, would be
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In Escherichia coli several systems are known to transport glucose into the cytoplasm. A series of mutant strains were constructed, which lack one or more of these uptake systems. These were analyzed in aerobic and anaerobic batch cultures, as well as glucose limited continuous cultivations.

Transcriptional and physiological responses of anaerobic steady state cultures to pulses of electron acceptors, specifically nitrate, trimethylamine-N-oxide (TMAO)

Changing the oxygen availability leads to an adaptation of Escherichia coli at different biological levels. After pertubation of oxygen in chemostat experiments the microorganism(s) will come back to another steady state. This investigation deals with these stationary responses of Escherichia coli within the aerobiosis scale. The change for different biological variables, in different areas of the organism like the electron transport chain, the TCA cycle or globally is investigated by wildtype
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Changing the oxygen availability leads to an adaptation of Escherichia coli at different biological levels. After pertubation of oxygen in chemostat experiments there are very quick responses. This investigation deals with this dynamical behaviour (transitions) of Escherichia coli within the aerobiosis scale. The change for different biological variables, in different areas of the organism like the electron transport chain, the TCA cycle or globally is investigated by wildtype and mutants experiments
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A set of isogenic mutant strains was constructed which lack NADH Dehydrogenase I as well as two terminal oxidases, resulting in strains with linear respiratory chain. The different strains hence differ in the terminal oxidase and express either cytochrome bo, cytochrome bdI or cytochrome bdII.
The different strains were cultivated in glucose-limited chemostats with defined low levels of oxygen supply. Biomass and by-product formation, gene expression and the phosphorylation state of the important
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Mutant strains in which one or more of the potential glucose uptake systems was deleted have been analyzed in aerobic and anaerobic batch cultures, as well as aerobic chemostat cultures.

Goals:
1. Understanding the regulatory principles of Escherichia coli’s electron transport chain (ETC) for varying oxygen conditions in glucose-limited continuous cultures (especially regulatory loops via the transcription factors FNR and ArcA).
2. Explaining the observed phenomena in the measurement data.
3. Predicting unmeasured variables especially of the gene expression regulatory loops.

Means:
1. Experiments (chemostat experiments within the aerobiosis scale).
2. Kinetic modelling (especially
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Mutant strains which carry deletions of important metabolic enzymes, as well as mutant strains with altered regulation, need to adapt by changing fluxes or gene expression to compensate with the absence/differed concentration of these key enzymes. This may give new insights in the regulation of these pathways/enzymes.

Mutants with a linear respiratory chain consisting of NADH Dehydrogenase II and one of the terminal oxidases cytochrom bo, cytochrome bd I or cytochrome bd II were growth in chemostats with defined oxygen supply. The amounts of biomass formed and of acetate and formate produced were determined.

Mutant strains with linear electron transport chain were grown in chemostat cultures at different defined aerobiosis levels. Expression of selected genes was determined by Real Time RT-PCR

Mutants with linear respiratory chains were grown under SUMO chemostat conditions at different defined aerobiosis levels. The ArcA phoshorylation state as determined.

ArcA phosphorylation in chemostat cultures grown at different aerobiosis levels was quantitated by Phos-tag SDS-PAGE gel analysis and subsequent immunodetection of ArcA.

E. coli MG1655 and ∆sdhC and ∆frdA isogenic mutant strains were characterized in batch growth curves aerobic and anaerobically. Optical density, glucose consumption and by-product accumulation were measured during growth.

Glucose transporter mutants were analyzed under aerobic and aerobic conditions in batch cultures with glucose as substrate. Acetate formation rates and glucose consumption rates were measured, as well as extracellular cAMP concentrations.

Mutant strains which lack one or more of the glucose transport systems were analyzed in aerobic chemostat cultures and compared to batch cultures.

MG1655 and mutant strains with defects in glucose transport systems were analyzed in aerobic and anaerobic batch cultures.

This experiment uses a low-copy plasmid based system (MG1655 Δlac FF(-41.5)/RW50) for measuring FNR activity. Initial acetate calibration of the chemostat with the MG1655 Δlac strain was carried out, with β-galactosidase activity from the FF(-41.5)/RW50 reporter plasmid measured at 100%, 80%, 50%, 20% and 0% aerobiosis levels. Finally, the aerobiosis levels were re-determined by calculating the actual acetate flux in the sampled chemostat runs.

Note: the strain used (MG1655 Δlac) is not the same
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The file contains simulated data of the electron transport chain model (EcoliETC1) for varying parameter values, i.e. a local sensitivity analysis.

This data file shows results from the different chemostat experiments.Gene expression rates are presented.

Mutants with defects in glucose transport systems were analyzed in a bioreactor and the transcription of certain uptake systems analyzed. Transcription profiles between batch and chemostat conditions were compared

by-product formation rates and glucose uptake rates of mutants with linear electron transport chain at different aerobiosis levels

The ArcA phosphorylation state was determined for mutants with linear respiratory chain at defined aerobiosis levels.

Gene expression levels in mutants with linear ETC were determined by RealTime RT-PCR

This document shows the ArcA phosphorylation levels at different aerobiosis units, measured using Phos-tag gels, western immunoblotting. Exposed films were quantitated using ImageJ and the results shown here.

The data that was published in Alexeeva et al. [1-3] and Alexeeva [4] is an important prerequisite for SUMO. It is used for the development of the models and for the comparison with the SUMO data.
By means of the program EasyNPlot [5] the data in the important plots of [1-3] and of the plot of the ArcA activity in [4] was digitalized. The result can be found in the attached files.

[1] Svetlana Alexeeva, Bart de Kort, Gary Sawers, Klaas J. Hellingwerf, and M. Joost Teixeira de Mattos. Effects of
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The model describes the catabolism of Escherichia coli and its regulation. The metabolic reactions are modeled by the thermokinetic model formalism. The model is simplified by assuming rapid equilibrium of many reactions. Regulation is modeled by phenomenological laws describing the activation or repression of enzymes and genes in dependence of metabolic signals. The model is intended to describe the behavior of E. coli in a chemostat culture in depedence on the oxygen supply.

The model is described
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This ordinary-differential equation model is a spatially lumped model showing the behaviour of oxygen in the three compartments medium, membrane and cytoplasm and its impact on FNR inactivation, hereby showing the effects of different oxygen concentrations, diffusion coefficients and reaction rates. The model was created with the Matlab SimBiology toolbox.

This partial-differential equations model focuses on the oxygen gradients in consideration of the three-dimensional cell and environment.

Code for joint probabilistic inference of transcription factor behaviour and gene-transcription factor as well as metabolite-transcription factor interaction based on genome and metabolite data.

The model presents the response of E.coli to different levels of oxygen supply, in which the oxidases, Cyo and Cyd, and their regulators, FNR and ArcBA systems, are included. The initial file 0.xml and supporting documents are for the model with FNR only. Four 0.xml files provided are at AAU level 31, 85, 115 and 217 respectively. The ArcBA system can be activated by revising the number of agents, ArcB, ArcA dimer, ArcA monomer, ArcA tetramer and ArcA octamer, in the initial file. The model needs
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Bayesian model for inference of the activity of transcription factors from targets' mRNA levels. A standalone C sharp package (runs on linux and mac under MONO).

The model describes the electron transport chain (ETC) of Escherichia coli by ordinary differential equations. Also a simplified growth model based on an abstract reducing potential describing the balance of electron donor (glucose) and electron acceptors is coupled to the ETC. The model should reproduce and predict the regulation of the described system for different oxygen availability within the aerobiosis scale (glucose limited continuous culture<=>chemostat). Therefore oxygen is changed
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Simplified model of the electron-transport chain(s) (ETC) of Escherichia coli and its regulation by ArcA and FNR. The goal is to demonstrate a hypothetical design principle in the regulatory structure (->partly qualitative parameter values). Oxygen is changed slowly (100% aerobiosis at 1000000 time units) thus the basis variable is not the time but the oxygen flux voxi.

The agent-based model involves the representation of each individual molecule of interest as an autonomous agent that exists within the cellular environment and interacts with other molecules according to the biochemical situation. FLAME environmet has beem used for agent-based development. The FLAME framework is an enabling tool to create agent-based models that can be run on high performance computers (HPCs). Models are created based upon extended finite state machines that include message input
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This assay uses a dual-wavelength spectrophotometer to quantify cytochromes present in the E. coli respiratory chain.

This is a well-established, classical genetic method of constructing chromosomal monolysogenic fusions to a promoterless lacZ gene.

The phosphorylation level of a particular protein can be determined using a procedure based upon western immunoblotting, with Phos-tag™ reagent present in the SDS-PAGE gel. The Phos-tag™ reagent, supplied in the form of Phos-tag™ acrylamide (Wako Pure Chemical Industries, AAL-107), causes proteins to be resolved both on the basis of size and phosphorylation state. This means that phosphorylated and de-phosphorylated forms of the same protein can be distinguished.

The Gene-doctoring method of lambda-red deletion (Lee et al., 2009) was modified slightly to create chromosomal mutations of fnr.

This method describes how one can quench metabolism of Escherichia coli and extract metabolites from many kinds of metabolite classes like: nucleotides, sugar-phosphates, organic acids ....

This protocol describes the transcriptional profiling of E. coli cultures using microarrays. The protocol utilises RNA isolated as described in another SOP (SUMO RNA isolation from E. coli) and with hybridisation to Ocimum Ocichip E. coli K-12 microarrays.

This SOP describes the preparation of E. coli RNA

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Presentation by Michael Ederer and Klaas Hellingwerf at the SysMO Conference 2013 (Feb 2013, Berlin)

Presentation by Robert Pool at the SysMO Conference (Feb 2013 in Berlin)

Summary
1.1 modifying TFinfer to model the TFs using ON/OFF switches (fast response model),
1.2 trying to infer metabolites effect using a joint gene-tf-metabolite model,
2 analysing aerbiosis data using a similar model,
3 clustering genes for extending the EC network to obtain better fits to the data (feedback loop).