Gene regulation and metabolic flux reorganization in aerobic/anaerobic

switch of E. coli

Chao WANGJuly 19, 2006

E. coli is a prokaryote model organism with relatively complete knowledge on both transcriptional regulation (TR) and metabolism.

In response to external oxygen level, two global regulators, FNR and ArcA, activate or repress a large number of enzymes, which in turn switches on/off certain metabolic pathways.

Based on metabolic flux simulations and the known regulatory network, we investigate the regulatory mechanisms underlying the presumably efficient switch.

The target genes regulated by FNR and ArcA are compared with the metabolic flux pattern generated from the Flux Balance Analysis (FBA) under aerobic, micro-aerobic and anaerobic conditions, and their physiological role examined.

We also compare the theoretical study with the microarray gene expression data to cross-validate the data from different sources, thereby gaining a more complete view of the regulatory processes involved.

Introduction

E. coli can grow with glucose as the sole organic constituent and metabolically it can transform glucose into all of the macromolecular components that make up the cell. E. coli can grow in the anaerobic or aerobic environments.

Fnr, DNA binding activity is found to be associated with the [4Fe-4S]2+ form, not with the [2Fe-2S]2+ species.

ArcB can sense changes in the electron transport chain. Also ArcB responds to metabolites. ArcB undergoes autophosphorylation, and the phosphoryl group is transferred to ArcA

Transcriptional Regulation Network

Metabolic Network from KEGG

The metabolic sub network corresponding to Fnr and/or ArcA. Blue box: enzymes up-regulated by Fnr. Black diamond: enzymes up-regulated by ArcA. Yellow triangle: enzymes up-regulated by both Fnr and ArcA. Red ellipse: compounds.

Expression Data

1 ArcA deletion aerobic

2 ArcA deletion anaerobic

3 FNR deletion aerobic

4 FNR deletion anaerobic

5 ArcA/FNR double deletion aerobic

6 ArcA/FNR double deletion anaerobic

7 Wild type aerobic

8 Wild type anaerobic

Flux Balance Analysis of iJR904 Model

carbon source (e.g. glucose) flux fixed

Freely available compounds Na+, K+, NH4

+, SO4-2, H2O, CO2, H+, P, Fe

aerobic/anaerobic (oxygen)

waste

biomass

S v =0

89 external compounds can sustain model growth. Carbon source is used both as carbon atoms and energy source.

The Simulation from Anaerobiosis to Aerobiosis

We feed the glucose as the carbon source and set the glucose uptake rate with a max of 10.

We set the oxygen uptake rate from 0 to 20, gradually increased by 1, which can simulate the external oxygen level from anaerobiosis to aerobiosis.

Metabolic Flux Patterns

There are totally 334 flux carrying reactions with different frequency. And 260 of these reactions have none zero flux for all the 21 conditions.

In anaerobic and aerobic conditions, 258 reactions increase or reduce their flux rate in the same direction, 50 reactions switch on or off their flux and only 10 reactions change their flux’s direction.

Fnr/ArcA Target Portion in the Simulation Process

Anaerobiosis Aerobiosis

TCA Cycle Metabolic Flux Reorganization Missing information, for example, ‘akg + coa + nad --> co2 + nadh + succoa’, catalyzed by enzyme with EC number ‘1.2.4.2’ , coded by genes sucAB.

Aerobiosis

Anaerobiosis

Linear Superpostion of Biomass Solutions

With the initial onset of anaerobiosis, ArcA is activated, and if this condition persists or becomes more severe, Fnr is activated. We assume both Fnr and ArcA are involved in this adaptation process with respective effect. And this effect will gradually vary with the change of oxygen level. Given the biomass yields in anaerobic and aerobic conditions, we can get a linear superposition solution for the simultaneous optimization of them with the linear proportion.

/lsp optY YOxygen uptake rate

Optimal solution Linear superposition solution

0 0.216255 0.216255 1.000000

1 0.251540 0.257339 0.977464

2 0.286824 0.298144 0.962033

3 0.322109 0.338949 0.950317

4 0.357394 0.379754 0.941119

5 0.392678 0.420557 0.933710

6 0.427963 0.461363 0.927606

7 0.463248 0.500188 0.926147

8 0.498532 0.537513 0.927479

9 0.533817 0.574843 0.928631

10 0.569102 0.612168 0.929649

11 0.604386 0.649498 0.930544

12 0.639671 0.686825 0.931345

13 0.674955 0.724153 0.932062

14 0.710240 0.761480 0.932710

15 0.745525 0.790232 0.943425

16 0.780809 0.816981 0.955725

17 0.816094 0.843727 0.967249

18 0.851379 0.870480 0.978057

19 0.886663 0.897230 0.988223

20 0.921948 0.921948 1.000000

The interruption of TCA cycle in anaerobic condition is due to the silence of reaction ‘akg + coa + nad --> co2 + nadh + succoa’, which should be catalyzed by the enzyme with EC assignment [1.2.4.2].

The corresponding gene to the enzyme [1.2.4.2] is sucA. From Chapter 2 we know this gene is repressed by regulator Fnr in anaerobic condition. We check the gene expression data, in the eight experimental conditions that are described in Chapter 4, to obtain the expression ratio that is [-4.6860 -4.5878 -5.1599 -6.6164 -4.9745 -4.7465 -4.8279 -7.1273] respectively. In wild type condition its expression ratio is the lowest. Such information assume that the gene sucA plays a very key role in the anaerobic/aerobic switch.

Once the TCA cycle is interrupted the flux rate through related reactions will reduce significantly, which can be illustrated in 7.2. Particularly we investigate the reaction ‘atp + coa + succ <==> adp + pi + succoa’, which is the reaction following the interrupted reaction.

The enzyme catalyzing this reaction has the EC assignment [6.2.1.5]. The corresponding genes are sucC and sucD. Both them are repressed by Fnr in anaerobic condition. After deleting the aerobic/anaerobic response factors the expression ratios of these two genes increase significantly more than 50%.

These three reactions, 'fum + mql8 --> mqn8 + succ' (FRD2), '2dmmql8 + fum --> 2dmmq8 + succ' (FRD3) and 'fad + succ --> fadh2 + fum' (SUCD1i), are all catalyzed by the enzyme with assignment [1.3.99.1] whose corresponding genes are sdhABCD and frdABCD. It is very interesting that sdhABCD are repressed by Fnr whereas frdABCD are activated by Fnr.

Obviously enzymes coded by sdhABCD play the role in reaction SUCD1i whose flux is from Succinate to Fumarate, which is reverse to the other two reactions. Such direction should be present in TCA cycle. In anaerobic condition the flux rate of FRD2 is not zero, which indicate that this reaction should be catalyzed by the enzymes coded by gene frdABCD.

Many other reactions’ flux rate change can also be characterized based on our transcriptional regulation and gene expression information. But some reactions can not be interpreted clearly. For example, the reaction 'cit <==> icit' shows some unclear mechanism.

This reaction is catalyzed by the enzymes with assignment [4.2.1.3], which can be coded by genes acnB and acnA. These two genes are both repressed by ArcA. Maybe ArcA only plays its role when the oxygen uptake rate is less than 14.

In aerobic conditions ArcA has no influence on these anaerobic respiratory pathway genes, which can be validated by gene expression date.

In aerobic conditions, oxygen is the main electron acceptor. While in aerobic conditions, electron can be accepted by some metabolites or nitrogen. The reaction ‘(2) h[c] + no3[c] + q8h2[c] --> (2) h[e] + h2o[c] + no2[c] + q8[c]’ is very important in anaerobic conditions, which can discharge the electrons by transforming NO3 into NO2. This reaction is catalyzed by the enzymes with assignment [1.7.99.4], which can be coded by genes narGHJI. Gene narGHJI are anaerobic respiratory pathway genes (Cotter PA and Gunsalus RP, 1992), which are activated by Fnr in anaerobic conditions. But in our iJR904 model, we obtain zero flux rate for this reaction. So from this aspect we should update and consummate our model.