Archives of Microbiology

, 190:559

Effect of cra gene knockout together with edd and iclR genes knockout on the metabolism in Escherichia coli

  • Dayanidhi Sarkar
  • Khandaker Al Zaid Siddiquee
  • Marcos J. Araúzo-Bravo
  • Takahiro Oba
  • Kazuyuki Shimizu
Original Paper

DOI: 10.1007/s00203-008-0406-2

Cite this article as:
Sarkar, D., Siddiquee, K.A.Z., Araúzo-Bravo, M.J. et al. Arch Microbiol (2008) 190: 559. doi:10.1007/s00203-008-0406-2

Abstract

To elucidate the physiological adaptation of Escherichia coli due to cra gene knockout, a total of 3,911 gene expressions were investigated by DNA microarray for continuous culture. About 50 genes were differentially regulated for the cra mutant. TCA cycle and glyoxylate shunt were down-regulated, while pentose phosphate (PP) pathway and Entner Doudoroff (ED) pathway were up-regulated in the cra mutant. The glucose uptake rate and the acetate production rate were increased with less acetate consumption for the cra mutant. To identify the genes controlled by Cra protein, the Cra recognition weight matrix from foot-printing data was developed and used to scan the whole genome. Several new Cra-binding sites were found, and some of the result was consistent with the DNA microarray data. The ED pathway was active in the cra mutant; we constructed cra.edd double genes knockout mutant to block this pathway, where the acetate overflowed due to the down-regulation of aceA,B and icd gene expressions. Then we further constructed cra.edd.iclR triple genes knockout mutant to direct the carbon flow through the glyoxylate pathway. The cra.edd.iclR mutant showed the least acetate production, resulting in the highest cell yield together with the activation of the glycolysis pathway, but the glucose consumption rate could not be improved.

Keywords

Escherichia coli cra mutant cra.edd mutant cra.edd.iclR mutant DNA microarray 

Introduction

The central metabolic pathways of Escherichia coli are controlled by a number of global regulators depending on the carbon sources available and the culture condition. Among them, the catabolite repressor/activator protein (Cra) initially characterized as the fructose repressor, FruR plays an important role in the control of carbon flow in E. coli (Moat et al. 2002; Saier and Ramseier 1996; Saier et al. 1997). The genes such as ptsHI, pfkA, pykF, acnB, edd–eda, fruBKA, mtlADR, gapB are reported to be negatively controlled, while ppsA, fbp, pckA, acnA, icd, aceA, aceB, and cydA,B are positively controlled by the Cra protein (Saier and Ramseier 1996; Cunningham et al. 1997; Moat et al. 2002; Perrenoud and Sauer 2005). It has been known that the mutant defective in cra gene is unable to grow on the gluconeogenic substrates such as pryruvate, acetate, and lactate. This phenomenon appears to be due to the deficiency in the gluconeogenic enzymes such as PEP synthase, PEP carboxykinase, some TCA cycle enzymes, the two glyoxylate shunt enzymes, and certain electron transport carrier (Saier et al. 1997). The gluconeogenic pathway will be deactivated by cra gene knockout as such, and the carbon flow toward catabolism or the glucose consumption rate may increase, since the glycolysis pathway genes such as ptsHI, pfkA, and pykF are derepressed. However, the regulation mechanism is complex and the story is not so simple. The details of such complex regulation network have not yet been fully investigated for the cra mutant (Saier et al. 1997). Some studies on the cra mutant have been performed based on the molecular level approaches using the lacZ-transcriptional fusion, flux analysis, etc. (Ryu et al. 1995; Mikulskis et al. 1997; Prost et al. 1999; Ramseier et al. 1996; Cortay et al. 1994; Perrenoud and Sauer 2005; Phue et al. 2005).

In the present research, we investigated the effect of cra gene knockout on the metabolism in E. coli based on gene expressions obtained by DNA microarray together with some of the enzyme activities. Moreover, based on the metabolic analysis of cra gene knockout mutant, we constructed cra.edd double genes knockout mutant and cra.edd.iclR triple genes knockout mutant, and analyzed the phenotypes of those mutants as compared with the wild type in relation to the activation of the glycolysis, thus improving the glucose consumption rate.

Materials and methods

Strains and cultivation conditions

The strains used are the wild-type E. coli BW25113 (lacIq rrnBT14 ΔlacZWJ16hsdR514 ΔaraBADAH33 ΔrhaBADLD78) and its cra gene knockout mutant JWK0078. The cra gene knockout mutant was constructed previously by Baba et al. (2006) by deletion of the corresponding cra gene from E. coli BW25113 using the method of Datsenko and Wanner (2001). The cra.edd double genes knockout mutant and cra.edd.iclR triple genes knockout mutant were also constructed in the present study based on the method of Datsenko and Wanner (2001) (Table 1).
Table 1

Bacterial strains and plasmids

Strain or plasmid

Relevant characteristics

Source

Strains

 BW25113

lacIq rrnBT14ΔlacZWJ16hsdR514

ΔaraBADAH33 ΔrhaBADLD78

Keio University

 cra mutant

Δcra::kan

Keio University

 cra mutant (for competent cell)

Δcra::cm

Keio University

 cra.edd double mutant (cassette free)

Δcra.edd

This study

 cra.edd.iclR triple mutant

Δcra.edd.iclR::kan

This study

Plasmids

 PKD3

Ampicillin(amp)r and chloramphenicol(cm)r

Yale University

 PKD4

kanamycin(kan)r and ampr

Yale University

 PKD13

ampr and kanr

Yale University

 PKD46

ampr, helper plasmid

Keio University

 PCP20

ampr and cmr

Keio University

The M9 minimal medium was used for all the experiments as described before (Siddiquee et al. 2004a, b). The cultivation was made at 37°C in a 20-l reactor (M-100, Tokyo, Rikakiki Co., Tokyo, Japan) with the working volume of 1 l equipped with pH, dissolved oxygen (DO) and temperature sensors. The air flow was maintained at 1 l/min, and the DO concentration was kept around 30–40% of air saturation. The pH of the culture was maintained at 7.0 by automatic addition of 2.0 M HCl or 2.0 M NaOH with a pH controller. Continuous cultivation was conducted with the working volume of 500 ml in a 1-l reactor at the dilution rate of 0.2 and 0.6 h−1, where the feed glucose concentrations were either 4 or 10 g/l. The working volume was kept constant by removal of effluent by use of precalibrated peristaltic pumps.

Analytical procedures

Cell concentration was measured by the optical density (OD) of the culture with a spectrophotometer (Ubet-30, Jasco Co., Tokyo, Japan), and then converted to dry cell weight (DCW) per liter based on the relationship between OD and DCW. Glucose concentration was measured using enzymatic kit (Wako Co., Osaka, Japan). The concentrations of the metabolites such as acetic acid were measured using enzymatic kits (Boehringer Co., Mannhiem, Germany). Oxygen and carbon dioxide concentrations in the bioreactor off gas were measured by the off-gas analyzer (LX-750, Iijima Electronics Co., Japan).

The preparation of crude cell extract and the analyses of enzyme activities involved in the main metabolic pathways such as phosphoglucosetransferase system (PTS), phosphofructo kinase (Pfk), pyruvate kinase (Pyk), glucose-6-phosphate dehydrogenase (G6PDH), 6-phosphogluconate dehydrogenase (6PGDH), acetate kinase (Ack), citrate synthase (CS), aconitase (Acn), isocitrate dehydrogenase (ICDH), isocitrate lyase (Icl), malate synthase (MS), malic enzyme (Mez), phosphoenol pyruvate carboxylase (Ppc), phosphoenol pyruvate carboxykinase (Pck), and ED pathway enzymes were made as described previously, where specific ED pathway activity was determined from the combined Edd and Eda reactions (Peng and Shimizu 2003). Each measurement was performed in triplicate from three samples of the same culture.

RNA isolation and semi-quantitative RT-PCR

Total RNA was isolated from E. coli cells by Qiagen RNeasy Mini Kit (QIAGEN K.K., Japan) according to their protocol. The quantity and purity of RNA were determined by measuring the optical density at 260 and 280 nm and by 1% formaldehyde agarose-gel electrophoresis. Criteria for the design of the gene-specific primer pairs were followed according to Sambrook and Russel (2001). The primers used in the present study were synthesized at Hokkaido System Science Co. (Sapporo, Hokkaido, Japan), where the primers used for the gene expressions by RT-PCR are described elsewhere (Kabir and Shimizu 2003).

RT-PCR reactions were carried out in a Takara PCR Thermal Cycler (Takara TP240, Japan) using a Qiagen one-step RT-PCR kit (Qiagen K.K., Japan) as described previously (Kabir and Shimizu 2003). We determined the optimal amount of input RNA using twofold dilution of RNA for RT-PCR assays under identical reaction condition to construct a standard curve for each gene product. After the optimal amount of input RNA was determined for each gene product, RT-PCR was carried out under identical reaction condition to detect differential transcript levels of genes. The gene dnaA, which is expressed at relatively constant rate (Kabir and Shimizu 2003), was used as internal control. To calculate the standard deviation, RT-PCR was independently performed three times for each gene under identical condition.

DNA microarray

The isolation of RNA for the DNA microarray was similar to RT-PCR as mentioned above. Instead of mini kit, the Qiagen Maxi kit and 10 ml of bacterial cultures were used. The DNA microarray experiment needs high purity of RNA. Therefore, after isolation, the RNA was treated with the DNaseI from Qiagen using a protocol of Gross laboratory of University of California, San Francisco (http://www.microarrays.org/pdfs/Total_RNA_from_Ecoli.pd), that was modified in our laboratory (Rahman et al. 2006). The original RNA sample was diluted 100-fold with 10 mM TAE buffer (pH 7.5), and the sample with the absorbance at 260 and 280 nm was taken to determine the concentration of RNA and protein in the sample.

Takara IntelliGene E. coli chips Version 2 and Takara labeling kit were used for this study, and the Cy3-dUTP and Cy5-dUTP dyes were supplied from Amersham Bioscience Co. The labeled cDNA probes were prepared according to Takara protocol, where 300 pmol/μl of random hexamer, 10 μg of total RNA, 5× reaction buffer, 10× dNTP mixture for Cy3/Cy5, 1 μl of Cy3/Cy5-dUTP, RNase inhibitor (40 U/μl), and M-MLV reverse transcriptase (2,000 U/μl) were added. Before starting the cyber-labeling experiment, 1 μl (1 ng/μl) of human TFR RNA was added to the reaction mixture as a negative control. Then the labeled cDNA probes were purified by the columns supplied from Takara Co., and after that further purified by phenol and ethanol precipitation. After drying the precipitates, these were dissolved in a 25 μl of hybridization buffer containing 6× SSC, 0.2% SDS, 5× Denhardt’s solution, 0.1 mg/ml denatured salmon sperm DNA. The intensity of the Cy3 and Cy5 labeling cDNA were checked by scanning the gel at 532 and 635 nm in fluorescent image analyzer (FLA-8000, Fuji Photo Film Co.). The preparation for the set-up of the chamber and hybridization was performed as described by Takara protocol. After hybridization and washing, the slides were dried by low-speed centrifugation at 500×g for 2 min. The fluorescent signal of each spot was read with a DNA microarray scanner (Fluorescent image analyzer, FLA-8000, Fuji photo film Co.) at 532 and 635 nm. After scanning of the image data, it was analyzed by microarray software Array vision version 6.0 (Amersham Bioscience Co.).

DNA microarrays were duplicated for each hybridization. The signal intensity of each gene was first corrected by subtracting the local background value. Then, gene expressions were compared with the intensity of the negative control spots. The gene expressions for which both Cy3 and Cy5 signal intensities were greater than the mean + 1 standard deviation (SD) of the negative control were used. Expression differences (ratios of the fluorescence intensities of Cy3 and Cy5) of genes were then normalized by defining the mean of ratios of all genes as 1.0. Significant change was then recognized if one of the following criteria were satisfied:
  1. 1.

    For genes whose expression ratios are reproducible and the values are >2.0 or <0.5 (>1 or <−1 in log2 representation).

     
  2. 2.

    In good consistency (p < 0.05) under Student’s t test.

     

Results

Fermentation characteristics of cra gene knockout mutant

Figure 1 shows the aerobic batch cultivation result for the wild type and its cra gene knockout mutant, where acetate tended to be less consumed at the late growth phase in the case of cra mutant as compared with the parent strain.
Fig. 1

Batch cultivation of aE. coli BW25113 and b its cra mutant: open square glucose concentration, filled square biomass concentration, open triangle acetate concentration

The glucose limited continuous cultures were also conducted for both parent and cra gene knockout mutant strains at the dilution rate of 0.2 h−1, where the cell growth parameters are summarized in Table 2. The result shows the increases in the specific glucose uptake rate and the acetate production rate for the mutant as compared to the parent strain. Table 2 also shows that the cell yield for the mutant is reduced as compared to the parent strain.
Table 2

Growth parameters for E. coli BW25113 and its cra mutant cultivated at the dilution rate of 0.2 h−1 where feed glucose concentration was 4 g/l

Growth parameters

BW25113

cra Mutant

Biomass yield (g/g)

0.44 ± 0.01

0.30 ± 0.02

Glucose uptake rate [mmol/(g h)]

2.54 ± 0.11

3.61 ± 0.03

Acetate production rate [mmol/(g h)]

0.02 ± 0.01

0.84 ± 0.02

O2 uptake rate [mmol/(g h)]

10.24 ± 0.52

8.88 ± 0.63

CO2 evolution rate [mmol/(g h)]

8.51 ± 0.35

8.57 ± 0.8

Gene expressions by DNA microarray

A total of 3,911 ORF signals were obtained for the samples taken from the continuous culture for the cra gene knockout mutant and the parent strains after the subtraction of the background signals. After the treatment of the data as mentioned in “Materials and methods”, about 50 genes were found to be differentially expressed (Table 3). Those genes were categorized depending on different metabolic functions.
Table 3

Gene expressions of cra mutant as compared with the wild type strain

Gene

Logarithmic ratio, Log2 (cra/parent strain)

Description

(a) Carbon and energy related genes

 aceA

−1.43

Isocitrate lyase (EC 4.1.3.1)

 aceK

−0.30

Isocitrate dehydrogenase kinase/phosphatase (EC 2.7.1.116) (EC 3.1.3.-)

 adhE

1.39

Alcohol dehydrogenase (EC 1.1.1.1)

 cydB

−1.09

Cytochrome d ubiquinol oxidase subunit II (EC 1.10.3.-)

 cydA

−1.12

Cytochrome d ubiquinol oxidase subunit I (EC 1.10.3.-)

 fbp

−0.81

Fructose-1,6-bisphosphatase (EC 3.1.3.11)

 fruB

1.29

PTS system, fructose-specific IIA/FPR component (EIIA-Fru)

 fruK

1.42

1-Phosphofructokinase (EC 2.7.1.56) (fructose 1-phosphate kinase)

 fucA

1.14

l-Fuculose phosphate aldolase (EC 4.1.2.17)

 fuci

1.03

Fucose isomerase FucI (EC 5.-.-.-)

 fucK

1.56

l-Fuculokinase (EC 2.7.1.51) (l-fuculose kinase)

 fucO

1.48

Lactaldehyde reductase (EC 1.1.1.77)

 fucP

1.12

Fucose permease

 fucU

0.93

Fucose operon FucU protein

 gcl

−1.06

Glyoxylate carboligase (EC 4.1.1.47) (tartronate-semialdehyde synthase)

 gltA

−0.36

Citrate synthase (EC 4.1.3.7)

 gpsA

−0.58

l-Glycerol 3-phosphate dehydrogenase

 mdh

−0.39

Malate dehydrogenase (EC 1.1.1.37)

 ppsA

−0.84

Phosphoenolpyruvate synthase (EC 2.7.9.2)

 pykF

1.43

Pyruvate kinase (EC 2.7.1.40)

 tktA

1.52

Transketolase 1 (EC 2.2.1.1) (tk 1)

 xylA

1.6

Xylose isomerase (EC 5.3.1.5) (version 1)

 zwf

1.76

Glucose-6-phosphate 1-dehydrogenase (EC 1.1.1.49)

(b) Metabolic transport related genes

 gltL

1.47

Glutamate/aspartate transport ATP-binding protein gltL

 malK

1.46

Maltose/maltodextrin transport ATP-binding protein MalK

 manX

1.65

Phosphotransferase system enzyme II (EC 2.7.1.69), mannose-specific, factor III

 mglC

1.34

Galactoside transport system permease protein

 proV

1.41

Glycine betaine/l-proline transport ATP-binding protein ProV

 ptsH

1.57

PTS system, phosphocarrier protein HPr (histidine-containing protein)

 xylE

1.75

d-Xylose-proton symporter (d-xylose transporter)

(c) Fatty acids, purine and pyrimidine metabolism related genes

 fabA

2.00

3-Hydroxydecanoyl-[acyl-carrier-protein] dehydratase (EC 4.2.1.60)

 fabB

1.02

3-Oxoacyl-[acyl-carrier-protein] synthase I (EC 2.3.1.41)

 fabH

1.32

3-Oxoacyl-[acyl-carrier-protein] synthase (EC 2.3.1.41) III

 kdsB

−1.00

3-Deoxy-manno-octulosonate cytidylyltransferase (EC 2.7.7.38)

 nth

−2.06

Endonuclease III (EC 4.2.99.18) (DNA-(apurinic or apyrimidinic site) lyase)

 purE

0.82

Phosphoribosylaminoimidazole carboxylase catalytic subunit (EC 4.1.1.21) (AIR carboxylase) (AIRC)

 purF

0.85

Amidophosphoribosyltransferase (EC 2.4.2.14)

(d) Amino acid metabolism genes

 aroC

−0.76

Chorismate synthase (EC 4.6.1.4).

 aroG

−0.78

Phospho-2-dehydro-3-deoxyheptonate aldolase, Phe-sensitive (EC 4.1.2.15) (phospho-2-keto-3-deoxyheptonate aldolase)

 artI

−1.12

Arginine-binding periplasmic protein 1 precursor

 aroL

−0.74

Shikimate kinase (EC 2.7.1.71) II

 aroP

−3.06

Aromatic amino acid transport protein aroP (general aromatic amino acid permease)

 cysK

−0.78

Cysteine synthase A (EC 4.2.99.8)

 hisI

−1.09

Histidine biosynthesis bifunctional protein hisIE [includes: phosphoribosyl-AMP cyclohydrolase (EC 3.5.4.19) (PRA-CH); phosphoribosyl-ATP pyrophosphatase (EC 3.6.1.31) (PRA-PH)]

 hisC

−0.92

Histidinol-phosphate aminotransferase

 ilvG

−0.78

Acetolactate synthase (EC 4.1.3.18) II large chain

 mhpE

−1.06

4-Hydroxy-2-oxovalerate aldolase (EC 4.1.3.-)

 pepD

−2.06

X-his dipeptidase (EC 3.4.13.3) precursor

 torA

−1.00

Trimethylamine-n oxide reductase precursor (EC 1.6.6.9)

 trpE

1.59

Anthranilate synthase component I (EC 4.1.3.27)

 trpC

0.96

Tryptophan biosynthesis protein trpCF [includes: indole-3-glycerol phosphate synthase (EC 4.1.1.48) (IGPS); N-(5′-phospho-ribosyl)anthranilate isomerase (EC 5.3.1.24) (PRAI)]

 ybaS

−1.32

Probable glutaminase ybaS (EC 3.5.1.2)

(e) Global and metabolic regulatory genes

 iclR

1.96

Acetate operon repressor (repressor protein IclR)

 fis

1.52

DNA-binding protein fis (factor-for-inversion stimulation protein) (HIN recombinational enhancer binding protein)

 fucR

−0.47

l-Fucose operon activator

 lysR

1.51

Transcriptional activator protein lysR

 purR

−0.45

Purine nucleotide synthesis repressor

 rpoS

1.62

RNA polymerase sigma-stationary phase

Table 3(a) shows that the expression of the glycolytic pathway gene pykF was up-regulated (while pykA expression was slightly down-regulated (0.88 which corresponds to −0.184 in log2 representation), data not shown in Table 3), and those of the gluconeogenic pathway genes such as ppsA and fbp were down-regulated as expected. The gene expression related to TCA cycle such as acnA was down-regulated, and the glyoxylate pathway related genes such as aceA and aceK were down-regulated in the mutant as expected. The pentose phosphate (PP) pathway related genes such as zwf were up-regulated in the mutant, which will be discussed later in the present paper. The adhE gene was also up-regulated in the mutant as compared with the parent strain, consistent with the result of Mikulskis et al. (1997). The respiratory pathway related genes such as cydA and cydB genes were down regulated, which is known to be positively controlled by Cra (Ramseier et al. 1996). Several other genes were also differentially regulated as explained in Appendix A.

Verification of DNA microarray result by RT-PCR

Some of the genes investigated by DNA microarray were randomly selected, and their expressions were compared with those measured by RT-PCR to check the validity of the DNA microarray result. Figure 2 shows the comparison of the expressions of such genes as ppsA, gltA, cydA, fnr and arcA, where the former three genes changed significantly in the mutant as compared with those of the parent strain as shown in Table 3, and the latter two genes did not change much as compared with the wild type (data not shown). Although the number of genes tested is limited, Fig. 2 indicates that the gene expressions obtained by DNA microarray is comparable with those obtained by RT-PCR, which implies the reliability of the DNA microarray result to some extent.
Fig. 2

Comparison between RT-PCR (white bar) and DNA microarray analyses (black bar) of gene expression in response to cra gene knockout

Some of the DNA micro-array results are consistent with the previously published data, while several others seem to be under control of Cra as well. This was investigated by detecting the Cra-binding sites (Appendix B).

Enzyme activities

Some of the enzyme activities were given in Fig. 3, where EMP pathway enzymes such as Pfk and Pyk were up-regulated as well as G6PDH and ED pathway enzyme activities. On the other hand, the activity of gluconeogenic enzyme such as Pck and the activities of ICDH and Icl were down-regulated, and the Ack activity was up-regulated.
Fig. 3

Comparison of enzyme’s activities during glucose limited chemostat culture at the dilution rate of 0.2 h−1 between E. coli BW25113 (white bar) and E. coli cra mutant (gray bar) where feed glucose concentration was 4 g/l: glucose:PEP phosphotransferase (PTS), phosphofructose kinase (Pfk), pyruvate kinase (Pyk), glucose 6 phosphate dehydrogenase (G6PDH), 6-phosphogluconate dehydrogenase (6PGDH), overall activity of E–D pathway (ED enzyme), acetate kinase (Ack), citrate synthase (CS), NADP+ dependent isocitrate dehydrogenase (ICDH), isocitrate lyase (Icl), malate synthase (MS), malic enzyme (Mez), aconitase (Acn), phosphoenol pyruvate carboxylase (Ppc), phosphoenol pyruvate carboxykinase (Pck)

Efect of cra.edd and cra.edd.iclR genes knockout on the metabolism

In order to avoid large flux rerouting through inefficient ED pathway, we knocked out edd gene as well as cra gene. Figure 4 shows the batch cultivation result for the cra.edd mutant, where more carbon may be utilized via EMP pathway, and acetate was overflowed as well as the case of cra mutant (Fig. 1b). Since icd, aceA and aceB genes were still repressed in the cra.edd genes knockout mutant as well as cra gene knockout mutant, TCA cycle tended to be repressed and the carbon overflowed for the acetate production.
Fig. 4

Batch cultivation results of acra.edd double mutant of E. coli and bcra.edd.iclR triple mutant of E. coli: open square glucose concentration, filled square biomass concentration, open triangle acetate concentration

In order to reduce the acetate production, we further knocked out iclR gene so that the glyoxylate pathway is activated. Figure 4b shows the batch cultivation result for the cra.edd.iclR triple genes knockout mutant, where the figure indicates that acetate production was reduced and the cell concentration became the highest among the four strains used in the present research.

To understand the metabolism, some of the enzyme activities were measured for all the four strains under continuous cultivation at the dilution rate of 0.6 h−1, which corresponds to the exponential growth phase in the batch culture, as given in Fig. 5. Figure 5 indicates that ICDH activity decreased for cra and cra.edd mutants and further decreased in cra.edd.iclR mutant as compared with the wild type. On the other hand, the Icl activity decreased for cra and cra.edd mutants, but its activity increased for cra.edd.iclR mutant. The glucose consumption rates for the wild-type, cra mutant, cra.edd mutant, and cra.edd.iclR mutant were 7.12 ± 0.20, 9.75 ± 0.51, 8.79 ± 0.48, 8.09 ± 0.35, respectively.
Fig. 5

Comparison of enzyme’s activities during glucose limited chemostat culture at the dilution rate of 0.6 h−1 where its feed concentration was 10 g/l. Enzyme name refers to the same as in Fig. 3

Discussion

In Escherichia coli, Crp and Cra are known to control transcriptional responses to carbon availability (Saier and Ramseier 1996). While cAMP–Crp complex primarily controls the initiation of carbon source utilization, Cra influences the direction of carbon flux (Ramseier et al. 1995). It is quite important to understand the regulation mechanism for the carbon flow in terms of the global regulatory genes, and it is useful to utilize such information for the improvement of fermentation characteristics. Since Cra represses the glycolysis pathway genes such as ptsHI, pfkA, pykF, and activates the gluconeogenic pathway genes such as fbp, ppsA, pckA, etc., cra gene knockout may activate glycolysis, and the glucose consumption rate may be increased as shown in Table 2.

As stated above in “Results”, although the glucose consumption rate could be increased by cra gene knockout mutant (Table 2), the acetate was more produced and less consumed as compared with the wild-type strain (Fig. 1), resulting in the decrease in the cell yield (Table 2). This may be due to the activation of ED pathway (Fig. 3) and the repression of the TCA cycle [Table 3(a), Fig. 3]. We then blocked the ED pathway by constructing cra.edd double genes knockout mutant. Noting that aceA,B and icd genes were repressed in cra and cra.edd mutants, we constructed cra.edd.iclR mutant to reduce acetate formation. Usually, iclR is activated by fadR and induces aceBAK operon upon growth on either acetate or fatty acids.

Let us consider in more detail one by one about the TCA cycle regulation. The first enzyme of the TCA cycle, citrate synthase (CS) catalyzes the condensation of OAA and AcCoA to produce citrate plus coenzyme A. This enzyme is encoded by gltA in E. coli, which is under control of ArcA, while its regulation is independent of fnr, crp, and cra gene products (Park et al. 1994). On the other hand, aconitase genes (acnA and acnB) are transcriptionally regulated by a variety of global regulatory genes, where acnB expression is activated by Crp and repressed by ArcA, Fis, and Cra, while acnA expression is initiated by σ38, activated by Crp, Fur, SoxR/S, Cra and repressed by ArcA and Fnr (Cunningham et al. 1997). Thus, roughly speaking, acnB predominantly expresses during exponential growth phase, while acnA expresses at the stationary phase. In the case of cra gene knockout mutant, acnB is activated, while acnA is repressed as shown in Table 3(a), which indicates that the aconitase activity may be enhanced during the cell growth phase, or in the continuous culture at the dilution rate of 0.6 h−1(due to the activation of acnB gene), while its activity may be repressed at the stationary phase or in the continuous culture at the dilution rate of 0.2 h−1(due to the repression of arcB gene). The latter phenomenon can be observed in Fig. 3, while the former phenomenon cannot be seen in Fig. 5, which might be due to other global regulatory proteins such as Crp, etc.

The ace operon of E. coli contains three structural genes such as aceB, aceA, and aceK, which are transcribed in this order. The aceB and aceA encode two such enzymes of the glyoxylate pathway as malate sysnthase (MS) and isocitrate liase (Icl), respectively, while aceK encodes the bifunctional enzyme ICDH kinase/phosphatase, which regulate the activity of ICDH by reversible phosphorylation. The activity of this enzyme determines the fluxes of the junction point between the TCA cycle and the glyoxylate pathway. The ace operon is negatively regulated by iclR, which is located downstream from the aceK gene. Moreover, since Cra positively regulate ace operon, the glyoxylate pathway is repressed in cra gene knockout mutant. Figure 5 indicates that ICDH activity decreased for cra and cra.edd mutants as compared with the wild type, which is due to cra gene knockout. Moreover, the ICDH activity further decreased in cra.edd.iclR genes knockout mutant, which may be caused by the phosphorylation of ICDH due to iclR gene knockout. As for Icl activity, it decreased for cra and cra.edd mutants as compared with the wild type, which is due to cra gene knockout, while the Icl activity increased for cra.edd.iclR mutant (Fig. 5), which is due to the release from the inhibition by iclR. The fadR gene knockout (Farmer and Liao 1997; Peng and Shimizu 2006) also shows the reduction of acetate formation, giving the cell yield improvement by reducing the CO2 production via glyoxylate pathway utilization. However, the current cra.edd.iclR mutant shows also the activation of the glycolysis pathway genes such as ptsH, pfkA, and pykF (data not shown), thus increasing the glucose consumption rate, which is different from fadR (or iclR) gene knockout mutant. Although glucose consumption rate can be increased by the reduction of ATP production (Koebman et al. 2002), the present phenomenon is different from such mechanism.

Escherichia coli possesses two terminal oxidases Cyo and Cyd; whereas Cyo functions under fully oxidizing condition, Cyd functions under microaerophilic condition. The cydA,B operon is known to be controlled by ArcA and Fnr in response to oxygen limitation, and also controlled by Cra by carbon source availability (Ramseier et al. 1996). As shown in Table 3(a), cydA,B gene expressions were down-regulated for cra gene knockout mutant. In the case of continuous culture, enough oxygen is supplied and Cyo plays the role, and the effect of down-regulation of cyd is the least, while its effect may become significant at the stationary phase of batch culture. Although it has been reported that cyd operon is regulated by the interdependency of Cra, Fnr, and ArcA (Ramseier et al. 1996), the down-regulation of this operon was due to Cra in the present case since fnr and arcA changed little for the continuous culture at the present aerobic condition.

Table 3(a) shows the up-regulation of adhE gene. Cra is reported to repress adhE gene in the aerobic condition (Mikulskis et al. 1997). Although this did not result in the ethanol production, this may become important for the microaerobic or anaerobic condition, since this enzyme is allostelically affected by NADH/NAD+, which is not high in the current aerobic condition.

The up-regulation of zwf in Table 3(a) resulted in the increased activity of G6PDH as shown in Fig. 3. Although zwf is probably under control of Cra as shown in Table 4, the activity of G6PDH may be enhanced by the activation of ED pathway in the cra mutant due to enzyme level regulation via reduced 6-phosphogluconate, which flowed toward ED pathway.
Table 4

Cra-controlled operons used to construct the Cra recognition weight matrix

Operon

Putative Cra-binding site

Reference

aceB

GC-TGAATC|GCTTAA-CG

Ramseier et al. (1993)

adhE

GC-TGAAAG|GTGTCA-GC

Mikulskis et al. (1997)

edd-eda

AC-TGAAAC|GTTTTT-GC

Ramseier et al. (1995)

epd (gapB)

AC-TGAAAC|GCTTCA-GC

Ramseier et al. (1995)

fruB O1

GC-TGAAAC|GTTTCA-AG

Ramseier et al. (1993)

fruB O2

GC-TGAATC|GTTTCA-AT

Ramseier et al. (1993)

icd

GC-TGAATC|GCTTAA-CC

Ramseier et al. (1993)

mtlA

AC-TGAATC|GGTTAA-CT

Ramseier et al. (1995)

nirB

GC-TGAATC|GTTAAG-GT

Tyson et al. (1997)

pckA

GG-TGAATC|GATACT-TT

Ramseier et al. (1995)

pfkA

CC-TGAATC|AATTCA-GC

Nègre et al. (1996)

ppsA

GG-TGAATC|GTTCAA-GC

Ramseier et al. (1993)

ptsH

GC-TGAATC|GATTTT-AT

Ramseier et al. (1993)

pykF

GC-TGAAAC|CATTCA-AG

Ramseier et al. (1995)

The vertical line indicates the center of the palindrome, and hyphen indicates two boundaries of the palindrome

In conclusion, the present research shows the importance of the metabolic regulation analysis for the construction of multiple genes knockout mutants. Namely, we paid attention to the role of global regulatory gene cra for changing the direction of the carbon flow by knockout of this gene. As expected, the important glycolysis enzymes such as PTS, Pfk and Pyk were activated, and thus glucose consumption rate was increased. Since Cra activated ED pathway, and repressed TCA cycle and the glyoxylate pathway, we constructed cra.edd.iclR genes knockout mutant to reduce the acetate production by activating the glyoxylate pathway, thus improving the cellular performance. If we compare the activities of PTS, Pfk, and Pyk between Fig. 3 (dilution rate at 0.2 h−1) and Fig. 5 (dilution rate at 0.6 h−1), the extent of the increased activities were less for the latter. This may be due to the fact that cra gene is more expressed at the stationary phase (or at low dilution rate in the continuous culture) as compared with the exponential growth phase (or at high dilution rate in the continuous culture) (Rahman and Shimizu 2008).

Acknowledgments

Marcos J. Araúzo-Bravo would like to acknowledge Japanese Society for Promotion of Science (JSPS) for supporting him for this research. Dayanidhi Sarkar would like to acknowledge Japanese Government Scholarship, Monbukagakusho (Ministry of Education, Culture, Sports, Science and Technology, Japan) for supporting his research.

Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • Dayanidhi Sarkar
    • 1
  • Khandaker Al Zaid Siddiquee
    • 1
  • Marcos J. Araúzo-Bravo
    • 1
  • Takahiro Oba
    • 2
  • Kazuyuki Shimizu
    • 1
    • 3
  1. 1.Department of Bioscience and BioinformaticsKyushu Institute of TechnologyIizukaJapan
  2. 2.Biotechnology and Food Research InstituteFukuoka Industrial Technology CenterKurumeJapan
  3. 3.Institute for Advanced BiosciencesKeio UniversityTsuruokaJapan

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