enhanced uridine 5′-monophosphate production by whole cell of saccharomyces cerevisiae through...
TRANSCRIPT
ORIGINAL PAPER
Enhanced uridine 50-monophosphate production by whole cellof Saccharomyces cerevisiae through rational redistributionof metabolic flux
Dong Liu • Yong Chen • An Li • Jingjing Xie •
Jian Xiong • Jianxin Bai • Xiaochun Chen •
Huanqing Niu • Tao Zhou • Hanjie Ying
Received: 15 September 2011 / Accepted: 3 November 2011 / Published online: 15 November 2011
� Springer-Verlag 2011
Abstract A whole-cell biocatalytic process for uridine
50-monophosphate (UMP) production from orotic acid by
Saccharomyces cerevisiae was developed. To rationally
redistribute the metabolic flux between glycolysis and
pentose phosphate pathway, statistical methods were
employed first to find out the critical factors in the process.
NaH2PO4, MgCl2 and pH were found to be the important
factors affecting UMP production significantly. The levels
of these three factors required for the maximum production
of UMP were determined: NaH2PO4 22.1 g/L; MgCl22.55 g/L; pH 8.15. An enhancement of UMP production
from 6.12 to 8.13 g/L was achieved. A significant redis-
tribution of metabolic fluxes was observed and the under-
lying mechanism was discussed.
Keywords Uridine 50-monophosphate � Saccharomyces
cerevisiae � Metabolic flux analysis � Whole-cell
biocatalysis � Response surface method
Introduction
Uridine 50-monophosphate (UMP) is widely used as an
important pharmaceutical intermediate and food additive.
It is a membrane phosphatide precursor and can increase
brain cytidine diphosphate choline (CDP-choline) and
acetylcholine levels [1, 2]. UMP can also activate the
activity of mitochondrial ATP-dependent potassium chan-
nel (mitoKATP) of the heart, playing an essential role in
cardioprotection [3]. As a product of both the biosynthetic
and salvage pathways, UMP serves as the precursor for all
other pyrimidine nucleotides and contributes to pyrimidine
nucleotides-related oligosaccharides synthesis [4].
Generally, 50-nucleotides can be obtained by the reac-
tion of corresponding nucleosides with phosphorylating
agents [5]. However, due to the poor selectivity of the
reaction, in which 20-nucleotides and 30-nucleotides are
often produced, chemical synthesis is not suitable for UMP
production in large scales. UMP can also be produced by
fermentation and biocatalytic process. Corynebacterium
ammoniagenes have been exploited for fermentation, in
which UMP was accumulated in the culture broth con-
taining orotic acid (OA). The yield of UMP produced with
C. ammoniagenes by the fermentative process was 4.3 g/L
from 2 g/L orotic acid [6]. While in the biocatalytic pro-
cess, the strain was first cultivated in a mineral salt med-
ium, and then cells were harvested and used as the
biocatalyst in the reaction. The concentration of UMP
reached 10.4 g/L after optimization of cultivation and
reaction conditions by C. ammoniagenes ATCC 6872 [7].
Much attention has been paid to whole-cell biocatalyst
used for nucleotides and oligosaccharides production
[7–9]. Compared to chemical catalysts, enzymes have two
key advantages. One is their high selectivity; the other is
their great diversity in nature [10]. Whole-cell biocatalysis
combines these benefits with simple, low-cost catalyst
preparation and the possibility to develop efficient pro-
cesses for cofactor regeneration and multistep conversions.
Although the process using C. ammoniagenes as whole-cell
biocatalyst for UMP production was efficient, it was not
suitable for industrial application due to the high cell
concentrations required to provide enough enzymes [11].
D. Liu � Y. Chen � A. Li � J. Xie � J. Xiong � J. Bai � X. Chen �H. Niu � T. Zhou � H. Ying (&)
State Key Laboratory of Materials-Oriented Chemical
Engineering, College of Life Science and Pharmaceutical
Engineering, Nanjing University of Technology,
Nanjing 210009, People’s Republic of China
e-mail: [email protected]
123
Bioprocess Biosyst Eng (2012) 35:729–737
DOI 10.1007/s00449-011-0653-5
Since Saccharomyces cerevisiae is a by-product of estab-
lished fermentation process of making beer and can be
easily obtained in considerably substantial quantities at low
costs, it was used as the enzyme source to produce UMP
from orotic acid for the first time. The biological conver-
sion of orotic acid to UMP is catalyzed by two enzymes.
Orotate phosphoribosyltransferase (OPRTase, EC 2.4.2.10)
catalyzes the formation of orotidine 50-monophosphate
(OMP, EC 4.1.1.23) from orotic acid and 5-phosphor-
ibosyl-1-pyrophosphate (PRPP). OMP is subsequently
decarboxylated by OMP decarboxylase (ODCase) to form
UMP (Fig. 1). The availability of intracellular PRPP is
critical for UMP production. PRPP is synthesized from
ribose 5-phosphate (R5P) and ATP, which are derived from
the pentose phosphate pathway (PPP) and glycolytic
pathway, respectively. So, a rational flux distribution
between PPP and glycolytic pathway is of essential
importance for UMP production.
However, in our preliminary experiments, we had found
that the flux through the glycolytic pathway was larger than
expected. The ATP produced in glycolysis was much more
than the R5P produced in PPP. Due to the imbalance
between ATP and R5P, PRPP supply was not sufficient and
UMP production was low. Therefore, glycolysis should be
suppressed and more carbon source should be redirected
toward PPP for R5P synthesis. To rationally redistribute
the metabolic flux between glycolysis and PPP, statistical
methods were employed first to find out the critical factors
in the process. NaH2PO4, MgCl2 and pH were found to be
the important factors affecting UMP production signifi-
cantly. Then, we further investigated the levels of these
three factors required for the optimal distribution of met-
abolic flux with a response surface analysis. A significant
redistribution of metabolic fluxes was observed and the
mechanism was studied.
Materials and methods
Strain, media and cultivation
The strain used for UMP production was S. cerevisiae 1002
(China Center of Industrial Culture Collection).
The seed culture medium contained (g/L): yeast extract
10; peptone 20; glucose 20. The pH of the medium was
adjusted to 5.8 with 1.0 M NaOH and 0.1 M HCl. The
prepared seed culture was inoculated (5%, v/v) into a 5-L
fermenter (NBS Bioflo-110) containing 3 L of fermenta-
tion medium. The fermentation medium contained (g/L):
glucose 50; peptone 5; yeast extract 2; (NH4)2HPO4 2;
MgSO4�7H2O 1; KH2PO4 2. The pH of the medium was
adjusted to 7.4 with 1.0 M NaOH and 0.1 M HCl. Culti-
vation was carried out at 30 �C for 48 h.
The cultured yeast cells were collected by centrifugation
(8,0009g, 10 min at 4 �C) and washed twice with distilled
water. Then the harvested cells were lyophilized and stored
at -20 �C.
Biocatalytic reaction
The biocatalytic reaction mixture contained the permeabi-
lized cells, necessary substrates (orotic acid and glucose),
phosphate and other required ingredients. The basic bio-
catalytic reaction mixture (300 mL) contained 24 g glu-
cose, 6 g NaH2PO4, 0.75 g MgCl2, 3 g orotic acid, 6 mL
glycerol, 6 mL dodecyl dimethyl benzyl ammonium bro-
mide (I5) and 80 g cells, at pH 8.0 and temperature 30 �C.
However, precise compositions were described in the
related sections. The reactions were performed at 30 �C in
500-mL flasks containing 300 mL of the reaction mixture
on a reciprocal shaker at 100 rpm for 20 h.
Analytical method
The glucose concentration was measured using an SBA-
40C biosensor analyzer (Institute of Biology, Shandong
Province Academy of Sciences, P.R. China). Concentra-
tions of UMP, UDP, UTP and UDPG in the reaction wereFig. 1 Schematic illustration of the biosynthesis of UMP from orotic
acid
730 Bioprocess Biosyst Eng (2012) 35:729–737
123
measured by high-performance liquid chromatography
(HPLC). The HPLC system was equipped with a SepaxHP-
C18 column (250 mm 9 4.6 mm 9 5 lm) and a UV
detector operating at a wavelength of 260 nm. The column
was eluted with 6% (v/v) phosphoric acid (adjusted to pH
6.6 with triethylamine) at a flow rate of 1 mL min-1 and
room temperature.
Concentrations of organic acids (succinate, citrate,
acetate, malate) were determined using an Aminex HPX-
87H ion exclusion column (300 9 7.8 mm; Bio-Rad Lab-
oratories, Hercules, CA, USA), with 5.0 mM H2SO4
solution used as the mobile phase (0.6 mL/min) at 50 �C,
and with a UV detector at 210 nm. A refractive index
detector was used instead to measure the concentrations of
ethanol and glycerol. Quantitative data were obtained by
comparing the peak areas of the query compounds with
those of standards of known concentrations.
The concentrations of glucose 6-phosphate (G6P),
fructose 6-phosphate (F6P) and fructose 1, 6-bisphosphate
(FBP) were determined according to our previously
described method based on the specificity of enzymatic
conversion [12]. Inorganic phosphate concentrations were
measured by the spectrophotometric molybdenum blue
method [13].
Experimental design and data analysis
As a first step, the components were tested individually
(one-factor-at-a-time optimization). Fractional factorial
design (FFD) was then used to identify the factors affecting
UMP production significantly. The steepest ascent was
generated by the first-order equation obtained by FFD and
led to optimization by a central composition design (CCD),
which was used to evaluate the quadratic effects and two-
way interactions among these variables.
Design expert, version 7.1 (STATEASE Inc., Minne-
apolis, USA) was used for the experimental designs and
regression analysis of the experimental data. Statistical
analysis of the model was performed to evaluate the
analysis of variance (ANOVA). The statistical significance
of the polynomial model equation was judged statistically
by R2 and was determined by an F-test.
Metabolic flux analysis
The stoichiometric model assumed to describe the meta-
bolic network of S. cerevisiae was adapted from Kyoto
Encyclopedia of Genes and Genomes (KEGG) pathway
database. The production rates of glucose, ethanol,
glycerol, succinate, citrate, acetate, malate, glucose
6-phosphate (G6P), fructose 6-phosphate (F6P), fructose
1,6-bisphosphate (FBP), uridine diphosphoglucose
(UDPG), UMP, uridine diphosphate (UDP), uridine
triphosphate (UTP) and inorganic phosphate were mea-
sured to calculate or test the fluxes. The production rates of
the other intermetabolites were assumed to be zero. The
calculation of fluxes was performed in MATLAB (Math-
works Inc.). Flux for glucose uptake was set to 100 and the
other fluxes in the network were given as relative molar
flux normalized to the flux for glucose uptake.
Results and discussion
Optimization of reaction components
using one-factor-at-a-time method
Saccharomyces cerevisiae cells, orotic acid, glucose, phos-
phate and surfactants are essential ingredients in the bio-
catalytic reaction mixture. Orotic acid is the substrate of the
reaction. Glucose is the source of energy for ATP regener-
ation. Phosphate is the phosphate donor for PRPP biosyn-
thesis and is essential for nucleotides synthesis [14, 15]. The
cells used as the source of enzymes were permeabilized with
the surfactant I5 (dodecyl dimethyl benzyl ammonium bro-
mide). The surfactant was used to facilitate the substrates and
products to permeate across the cell membrane [16].
Apart from the basic reaction components mentioned
above, several effector molecules were also investigated,
including divalent magnesium Mg2?, NH4? and citrate. An
effector molecule is an allosteric inhibitor or activator
that can bind to an enzyme and exert its effect by changing
the conformation of the enzyme to decrease or enhance the
activity of the enzyme [17]. Mg2? is necessary for the
activities of most enzymes in UMP production, such as
hexokinase, phosphofructokinase and orotate phosphor-
ibosyltransferase [18, 19]. NH4? is a typical activator of
phosphofructokinase in S. cerevisiae. Citrate decreases the
activities of both phosphofructokinase and pyruvate kinase,
being used as a powerful tool to regulate the metabolic
fluxes distribution among glycolysis and PPP [20].
The one-factor-at-a-time method was adopted at first to
optimize the reaction components. The effects of these com-
ponents on UMP production are shown in Figs. 2 and 3. The
optimum concentrations of the components in the reaction
mixture were determined: orotic acid 10 g/L; NaH2PO4
20 g/L; glucose 80 g/L; surfactant I5, 20 mL/L; cells 267 g/L;
magnesium chloride 2.5 g/L; ammonium chloride 0.4 g/L;
citrate 1.2 g/L; glycerol 20 mL/L; pH 8.0; temperature 30 �C.
Screening key factors with the fractional factorial
design
After the one-factor-at-a-time optimization, fractional fac-
torial design (FFD) was used to pick out the key factors
that significantly influenced UMP production. The factors
Bioprocess Biosyst Eng (2012) 35:729–737 731
123
and the two levels for each factor were chosen based on the
one-factor-at-a-time optimization. Results of the design are
given in Table 1. Regression analysis resulted in the fol-
lowing equation, which describes UMP production (Y g/L)
as a function of the coded values of all factors:
Y ¼ 4:13� 0:11 X1 þ 0:13 X2 � 0:12 X3 � 0:092 X4
þ 0:031 X5 þ 0:17 X6 þ 0:61 X7 þ 0:74 X8 þ 0:49 X9
� 0:026 X10 þ 0:32 X11 ð1Þ
where, X1, X2,…, X11 are coded values of orotate, glu-
cose, citrate, glycerol, temperature, NH4Cl, NaH2PO4,
MgCl2, pH, surfactant I5 and cell concentration,
respectively.
Statistical analysis of the data showed that NaH2PO4,
MgCl2 and pH were the most significant factors for UMP
production. These three key effectors were selected for
further study.
a b
c d
e f
Fig. 2 Effects of a temperature, b pH, c orotic acid, d NaH2PO4, e glucose and f surfactant on UMP production
732 Bioprocess Biosyst Eng (2012) 35:729–737
123
a b
c d
Fig. 3 Effects of effector molecules: a MgCl2, b NH4Cl, c citrate and d glycerol on UMP production
Table 1 The results of the fractional factorial design
Run X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 UMP (g/L)
Observed Predicted
1 5 40 0.6 20 26 0.4 20 2.5 6 20 260 5.496 5.426
2 10 80 1.8 10 30 0.2 10 1.5 6 20 260 2.506 2.436
3 5 80 0.6 20 30 0.2 20 1.5 8 10 260 4.532 4.967
4 10 80 1.8 20 30 0.4 20 2.5 8 20 260 6.618 6.269
5 5 80 1.8 10 26 0.2 20 2.5 8 10 180 6.012 5.685
6 5 80 0.6 10 30 0.4 10 2.5 6 10 260 4.782 4.766
7 10 40 0.6 10 30 0.2 20 2.5 6 10 180 4.627 4.535
8 5 40 0.6 10 26 0.2 10 1.5 8 20 260 3.915 3.566
9 10 40 0.6 20 30 0.4 10 1.5 8 10 180 3.299 2.972
10 10 40 1.8 20 26 0.2 20 1.5 6 10 260 3.216 3.200
11 10 80 0.6 10 26 0.4 20 1.5 8 20 180 4.275 4.516
12 5 80 1.8 20 26 0.4 10 1.5 6 10 180 2.241 2.149
13 10 80 0.6 20 26 0.2 10 2.5 6 20 180 3.101 3.278
14 5 40 1.8 20 30 0.2 10 2.5 8 20 180 3.796 4.037
15 10 40 1.8 10 26 0.4 10 2.5 8 10 260 4.537 4.972
16 5 40 1.8 10 30 0.4 20 1.5 6 20 180 3.125 3.302
Bioprocess Biosyst Eng (2012) 35:729–737 733
123
Prediction of the optimal conditions using central
composite design
Based on the FFD experiments, NaH2PO4 (X7), MgCl2 (X8)
and pH (X9) were recognized as the most significant fac-
tors. Experiments of central composite design (CCD) were
carried out to predict the optimal values of these factors.
The design and experimental results are shown in Table 2.
A full second-order polynomial model was obtained from
regression analysis of the experimental data of CCD:
Y¼7:89þ0:27A�0:051Bþ0:20C�0:16AB
þ0:23AC�0:026BC�0:49A2�0:46B2�0:49C2 ð2Þ
where, Y is the predicted response, and A, B and C are
coded values of NaH2PO4, MgCl2 and pH, respectively.
The statistical significance of Eq. 2 was checked by
F test, and the ANOVA for response surface quadratic
model is summarized in Table 3. The 3D response surface
curves were then plotted to illustrate the interactions of the
factors and the optimal value of each factor required for
UMP production (Figs. 4, 5, 6). Each figure presents the
effect of two factors when the other one is held at zero
level. These 3D plots and their contour plots provide visual
interpretation of the interaction between the two factors
and facilitate location of the optimum experimental con-
ditions. The optimum values of NaH2PO4, MgCl2 and pH
predicted by the model were 22.10 g/L, 2.55 g/L and 8.15,
respectively. The predicted UMP production under this
condition was 7.97 g/L.
Redistribution of the metabolic flux
under the optimized condition
To confirm the model adequacy for predicting the maxi-
mum UMP production, three additional experiments under
the optimized condition were performed. The mean value
of UMP concentration was 8.03 g/L, which was in excel-
lent agreement with the predicted value 7.97 g/L. The
results of FFD showed that UMP production was mainly
affected by NaH2PO4, MgCl2 and pH. Indeed, after opti-
mization of these three factors, UMP production was
increased by 31%, from 6.12 to 8.03 g/L.
To evaluate the flux redistribution induced by optimiza-
tion of the key factors, the metabolic fluxes at 5, 10 and 15 h
before and after optimization were calculated. At the early
production stage (5 h), the flux through glycolytic pathway
was lowered by 24% after optimization, while the flux
through PPP was 2.5-fold higher (Fig. 7a). Although UMP
synthesis flux was increased, UDP and UTP synthesis fluxes
were decreased significantly, suggesting that ATP supply
was insufficient. Thus, a large amount of ribulose 5-phos-
phate (R5P) was converted back to the glycolytic pathway by
the non-oxidative branch of the PPP, probably to generate
ATP. At both middle and late stages, the fluxes in glycolysis
Table 2 Experimental results
of the central composite designRun Type A (NaH2PO4) B (MgCl2) C (pH) UMP (g/L)
1 Fact 18 (-1) 2.2 (-1) 8.5 (?1) 6.105
2 Axial 21 (0) 2.6 (0) 8.8409 (?1.68) 6.894
3 Center 21 (0) 2.6 (0) 8 (0) 7.980
4 Center 21 (0) 2.6 (0) 8 (0) 7.887
5 Fact 24 (?1) 2.2 (-1) 7.5 (-1) 6.511
6 Fact 24 (?1) 3 (?1) 8.5 (?1) 6.922
7 Fact 18 (-1) 2.2 (-1) 7.5 (-1) 5.982
8 Fact 18 (-1) 3 (?1) 8.5 (?1) 6.115
9 Center 21 (0) 2.6 (0) 8 (0) 7.892
10 Center 21 (0) 2.6 (0) 8 (0) 7.802
11 Axial 21 (0) 1.9273 (-1.68) 8 (0) 6.682
12 Fact 24 (?1) 3 (?1) 7.5 (-1) 5.970
13 Axial 21 (0) 2.6 (0) 7.1591 (-1.68) 6.252
14 Center 21 (0) 2.6 (0) 8 (0) 7.961
15 Axial 15.955 (-1.68) 2.6 (0) 8 (0) 6.107
16 Center 21 (0) 2.6 (0) 8 (0) 7.791
17 Axial 21 (0) 3.2727 (?1.68) 8 (0) 6.589
18 Fact 24 (?1) 2.2 (-1) 8.5 (?1) 7.306
19 Fact 18 (-1) 3 (?1) 7.5 (-1) 6.361
20 Axial 26.045 (?1.68) 2.6 (0) 8 (0) 7.017
734 Bioprocess Biosyst Eng (2012) 35:729–737
123
under the optimized condition were decreased by nearly
10%, while the fluxes through PPP were increased by 40%
(Fig. 7b, c). Consequently, more glucose was metabolized
via PPP and a higher UMP production was achieved.
In the whole-cell biocatalytic process, the cells used as
the source of enzymes were freeze-thawed and permeabi-
lized with the surfactant I5 to ensure an efficient perme-
ation. The intracellular pH homeostasis might be disrupted
and the biocatalytic performance was thus significantly
affected by pH. pH has a marked effect on the stability,
structure and function of many proteins due to their ability
to influence the state of ionization of the enzymes. In
S. cerevisiae, the optimal pH of yeast hexokinase shared by
both glycolysis and PPP is 7.5–8.5. The optimum pH of
other key enzymes in the glycolytic pathway and PPP are
different. The optimal pH of glucose-6-phosphate dehy-
drogenase is 7.4–9.2 [21, 22] and orotate phosphoribosyl-
transferase 7.8 [23], whereas the optimal pH of phos-
phofructokinase is about 7.0 [24] and pyruvate kinase
6.5–7.5. Hence, one can infer that PPP will be most active
under slightly alkaline conditions (pH 7.4–9.2), while
glycolysis is most active under neutral conditions
(pH 6.5–7.5). The optimum pH predicted by the model was
8.15. During the biocatalytic process, the pH decreased, but
not significantly, from 8.15 to about 7.4. At these pH
values, glycolysis might be slightly repressed, while PPP
exhibited greatest activity, which redirected the carbon flux
from glycolysis toward PPP and resulted in an enhanced
UMP production.
Phosphate is the phosphate donor for ATP regeneration
and PRPP biosynthesis. Its significant effect was also
confirmed by other studies [7, 8]. Also, phosphate can
affect the metabolism by altering enzyme activity. Shi-
mano et al. [15] found that during phosphate starvation,
there was an increase in the activities of various
Table 3 Regression results of the central composite design
Factor Coefficient F value P value
Model – 111.88 \0.0001a
A 0.27 94.74 \0.0001a
B -0.051 3.36 0.0967
C 0.20 51.24 \0.0001a
AB -0.16 20.66 0.0011a
AC 0.23 41.84 \0.0001a
BC -0.026 0.54 0.4802
A2 -0.49 330.5 \0.0001a
B2 -0.46 296.34 \0.0001a
C2 -0.49 325.27 \0.0001a
Lack of fit – 2.41 0.1780
Adj R2: 0.9813a Statistically significant at a confidence level of 95%
Fig. 4 Response surface curve for UMP production as a function of
NaH2PO4 and MgCl2 concentrations, when pH was maintained at 8.0
Fig. 5 Response surface curve for UMP production as a function of
NaH2PO4 concentration and pH, when MgCl2 concentration was
maintained at 2.6 g/L
Fig. 6 Response surface curve for UMP production as a function of
MgCl2 concentration and pH, when NaH2PO4 concentration was
maintained at 21.0 g/L
Bioprocess Biosyst Eng (2012) 35:729–737 735
123
nucleotidases and other hydrolyzing enzymes participating
in the hydrolysis of nucleotides. Phosphate behaves not
only as a classical allosteric activator of yeast phospho-
fructokinase, but also modifies significantly the qualitative
features of the regulatory properties. At pH 6.8, the activity
of yeast phosphofructokinase was stimulated by phosphate
up to 25 mM. However, in the presence of phosphate the
optimum pH of the enzyme would be displaced toward a
more acidic region. At pH 7.5, the phosphofructokinase
was inhibited by 10 mM phosphate instead [25–27]. In
contrast to phosphofructokinase, glucose 6-phosphate
dehydrogenase was not be inhibited by phosphate less than
50 mM. The Ki for commercial glucose 6-phosphate
dehydrogenase from yeast was about 100 mM in vitro, and
200 mM phosphate only partially reduced the activity (less
than 14%) of yeast glucose-6-phosphate dehydrogenase at
pH 7.5 [22, 28]. In the experiments, the initial phosphate
concentration was 142 mM, which then decreased gradu-
ally as phosphate was consumed. The final phosphate
concentration was about 24 mM. Considering the pH val-
ues and phosphate concentrations in the experiments, the
inhibition of glycolysis by phosphate might be more severe
than the inhibition of PPP, especially in early stage. This
was in excellent agreement with the enhanced flux through
PPP calculated at 5 h (Fig. 7a). Consequently, more carbon
source was used to produce R5P, which led to a higher
UMP yield from glucose.
Protein structure of some enzymes can be modified by
magnesium ion, and these structural alterations can cause
modifications in protein function. The Mg2?–ATP complex,
formed by Mg2? and ATP, was a biologically active form for
most enzymes involved in the formation and utilization of
ATP, such as hexokinase [18], phosphofructokinase [25]
and pyruvate kinase [29]. The divalent magnesium is
Fig. 7 Metabolic flux distributions at a 5 h, b 10 h, c 15 h. Numbers indicate flux ratios between before and after optimization
736 Bioprocess Biosyst Eng (2012) 35:729–737
123
indispensable for the formation of the OA/Mg2?–PRPP
ternary complex in S. cerevisiae. In the absence of Mg2?,
PRPP cannot bind to OPRTase [19, 23]. This may explain
why Mg2? effected UMP production significantly.
Conclusions
In the present study, S. cerevisiae was used as whole-cell
biocatalyst for UMP production from orotate. Among the
factors in the biocatalytic process, NaH2PO4, MgCl2 and
pH were found to be the most important ones affecting
UMP production significantly. Their optimum values were
finally determined: NaH2PO4 22.1 g/L; MgCl2 2.55 g/L;
pH 8.15. Under the optimized condition, the metabolic flux
was successfully redistributed and the UMP production
was enhanced from 6.12 to 8.13 g/L.
Acknowledgments This work was supported by a grant from the
National Outstanding Youth Foundation of China (Grant No.:
21025625), the Major Basic R&D Program of China
(2007CB707803), National Key Technology R&D Program
(2008BAI63B07) and Natural Science Foundation of Jiangsu Prov-
ince (BK2007527).
References
1. Wang L, Albrecht MA, Wurtman RJ (2007) Dietary supple-
mentary with uridine 50-monophosphate (UMP), a membrane
phosphatide precursor, increases acetylcholine level and release
in striatum of aged rat. Brain Res 1133:42–48
2. Cansev M, Watkins CJ, van der Beek EM, Wurtman RJ (2005)
Oral uridine-50-monophosphate (UMP) increases brain CDP-
choline levels in gerbils. Brain Res 1058:101–108
3. Krylova IB, Kachaeva EV, Rodionova OM, Negoda AE, Evd-
okimova NR, Balina MI, Sapronov NS, Mironova GD (2006) The
cardioprotective effect of uridine and uridine-50-monophosphate:
the role of the mitochondrial ATP-dependent potassium channel.
Exp Gerontol 41:697–703
4. Varki A (1993) Biological roles of oligosaccharides: all of the
theories are correct. Glycobiology 2:97–130
5. Haze A, Hatano H (1997) Method of producing 50-nucleotide.
United State Patent: 5623069
6. Nakayama K, Tanaka H (1971) Production of nucleic acid-related
substances by fermentative processes XXXVIII. Production of
uridine 50-monophosphate and orotidine 50-monophosphate by
Brevibacterium ammoniagenes. Agr Biol Chem 35:518–525
7. Wang X, Wang XW, Yin MX (2007) Production of uridine 50-monophosphate by Corynebacterium ammoniagenes ATCC 6872
using a statistically improved biocatalytic process. Appl Micro-
biol Biotechnol 76:321–328
8. Ying HJ, Chen XC, Cao HP, Xiong J, Hong Y, Bai JX, Li ZJ (2009)
Enhanced uridine diphosphate N-acetylglucosamine production
using whole-cell catalysis. Appl Microbiol Biotechnol 84:677–683
9. Tang JP, Yao YL, Ying HJ, Xiong J, Zhang L, Li ZJ, Bai JX,
Zhang YY, Ouyang PK (2009) Effect of NH4? and glycerol on
cytidine 50-diphosphocholine synthesis in Saccharomyces cere-visiae. Bioresour Technol 100:4848–4853
10. Robertson DE, Steer BA (2004) Recent progress in biocatalyst
discovery and optimization. Curr Opin Chem Biol 8:141–149
11. Chen Y, Li SY, Xiong J, Li ZJ, Bai JX, Zhang L, Ye Q, Ouyang
PK, Ying HJ (2010) The mechanisms of citrate on regulating the
distribution of carbon flux in the biosynthesis of uridine 50-monophosphate by Saccharomyces cerevisiae. Appl Microbiol
Biotechnol 86:75–81
12. Ying HJ, OuYang PK (2000) Inquiry into mechanism of FDP
accumulating using model of metabolic pathway flux. J Chem Ind
Eng (China) 3:313–319
13. Murphy J, Riley JP (1962) A modified single solution method for
the determination of phosphate in natural waters. Anal Chim Acta
27:31–36
14. Maruyama A, Fujio T (2001) ATP production from adenine by a
self-coupling enzymatic process: high-level accumulation under
ammonium-limited conditions. Biosci Biotechnol Biochem
65:644–650
15. Shimano F, Ashihara H (2006) Effect of long-term phosphate
starvation on the levels and metabolism of purine nucleotides in
suspension-cultured Catharanthus roseus cells. Phytochemistry
67:132–141
16. Fujio T, Maruyama A (1997) Enzymatic production of pyrimi-
dine nucleotides using Corynebacterium ammoniagenes cells and
recombinant Escherichia coli cells: enzymatic production of
CDP-choline from orotic acid and choline chloride (Part I).
Biosci Biotechnol Biochem 61:956–959
17. Arkin MR, Wells JA (2004) Small-molecule inhibitors of pro-
tein–protein interactions: progressing towards the dream. Nat Rev
Drug Discov 3:301–317
18. Romero CS, Olmo R, Teijon C, Blanco MD, Teijon JM, Romero
A (2005) Structural and functional implications of the hexoki-
nase–nickel interaction. J Inorg Biochem 99:2395–2402
19. Segura LG, Witte JF, McClard RW, Hurley TD (2007) Ternary
complex formation and induced asymmetry in orotate phos-
phoribosyltransferase. Biochemistry 46:14075–14086
20. Brul S, Coote P (1999) Preservative agents in foods-mode of
action and microbial resistance mechanisms. Int J Food Microbiol
50:1–17
21. Anderson WB, Nordlie RC (1968) Glucose dehydrogenase
activity of yeast glucose 6-phosphate dehydrogenase. I. Selective
stimulation by bicarbonate, phosphate, and sulfate. Biochemistry
7:1479–1485
22. Ashihara H, Komamine A (1976) Characterization and regulatory
properties of glucose-6-phosphate dehydrogenase from black
gram (Phaseolus mungo). Physiol Plant 36:52–59
23. McClard RW, Holets EA, MacKinnon AL, Witte J (2006) Half-
of-sites binding of orotidine 50-phosphate and R-D-5-phospho-
rylribose 1-diphosphate to orotate phosphoribosyltransferase
from Saccharomyces cerevisiae supports a novel variant of the
Theorell-Chance mechanism with alternating site catalysis. Bio-
chemistry 45:5330–5342
24. Hofmann E, Kopperschler G (1982) Phosphofructokinase from
yeast. Methods Enzymol 90:49–60
25. Baiwjelos M, Gancedo C, Gancedo JM (1977) Activation by
phosphate of yeast phosphofructokinase. J Biol Chem 252:
6394–6398
26. Laurent M, Seydoux F (1977) Influence of phosphate on the
allosteric behavior of yeast phosphofructokinase. Biochem Bio-
phys Res Commun 78:1289–1295
27. Yoshino M, Murakami K (1981) AMP deaminase reaction as a
control system of glycolysis in yeast. J Biol Chem 257:2822–2828
28. Van Noorden C, Tas J (1980) Quantitative aspects of the cyto-
chemical demonstration of glucose-6-phosphate dehydrogenase
with tetra nitro BT studied in a model system of polyacrylamide
films. Histochem J 12:669–685
29. Kuczek M (1999) A hypothetical model of the influence of
inorganic phosphate on the kinetics of pyruvate kinase. BioSys-
tems 54:71–76
Bioprocess Biosyst Eng (2012) 35:729–737 737
123