=Paper=
{{Paper
|id=None
|storemode=property
|title=Identification of key regulators in glycogen utilization in E. coli based
on the simulations from a Hybrid Functional Petri Net model
|pdfUrl=https://ceur-ws.org/Vol-988/paper7.pdf
|volume=Vol-988
|dblpUrl=https://dblp.org/rec/conf/apn/TianFMM13
}}
==Identification of key regulators in glycogen utilization in E. coli based
on the simulations from a Hybrid Functional Petri Net model==
https://ceur-ws.org/Vol-988/paper7.pdf
Identification of Key Regulators in Glycogen
Utilization in E. coli Based on the Simulations
from a Hybrid Functional Petri Net Model
Zhongyuan Tian1 , Adrien Fauré1 , Hirotada Mori2 , and Hiroshi Matsuno1,?
1
Graduate School of Science and Engineering, Yamaguchi University,
1677-1 Yoshida, Yamaguchi-shi, Yamaguchi 753-8512, Japan
{r002wa,afaure}@yamaguchi-u.ac.jp
matsuno@sci.yamaguchi-u.ac.jp
2
Graduate School of Biological Sciences, Nara Institute of Science and Technology,
8916-5 Takayama, Ikoma, Nara 630-0101, Japan
hmori@gtc.naist.jp
Abstract. Glycogen and glucose are two sugar sources available during
the lag phase of E. coli, but the mechanism that regulates their utiliza-
tion is still unclear. Attempting to unveil the relationship between glu-
cose and glycogen, we propose an integrated hybrid functional Petri net
(HFPN) model including glycolysis, PTS, glycogen metabolic pathway,
and their internal regulatory systems. By comparing known biological re-
sults to this model, basic regulatory mechanism for utilizing glucose and
glycogen were identified as a feedback circuit in which HPr and EIIAGlc
play key roles. Based on this regulatory HFPN model, we discuss the
process of glycogen utilization in E. coli in the context of a systematic
understanding of carbohydrate metabolism.
Keywords: metabolic pathway, glycogen, hybrid functional Petri net,
PTS, HPr and EIIAGlc proteins, gene regulation
1 Introduction
The carbohydrate pathway occupies a central position in a cell’s metabolism.
In our previous paper [1], we proved that glycogen plays an important role
in the lag phase of E. coli. But how the cell regulates the utilization of these
carbon sources, intracellular glycogen and extracellular glucose, was yet to be
clarified. In a cell, glycogen works as a sugar store or a sugar supply depending on
different nutrition conditions, under the regulation of enzymes expressed by glg
gene clusters (glgBXCAP ) [2]. Uptake of extracellular glucose is conducted via
the phosphotransferase system (PTS) in E. coli, whose enzymes are expressed
from two operons, ptsHIcrr and ptsG [3]. Although several shared regulators of
PTS and glycogen metabolism, such as ppGpp, Cra, CsrA and cAMP/CRP, have
?
Corresponding author.
G. Balbo and M. Heiner (Eds.): BioPPN 2013, a satellite event of PETRI NETS 2013,
CEUR Workshop Proceedings Vol. 988, 2013.
76 Tian, Faur, Mori, Matsuno
been studied [2, 4–10], a basic regulation system for the utilization of glucose and
glycogen has not been studied yet.
Computer modeling is a general and effective method for the integration
of biological systems. The purpose of this paper is to construct an integrated
model for the systematic understanding of the carbohydrate pathway system
of E. coli. In this work we first transposed into the hybrid functional Petri net
(HFPN) [11] two published models controlling different aspects of the central
carbohydrate pathway: glycolysis and pentose phosphate (PP) pathway [12],
and PTS [13]. These models have then been assembled together with a newly
developed general mass action model of the glycogen metabolic pathway into a
single comprehensive HFPN model.
By applying metabolic regulatory mechanisms in our combined HFPN model,
a basic control system regulating the utilization glucose and glycogen was iden-
tified, in which HPr::GlgP complex [14–16], EIIAGlc &cAMP system [8, 17], EI
dimerization [18, 19], FDP&Cra mutual feedback [6], HPr subcellular location
[2, 16, 20] etc. are working as regulators. In this paper, with the support of sim-
ulation results from the HFPN model, we clarify functions of HPr and EIIAGlc
as key regulators of glucose and glycogen utilization.
2 Molecular mechanism for regulating glucose and
glycogen utilization
2.1 Regulators
Fig. 1 shows possible regulators that control glucose and glycogen utilization,
in which these components are classified into five levels, labeled 0-4, according
to regulation “source” and “target”. These regulators constitute a circuit that
gives a whole view of the regulation of glucose and glycogen utilization as shown
in Fig. 2 .
Level-1 P2P (Regulation from protein to protein). HPr regulates consump-
tion of both glucose and glycogen by its phosphorylation state and concentra-
tion [8]. HPr is a member enzyme of PTS, which is involved in glucose up-
take in E. coli. (From here on, PHPr denotes the phosphorylated form of HPr,
HPr denotes the unphosphorylated form, and (P)HPr denotes either phosphory-
lated or unphosphorylated Hpr). The phosphorylation state of the (P)HPr::GlgP
complex controls glycogen decomposition. The glycogen decomposing activity of
HPr::GlgP is about five times higher than that of PHPr::GlgP [14]. In PTS, HPr
transfers phosphate groups from (P)EI to (P)EIIAGlc . Thus (P)HPr regulates
the speed of carbohydrate decompositions from both glycogen and glucose.
Level-2 F2P (Regulation from molecule flux speed to protein). EI dimeriza-
tion is thought to be the limiting step in the process of PTS transfer phosphate
from PEP to G6P via PTS, which is regulated by PEP [19]. Whether EI acts
as a dimer or a monomer to transfer phosphate from PEP to HPr is still under
discussion [19, 21, 22]. Different phosphorylation states of HPr result from the
balance of phosphate influx into PTS from PEP and outflux to G6P, in which
phosphate influx is under the regulation of EI dimerization.
Proc. BioPPN 2013, a satellite event of PETRI NETS 2013
Identification of Key Regulators 77
Fig. 1. Regulation mechanisms controlling glucose and glycogen utilization.
Level-1: HPr controls glucose phosphorylation (as a PTS enzyme) and glycogen de-
composition (in complex with GlgP). Level-2: Phosphorylation of HPr is controlled by
the balance between phosphate groups influx into and outflux from the PTS. Level-
3.1: Gene expression regulates PTS the speed of transportation of phosphate and
the process of glycogen metabolism. Level-3.2: In HPr function, either for PTS or
for glycogen degradation, depends on its subcellular location. Level-4: PTS and glg
genes expression are controlled by cAMP/CRP and Cra. Level-0.1: PEP concentra-
tion controls the amount of phosphate entering the PTS. Level-0.2: Cra expression is
controlled by FDP amount, and cAMP/CRP is enhanced by PEIIAGlc .
Fig. 2. Regulatory circuit system for glucose and glycogen utilization. M2F
is a regulation from metabolite to molecule flux speed; M2P is a regulation from
metabolite to protein; P2G is regulation from protein to gene expression; G2F is
a regulation from gene expression to molecule flux speed; L2F is a regulation from
molecule subcellular location to molecule flux speed; F2P is a regulation from molecule
flux speed to protein; P2P is a regulation from protein to protein.
Proc. BioPPN 2013, a satellite event of PETRI NETS 2013
78 Tian, Faur, Mori, Matsuno
Level-3.1 G2F (Regulation from gene expression level to protein). PTS
enzymes for glucose uptake in E. coli include EI, HPr, EIIAGlc and EIICBGlc ,
the former three enzymes are expressed from ptsHIcrr gene cluster and EIICBGlc
is from ptsG. After an exponential increasing, when an enzyme concentration
increases above a certain threshold, its catalyzed reaction speed will remain in a
high level [23]. Here we assumed that, when PTS enzymes are expressed above a
certain threshold, the whole PTS reaction speed would be extremely accelerated.
Level-3.2 L2F (Regulation from molecule subcellular location to molecule
flux speed): When (P)HPr is located at the cell’s poles, it mainly functions for
glycogen phosphorylation. And when (P)HPr is scattered in cytosol, it serves
for the function of PTS, which is responsible for glucose uptake. The deduc-
tion of subcellular location of (P)HPr controlling system will be explained in
Subsection 2.2.
Level-4 P2G (Regulation from protein to gene expression). Cra is a global
regulator of the genes for carbon metabolism in E. coli [6], which directly regu-
lates glgC and glgA and ptsHIcrr operon, or indirectly influences ptsG transcrip-
tion via SgrST pathway [6, 24]. The function of upregulation of glgC and glgA
by cAMP/CRP complex is confirmed by experiments of [17]. Comprehensively
say, when Cra levels decreases, it releases the inhibition of glgC and glgA; as
a consequence cAMP/CRP activates extremely strong expression of glgC and
glgA.
Level-0.1 M2F (Regulation from metabolite to molecule flux speed). High
enough PEP levels activate the phosphate influx into PTS by stimulating EI
dimerization [18, 19]. This reaction EI+EI⇒EIEI has been thought to be the
limiting speed of PTS.
Level-0.2 M2P (Regulation from metabolite to protein): When fructose-
1,6-bisphosphate (FDP) reaches a high level, Cra expression is repressed, which
releases its inhibition of glgC and glgA [6]. High concentration PEIIAGlc leads
to the accumulation of cAMP [8].
2.2 HPr role in glycogenolysis or PTS depends on its subcellular
localization
Lopian et al. (2010) described the spatial and temporal organization of PTS
enzymes in E. coli, especially HPr and EI [20]. According to their study, HPr
and EI mainly stay in the poles of a cell independently, and if HPr is released
to the cytosol, it should be phosphorylated by PEI in the presence of glucose.
Genobase also shows a photo of HPr scattering in the cytosol [25].
In the glycogen metabolism, interestingly, glycogenesis enzymes (GlgC, GlgA)
and glycogen granules locate at the poles, while GlgP is scattered in the cytosol
[2]. GlgP is considered always bound in a complex with HPr, since the concen-
tration of HPr is much higher than that of GlgP in E. coli [14, 15].
Based on these studies, we hypothesize that HPr controls the priority in glu-
cose and glycogen utilization in E. coli : (1) If there is no glucose, HPr cannot
get phosphate from EI, keeping its location at the poles. Hence, this pole-located
Proc. BioPPN 2013, a satellite event of PETRI NETS 2013
Identification of Key Regulators 79
HPr mainly serves for glycogen decomposition, whose speed is regulated by phos-
phorylation state of (P)HPr:GlgP as described in Subsection 2.1. (2) If there
is a little glucose supply, at the very beginning of lag phase, glucose uptake takes
place at poles areas for a very short time until all the phosphates are removed
from these PTS enzymes including HPr (See Early lag phase (1) in Subsec-
tion 4.1). Note that the pole-located HPr also has the ability of exchanging
phosphate with other PTS enzymes. (3) If glucose is abundant, HPr gets phos-
phate from PEI, causing its release to the cytosol. Cytosol-scattered HPr works
as a PTS protein, but not for glycogenolysis, hence, transporting phosphate from
EI to EIIAGlc .
3 Construction of a dynamic simulation model of central
metabolic pathway with HFPN
Central metabolic pathway in E. coli is constituted by the glycolysis, the PP
pathway, and the tricarboxylic acid cycle (TCA cycle). Most glycolysis models
are based on ordinary differential equation (ODE) [12, 26, 27]. Chassagnole et al.
(2002) constructed an integrated ODE model of glycolysis and PP pathways [12],
which is often used as a base model in many studies [26–29]. By assembling TCA
cycle with the model of [12], Kadir et al. (2010) set up an ODE model together
with six pieces of logical controlling rules [27], and Usuda et al. (2010) included
gene regulation in [26]. Kinetic parameters of these ODE model has been stored
in many databases, such as BRENDA [30], SABIO-RK [31], and BioModels [32],
and a number of works focused on parameter optimization [33, 34]. PTS are
usually represented by one or a few equations in these ODE models. Rohwer
at el (2000) set a mass balance theory model of PTS, by using experimentally
tested mass action constant for each elementary biochemical reaction within PTS
enzymes [13], and some studies are based on it [9, 35].
The simulation of our HFPN models are conducted on Cell Illustrator 4.0
[36]. Before realizing a whole model, we have first set up two independent HFPN
models based on these published, ODE models of glycolysis and PP pathway
[12, 32] and mass balance theory models of PTS [13, 35]. Subsequently, these two
HFPN models are combined into one.
This HFPN model was further extended by incorporating glycogen metabolism
pathway and basic regulatory mechanisms, and finally we got an extended HFPN
model of carbohydrate metabolism, as shown in Fig. 3. We employed general
mass action method to construct this integrated HFPN model, in which mass
action constants were manually fitted so as to meet biological data of glycogen
and other metabolites concentrations from our former study [1]. From this URL0 ,
a complete HFPN model, lists of places, transitions, and arcs can be obtained.
0
http://ds0n.cc.yamaguchi-u.ac.jp/~mzemi/etchp/ecoli_doc/MatsunoLab.htm
Proc. BioPPN 2013, a satellite event of PETRI NETS 2013
80 Tian, Faur, Mori, Matsuno
Fig. 3. HFPN model of extent center metabolism pathway in E. coli . This
model includes 3 major parts: glycolysis and pentose phosphate pathway part is in
bright yellow area, PTS part is in bright green area and glycogen metabolism
pathway part is bright blue area. Green filed transitions are degradation or dilu-
tion processes of their connected metabolites or enzymes. Black border components
are of the 3 major parts. Red border components are of regulatory mechanisms, in
which transition ptsG and ptsHIcrr represent PTS genes expression process; G cAMP
is the process of PEIIAGlc activating cAMP production; Dimer is the process of EI
dimerization; k is the parameter controlling the whole PTS reaction speed; Location
is of the molecular subcellular localization regulation mechanism; (P)HPr::GlgP rep-
resent the process of the binding of (P)HPr::GlgP catalyzing glycogen decomposition.
This is the snapshot of main part of our HFPN model, other components can be found
in Suppl. documents in the URL0
The integrated HFPN model produced the correct behavior of metabolite
concentrations of G6P, PEP, FDP etc. in a batch culture as well as the concen-
trations of glycogen and extracellular glucose in Fig. 4, which can be confirmed
by comparing with their experimental data in Supplementary data of [1]. Fur-
ther, PTS enzymes level are also illustrated in this figure, and the noisy behaviors
in EIEI and PEI come from the rapid alternation of phosphate between these
molecules. Although more evaluations are required, we can say that our simula-
tion results express similar behavior to the experimental data.
4 Confirmation of the role of HPr and EIIAGlc as key
regulators by simulation
4.1 Biological analyses based on the simulation results
With running simulations on the constructed HFPN model, we are able to sys-
tematically understand the process of carbohydrate metabolism in a batch cul-
Proc. BioPPN 2013, a satellite event of PETRI NETS 2013
Identification of Key Regulators 81
Fig. 4. Calculation results of HFPN model of extended central metabolism
pathway in E. coli . Solid-curve is simulation result of this work. Red-bar denotes
experimental data of our previous work [1].
ture in E. coli along its lifetime, which consists of 5 phases, early lag phase, late
lag phase, early log phase, late log phase, and stationary phase. Simulated con-
centrations of glucose, glycogen, FDP, HPr (EIIAGlc ), PHPr (PEIIAGlc ), and
cAMP are shown in the left panel of Fig. 5.
Early lag phase (1). At the beginning of this phase, E. coli begins its
growth just after being put into a fresh medium. At this point, (P)HPr is mainly
present at the poles and causes a little glucose uptake locally. Glycogen is not
utilized well in this phase, because it is surrounded by PHPr. Indeed the higher
affinity of PHPr than HPr isolates GlgP from glycogen, resulting in a very slow
speed decomposition rate of glycogen.
Early lag phase (2). Although this phase begins with PHPr, this protein
slowly loses its phosphate. Because glycolytic pathway is not working in this
phase, so phosphate cannot be provided through PTS. As HPr dephosphoryla-
tion completes, glycogen catalysis by HPr::GlgP begins, and E. coli uses glycogen
as its main carbon source. Along with the quick consumption of glycogen, HPr is
moved to the cytosol by the function of PEI [20]. Meanwhile, glycogen supplied
phosphate flows into the central metabolic pathway, causing PEP accumulation.
Distribution of (P)HPr in the cytosol will be finished at almost the same time.
Late lag phase. This is a period of slow glucose uptake, which is caused
by a relevant lower level of PEP, due to a low speed EI dimerization [18]. This
means that metabolites produced from glycogen support the transportation of
phosphate for glucose uptake. During this period, (P)HPr has been distributed
in the cytosol, whose major role is to work for PTS not for glycogen, and this
Proc. BioPPN 2013, a satellite event of PETRI NETS 2013
82 Tian, Faur, Mori, Matsuno
Fig. 5. Systematic understanding of the phases of extended central
metabolism in an E. coli along its whole lifetime based on this works HFPN
model. In the figure, left panel illustrates experiment and simulation behaviors of
some major metabolites and enzymes, right panel shows sugar and phosphate flux
processes of E. coli utilizing glucose and glycogen, and same colored area of left panel
and right panel are of the same phase. In right panel: Blue colored PTS represents
unphosphorylated PTS, orange colored PTS is phosphorylated PTS. Blue filled
arrows indicate carbon flux routes, in which deeper blue color represents more flowing
amount; orange color filled arrows indicate phosphate flux routes, in which deeper
orange color represents more flowing amount. Closed red locks means inactivated
pathway; open green locks means activated pathway. The whole orange colored
E. coli marked with “HPr” indicates HPr is scattered in cytosol; only head area
orange colored E. coli marked with “HPr” indicates HPr is at poles.
also causes the start of glycogen accumulation. Meanwhile in this phase more
PTS enzymes are expressed, preparing for the impending log phase.
Early log phase. Uptake of glucose is very fast in this phase due to the
highly expressed PTS proteins and the active transportation of phosphate by
these PTS proteins. Glucose is the main sugar source in this phase.
Late log phase. In this phase, under the combined regulation of PEIIAGlc
(via cAMP/CRP), and FDP (via Cra), glgC and glgA are expressed at ex-
tremely high levels [2, 6, 8], causing efficient glycogen accumulation. Due to the
lower speed of phosphate output from the PTS comparing with its input speed
from PEP, high level of PHPr are working for glucose uptake. (P)HPr is mainly
expressed in the cytosol, so it can hardly contribute to glycogen decomposition.
Stationary phase. When cells come to a stationary phase, glycogen is in
its slow speed catalyzing state. Since (P)HPr is maintained in phosphorylated
state, it concentrates towards the poles, where glycogen is located. In the post
stationary phase, there is no glucose supplied outside, glycogen is used as a
carbon source for cells to survive. Glycogen low speed catalyzation is regulated
by surrounding PHPr in poles. Next, if the E. coli is put into another culture, a
new lag phase begins.
Proc. BioPPN 2013, a satellite event of PETRI NETS 2013
Identification of Key Regulators 83
Table 1. Multi-valued formulation of the regulation in utilizing glycogen and
glucose in E. coli . α represents α (glgC & glgA activation), β represents β (glgC &
glgA activation), γ represents γ (glycogen composition). The meaning of multi-values
are 0 (no/off), 1 (on/slow) , and 2 (fast).
α β γ
glgC & glgA glgC & glgA glycogen
activation activation composition
0 0 0
1 0 1
0 1 1
1 1 2
4.2 Logical expressions of regulator states throughout the phases
Multi-valued logic rule. glgC and glgA are the genes that forms an operon
with glgP [2, 17, 37]. According to experimental result, glgC and glgA are regu-
lated by cAMP [2, 17] and FDP [6], respectively. Hence we can consider that the
transcription of this two genes is regulated by the combination of FDP amount
and cAMP level, which are distinguished α (glgC & glgA activation) and β (glgC
& glgA activation), respectively. Actually, from the biological literature [2, 6, 17],
it is known that the composition speed of glycogen varies depending on the
expression pattern of α and β. If either α or β is expressed, glycogen is com-
posed in slow speed, but if both α and β are expressed, glycogen is composed in
high speed. This function can be expressed by multi-valued logic as presented in
Table 1.
Phase transitions based on the regulatory factors. According to afore-
mentioned analysis, the importance of HPr and EIIAGlc on glycogen regulation
is pointed out from a biological point of view. To make it more precise, we will
express this regulatory system from an engineering point of view, presenting
logical representation of this system as shown in Table 2. Glycogen process is
controlled by the regulators FDP, EIIAGlc , and HPr in the left column of this
table. Among them, FDP and EIIAGlc are involved in glycogen synthesis, and
HPr in its decomposition. In the following, we will show, phase by phase, how
composition and decomposition take place on the controls with these regulators
in this table.
Early lag phase. Because of “very slow” uptake speed of glucose, FDP
amount is in “low” level, resulting in “off” expression of glgC & glgA genes (α).
EIIAGlc and HPr display the same behavior, changing these phosphorylation
states, “yes → no”. In addition, glgC & glgA activation (β) is influenced by this
state transition as “on → off” in Table 2. Glycogen composition, however, is not
influenced by these regulations, because the uptake speed of glucose is too slow to
produce glycogen. On the other hand, glycogen decomposition takes place in this
phase, with changing its speed “slow → fast” according to the phosphorylation
Proc. BioPPN 2013, a satellite event of PETRI NETS 2013
84 Tian, Faur, Mori, Matsuno
Table 2. Behaviors of key regulators (HPr and EIIAGlc ) adjusting glucose
and glycogen utilization in an E. coli . In this table, the five proliferation phases
(e.g. Late lag phase) are corresponding with their processes of experiment and simula-
tion data in Fig. 5 .
Lag phase Log phase Stationary
Regulator Early Late Early Late phase
speed of glucose uptake very slow slow very fast fast no
FDP amount low high low→high high→low no
α(glgC&glgA activation) off on off→on on→off off
EIIAGlc phosphorylation yes→no no no yes yes
(regulated cAMP level) high→low low low high high
β(glgC&glgA activation) on→off off off on on
γ(composition) no slow slow fast→slow no
glycogen
(decomposition) slow→fast no no no slow
(phosphorylation) yes→no no no yes yes
HPr (localization) pole cytosol cytosol cytosol pole
state transition of HPr “yes → no”. Hence, glycogen is the major sugar source
in this phase.
Late lag phase. Since E. coli have not consumed much energy yet in this
phase, FDP accumulates in “high” levels despite the “slow” glucose uptake
speed. Hence glgC & glgA (α) is “on”. On the contrary, glgC & glgA (β) is
“off”, resulted from “no” phosphorylation state of EIIAGlc via “low” cAMP
level. According to the rule (if α=1 and β=0 then γ=1) in Table 1, glycogen
is composed (γ) in “slow” speed. On the other hand, glycogen decomposition
does not take place in this phase, because HPr is not located at the poles but
distributed in the cytosol, which does not satisfy the requirement for glycogen
decomposition.
Early log phase. Due to “very fast” speed of glucose uptake, FDP is accu-
mulated in E. coli, despite its high metabolic activity, changing its amount as
“low → high”. Accordingly, the state of glgC & glgA (α) activation is changed
as “off → on”. In this stage, HPr is not phosphorylated, then the expression
of glgC & glgA(β) is “off”; consequently the composition speed of glycogen (γ)
is “slow”, though it temporally drops to “no” level. On the other hand, “no”
decomposition of glucose takes place in this phase from the same reason as late
lag phase above.
Late lag phase. Because much glucose was consumed in the previous phase,
its uptake speed is going to be slow down. Accordingly, for the phosphate flow
in PTS, the input speed of phosphate from PEP becomes faster than the output
speed to G6P, causing EIIAGlc phosphorylation “yes” and cAMP level “high”.
As a result, glgC & glgA activation (β) turns “on”. In addition, because, in
the early half of this phase, FDP is in a high level, glgC & glgA activation
(α) is also turned “on”. Hence, both α and β regulations are working. In this
case, according to Table 1, glycogen composition (γ) should be marked at “fast”
Proc. BioPPN 2013, a satellite event of PETRI NETS 2013
Identification of Key Regulators 85
speed. Accompanying with decreasing glucose amount, FDP concentration drops
later in this phase, that is “high → low”, resuling in glgC & glgA activation
(α) as “on → off”. As a result, in the later part of this phase, the speed of
glycogen composition (γ) changes as “fast → slow”. On the other hand, in this
phase, HPr is still in cytosol working for PTS, not for glycogenolysis. In all, since
“fast” composition and “no” decomposition are conducted, glycogen accumulates
quickly in this period.
Stationary phase. In this period, because extracellular glucose has been
totally consumed off, the speed of glycogen is marked as “no” despite the “on”
state of glgC & glgA activation (β). Hence there is “no” glycogen composition
(γ). Because of the inactive PTS and the high amount glycogen, (P)HPr is
concentrated at the “poles”, decomposing glycogen (γ) in a “slow speed” for
long survival of cells.
5 Conclusion
Some works focus on modeling glycolysis, pentose phosphate pathway, TCA
cycle etc. [12, 26, 27], and some focus on the calculation of PTS performance
with a protein mass balance theory method [13, 35]. And also some of them set
up ODE models by combining PTS into their glycolysis pathways [26, 27]. But
none of them take the glycogen metabolic pathway into account. In this work
we firstly integrated general mass action based glycogen metabolism model and
mass balance theory based PTS model into a computational model with HFPN.
By applying this model, basic regulators for E. coli to utilize extracellular
glucose and intracellular glycogen were identified. That is, (P)HPr not only works
as a member of PTS enzymes but also functions to realize different catalyzing
speeds of glycogen by its phosphorylation state combined with GlgP. Actually,
phosphorylation state of (P)HPr is controlled by the phosphate flux speed influx
and outflux of PTS, and this flux speed is controlled by gene expression, sub-
cellular localization, and metabolite concentration (glucose, PEP, FDP). HPr
and EIIAGlc are considered to be key roles among these regulators during the
utilization of glycogen and glucose by E. coli.
Based on the model with regulatory systems in this work, we provided a
systematic view of glucose and glycogen utilization by E. coli. This confirms our
previous conclusion that glycogen plays an important role as a primary carbon
source in lag phase [1].
In our model, the behavior after log phase does not correspond well to ex-
perimental data. The reasons might be inconsistencies in the referenced ODE
and PTS that were modeled so as to function in a short time course (50 s) or
steady stat context, and the difficulty in controlling its flux speed dynamically
in an hour time scale. One of our future tasks is to address this limitation.
Proc. BioPPN 2013, a satellite event of PETRI NETS 2013
86 Tian, Faur, Mori, Matsuno
Acknowledgement
This work was supported by Grant-in-Aid for Scientific Research on Innovative
Areas “Synthetic Biology” from the Ministry of Education, Culture, Sports,
Science and Technology, Japan.
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