Rajesh Kumar Pathak1, Gohar Taj, Dinesh Pandey, Sandeep Arora, Anil Kumar. 1. Department of Molecular Biology & Genetic Engineering, College of Basic Sciences & Humanities, G.B. Pant University Of Agriculture & Technology, Pantnagar-263145, Uttarakhand, India.
Abstract
Mitogen-Activated Protein Kinases (MAPKs) cascade plays an important role in regulating plant growth and development, generating cellular responses to the extracellular stimuli. MAPKs cascade mainly consist of three sub-families i.e. mitogen-activated protein kinase kinase kinase (MAPKKK), mitogen-activated protein kinase kinase (MAPKK) and mitogen activated protein kinase (MAPK), several cascades of which are activated by various abiotic and biotic stresses. In this work we have modeled the holistic molecular mechanisms essential to MAPKs activation in response to several abiotic and biotic stresses through a system biology approach and performed its simulation studies. As extent of abiotic and biotic stresses goes on increasing, the process of cell division, cell growth and cell differentiation slow down in time dependent manner. The models developed depict the combinatorial and multicomponent signaling triggered in response to several abiotic and biotic factors. These models can be used to predict behavior of cells in event of various stresses depending on their time and exposure through activation of complex signaling cascades.
Mitogen-Activated Protein Kinases (MAPKs) cascade plays an important role in regulating plant growth and development, generating cellular responses to the extracellular stimuli. MAPKs cascade mainly consist of three sub-families i.e. mitogen-activated protein kinase kinase kinase (MAPKKK), mitogen-activated protein kinase kinase (MAPKK) and mitogen activated protein kinase (MAPK), several cascades of which are activated by various abiotic and biotic stresses. In this work we have modeled the holistic molecular mechanisms essential to MAPKs activation in response to several abiotic and biotic stresses through a system biology approach and performed its simulation studies. As extent of abiotic and biotic stresses goes on increasing, the process of cell division, cell growth and cell differentiation slow down in time dependent manner. The models developed depict the combinatorial and multicomponent signaling triggered in response to several abiotic and biotic factors. These models can be used to predict behavior of cells in event of various stresses depending on their time and exposure through activation of complex signaling cascades.
Entities:
Keywords:
Abiotic; Biotic; CellDesigner; MAPKs; Modeling; SBMLsqueezer; Simulation; System Biology
MAPK cascades are conserved signaling modules found in all
eukaryotic cells including plant, fungi and animals. A mitogenactivated
protein kinase cascade minimally consists of three
kinases such as MAPKKK, MAPKK and MAPK. The MAPK
cascades play important role in intra-cellular and extra-cellular
signaling in plants [1]. They play a essential roles in
transduction of diverse extra- cellular stimuli such as biotic and
abiotic stresses as well as a range of developmental responses
including differentiation, proliferation and death. Several
cascades are induced by different biotic and abiotic stresses
stimuli such as pathogen infections, heavy metal, wounding,
high and low temperature, high salinity, UV radiation, Ozone
reactive oxygen species, drought and high or low osmolarity.
MAPKs regulate a diverse set of processes, including
abscission, stomatal and ovule development, signals for various
abiotic stresses, and defense responses against bacterial and
fungal pathogens [2,
3]. Environmental stresses, such as cold,
drought, salinity and heavy metals are important factors that
affect growth and metabolism of plants. Several MAPK
cascades are induced by different stresses and mediate signal
transduction from cell surface to the nucleus [4]. Plant responds
to pathogen attack by activating multi-step defense responses,
including rapid production of reactive oxygen species (ROS),
strengthening of cell walls and induction of hypersensitive
response leading to localized cell death at the sites of infection.
Plant defense responses also include synthesis of pathogenrelated
protein and phytoalexins [4,
5]. It has been firmly
established that MAPKs play a central role in pathogen defense
in Arabidopsis, Tobacco, Tomato, Parsley, Brassica and Rice.Crystallographic studies demonstrate that approximately all
members of MAPK family share similar three dimensional
structures and function that are highly conserved. It functions
by protein-protein interaction and post translational
modification. MAPK showing protein-protein interaction to
different type of transcription factor such as WRKY, MYB, and
MYB related, NAC, AP-2 and bZIP etc. In earlier study at our
lab, we selected only six major transcription factor such as
WRKY, MYB, MYB related, NAC, AP-2 and bZIP because
literature survey shows that these transcription factor showing
protein-protein interaction to MAPK and bind to specific
promoter sequence and play a regulatory role in plant defense
mechanisms. Plants grown in the natural environment are
continually exposed to a variety of potential pathogens without
becoming diseased. This is because plants can identify and react
to pathogenic organisms and activate multiple defenses,
including the production of diverse antimicrobial metabolites
and protein [6].WRKY genes act as an important transcription factors
superfamily and they involved in response to environmental
stimuli, such as high salt, drought, heat, cool and other abiotic
stresses. They participate in plant growth and development and
material metabolic pathways, and also play an important
regulatory role in anti-viral, anti-bacterial and mechanical
injury pathways, showing that WRKY transcription factor have
a complex and important role in regulation [7]. Transcriptional
regulation of defense gene expression is a crucial part of plant
defense environment stresses. As one of the largest plant
transcription factor families, MYB transcription factors play an
important role in plant stress tolerance [8]. Protein encoded by
the NAC gene family constitute one of the largest plant-specific
transcription factors, which have been identified to play many
important role in both abiotic and biotic stress adaptations as
well as plant development regulation [9]. Transcription factors
of basic leucine zipper (bZIP) family control important process
in all eukaryotes. In plants, bZIPs are regulators of many central
developmental and physiological processes including
photomarphogenesis, energy homeostasis, and abiotic and
biotic stress responses [10]. In order to understand the multistep
signaling in such intricate process, there is a need of modeling
through computational tools. In the present study attempts
have been made to dissect the complex MAPK cascades
initiated in response to different stimuli through system biology
approach that shows the behavior of a single plant cell, using
modeling and simulation study.
Methodology
Construction of the MAPK activation Model:
Literature studies follow us to determine the relationships
between the species in the model Table 1 &
Table 2 (see
supplementary material). The network of MAPKs signaling
pathway was created using CellDesigner 4.1 (http://www.celldesigner.org/), software that enables user to describe
molecular interactions using a well defined and consistent
graphical notation [11,
12].
Simulation data:
In the present study, real concentration was not used as there
were no experimental investigations that reported quantitative
data for a single cell. In absence of quantitative data of a single
cell, it is not possible to define a concentration; that refer in term
of amount. We set every species in model equal to a unit of
amount, the value ranged 0.5 to 2.5. The amount of different
types of abiotic and biotic stresses was set equal to 0.5, amount
of receptors was set equal to 0.8, amounts of MAPK family
(MAPKKK, MAPKK and MAPK) was set equal to 1, amount of
transcription factor WRKY was set equal to 1.2, MYB 1.5, NAC
1.8, bzip 2, AP-2 2.2 and response was set equal to 2.5 as
amount. The data of molecular interaction are stored in System
Biology Markup Language (SBML; http://www.sbml.org/). SBML is
a standard machine readable model representation format
[13].
Model Kinetics:
The software SBMLsqueezer was used to generate kinetic rate
equations for our model. In which the kinetic equations have to
be associated with each reaction. This approach facilitates the
modeling step via automated generation of equation. The
software SBMLsqueezer offers different type of kinetics (i.e.
mass action, Hill, and several Michaelis-Menten based kinetics)
each including activation, inhibition and reversibility or
irreversibility for representing signaling pathways and
networks [14]. SBMLsqueezer generates the kinetic equation for
our model, which was then simulating in CellDesigner ver4.1.
Results
Description of model:
Model of the MAPK machinery activation in response to
various abiotic and biotic stresses in plants was created to
simulate MAPK signaling pathway for better understanding.
The Abiotic model (Figure 1) showing the action of abiotic
stresses such as cold, salt, Drought, H2O2, Heavy metal,
Ethylene on different types of receptors in cell surface and
activation of MAPK members in cytosol with downstream
transcription factors in nucleus, then showing the response
using phenotype symbol of System Biology Graphical Notation
(SBGN) in CellDesigner. Biotic model (Figure 2) showing the
action of biotic stresses such as bacterial pathogen and fungal
pathogen on MAPK machinery with upstream receptors and
downstream transcription factors, then showing the response
using phenotype symbol of SBGN in CellDesigner.
Figure 1
MAPK abiotic activation model was created using CellDesigner ver.4.1. The graphical representation is compliant with
system biology graphical notation (SBGN), Process diagrams, explicitly displaying simple molecules like abiotic stresses (Cold,
Salt, Drought, H2O2, Heavy metal, Ethylene), receptors, proteins (different members of MAPKs with transcription factors) some of
phosphorylated forms. The active state of the molecules is indicated by a dashed line surrounding the molecule and response in the
form of phenotype symbol by using different form of colors and shape for some species, the frame in yellow represents the cellular
membrane.
Figure 2
MAPK biotic activation model was created using CellDesigner ver.4.1. The graphical representation is compliant with
system biology graphical notation (SBGN), Process diagrams, explicitly displaying simple molecules like biotic stresses (Fungal
pathogens, Bacterial pathogens), receptors, proteins (different members of MAPKs with transcription factors) some of
phosphorylated forms. The active state of the molecules is indicated by a dashed line surrounding the molecule and response in the
form of phenotype by using different form of colors and shape for some species, the frame in yellow represents the cellular
membrane.
Model simulations:
Simulation can help us to understand the internal nature and
dynamics of biological processes and to arrive at well funded
prediction about their future development. Simulation results
of abiotic and biotic stress activation model shows that, when
the intensity of abiotic and biotic stresses were increases at this
time the responses like cell division, cell growth and cell
differentiation slow down rapidly.
Discussion
Modeling, the heart of system biology of complex processes is a
wide scientific discipline where many approaches from
different areas are confronted with the aim of betterunderstanding,
identifying and modeling of complex data
coming from various sources [15]. Systems biology facilitates
abiotic and biotic stress signaling studies allowing for more
robust identifications of molecular targets for future
biotechnological applications in crops [16]. Over the last decade,
in animal systems the MAP kinase pathway has been used
repeatedly as a testable paradigm for pioneering computational
system biology. By focusing on Ras-dependent activation of the
MAP kinase module, Huang and Ferrell developed the first
mathematical model that predicted highly ultra-sensitive
responses of the MAP kinase cascade [17]. Abiotic stress is
defined as environmental conditions that reduce growth and
yield below optimum levels. Plant responses to abiotic stresses
are dynamic and complex [18]. The level and duration of stress
can have a significant effect on the complexity of the response
[19]. Our integrated approach shows that a computational
model can generate and describe correctly the whole array of
MAPKs signaling pathway in response to various abiotic and
biotic stresses in plants.The concept of integrated biological system has emerged as a
means of envisioning how multifunctional biological process
operates as a whole [20]. Here, we attempted to evaluate the
current state of knowledge about MAPKs components in the
context of abiotic and biotic stresses to predict the behavior of
this pathway in stress condition. This model is able to
accurately predict the behavior of single cell according to
quantity of abiotic and biotic stresses. According to these data
the curve reported in (Figure 3a & 3b) has shown that when the
intensity of abiotic and biotic stresses increases, the cellular
responses like cell division, cell growth and cell differentiation
slow down. Therefore, the knowledge of the integrated
approach can be useful to develop new resistance approaches to
control and regulate MAPK machinery in plants systems.
Figure 3
a) Response curve showing the effect of abiotic stresses (Cold, Salt, Drought, H2O2, Heavy metal, Ethylene); b) Response
curve showing the effect of biotic stresses (Fungal pathogen, Bacterial pathogen).
Conclusion
Systems biology is an attempt to understand the living cells as
systems, rather than a collection of individual genes and
proteins. The present study has provided the dynamics and
behavior of the MAPK signaling pathway activated by several
abiotic and biotic stresses and able to respond to the external
perturbation in same way of the real cell. Therefore, system
modeling can provide an important insight in the operational
and common principles of organization of biological systems.
Also it can propose new experiments for testing assumption,
based on the modeling practice.
Authors: M Hucka; A Finney; H M Sauro; H Bolouri; J C Doyle; H Kitano; A P Arkin; B J Bornstein; D Bray; A Cornish-Bowden; A A Cuellar; S Dronov; E D Gilles; M Ginkel; V Gor; I I Goryanin; W J Hedley; T C Hodgman; J-H Hofmeyr; P J Hunter; N S Juty; J L Kasberger; A Kremling; U Kummer; N Le Novère; L M Loew; D Lucio; P Mendes; E Minch; E D Mjolsness; Y Nakayama; M R Nelson; P F Nielsen; T Sakurada; J C Schaff; B E Shapiro; T S Shimizu; H D Spence; J Stelling; K Takahashi; M Tomita; J Wagner; J Wang Journal: Bioinformatics Date: 2003-03-01 Impact factor: 6.937
Authors: I Kuperstein; E Bonnet; H-A Nguyen; D Cohen; E Viara; L Grieco; S Fourquet; L Calzone; C Russo; M Kondratova; M Dutreix; E Barillot; A Zinovyev Journal: Oncogenesis Date: 2015-07-20 Impact factor: 7.485
Authors: Michael Römer; Johannes Eichner; Andreas Dräger; Clemens Wrzodek; Finja Wrzodek; Andreas Zell Journal: PLoS One Date: 2016-02-16 Impact factor: 3.240
Authors: Andreas Dräger; Daniel C Zielinski; Roland Keller; Matthias Rall; Johannes Eichner; Bernhard O Palsson; Andreas Zell Journal: BMC Syst Biol Date: 2015-10-09