Complex Systems Biology of Networks: The Riddle and the Challenge - Systems Biology of Metabolic and Signaling Networks - page 20

signaling networks, which in turn regulate transcription factors. The modulation of
gene expression therefore represents a later event (Gherardini and Helmer-Citterich
2013 ). The rapid relaxation provided by molecular mechanisms involved in signal-
ing networks is crucial for fast adaptation (Aon and Cortassa 1997 ; Aon et al. 2004 ;
Lloyd et al. 1982 ). Signaling networks exhibit their own intrinsic dynamics (Bhalla
2003 ; Bhalla and Iyengar 1999 ; Eungdamrong and Iyengar 2004 ) (see Chap. 4 ) .
Several different kinds of dynamic behaviors have been described, among them
ultrasensitivity, bistability, hysteresis, and oscillations (Dwivedi and Kemp 2012 ;
Kholodenko et al. 2012 ). Ultrasensitive behavior arises in protein modification
cycles, whereas bistability stems from positive feedback loops, e.g., MAPK
cascades, present in signaling cascades that may result in all- or none responses.
Positive feedback loops alone or in combination with negative feedbacks can
trigger oscillations. Emergent properties such as negative-feedback amplification
could be demonstrated in the Raf-MEK-ERK signaling network with negative
feedbacks. The “negative-feedback amplifier” confers resistance to perturbations
of the amplifier resulting in resistance to inhibitors (e.g., that account for drug
resistance) (Kholodenko et al. 2012 ).
The output of mass-energy networks is the metabolome as constituted by
the ensemble of intracellular metabolites, e.g., cAMP, AMP, phosphoinositides,
Reactive oxygen species (ROS), or nitrogen (RNS) species (Fig. 2.2 ). The outcome
of information networks is represented by mRNAs, proteins or small peptides, and
growth and transcriptional factors. Metabolites such as ROS, cAMP, and ADP
exhibit a dual role; on the one hand, they are essential constituents from
mass-energy networks that produce them, but on the other hand, they may act as
intracellular sensors/messengers with allosteric effects (positive or negative) that
react on enzymatic activities present in signaling networks. These dual roles of
metabolites compose crucial cellular mechanisms in response to increasing envi-
ronmental challenges (e.g., oxygen or substrate restriction) or cues (e.g., light,
temperature). For example, the alterations of AMP:ATP ratio in response to
starvation activates the AMPK signaling pathway, and at the same time AMP
functions as an allosteric activator of the AMP kinase within the signaling network
thus contributing to modulation of its dynamics. This results in the activation of
catabolic and repression of anabolic processes thereby modulating the spatio-
temporal unfolding of the mass-energy networks by, e.g., favoring organelle
autophagy over biogenesis.
The spatio-temporal dynamics of the fluxome (Fig. 2.2 ) changes in response to
signaling networks, through which cells can modulate, suppress, or activate gene
expression (transcription, translation), whole metabolic pathways (e.g., respiration
and gluconeogenesis during carbon catabolite repression), or specific enzymatic
reactions within them.
Signaling networks are characterized by specific: (1) components and
mechanisms; (2) metabolic pathway targeted; (3) conditions for signaling activa-
tion; and (4) physiological response (Cortassa et al. 2012 ). Each one of these
characteristics can be identified in the AMP-activated protein kinase (AMPK)
signaling pathway.