Metabolic Dissipative Structures - Systems Biology of Metabolic and Signaling Networks - page 195

(II) the density of effective links increases from 10.802 (two stimuli) to 13.580 (one
stimulus), and (III) not only the density increased but the connections were made
stronger (mean values increase from 0.079 to 0.133 and the maximum value of
effective connectivity is 0.377 versus 0.179 molecular information bits).
The metabolic core also manifests qualitative and quantitative changes in the
molecular information flows. Specifically, increasing the TE values and modifying
the connectivity to several subsystems, for example, under stimuli S1 and S2, the
core receives a causal information flow with a TE

0.116 from MSb8 (Fig. 8.6 ).
When the substrate input flux S2 is removed, the directionality of the signal reverses
and the core sends an information flow of TE ¼ 0.153 to MSb8 (see Fig. 8.6 ).
TE analysis reveals that a systemic functional structure of effective information
flows emerges in the network, which is able to modify the catalytic activity of all
the metabolic subsystems. Moreover, the level of information flows is highly
responsive to environmental influences.

¼

8.3.2 Modular Organization of the Biomolecular
Information Flows: Metabolic Switches

Our analyses also showed a modular organization of the effective information flows
in which some sets of catalytic subsystems are clustered forming functional meta-
bolic sub-networks. A detailed study of TE data allows us to infer different modular
organization: (I) a set of effective connections between certain subsystems is
preserved under both external conditions (Module

) (Fig. 8.5 a1-a2), (II) a second
sub-network of effective information flows exhibit reverse directionality (Module
β

α

) (Fig. 8.5 b1-b2), meaning that the TE connections are preserved but their
direction is inversed, and (III) the third set of connections emerges only in one of
the stimulation conditions (Modules ) (Fig. 8.5 c1-c2).

Under both stimuli S1 and S2, the diversity of the enzymatic behavior is
systemically self-regulated by means of modules

γ and δ

. However, when
only a stationary input flux of substrate S1 is considered, the network undergoes a
dramatic reorganization of all catalytic dynamics exhibiting flux and structural

α , β , and γ

Fig. 8.5 (continued) not scale with the TE value as it was plotted as thin as possible to be
visualized. The values of TE are statistical significant ( p value < 0.05, Bonferroni correction,

n 50 experiments). The metabolic subsystem activities shape four modules of effective connec-

tivity. Panels a1-a2, the module

¼

is preserved during both external stimuli; Panels b1-b2, a
second sub-network of effective information flows are preserved but with inverted directionality
(Module

α

); Panels c1-c2, a third class of modules emerges only in one of the external
perturbations considered (Modules

β

); Panels d1-d2, all modules together. The transitions
between modules (metabolic switches) provoke permanent changes in all catalytic activities of the
metabolic subsystems, and these metabolic switches are triggered by changes in the external
conditions (I: two stimuli S1 and S2, II: only stimulus S1). Adapted from Fig. 5 in (De la Fuente
et al. 2011 )

γ and δ