The Control Analysis of Signal Transduction - Systems Biology of Metabolic and Signaling Networks - page 37

of NADH through a network of processes that involves the electrochemical poten-
tial difference for protons across the inner mitochondrial membrane (Mitchell
1961 ). The required robustness towards fluctuations and intrinsic noise is a neces-
sary property of the stable stationary state a system relaxes to; the balancing of
control coefficients and component properties this requires is at the basis of some of
the laws of metabolic control analysis (Westerhoff and Chen 1984 ). The robustness
against sustained perturbations in parameter values is greatly enhanced by the
feature that biological functions depend on the integral of multiple processes that
would typically be perturbed independently (Quinton-Tulloch et al. 2013 ).
In all these cases it is particular interactions between processes or substances that
lead to what is essential for biology. These particular interactions deviate from
mainstream physics in that they do not correspond to the simplest case but rather to
the most functional case. They may lead away from Onsager's precise reciprocity
relations (Westerhoff and Dam 1987 ) that are valid near equilibrium (Cortassa
et al. 1991 ). It is these particular cases of physics, away from mainstream physics,
that “systems biology” should focus on.
With all this, is the whole still the sum of the parts, or is it different from that?
Well, physiology continues to be the sum of the parts in the way the parts are active
in vivo and in situ. However, when together, the parts behave in ways that are
different from how they behave in isolation. One reason is that the conditions
in vivo are different from what they are when we characterise the parts in isolation
and the differences matter for the activity of the parts (van Eunen et al. 2010 ;
Garc ´ a-Contreras et al. 2012 ). However, a second and more important reason is that
these conditions themselves are influenced by the components. This may put in
place a regulatory loop through which a component on itself depends on the
response the other components' activities exhibit to changes in its behaviour. It is
this aspect of regulatory looping that we cannot measure by assaying each compo-
nent in isolation of all other components, even if we perform this measurement
under otherwise in vivo conditions. It is in this second aspect where the functioning
whole may differ essentially from the sum of the parts functioning in isolation.
We can only evaluate this aspect properly by measuring the components
together, in situ (i.e. by observing physiology), or by measuring their properties,
inclusive of their response properties, in vitro, and then reconstructing their collec-
tive behaviour in silico, i.e. in a computer model (Westerhoff et al. 2009b ). The
latter strategy enables understanding as well as observation, as it allows one to
change parameter values in the model and evaluate the consequences. This strategy
is the essence of systems biology: systems biology is about the difference between
the whole and the sum of the parts in isolation (Alberghina and Westerhoff 2005 ).
Thereby the essence of systems biology are the regulatory loops (or spirals) that
enable a system's component to influence its own behaviour in ways that depend on
the activity of other components, and this then for all components that are involved.
Since virtually all molecules of a living cell are connected (Wagner and Fell 2001 ),
this makes systems biology an activity that is in principle genome-wide.
Components interact in various ways. A direct mode of interaction is that of
metabolism, where a substrate and a product of an enzyme in a metabolic pathway