Biology Reference
In-Depth Information
track of the bigger picture. In ethoecology, animal behavior
at the single individual level is studied to deduce general
principles of evolution that are also used to obtain insights
into population dynamics. As a more pertinent example,
although the amino acid sequences of many proteins and
the interaction rules of amino acids are known, we are still
unable to compute the folded structure of a protein from its
amino acid sequence. The problem needs to be studied at its
proper scale, hence the main tool in structural biology is
measuring the structure of a folded protein with crystal-
lography or NMR. From this structure we can derive
putative interaction partners or correlate the structural
differences of isomers with their respective functional
differences. Conversely, complete knowledge of structure
and functionality of, for example, a small G protein on
a molecular level will never be sufficient to explain its role
in the cellular context. To resolve this, additional layers of
information, for example intracellular localization, the role
of this protein in the different signaling networks, and their
impact on inter- and intracellular communication, must be
integrated. In this respect, systems biology is not supposed
to be a new tool to gather detailed information on an iso-
lated facet of biology. Instead, it strives to holistically
collect data and paradigms from different disciplines into
a more complete representation of the investigated problem
at the correct scale. From this, the rules that govern systems
behavior at different scales can then be extracted.
In cellular systems biology we are trying to piece
together complex networks of protein interactions, which at
first glance might be reduced to a few components that
nonetheless yield an extraordinarily large diversity. This is
inextricably linked to pattern formation, as can be seen
from the fact that in vitro experiments rarely reproduce or
quantify the in vivo functionality of proteins. The reason
for this is the trivial seeming difference between a cell and
a beaker: the beaker is well mixed, isotropic and large,
while a cell is viscous, structured with shifting compart-
mentalization, but at least still large in comparison to the
nanometer-size of a protein. In a real sense, cell biology
boils down to pattern formation, because in its constant
striving against entropy a cell must be continuously and
consistently rebuilt. In this way, a cell depends on robust
mechanisms of self-organization and thus poses the ideal
platform to adapt these mechanisms to new functionality.
On a larger organism scale, pattern formation is well
established. In the 1960s the coloration of animals was
linked to the action of so-called morphogens
[4]
. The
interplay of apoptotic and proliferative networks via tissue
spanning morphogenetic cues can result in embryonic
changes. This is how tissue determines where to grow the
fingers of a hand, and how to 'retract' a tadpole's tail. And
the ability to differentiate tissue into veins on cue is
essential for wound healing, and detrimental in case of
tumor angiogenesis factor-induced tumor vascularization.
Similarly, the coupling of electrical and chemical stimuli
across nerve cells with the intracellular protein state
generates long-term memory in the brain. Furthermore,
chemical synchronization by cyclic adenosine mono-
phosphate (cAMP) waves analogous to the BZ reaction
generates spatial organization in one stage of the lifecycle
of Dictyostelium discoideum. When the resources of their
environment diminish, single Dictyostelium cells exude
cAMP. Neighboring cells not only can hydrolyze cAMP by
a membrane-bound phosphodiesterase, but have receptors
that are part of a system to sense shallow cAMP gradients
with high precision and trigger a delayed but amplified
cAMP release
[5]
. In close analogy with the BZ reaction,
excitation centers are self-organized by spiral waves of
cAMP. Dictyostelium uses this to organize a chemotactic
gradient that leads to a multicellular organism. In reacting
to this gradient, single Dictyostelium cells generate motive
force by a very complex network of extracellular adhesions
and intracellular cytoskeletal interactions. This last type of
network is especially challenging, because correlation
between spatial, temporal and compositional structure of
the extracellular contacts is not clear. Does the context
define the network motifs that organize the contacts, or vice
versa?
For cell motility in tissue patterning the direction of
cause and effect is unclear, which makes it an example of
self-organization. With simultaneous upward and down-
ward causation the large-scale patterns modulate the same
local interactions from which they emerge. While the
formation of the Dictyostelium slug on a larger scale
obviously represents a self-organizational process, on the
tissue level this type of intracellular pattern formation has
been poorly represented in the literature, although it
follows some similar principles, such as the emergence of
patterning by coupling an autocatalytic amplification with
a negative feedback. For example, these principles of self-
organization are easily understood for cell polarity in the
yeast Saccharomyces cerevisiae as a related phenomenon
[6]
. The essential component to establish cell polarity is
CDC42, a membrane-bound small G protein of the Rho
subfamily. Translocation of CDC42 to a subcellular spot
triggers downstream cytoskeletal reorganization. Consider
the interconnecting levels: a symmetric cell establishes an
asymmetric protein distribution to derive an asymmetric
cell shape. But how to spontaneously establish the neces-
sary CDC42 localization from otherwise symmetric initial
conditions? In contrast to the analogy of a parked car
waiting to be started, proteins in cells are perpetually
synthesized, modified, degraded and
most importantly
e
in motion. This refers to diffusion as well as a protein's
'state', as defined by its binding partners and post-trans-
lational modifications. In the case of the CDC42
protein these are different but interlinked processes: as a G
protein it can exist in a GTP- or GDP-bound state, and as
e
