Biology Reference
In-Depth Information
2.2. What is contemporary systems biology?
Development of the various high-throughput technologies used in genome
sequencing, transcriptomics, proteomics and metabolomics have enabled the
comprehensive analysis of complete living systems in terms of the identity and
concentration of all their components (Joyce & Palsson, 2006). However, on
their own these methodologies will not lead to the understanding of the living
cell, hence of life, for they do not study the interactions between those molecules
and their organization within the cell. Reaching such understanding will require
a systems biology that is defined as the science that deciphers how biological
functions arise from the interactions between components of living organisms.
Because the simplest systems that are alive are unicellular organisms, systems
biology studies the gap between ('dead') molecules and life, and it is on this
new terrain that the contents of this topic focus.
2.3. Approaches to systems biology
Two approaches to systems biology can be distinguished: Top-down and
bottom-up systems biology (see Chapters 2 and 9). Top-down systems biology
starts with experimental data on the behaviour of molecules in living systems
as a whole. Nowadays, this is often done using high-throughput approaches to
measure types and levels of (macro)molecules in the cell on a large scale, e.g.
through metabolomics, transcriptomics, proteomics or fluxomics, together called
functional genomics (Joyce & Palsson, 2006). In the analysis of such data, new
hypotheses on the molecular organization and functioning of the organism may
be induced on the basis of correlations in the behaviour of the concentrations of
the molecules (Kell, 2004). In contrast, bottom-up systems biology starts from
the interactive properties of the molecules and determines how these interac-
tions lead to functional behaviour. The interactions affect or effect processes
that enable a living system to develop in time or maintain its state through pro-
cesses that repair damage or compensate for dissipation. In some systems, the
molecular constituents are sufficiently understood to allow the construction of
detailed kinetic models of reaction networks ('silicon cells') (Bakker et al., 1997;
Kholodenko et al., 1999; Rohwer et al., 2000; Teusink et al., 2000; Bruggeman
et al., 2005). The emergent properties are predicted by calculating how the model
behaves
in silico
and compared to observations made on the system level. The
lack of correspondence leads to the discovery of interactive or organizational
properties that are important for biological function (e.g. Teusink et al., 1998;
Bakker et al., 2000). Such properties are then inserted in new generations of the
model, and eventually detailed and accurate models should be obtained. These
can be used to design drugs
in silico
(Bakker et al., 2002) to engineer strains for
biotechnology (Hoefnagel et al., 2002) or to better understand how molecules
