52
this physiological “divergence” between the effect of these stresses on the plants
when they are applied separately, is finally manifested when these perturbations are
combined on plants. Interestingly, physiological (Geissler et al. 2010 ; Perez-Lopez
et al. 2009 , 2012 ; Ratnakumar et al. 2013 ; Takagi et al. 2009 ) and high-through-
put omic studies (Kanani et al. 2010 ) have shown that short-term application of
elevated CO 2 in the growth environment of salt-stressed plants can alleviate the
negative effect of high salinity on the plant growth. Different justifications have
been provided for this observation, with more prevalent the one supporting that
the additional CO 2 contributes to the maintenance of the redox homeostasis of the
plants (Perez-Lopez et al. 2009 ). According to the presently single integrated tran-
scriptomic and metabolomic analysis of the combined high-salinity and short-term
elevated CO 2 perturbations on Arabidopsis thaliana plant liquid cultures presented
below (Kanani et al. 2010 ), a major reason for the positive effect of the elevated
CO 2 on the salt-stressed plants is the availability of additional carbon resources. The
latter enable the plants to produce the required osmoprotectant metabolites while at
the same time maintaining their normal growth rate.
3.3 Integrated High-Throughput Biomolecular Analyses
in Plant Systems Biology
The technologies for high-throughput biomolecular analysis (omics) have revolu-
tionized the way in which questions are approached in life sciences. Rather than
examining a small number of genes and/or reactions at any one time, we can now
begin to look at gene expression and protein activity in the context of networks and
systems of interacting genes and gene products (Sussman et al. 2009 ). Because our
knowledge of this domain is still not extensive, investigations are now routinely
moving from being purely “hypothesis driven” to being largely “data driven” with
analysis based on a search for biologically relevant patterns from which network
structures could be inferred. Recent developments have shown that educated use of
the existing biological knowledge in the application of data mining methods can in-
deed lead to the reconstruction of the active biomolecular networks at each level of
molecular function that characterize a particular physiology (“knowledge”-driven
approach). These technological advances have created enormous opportunities for
accelerating the pace of science. One can now envision the possibility of obtain-
ing a comprehensive picture of the mechanisms underlying the cellular function,
its regulation, and the interactions of an organism with its environment. While the
greatest attention to date has been paid to gene sequence and transcriptional expres-
sion analysis using mainly microarrays, it is becoming increasingly clear that these
alone cannot be used to accurately determine cellular function and system physiol-
ogy. Rather, a comprehensive analysis of biological systems requires the integration
of all fingerprints of cellular function (Vidal 2009 ), i.e., genome sequence, tran-
scriptional, proteomic, and metabolic profiles, and flux distributions. While each of
these fingerprints has significant value on its own, the picture that emerges from any
single approach is quite limited in nature. Gene transcription is a necessary but not
M.-E. P. Papadimitropoulos and M. I. Klapa