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As discussed above, the responses of the plants to various perturbations depend
also on the duration of the treatment. Time-series experiments are preferable to
gain deeper insight into the physiology of the plants as a function of the exposure
duration to stress. The first sampling should be carried out just before the perturba-
tion/treatment is applied to monitor the physiological state of the plants at the time
zero of the experiment. The rest of the samplings should be scheduled in such a
way to allow for the determination of the short-, mid-, and long-term responses
of the particular plant species (or cultivar or ecotype) to the applied perturbation/
treatment. When scheduling the sampling points, the circadian rhythm of the plants
and the difference in the timescale of the response between the transcriptional and
the metabolic processes should also be taken into consideration. Cramer et al. con-
ducted an interesting time-series experiment to study the metabolic responses of the
grapevine to high salinity and drought (Cramer et al. 2007 ). Instead of using one
fixed concentration of NaCl for the high-salinity “perturbed” plants, they started the
experiment with zero salt concentration in the irrigating solution and increased it
gradually over time. This experimental design enabled them to make the separation
between the plant responses due to the water-deficit effects and those arising from
ionic effects within the plants.
Three to six plants per group and per time point usually provide an adequate num-
ber of biological replicates for the extraction of accurate results from omic analyses.
In most of the studies cited above, leaves were sampled. Leaves are the main photo-
synthetic organs of plants and their reaction to elevated CO 2 and the salt stress is of
great interest. However, the first tissues that experience the salinity of the medium
or the soil are the roots, so it would be of value for the roots to be sampled and their
response to the applied perturbation(s) to be studied in comparison with that of the
leaves. Immediately after sampling, the collected samples should be frozen in liquid
nitrogen and kept at − 80 °C until further processing. Freezing with liquid nitrogen
is essential to stop all the enzymatic processes in the samples and to protect thermo-
sensitive molecules like sugar phosphates and mRNA molecules from degradation.
If the collected amount permits, the same sample should be divided and used for the
extraction of mRNAs, proteins, and metabolites for integrated omic analyses.
Great care should be paid to eliminate or correct for various systematic biases
introduced at various stages of the multistep omic analyses (see Fig. 3.1). For
example, in a typical metabolomic analysis, injection errors or unequal division
of a sample into replicates could affect the metabolic profiles. These types of er-
rors affect equally all metabolites detected in a profile. To account for these biases,
internal standard normalization is required. The selected internal standard should
not be produced by the plant species of interest. Ribitol or isotopes of known me-
tabolites are commonly used as internal standards in plant MS metabolomics (Fiehn
et al. 2001 ; Roessner et al. 2000 ). Errors that affect specific metabolites may also
occur. In the case of GC–MS metabolomics, the metabolites have to be deriva-
tized so that they are converted to their volatile, nonpolar, and thermostable deriva-
tives. The most common method for derivatization involves the conversion of the
original metabolites to their methoxime (MEOX) and trimethylsilyl (TMS) deriva-
tives ( Roessner et al. 2000 ). However, some metabolites produce more than one
M.-E. P. Papadimitropoulos and M. I. Klapa