Individual vs. combinatorial effect of elevated CO2 conditions and salinity stress on Arabidopsis thaliana liquid cultures: comparing the early molecular response using time-series transcriptomic and metabolomic analyses.

Background: In this study, we investigated the individual and combinatorial effect of elevated CO2 conditions and salinity stress on the dynamics of both the transcriptional and metabolic physiology of Arabidopsis thaliana liquid hydroponic cultures over the first 30 hours of continuous treatment. Both perturbations are of particular interest in plant and agro-biotechnological applications. Moreover, within the timeframe of this experiment, they are expected to affect plant growth to opposite directions.

Time-series integrated "omic" analyses to elucidate short-term stress-induced responses in plant liquid cultures.

The research that aims at furthering our understanding of plant primary metabolism has intensified during the last decade. The presented study validated a systems biology methodological framework for the analysis of stress-induced molecular interaction networks in the context of plant primary metabolism, as these are expressed during the first hours of the stress treatment. The framework involves the application of time-series integrated full-genome transcriptomic and polar metabolomic analyses on plant liquid cultures.

Standardizing GC-MS metabolomics.

Metabolomics being the most recently introduced "omic" analytical platform is currently at its development phase. For the metabolomics to be broadly deployed to biological and clinical research and practice, issues regarding data validation and reproducibility need to be resolved. Gas chromatography-mass spectrometry (GC-MS) will remain integral part of the metabolomics laboratory.

Data correction strategy for metabolomics analysis using gas chromatography-mass spectrometry.

Gas chromatography-mass spectrometry metabolomics requires the original sample's derivatization. Therefore, systematic biases that might distort the one-to-one proportional relationship between the original metabolite concentration and derivative peak area profiles have to be considered. The first type of such biases change only the value of the proportionality constant between the two profiles among samples and are corrected by the use of an internal standard.