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. The latter were selected as the model system for this type of analysis, because they provide a well-controlled growth environment, ensuring that the observed plant response is due only to the applied perturbation. An enhanced gas chromatography-mass spectrometry (GC-MS) metabolomic data correction strategy and a new algorithm for the significance analysis of time-series "omic" data are used to extract information about the plant's transcriptional and metabolic response to the applied stress from the acquired datasets; in this article, it is the first time that these are applied for the analysis of a large biological dataset from a complex eukaryotic system. The case-study involved Arabidopsis thaliana liquid cultures subjected for 30 h to elevated (1%) CO2 stress. The advantages and validity of the methodological framework are discussed in the context of the known A. thaliana or plant, in general, physiology under the particular stress. Of note, the ability of the methodology to capture dynamic aspects of the observed molecular response allowed for 9 and 24 h of treatment to be indicated as corresponding to shifts in both the transcriptional and metabolic activity; analysis of the pathways through which these activity changes are manifested provides insight to regulatory processes.
Dutta
Bhaskar
B
Metabolic Engineering and Systems Biology Laboratory, Department of Chemical & Biomolecular Engineering, University of Maryland, College Park, Maryland 20742.
Kanani
Harin
H
Metabolic Engineering and Systems Biology Laboratory, Department of Chemical & Biomolecular Engineering, University of Maryland, College Park, Maryland 20742.
Quackenbush
John
J
Metabolic Engineering and Systems Biology Laboratory, Department of Chemical & Biomolecular Engineering, University of Maryland, College Park, Maryland 20742.|The Institute for Genomic Research (TIGR), Rockville, Maryland 20850.
Klapa
Maria I
MI
Metabolic Engineering and Systems Biology Laboratory, Department of Chemical & Biomolecular Engineering, University of Maryland, College Park, Maryland 20742.|Metabolic Engineering and Systems Biology Laboratory, Institute of Chemical Engineering and High Temperature Chemical Processes (ICE-HT), Foundation for Research and Technology-Hellas (FORTH), GR-265 04 Patras, Greece.
D017360:Arabidopsis / Q000737:chemistry / Q000235:genetics / Q000502:physiology*; D002478:Cells, Cultured; D020869:Gene Expression Profiling; D018506:Gene Expression Regulation, Plant; D055442:Metabolome; D013312:Stress, Physiological; D049490:Systems Biology; D013997:Time Factors