[Show abstract][Hide abstract] ABSTRACT: Labeling whole Arabidopsis (Arabidopsis thaliana) plants to high enrichment with 13C for proteomics and metabolomics applications would facilitate experimental approaches not possible by conventional methods. Such a system would use the plant's native capacity for carbon fixation to ubiquitously incorporate 13C from 13CO2 gas. Because of the high cost of 13CO2 it is critical that the design conserve the labeled gas.
A fully enclosed automated plant growth enclosure has been designed and assembled where the system simultaneously monitors humidity, temperature, pressure and 13CO2 concentration with continuous adjustment of humidity, pressure and 13CO2 levels controlled by a computer running LabView software. The enclosure is mounted on a movable cart for mobility among growth environments. Arabidopsis was grown in the enclosure for up to 8 weeks and obtained on average >95 atom% enrichment for small metabolites, such as amino acids and >91 atom% for large metabolites, including proteins and peptides.
The capability of this labeling system for isotope dilution experiments was demonstrated by evaluation of amino acid turnover using GC-MS as well as protein turnover using LC-MS/MS. Because this 'open source' Arabidopsis 13C-labeling growth environment was built using readily available materials and software, it can be adapted easily to accommodate many different experimental designs.
[Show abstract][Hide abstract] ABSTRACT: To conduct studies of stable isotope incorporation and dilution in growing plants, a rapid microscale method for determination of amino acid profiles from minute amounts of plant samples was developed. The method involves solid-phase ion exchange followed by derivatization and analysis by gas chromatography-mass spectrometry (GC-MS). The procedure allowed the eluent to be derivatized directly with methyl chloroformate without sample lyophilization or other evaporation procedures. Sample extraction and derivatization required only ca. 30min and quantification of the 19 amino acids eluted from the cation exchange solid-phase extraction step from a single cotyledon (0.4mg fresh weight) or three etiolated 7-day-old Arabidopsis seedlings (0.1mg fresh weight) was easily accomplished in the selected ion monitoring mode. This method was especially useful for monitoring mass isotopic distribution of amino acids as illustrated by Arabidopsis seedlings that had been labeled with deuterium oxide and (15)N salts. Sample preparation was facile, rapid, economical, and the method is easily modified for integration into robotic systems for analysis with large numbers of samples.
Journal of chromatography. B, Analytical technologies in the biomedical and life sciences 08/2010; 878(24):2199-208. · 2.78 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Rapid environmental responses in plants rely on endogenous signaling mechanisms, which in many cases are mediated by changes in protein turnover rates. It is therefore necessary to develop methods for measuring protein dynamics that monitor large sets of plant proteins to begin to apply a systems biology approach to the study of plant behavior. The use of stable isotope labeling strategies that are adaptable to proteomic methods is particularly attractive for this purpose. Here, we explore one example of such methods that is particularly suitable for plants at the seedling stage, where measurement of amino acid and protein turnover rates is accomplished using a heavy water labeling strategy. The method is backed by microarray evaluation to define its feasibility for specific experimental approaches, and the CULLIN-ASSOCIATED AND NEDDYLATION DISSOCIATED 1 (CAND1) and TRANSPORT INHIBITOR RESPONSE 1 (TIR1) proteins are used to illustrate the potential utility in understanding hormonal signaling regulation. These studies provide insight not only into the potential utility of the method, but also address possible areas of concern regarding the use of heavy water labeling during plant growth. These considerations suggest a prescription for specific experimental designs that minimize interference resulting from the induction of treatment-specific gene expression in the results obtained.
The Plant Journal 08/2010; 63(4):680-95. · 6.82 Impact Factor