In order to elucidate the molecular mechanisms that condition a complex biological phenomenon such as Al tolerance, one important approach is the protein expression profiling in root tips of Al tolerant and sensitive maize genotypes. The goals here will be to identify proteins that exhibit a higher level of expression in the presence of Al in Al tolerant versus sensitive NILs for specific QTLs. The coordinated identification of highly expressed Al tolerance genes and proteins will help validate the selection of Al tolerance candidates.
Protein expression profiling. To profile patterns of protein expression in maize root tips, we propose to use high resolution, two-dimensional difference in-gel electrophoresis (2D-DIGE) This approach involves the covalent labeling of two protein extracts with different spectrally resolvable fluorescent cyanine dyes (Cy3 or Cy5). The two labeled protein samples are mixed, separated on the same 2-D gel and scanned on a variable wavelength, laser-based imaging system. Since the Cy dyes exhibit distinct excitation and emission spectra, it is possible to quantify and distinguish between proteins that were present in the original two extracts. Furthermore, since the Cy dyes are both mass and charge matched, any proteins that exist in both populations will migrate to the same location, dramatically facilitating comparisons of protein expression in the two protein samples. A third fluorescent dye, Cy2, will be used to label an internal calibrant to normalize subsequent statistical analysis. This allows a much more accurate statistical analysis of protein expression across multiple DIGE gels . Proprietary software (Progenesis SameSpots, Nonlinear Dynamics) will be used to optimize gel imaging, spot quantification, annotation and statistical aspects of the gel image comparisons. Proteins that are shown to exhibit changes in expression that correlate with Al tolerance/sensitivity will be excised from the gels, digested with trypsin and identified by mass spectrometry.
We will use 2-D DiGE to analyze the water soluble protein extracts. The analyses will be divided into ???experimental blocks??? using overlapping combinations of narrow pI range 24 cm IPG strips. Each DIGE analysis will be repeated at least three times for each comparison to improve the statistical validity of the data. Prior to electrophoresis, root tip protein extracts from maize tolerant/sensitive NIL pairs, or +/- Al treatments will be labeled with the Cy3 and Cy5 fluorescent dyes and compared pair wise. A third dye (Cy2) will be used to label an internal standard consisting of an equal parts mixture of all the samples in the experiment. The samples and internal standard will be labeled under ???minimal labeling??? conditions ensuring accurate protein quantification (Tonge et al., 2001). Quantitative comparisons of proteins between gels will be made based on the change in spot volume of the proteins in the samples relative to their spot volumes in the internal standard. This approach minimizes systematic variation enabling accurate quantification of biological changes between samples. To conform to best experimental practice, a randomized experimental design will be employed. Such an approach was found to improve the accuracy of protein quantification, allowing accurate detection of differences in protein expression as small as 10% with greater than 95% statistical confidence. To reveal both the position and relative abundance of the proteins following 2-DE, gels will be scanned on a Typhoon 9400 variable mode imager. The digitized gel images will be analyzed using Progenesis SameSpots software package. To determine what level of variability constitutes a significant change, we will use a Student???s T Test and analysis of variance. Proteins showing significant differential expression (P < 0.05) will be studied.
Proteins whose expression is shown to correlate with Al tolerance/sensitivity will be digested in situ with trypsin. The peptide produced will be extracted, and analyzed to generate peptide mass fingerprint (PMF) and MS/MS data using either a Model 4700 Proteomics Analyzer (MALDI TOF/TOF) or a Model 2000 Q-trap linear ion trap equipped with a nano electro spray ionization (nESI) interface. The data generated will be used to search the MaizeSeq Database ( http://www.maizeseq.org/html/index2.htm) for proteins capable of producing peptides and fragment ions consistent with the experimental data using GPS Explorer software. We expect to identify and characterize a large number of proteins that are likely associated with Al tolerance in maize. We will utilize databases such as Celera Discovery (available in-house through the GPS Explorer program), DIP (http://dip.doe-mbi.ucla.edu/dip/Guide.cgi) and KEGG (http://www.genome.ad.jp/kegg/), that provide information about protein-protein interactions and metabolic pathways. We will examine each protein for its possible involvement in relevant metabolic processes. In this way, we can prioritize the proteins to identify the best candidates for future study.