Statistical Analysis of the Experimental Variation in the Proteomic Characterization of Human Plasma by Two-Dimensional Difference Gel Electrophoresis

Abstract

The complexity of human plasma presents a number of challenges to the efficient and reproducible proteomic analysis of differential expression in response to disease. Before individual variation and disease-specific protein biomarkers can be identified from human plasma, the experimental variability inherent in the protein separation and detection techniques must be quantified. We report on the variation found in two-dimensional difference gel electrophoresis (2-D DIGE) analysis of human plasma. Eight aliquots of a human plasma sample were subjected to top-6 highest abundant protein depletion and were subsequently analyzed in triplicate for a total of 24 DIGE samples on 12 gels. Spot-wise standard deviation estimates indicated that fold changes greater than 2 can be detected with a manageable number of replicates in simple ANOVA experiments with human plasma. Mixed-effects statistical modeling quantified the effect of the dyes, and segregated the spot-wise variance into components of sample preparation, gel-to-gel differences, and random error. The gel-to-gel component was found to be the largest source of variation, followed by the sample preparation step. An improved protocol for the depletion of the top-6 high-abundance proteins is suggested, which, along with the use of statistical modeling and future improvements in gel quality and image processing, can further reduce the variation and increase the efficiency of 2-D DIGE proteomic analysis of human plasma.

Quantitative proteomics: assessing the spectrum of in-gel protein detection methods

“…While lys residues are almost ubiquitous in proteins, inter-protein variability can be expected as proteins do not have uniform amino acid content and lower abundance proteins are less likely to be labeled [10,132]. In addition, it has also been reported that gel-to-gel variation still contributes most of the inherent variability to DIGE [144]. It is also important to consider the ramifications of selectively labeling a sample and subsequently loading only a fraction of this sample for electrophoresis; the total complement of detectable protein is thus reduced by the very design of the protocol used for detection.…”

Multivariate Statistical Analysis of Diverse Strains of Yersinia pestis by Comparative Proteomics

“…For example, it is possible to analyze proteomic data using statistical packages [15]. These statistical analysis software packages can result in increased confidence for the differential expression data, but require extensive statistical expertise [16][17][18]. The Extended Data Analysis (EDA) module of DeCyder serves as an alternative analysis tool which can provide multivariate statistics, such as principal component analysis (PCA) [19][20][21][22], hierarchical clustering [23][24][25][26], K-means clustering [27], and biomarker selection [28][29][30], and can be evaluated by scientists with less statistical expertise.…”

Analysis of DIGE data using a linear mixed model allowing for protein‐specific dye effects

“…Karp and Lilley [16] noted that a certain spot was much brighter in the Cy5 image than in the Cy3 image. In a recent study of experimental variation in DIGE, Corzett et al [22] employed a linear mixed model, which included a protein-specific dye term. We, therefore, chose to carry out a systematic analysis of dye effects in DIGE.…”

“…The dye correcting term in the linear mixed model is the same as the one used in Corzett et al [22] and in the microarray literature [24,30]. The paper by Corzett et al [22] analyzes experimental variation in DIGE experiments and they included the dye term without discussing or showing the necessity of a dye correction.…”

“…The paper by Corzett et al [22] analyzes experimental variation in DIGE experiments and they included the dye term without discussing or showing the necessity of a dye correction. A total of 12 gels were used and no dye effects were observed.…”