Figure 1.
Steps in the acquisition and processing of RPPA data.
Cells derived from different in vitro and in vivo systems are lysed and protein extracted (1). Serially diluted extracts are printed onto the surface of slides (2) where primary and secondary antibodies bind to the protein of interest and generate a signal proportionate to the amount of protein in each sample. Each slide can accommodate 5808 printed spots, for different numbers of total samples depending on the layout and number of dilutions used (3). Readouts obtained are translated to sample intensities after scanning and processing of the slides (4). Intensities of positive control spots (horizontal yellow spots in (4)), which are technical replicates of each other, may be used to evaluate and correct spatial variation observed in each slide. Spatial correction of data can improve data quality resulting in better estimates of relative protein concentration and improved agreement between inter- and intra-slide replicates from various experiments.
Figure 2.
In the experimental design we use for the analysis of the samples in sets A and B, lysate is spotted in 96 arrays consisting of 22 samples, two positive controls and one buffer spot each.
Each of the samples and the positive controls is printed in five 1∶2 serial dilutions each.
Figure 3.
Coefficient of variation (%CV) of biological replicates across all antibodies before and after normalization clearly improve with normalization.
The degree of improvement varies from antibody to antibody (higher for EGFR-pY992 and cJUN-pS73 than YB1-pS102) and is significant for many antibodies relevant to signaling in the melanoma cell lines studied.
Figure 4.
Spatial normalization reduces variance between biological replicates in the majority of the slides comprising a melanoma cell line study.
In the study, a cutoff coefficient of variation (CV) of 15% is used to decide whether slides are retained for biological analysis. After spatial normalization, CVs in 8 slides (Caspase 9, IGFBP2, ATR, COX2, FAK_pY397, BCL2(mouse), PARP, AKT) that were previously unusable drop to acceptable values. One slide - PCNA(mouse) - that had earlier been used in analysis is rejected after normalization.
Figure 5.
Correlation between concentrations of samples printed across duplicate slides increases slightly with normalization (upper panels, L→R, melanoma samples and probed with anti-pMAPK antibody).
Coefficient of variation between the concentrations of biological replicates printed on one of these slides improves after normalization (lower panels, L→R).
Figure 6.
Coefficient of variation between intensities of intraslide technical replicates in dataset B decreases significantly with normalization.
One out of 5 dilutions of positive controls is used for spatial normalization. The correlation of the remaining positive controls, which are technical replicates within each dilution, is observed after normalization. Correlations increase with normalization for each of the observed dilutions.
Figure 7.
Correlation calculations performed using intensities of all spots printed onto duplicate slides may be a misleading measure of reproducibility because of experimental design that uses multiple dilutions to evaluate sample concentrations.
In the case of two identical slides probed with anti-pBAD antibody, overall correlation coefficient R = 0.82 whereas correlations of the individual dilutions are lower.