Ratio-dependent significance thresholds in reciprocal 15N-labeling experiments as a robust tool in detection of candidate proteins responding to biological treatment.

Metabolic labeling of plant tissues with (15)N has become widely used in plant proteomics. Here, we describe a robust experimental design and data analysis workflow implementing two parallel biological replicate experiments with reciprocal labeling and series of 1:1 control mixtures. Thereby, we are able to unambiguously distinguish (i) inherent biological variation between cultures and (ii) specific responses to a biological treatment. The data analysis workflow is based on first determining the variation between cultures based on (15)N/(14)N ratios in independent 1:1 mixtures before biological treatment is applied. In a second step, ratio-dependent SD is used to define p-values for significant deviation of protein ratios in the biological experiment from the distribution of protein ratios in the 1:1 mixture. This approach allows defining those proteins showing significant biological response superimposed on the biological variation before treatment. The proposed workflow was applied to a series of experiments, in which changes in composition of detergent resistant membrane domains was analyzed in response to sucrose resupply after carbon starvation. Especially in experiments involving cell culture treatment (starvation) prior to the actual biological stimulus of interest (resupply), a clear distinction between culture to culture variations and biological response is of utmost importance.