Patterns of Regulation from mRNA and Protein Time Series

The rapid advance of genome sequencing projects challenges biologists to assign physiological roles to thousands of unknown gene products. We suggest here that regulatory functions and protein–protein interactions involving specific products may be inferred from the trajectories over time of their mRNA and free protein levels within the cell. The level of a protein in the cytoplasm is governed not only by the level of its mRNA and the rate of translation, but also by the proteinʹs folding efficiency, its biochemical modification, its complexation with other components, its degradation, and its transport from the cytoplasmic space. All these co- and post translational events cause the concentration of the protein to deviate from the level that would result if we only accounted for translation of its mRNA. The dynamics of such deviations can create patterns that reflect regulatory functions. Moreover, correlations among deviations highlight protein pairs involved in potential protein–protein interactions. We explore and illustrate these ideas here using a genetically structured simulation for the intracellular growth of bacteriophage T7.