Highlights d ERK signaling in the Drosophila embryo antagonizes repression in a two-step process d ERK activation leads to rapid loss of a transcriptional repressor from the DNA d Transcriptional repression is reestablished once signal is removed d Signal must persist for proper gene expression and pattern formation

The most frequent extracellular signal-regulated kinase 2 (ERK2) mutation occurring in cancers is E322K (E-K). ERK2 E-K reverses a buried charge in the ERK2 common docking (CD) site, a region that binds activators, inhibitors, and substrates. Little is known about the cellular consequences associated with this mutation, other than apparent increases in tumor resistance to pathway inhibitors. ERK2 E-K, like the mutation of the preceding aspartate (ERK2 D321N [D-N]) known as the sevenmaker mutation, causes increased activity in cells and evades inactivation by dual-specificity phosphatases. As opposed to findings in cancer cells, in developmental assays in Drosophila, only ERK2 D-N displays a significant gain of function, revealing mutation-specific phenotypes. The crystal structure of ERK2 D-N is indistinguishable from that of wild-type protein, yet this mutant displays increased thermal stability. In contrast, the crystal structure of ERK2 E-K reveals profound structural changes, including disorder in the CD site and exposure of the activation loop phosphorylation sites, which likely account for the decreased thermal stability of the protein. These contiguous mutations in the CD site of ERK2 are both required for docking interactions but lead to unpredictably different functional outcomes. Our results suggest that the CD site is in an energetically strained configuration, and this helps drive conformational changes at distal sites on ERK2 during docking interactions.

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Significance To understand developmental patterning of an organism, it is necessary to accurately measure how the state of a gene regulatory network is changing over time. One way of extracting dynamics of a network involves simultaneously imaging several reporters within fixed tissue. Reconstructing dynamics from such data requires staging many samples over time and often leads to low temporal resolution. Time-lapse microscopy of fluorescent transcriptional reporters has revolutionized studies of biological dynamics at the single-cell level. However, this method is limited by the number of reporters that can be imaged at one time. We present a computational method for addressing this problem and demonstrate its application by modeling the gene regulatory network underlying Drosophila posterior patterning and reconstructing its developmental dynamics.

Modern studies of embryogenesis are increasingly quantitative, powered by rapid advances in imaging, sequencing, and genome manipulation technologies. Deriving mechanistic insights from the complex datasets generated by these new tools requires systematic approaches for data-driven analysis of the underlying developmental processes. Here we use data from our work on signal-dependent gene repression in the Drosophila embryo to illustrate how computational models can compactly summarize quantitative results of live imaging, chromatin immunoprecipitation, and optogenetic perturbation experiments. The presented computational approach is ideally suited for integrating rapidly accumulating quantitative data and for guiding future studies of embryogenesis.