The extracellular signal-regulated kinase (ERK) pathway leads to activation of the effector molecule ERK, which controls downstream responses by phosphorylating a variety of substrates, including transcription factors. Crucial insights into the regulation and function of this pathway came from studying embryos in which specific phenotypes arise from aberrant ERK activation. Despite decades of research, several important questions remain to be addressed for deeper understanding of this highly conserved signaling system and its function. Answering these questions will require quantifying the first steps of pathway activation, elucidating the mechanisms of transcriptional interpretation and measuring the quantitative limits of ERK signaling within which the system must operate to avoid developmental defects.

Optogenetic approaches are transforming quantitative studies of cell-signaling systems. A recently developed photoswitchable mitogen-activated protein kinase kinase 1 (MEK1) enzyme (psMEK) short-circuits the highly conserved Extracellular Signal-Regulated Kinase (ERK)-signaling cascade at the most proximal step of effector kinase activation. However, since this optogenetic tool relies on phosphorylation-mimicking substitutions in the activation loop of MEK, its catalytic activity is predicted to be substantially lower than that of wild-type MEK that has been phosphorylated at these residues. Here, we present evidence that psMEK indeed has suboptimal functionality in vivo and propose a strategy to circumvent this limitation by harnessing gain-of-function, destabilizing mutations in MEK. Specifically, we demonstrate that combining phosphomimetic mutations with additional mutations in MEK, chosen for their activating potential, restores maximal kinase activity in vitro. We establish that this modification can be tuned by the choice of the destabilizing mutation and does not interfere with reversible activation of psMEK in vivo in bothDrosophilaand zebrafish. To illustrate the types of perturbations enabled by optimized psMEK, we use it to deliver pulses of ERK activation during zebrafish embryogenesis, revealing rheostat-like responses of an ERK-dependent morphogenetic event.

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Phase separation underlies the organization of the nucleus, including the biogenesis of nucleoli and the packaging of heterochromatin. Here we explore the regulation of transcription factor condensates involved in gene repression by ERK signaling in gastrulating embryos of a simple proto-vertebrate (Ciona). ERK signaling induces nuclear export of the transcriptional repressor Ets-2 repressive factor (ERF), which has been linked to various human developmental disorders. Using high-resolution imaging, we show that ERF is localized within discrete nuclear condensates that dissolve upon ERK activation. Interestingly, we observe dynamic pulses of assembly and dissociation during interphase, providing visualization of a nuclear phase separation process regulated by cell signaling. We discuss the implications of these observations for producing sharp on/off switches in gene activity and suppressing noise in cell–cell signaling events.

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.

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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 fruit fly, Drosophila melanogaster, 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.