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Many canonical signaling pathways exhibit complex time-varying responses, yet how minutes-timescale pulses of signaling interact with the dynamics of transcription and gene expression remains poorly understood. Erk-induced immediate early gene (IEG) expression is a model of this interface, exemplifying both dynamic pathway activity and a rapid, potent transcriptional response. Here, we quantitatively characterize IEG expression downstream of dynamic Erk stimuli in individual cells. We find that IEG expression responds rapidly to acute changes in Erk activity, but only in a sub-population of stimulus-responsive cells. We find that while Erk activity partially predicts IEG expression, a majority of response heterogeneity is independent of Erk and can be rapidly tuned by different mitogenic stimuli and parallel signaling pathways. We extend our findings to an in vivo context, the mouse epidermis, where we observe heterogeneous immediate-early gene accumulation in both fixed tissue and single-cell RNA sequencing data. Our results demonstrate that signaling dynamics can be faithfully transmitted to gene expression and suggest that the signaling-responsive population is an important parameter for interpreting gene expression responses. 

Multicellular organisms rely on spatial signaling among cells to drive their organization, development, and response to stimuli. Several models have been proposed to capture the behavior of spatial signaling in multicellular systems, but existing approaches fail to capture both the autonomous behavior of single cells and the interactions of a cell with its neighbors simultaneously. We propose a spatiotemporal model of dynamic cell signaling based on Hawkes processes—self-exciting point processes—that model the signaling processes within a cell and spatial couplings between cells. With this cellular point process (CPP), we capture both the single-cell pathway activation rate and the magnitude and duration of signaling between cells relative to their spatial location. Furthermore, our model captures tissues composed of heterogeneous cell types with different bursting rates and signaling behaviors across multiple signaling proteins. We apply our model to epithelial cell systems that exhibit a range of autonomous and spatial signaling behaviors basally and under pharmacological exposure. Our model identifies known drug-induced signaling deficits, characterizes signaling changes across a wound front, and generalizes to multichannel observations. 

Abstract Many cell- and tissue-level functions are coordinated by intracellular signaling pathways that trigger the expression of context-specific target genes. Yet the input–output relationships that link pathways to the genes they activate are incompletely understood. Mapping the pathway-decoding logic of natural target genes could also provide a basis for engineering novel signal-decoding circuits. Here we report the construction of synthetic immediate-early genes (SynIEGs), target genes of Erk signaling that implement complex, user-defined regulation and can be monitored by using live-cell biosensors to track their transcription and translation. We demonstrate the power of this approach by confirming Erk duration-sensing by FOS , elucidating how the BTG2 gene is differentially regulated by external stimuli, and designing a synthetic immediate-early gene that selectively responds to the combination of growth factor and DNA damage stimuli. SynIEGs pave the way toward engineering molecular circuits that decode signaling dynamics and combinations across a broad range of cellular contexts. 

Abstract Biological organisms experience constantly changing environments, from sudden changes in physiology brought about by feeding, to the regular rising and setting of the Sun, to ecological changes over evolutionary timescales. Living organisms have evolved to thrive in this changing world but the general principles by which organisms shape and are shaped by time varying environments remain elusive. Our understanding is particularly poor in the intermediate regime with no separation of timescales, where the environment changes on the same timescale as the physiological or evolutionary response. Experiments to systematically characterize the response to dynamic environments are challenging since such environments are inherently high dimensional. This roadmap deals with the unique role played by time varying environments in biological phenomena across scales, from physiology to evolution, seeking to emphasize the commonalities and the challenges faced in this emerging area of research.