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Creators/Authors contains: "Zartman, Jeremiah J."

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  1. Abstract

    Cells communicate with each other to jointly regulate cellular processes during cellular differentiation and tissue morphogenesis. This multiscale coordination arises through the spatiotemporal activity of morphogens to pattern cell signaling and transcriptional factor activity. This coded information controls cell mechanics, proliferation, and differentiation to shape the growth and morphogenesis of organs. While many of the molecular components and physical interactions have been identified in key model developmental systems, there are still many unresolved questions related to the dynamics involved due to challenges in precisely perturbing and quantitatively measuring signaling dynamics. Recently, a broad range of synthetic optogenetic tools have been developed and employed to quantitatively define relationships between signal transduction and downstream cellular responses. These optogenetic tools can control intracellular activities at the single cell or whole tissue scale to direct subsequent biological processes. In this brief review, we highlight a selected set of studies that develop and implement optogenetic tools to unravel quantitative biophysical mechanisms for tissue growth and morphogenesis across a broad range of biological systems through the manipulation of morphogens, signal transduction cascades, and cell mechanics. More generally, we discuss how optogenetic tools have emerged as a powerful platform for probing and controlling multicellular development.

     
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  2. Phenomics requires quantification of large volumes of image data, necessitating high throughput image processing approaches. Existing image processing pipelines for Drosophila wings, a powerful genetic model for studying the underlying genetics for a broad range of cellular and developmental processes, are limited in speed, precision, and functional versatility. To expand on the utility of the wing as a phenotypic screening system, we developed MAPPER, an automated machine learning-based pipeline that quantifies high-dimensional phenotypic signatures, with each dimension quantifying a unique morphological feature of the Drosophila wing. MAPPER magnifies the power of Drosophila phenomics by rapidly quantifying subtle phenotypic differences in sample populations. We benchmarked MAPPER’s accuracy and precision in replicating manual measurements to demonstrate its widespread utility. The morphological features extracted using MAPPER reveal variable sexual dimorphism across Drosophila species and unique underlying sex-specific differences in morphogen signaling in male and female wings. Moreover, the length of the proximal-distal axis across the species and sexes shows a conserved scaling relationship with respect to the wing size. In sum, MAPPER is an open-source tool for rapid, high-dimensional analysis of large imaging datasets. These high-content phenomic capabilities enable rigorous and systematic identification of genotype-to-phenotype relationships in a broad range of screening and drug testing applications and amplify the potential power of multimodal genomic approaches. 
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  3. Maini, Philip K. (Ed.)