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Robinett, T.

Publications and source records attributed to Robinett, T..

2 recordsLinked to original sources

Piezo regulates epithelial topology and promotes precision in organ size control

Mechanosensitive Piezo channels regulate cell division through calcium-mediated activation of ERK signaling or activate Rho signaling to mediate cell extrusion and cell death. However, systems-level functions of Piezo in regulating organogenesis remain poorly understood. Here, we demonstrate that Piezo controls epithelial cell topology to ensure precise organ growth through the integration of live imaging experiments with pharmacological and genetic perturbations and computational modeling. Notably, knockout or knockdown of Piezo led to bilateral asymmetry in wing phenotypes. While pharmacological activation of Piezo stimulated an increase in the frequency of spikes in cytosolic Ca2+, we discovered that Piezo overexpression counterintuitively reduces Ca2+ signaling dynamics. Knockdown of Piezo inhibited proliferation and decreased apoptosis, resulting in an overall increase in epithelial overcrowding. In contrast, either genetic overexpression or pharmacological activation of Piezo increased cell proliferation and cell removal through basal extrusion. Surprisingly, Piezo overexpression increased the hexagonality of cellular topology. To test whether Piezo regulates cell topology, we formulated computational simulations to investigate how expression levels of Piezo protein regulate cell proliferation and apoptosis through modulation of the cut-off tension required for Piezo channel activation. Quantitative analysis validated computational simulation predictions of how perturbations to Piezo impacted epithelial topology. Overall, our findings demonstrate that Piezo promotes robustness in regulating epithelial topology and is necessary for precise organ size control.

developmental biology↗

MAPPER: A new image analysis pipeline unmasks differential regulation of Drosophila wing features

Phenomics requires quantification of large volumes of image data, necessitating high throughput image processing approaches. Existing image processing pipelines for Drosophila wings, a powerful model for studying morphogenesis, are limited in speed, versatility, and precision. To overcome these limitations, we developed MAPPER, a fully-automated machine learning-based pipeline that quantifies high dimensional phenotypic signatures, with each dimension representing a unique morphological feature. MAPPER magnifies the power of Drosophila genetics by rapidly identifying subtle phenotypic differences in sample populations. To demonstrate its widespread utility, we used MAPPER to reveal new insights connecting patterning and growth across Drosophila genotypes and species. The morphological features extracted using MAPPER identified the presence of a uniform scaling of proximal-distal axis length across four different species of Drosophila. Observation of morphological features extracted by MAPPER from Drosophila wings by modulating insulin signaling pathway activity revealed the presence of a scaling gradient across the anterior-posterior axis. Additionally, batch processing of samples with MAPPER revealed a key function for the mechanosensitive calcium channel, Piezo, in regulating bilateral symmetry and robust organ growth. MAPPER is an open source tool for rapid analysis of large volumes of imaging data. Overall, MAPPER provides new capabilities to rigorously and systematically identify genotype-to-phenotype relationships in an automated, high throughput fashion. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=102 SRC="FIGDIR/small/422888v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@bdbecdorg.highwire.dtl.DTLVardef@139a7fdorg.highwire.dtl.DTLVardef@43d5b9org.highwire.dtl.DTLVardef@1846af9_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗