The Dpp morphogen gradient derived from the anterior stripe of cells is thought to control growth and patterning of the Drosophila wing disc. However, the spatial-temporal requirement of dpp for growth and patterning remained largely unknown. Recently, two studies re-addressed this question. By generating a conditional null allele, one study proposed that the dpp stripe is critical for patterning but not for growth (Akiyama and Gibson, 2015). In contrast, using a membrane-anchored nanobody to trap Dpp, the other study proposed that Dpp dispersal from the stripe is required for patterning and also for medial wing disc growth, at least in the posterior compartment (Harmansa et al., 2015). Thus, growth control by the Dpp morphogen gradient remains under debate. Here, by removing dpp from the stripe at different time points, we show that the dpp stripe source is indeed required for wing disc growth, also during third instar larval stages.

Expansion microscopy (ExM) enables nanoscale imaging using a standard confocal microscope through the physical, isotropic expansion of fixed immunolabeled specimens. ExM is widely employed to image proteins, nucleic acids, and lipid membranes in single cells; however, current methods limit the number of samples that can be processed simultaneously. We developed High-throughput Expansion Microscopy (HiExM), a robust platform that enables expansion microscopy of cells cultured in a standard 96-well plate. Our method enables ~4.2 x expansion of cells within individual wells, across multiple wells, and between plates. We also demonstrate that HiExM can be combined with high-throughput confocal imaging platforms to greatly improve the ease and scalability of image acquisition. As an example, we analyzed the effects of doxorubicin, a known cardiotoxic agent, on human cardiomyocytes (CMs) as measured by the Hoechst signal across the nucleus. We show a dose-dependent effect on nuclear DNA that is not observed in unexpanded CMs, suggesting that HiExM improves the detection of cellular phenotypes in response to drug treatment. Our method broadens the application of ExM as a tool for scalable super-resolution imaging in biological research applications.