Visualizing Actin Dynamics at Drosophila NMJs

Female virgin flies with the genotype nSyb-Gal4>UAS-Act5C::GFP were crossed to UAS-YARS1, UAS-PLS3, or UAS-CD8::RFP male flies. Third instar larvae were dissected in HL3.1, fixed in 4% PFA solution (in HL3.1) for 10 min, washed three times for 10 min with 1XPBS, blocked with 2%BSA/Normal Goat Serum, 0.1% Triton-X 1X PBX, incubated with α-GFP nanobodies (Nanotag Biotechnologies) to amplify the Act5C::GFP signal and HRP-Rhodamin red to label the neuronal membrane (both at 1:250 in blocking solution) for 2 h at room temperature, washed three times for 10 min in 0.1% PBX and mounted on glass microscopic slide in Diamond ProLong. NMJs on muscle 6/7 on both sides of abdominal segment A3 and A4 were imaged using a Nikon Ni-E upright microscope equipped with a Yokogawa CSU-W1 spinning-disk head, an Andor iXon 897U EMCCD camera and Nikon Elements AR software. A 60× (NA 1.4) oil immersion objective was used to image the NMJs. Image acquisition settings were identical for all images. Act5C::GFP-labeled actin assemblies were assessed on maximum-intensity projection images. To analyze actin in boutons, boutons were cropped, and actin assemblies were analyzed with the pipeline described below. The Trainable Weka Segmentation (TWS) machine-learning tool^{59 (link)} in Fiji was used to manually annotate GFP-positive actin assemblies with different fluorescence intensities, and to train a classifier that will automatically segment these structures. The segmented objects were subjected to Huang auto thresholding to obtain binary masks. Next, we applied a Watershed processing on the binary image, to improve the isolation of individual neighboring objects from the diffraction-limited images. We performed particle analysis on the segmented actin assemblies to obtain their number and area. Mean fluorescence intensity of individual actin assemblies was measured by applying the mask on the original image. The number of actin assemblies was normalized to the bouton area. To determine the bouton area using TWS, we developed different classifier by annotating the Act5C-positive bouton (Gaussian blur 2).