DOI: 10.5281/zenodo.5698394
title: AP-4-mediated axonal transport controls endocannabinoid production in neurons - Imaging data 2

description: Imaging data from the article "AP-4-mediated axonal transport controls endocannabinoid production in neurons", published in Nature Communications by Davies et al., from Fig. 5 and S4. Super resolution structured illumination microscopy (SR-SIM) was used to image HeLa cells expressing endogenously-tagged SERINC1-Clover or SERINC3-Clover, treated with siRNA to knock down AP-4 or non-targeting control siRNA, and labelled with anti-GFP and either anti-ATG9A or anti-DAGLB. SR-SIM was performed on a Zeiss Elyra PS.1 microscope equipped with a 63x/1.46 oil objective (alpha Plan-Apochromat 63x/1.46 Oil Korr M27) and a PCO pco.edge 4.2 sCMOS Camera, and controlled with Zeiss ZEN 2 software with the SR-SIM module. Imaging was performed sequentially, with SERINC1 or SERINC3 (labelled with Alexa Fluor Plus 488) imaged first and DAGLB or ATG9A (labelled with Alexa Fluor 568) imaged second, using 3 rotations of the grid pattern and 5 phases for each rotation. Experiments were performed in biological duplicate, from separate dishes of cells, and with immunofluorescence and microscopy performed independently for each replicate. 20 cells were imaged per condition per replicate, and cell selection and manual focus were performed on the first acquired channel only, without viewing the second channel. For channel alignment, slides with multi-coloured fluorescent beads were imaged before and after each experiment using the same acquisition settings. The data were processed using the SIM module in Zen 2 software in manual mode, using default settings and a theoretical PSF model, except for the following settings: Noise filter -1; SR frequency weighting 2; Max.Isotrop on; Baseline shifted on; Raw scale on. Channel alignment fit parameters were calculated in Zen 2 software using a multi-coloured bead image as input, in affine mode. The resulting parameters were tested on further bead images and then applied to the experimental images. The channel-aligned images were used for colocalisation analysis (see methods of article for details). This dataset includes the raw unprocessed data and the processed and channel aligned input data used for the colocalisation analysis. See article for methods and further detail.
description: This work was funded by the German Research Foundation (DFG/Gottfried Wilhelm Leibniz Prize MA 1764/2-1) and the Max Planck Society for the Advancement of Science. A.K.D. received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement no. 896725 and a Humboldt Research Fellowship. D.E.-F. had support from the CureAP4 Foundation, the Spastic Paraplegia Foundation, the National Institute of Health / National Institute of Neurological Disorders and Stroke (2R25NS070682 & 1K08NS123552-01) and the National Institutes of Health (BCH IDDRC, 1U54HD090255). M.Z. received scholarships from the DAAD (German National Exchange Service) and the German National Academic Foundation. J.E.A. is supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) 270949263/GRK2162, the DAAD (German National Exchange Service), the German National Academic Foundation and the Max Weber-Program of the State of Bavaria.