Quantitative analysis of subcellular distributions with an open-source, object-based tool
Cite this dataset
Ryder, Pearl; Lerit, Dorothy (2021). Quantitative analysis of subcellular distributions with an open-source, object-based tool [Dataset]. Dryad. https://doi.org/10.5061/dryad.h70rxwdgb
The subcellular localization of objects, such as organelles, proteins, or other molecules, instructs cellular form and function. Understanding the underlying spatial relationships between objects through colocalization analysis of microscopy images is a fundamental approach used to inform biological mechanisms. We generated an automated and customizable computational tool, the SubcellularDistribution pipeline, to facilitate object-based image analysis from 3D fluorescence microcopy images. To test the utility of the SubcellularDistribution pipeline, we examined the subcellular distribution of mRNA relative to centrosomes within Drosophila embryos. Centrosomes are microtubule-organizing centers, and RNA enrichments at centrosomes are of emerging importance. Our open-source and freely available software detected RNA distributions comparably to commercially available image analysis software. The SubcellularDistribution pipeline is designed to guide the user through the complete process of preparing image analysis data for publication, from image segmentation and data processing to visualization.
Images were acquired on a Nikon Ti-E system fitted with a Yokogawa CSU-X1 spinning disk head, Hamamatsu Orca Flash 4.0 v2 digital CMOS camera, Perfect Focus system, and a Nikon LU-N4 solid state laser launch (15 mW 405, 488, 561, and 647 nm) using a 100x 1.49 NA Apo TIRF oil-immersion objective. This microscope was controlled through Nikon Elements AR software on a 64-bit HP Z440 workstation.
Images are single molecule fluorescence in situ hybridization (smFISH) signals for centrocortin and gapdh (channel 1) and direct fluorescence of GFP-Cnn (channel 2) in Drosophila embryos at nuclear cycle 12 in interphase or metaphase. The raw-data-metadata.csv file documents the type of RNA and cell cycle for each image.
National Institute of General Medical Sciences, Award: 5K12GM000680
National Institute of General Medical Sciences, Award: 1F32GM128407
National Heart Lung and Blood Institute, Award: 5K22HL126922