An open-source semi-automated robotics pipeline for embryo immunohistochemistry

Abstract

A significant challenge for developmental systems biology is balancing throughput with controlled conditions that minimize experimental artifacts. Large-scale developmental screens such as unbiased mutagenesis surveys have been limited in their applicability to embryonic systems, as the technologies for quantifying precise expression patterns in whole animals has not kept pace with other sequencing-based technologies. Here, we outline an open-source semi-automated pipeline to chemically fixate, stain, and 3D-image Drosophila embryos. Central to this pipeline is a liquid handling robot, Flyspresso, which automates the steps of classical embryo fixation and staining. We provide the schematics and an overview of the technology for an engineer or someone equivalently trained to reproduce and further improve upon Flyspresso, and highlight the Drosophila embryo fixation and colorimetric or antibody staining protocols. Additionally, we provide a detailed overview and stepwise protocol for our adaptive-feedback pipeline for automated embryo imaging on confocal microscopes. We demonstrate the efficiency of this pipeline compared to classical techniques, and how it can be repurposed or scaled to other protocols and biological systems. We hope our pipeline will serve as a platform for future research, allowing a broader community of users to build, execute, and share similar experiments.

Enhancer architecture and chromatin accessibility constrain phenotypic space during Drosophila development

“…The number of lines/embryos analyzed for each case are indicated in figure legends. For analyzing E3N mutant lines, 98 individual nuclei were identified using the automated threshold algorithm on ImageJ and a watershed to split large ROIs; average intensities for each nucleus were measured. For analyzing eveS2 mutant lines, we used ImageJ to perform Z-projections of max intensity, and a MATLAB (version R2018b; The MathWorks, Inc.) automated image analysis pipeline ( Data S1 ) was developed to capture expression signal along the AP axis on stage 5 embryos.…”

Developmental phenomics suggests that H3K4 monomethylation catalyzed by Trr functions as a phenotypic capacitor

“…Thus, this opens the avenue towards fast and cost-efficient metabolic phenotyping at a population scale. Our general approach, combined with advances in robotics 41,42 and automated behavioral characterization 43 , could turn phenomics into a standardizable phenotyping method for multiple fields of biological research.…”

Enhancer architecture and chromatin accessibility constrain phenotypic space during development

“…1l, 2k, 3g, 5i), images were analyzed in ImageJ: a circular ROI of constant size was used to measure average intensity across the different regions (selected as shown in figures); number of lines/embryos analysed for each case are indicated in figure legends. For analyzing E3N mutant lines (Fuqua et al, 2021), individual nuclei were identified using the automated threshold algorithm on ImageJ and a watershed to split large ROIs; average intensities for each nucleus were measured. For analyzing eveS2 mutant lines, we used ImageJ to perform Z-projections of max intensity, and a MATLAB (version R2018b; The MathWorks, Inc.) automated image analysis pipeline (named Script-GAC ) was developed to capture expression signal along the AP axis on stage 5 embryos.…”