A Dual Image Sensor Approach for Automated, High Resolution, Region-of-Interest Imaging in a 96-Well Plate

Abstract

Phenotypic screens are performed on model organisms to understand how chemical compounds affect biological systems. High-throughput devices are needed to efficiently gather large volumes of data for these screens. Recently we developed a low cost high-throughput imaging solution to capture the effects of chemicals on the egg-laying behaviour of C. elegans. We present a second-generation prototype capable of high-resolution (0.2 µm/px) imaging of individual worms and their internal structures. It features an automatic real time segmentation of C. elegans worms and is compatible with 96-well plates. In order to maximize efficiency in data collection, we developed an approach for simultaneous dual imaging through a single objective. A low-resolution (15 µm/px) arm continuously collects images of an entire well using a CCD camera (1280 px by 1024 px). The images are continuously fed into a Python image algorithm that tracks the movement of the worms in regions of interest (ROIs). Using this information, high resolution images of the worms are captured using a linescan camera (8000 px). This solution provides automated high-resolution imaging minimizing acquisition time by eliminating the need for multiple objectives, allowing image collection with a continuously moving system (high speed linescan camera) and minimizing the amount of stitching (large linescan sensor). The scan time of a 96-well plate is proportional to the number of ROIs, which is significantly less than imaging an entire plate. The high-resolution images can be fed into an image processing pipeline that will be able to classify the effects of chemicals on the internal structure of the worms. Simultaneous acquisition of high and low resolution data can be used to correlate deformations of internal structure with changes in mobility. This low cost solution provides users with an automated approach to obtain high-resolution images and mobility statistics of C. elegans.