Significance: High-throughput optical microscopy is currently transforming the research fields of genetics, drug discovery
and neuroscience. Large-scale optical assays now routinely use thousands of high-resolution images to offer critical insights
into the human body, our brain and the diseases that affect us. Today's optical microscopes and their associated image
processing software, however, are still far from ideal. Current microscopes cannot form images with cellular-scale resolution
over an area larger than a few square centimeters, which fundamentally limits our ability to monitor the detailed movements of
living systems. For screening many in vivo model organisms, such as zebrafish, this limitation prevents current setups from
simultaneously observing multiple freely moving organisms at cellular resolution, which makes high-resolution in vivo screening
experiments challenging and time-consuming. It has also led to a scarcity of effective image processing software for high-
resolution organism image analysis. Proposal: Over the course of successful Phase I and Phase II projects, Ramona Optics
has developed a new “micro-camera array microscope” (MCAM) that overcomes the above limitations by capturing video with
up to 1 gigapixel per frame, which can resolve hundreds of freely-swimming organisms at near-cellular-level detail (5
µm/pixel). In this proposal, Ramona Optics will produce a suite of software that takes full advantage of the MCAM's
information-rich recordings. This software will automatically track and measure key morphological and fluorescence features
across all zebrafish within a full well plate, simultaneously, to replace currently tedious and time-consuming tasks. Our MCAM
and its new software will transform current toxicology and pharmacology research that relies on in vivo organism screening, by
producing more experimental insights in less time and with higher accuracy and repeatability than current methods.
SA1: MCAM software for parallelized larval tracking and video registration: Ramona Optics will produce
Python software to track, crop and register all larvae within the MCAM FOV to produce per-larvae centered video for
subsequent morphological analysis. We will demonstrate the ability to register video of hundreds of larvae imaged
simultaneously (<0.1% error rate) to reduce saved data by 40X and produce standardized per-organism datasets.
SA2: Automated annotation of morphological endpoints: Working with the Tanguay Lab at Oregon State
University and the Yoder Lab at NC State University, we will create algorithms to automatically compute 10 larval zebrafish
morphological endpoints, such as gaze direction, pectoral fin position, and body curvature, which we will verify in a series of
toxicology titration experiments (validated across labs) to demonstrate at least 100X speed-up to current screening methods.
SA3: Automated bright-field video analysis: We will then extend our automated morphology analysis software to
bright-field video to provide a time-dependent per-organism statistical analysis. We will showcase this software by tracking eye
angle across 96 larvae simultaneously to demonstrate visual acuity as a new endpoint in toxicology screens (Tanguay Lab).
SA4: Enabling high-throughput fluorescence video analysis: We will extend our parallelized software to monitor
localized fluorescence across all larvae within a 96 well-plate, and then test it in an immunotoxicology experiment (Yoder Lab).
The outcome of this Phase IIB project will be a flagship MCAM software suite ready for deployment to all MCAM users.