The Benefits of Automatically Processing Zebrafish Imaging Data
Zebrafish are a promising emergent model system for biomedical research, having multiple advantages in pharmacokinetics, toxicity studies and genetic knockouts. Through zebrafish imaging, the zebrafish (Danio rerio) has developed into one of the most significant model organisms for in-vivo studies of vertebrates in biology, both for basic science and biomedical applications, over the past 30 years. Zebrafish imaging has become the go-to model in a wide range of research initiatives due to their genetic resemblance to mammals, small size, quick development, affordable care, and usefulness for substituting mammals in animal testing. The nearly full genome sequence and the increasing number of transgenic and mutant fish lines, which enable thorough in-vivo studies of gene regulation and function, are further factors contributing to the model’s appeal.

Another key characteristic of Zebrafish which makes it a perfect model organism for vertebrate bioimaging techniques is the relative transparency of its embryos and larvae, which makes them suitable for in-vivo imaging at great depth. With the aid of cutting-edge microscopy technology, developmental processes may be imaged in unprecedented detail, and complicated image-based readouts can be used for high-throughput/high-content screening.
One area of life science research where Zebrafish screening contributes to rapid progress in scientific findings is infection immunity studies in virology and microbiology. High content screening of live Zebrafish in multiwell plates enables the study of bacterial or viral infection at the single-cell level inside a living organism. For example, researchers at the London School of Hygiene & Tropical Medicine (LSHTM) use Zebrafish larvae to visualize Shigella flexneri infection. Using automated imaging and analysis, they simultaneously quantify bacterial replication together with host response and survival for studying the innate immune response at a resolution previously unachievable.
Another key research area which benefits from screens of Zebrafish models is cancer research and drug discovery for specific cancer types. For example, Leukemia researchers at UCL Cancer Institute, London, are using automated Zebrafish screening for Myeloid Leukemia drug discovery. The group achieves automated analysis of thousands of drug compounds and applies the same approach for all their experiments to obtain novel insights in an efficient manner.
Removing the bottleneck of manual quantification using AI
Zebrafish are an attractive model organism for studying human disease pathology and a great alternative to mammalian screening due to cost, throughput and reduced ethical concerns.However, Automated analysis of Zebrafish microscopy images imposes unique demands due to the versatility of organs and features needed to be detected. Extraction of meaningful information from Zebrafish microscopy images is quite challenging. While the images themselves are easily interpretable to the human eye, i.e. the fish and its organs can be easily distinguished for manual segmentation, automated computer-based analysis is not trivial.
Until now, many researchers who perform Zebrafish screening with automated microscopes have relied on manual analysis to identify areas of interest within the fish or measured total fluorescence within the fish area, disregarding anatomical context, and only obtained simplistics fluorescence readouts. This resulted in loss of meaningful information from anatomical areas within the Fish body, which were not included in the analysis.
Moreover, for researchers who image tens and hundreds of fish per week, manually analyzing all the data is very laborious and time consuming and automating this process becomes a must.
IDEA Bio-Medical specializes in automation, with a decade of experience supporting life science researchers in automating their microscopy research, by moving their imaging and image analysis workflows from manual work to automation. We are proud of the fact that wee work very closely with our clients and through them we recognized the unmet needs of Zebrafish researchers and the bottlenecks in their workflows. This has led us to develop a novel deep learning-powered image analysis algorithm that automatically identifies the fish contour and its internal anatomy in microscopy images taken in bright field illumination (transmitted light), which is a completely label-free image acquisition requirement.
This image analysis enables the segmentation of fish outline and its internal anatomy. This is followed by quantification of the morphological features of the fish and its organs, with the option to study the fluorescence signal that may be present in certain areas within the fish body, for instance if some pathogen was injected in the tail region but the researcher is interested in tracking the penetration of this pathogen to the fish’s head or eye. Ultimately, our software enables true high content screening of Zebrafish samples, for the very first time.
Our software offers simple and quick quantification of fluorescence, measurement of morphological changes & other phenotypic features in Zebrafish larvae in a high throughput format. Using novel Artificial Intelligence- based algorithms for fish & organ identification, no user intervention is required to readily detect fish & internal organs in brightfield, non-labeled images. These can be combined with fluorescent labeling for structural co-analysis.
Athena zebrafish software automatically detects fish contour and internal anatomy in brightfield images. By identifying these hard-to-detect structures, our software maintains the anatomical context of associated fluorescence signals to enable accurate high-content imaging in Zebrafish. This way, zebrafish morphology, along with region-specific spot/cell counting and fluorescence intensity measurement are readily quantified.
For statistical analysis of the imaging data, a useful tool of the software allows users to ensure proper fish orientation in post-analysis with customizable, software-based selection to exclude specified fish from the statistics if they are mis-oriented. Fish larva are analyzed from head to tail with supported image analysis from single plane, Z-stack and projection images.
We aim to empower Zebrafish researchers to extract more from their data. To support the Zebrafish community, the software is suitable for any researcher using any type of microscope, be it an upright or inverted stereo microscope,and for any level of usage, regardless of the number of images to be analyzed. Image formats from all types of microscopes are accepted , be it open-source TIFF images or proprietary image formats. This software is suited for researchers who need to analyze just a few dozen Zebrafish images per week as well as researchers screening hundreds of fish per week. There is no throughput limit. The software is designed for non-specialists in image analysis, with quick and easy user interface, such that any user, regardless of their background, can be trained and become productive and independent with the software right away.
Athena Zebrafish analysis software is now available for download in a novel pay-per-use basis. Download your free trial now!

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