Development of a quantitative morphological assessment of toxicant‐treated zebrafish larvae using brightfield imaging and high‐content analysis. Issue 9 (29th February 2016) - Deal, Samantha; Wambaugh, John; Judson, Richard; Mosher, Shad; Radio, Nick; Houck, Keith; Padilla, Stephanie
Abstract: One of the rate‐limiting procedures in a developmental zebrafish screen is the morphological assessment of each larva. Most researchers opt for a time‐consuming, structured visual assessment by trained human observer(s). The present studies were designed to develop a more objective, accurate and rapid method for screening zebrafish for dysmorphology. Instead of the very detailed human assessment, we have developed the computational malformation index, which combines the use of high‐content imaging with a very brief human visual assessment. Each larva was quickly assessed by a human observer (basic visual assessment), killed, fixed and assessed for dysmorphology with the Zebratox V4 BioApplication using the Cellomics® ArrayScan® V TI high‐content image analysis platform. The basic visual assessment adds in‐life parameters, and the high‐content analysis assesses each individual larva for various features (total area, width, spine length, head–tail length, length–width ratio, perimeter–area ratio). In developing the computational malformation index, a training set of hundreds of embryos treated with hundreds of chemicals were visually assessed using the basic or detailed method. In the second phase, we assessed both the stability of these high‐content measurements and its performance using a test set of zebrafish treated with a dose range of two reference chemicals ( trans ‐retinoic acid or cadmium). We found the measures were stable for at least 1 week and comparison of these automated measures to detailed visual inspection of the larvae showed excellent congruence. Our computational malformation index provides an objective manner for rapid phenotypic brightfield assessment of individual larva in a developmental zebrafish assay. Copyright © 2016 John Wiley & Sons, Ltd. Abstract : We developed a Computational Malformation Index that provides an objective manner for rapid phenotypic brightfield assessment of individual zebrafish larva in a developmental assay. By combining the use of high‐content imaging with a very abbreviated human visual assessment, each larva can be quickly assessed for both detailed features as well as in‐life parameters. Further, stability of these high‐content measurements and the index performance were verified using a test set of zebrafish treated with two reference chemicals.