Automated monitoring of early life-stage development in Atlantic cod (Gadus morhua) embryos exposed to a reference toxicant

Early life stages of fish are widely used for regulatory toxicity testing, and marine fish display high sensitivity to pollutant exposure. Exposure to pollutants during embryogenesis causes acute effects on embryonic development and survival, but also sub-lethal impacts manifested as maldeveloped larvae. Acquiring time- and exposure-dependent responses to pollutant exposure and other stressors in small organisms is labor intensive and often subjective. This leads to studies obtaining small sample sizes, with measurements often made infrequently during development. Automated monitoring methods can maintain consistency between measurements and allow many more measurements to be made, improving the quantity and quality of such data. We exposed Atlantic cod embryos to 3,4-dichloroaniline, a reference chemical widely used as a positive control agent in regulatory fish embryo toxicity testing. We monitored their growth through daily imaging with an automated flow-through imaging system. Biologically relevant sublethal endpoints were estimated from these images with a neural network and traditional machine vision methods. We demonstrate the automated capture and analysis of tens of thousands of images, producing detailed morphometric data from hundreds of fish over a 10-d study period, and assess the effectiveness of the automated system. The automated method presented allows measurements to be made frequently without sacrificing the sampled organisms, making detailed time series of development obtainable. We show dose-dependent effects of the toxicant on development and capture nonlinear responses that would not be attainable under a conventional manual sampling regime.