To determine whether a C. elegans bioassay could predict mammalian developmental activity, we selected diverse compounds known and known not to elicit such activity and measured their effect on C. elegans egg viability. 89% of compounds that reduced C. elegans egg viability also had mammalian developmental activity. Conversely only 25% of compounds found not to reduce egg viability in C. elegans were also inactive in mammals. We conclude that the C. elegans egg viability assay is an accurate positive predictor, but an inaccurate negative predictor, of mammalian developmental activity. We then evaluated C. elegans as a tool to identify mechanisms affecting toxicological outcomes among related compounds. The difference in developmental activity of structurally related fungicides in C. elegans correlated with their rate of metabolism. Knockdown of the cytochrome P450s cyp-35A3 and cyp-35A4 increased the toxicity to C. elegans of the least developmentally active compounds to the level of the most developmentally active. This indicated that these P450s were involved in the greater rate of metabolism of the less toxic of these compounds. We conclude that C. elegans based approaches can predict mammalian developmental activity and can yield plausible hypotheses for factors affecting the biological potency of compounds in mammals.

We investigated the metabolic capabilities of C. elegans using compounds whose metabolism has been well characterised in mammalian systems. We find that similar metabolites are produced in C. elegans as in mammals but that C. elegans is deficient in CYP1-like metabolism, as has been seen in other studies. We show that CYP-34A9, CYP-34A10 and CYP-36A1 are the principal enzymes responsible for the metabolism of tolbutamide in C. elegans. These are related to the mammalian enzymes that metabolise this compound but are not the closest homologs suggesting that sequence comparison alone will not predict functional conservation among cytochrome P450s. In mammals, metabolite production from amytryptiline and dextromethorphan is dependent on specific cytochrome P450s. However, in C. elegans we did not find evidence of similar specificity: the same metabolites were produced but in small amounts by numerous cytochrome P450s. We conclude that, while some aspects of cytochrome P450 mediated metabolism in C. elegans are similar to mammals, there are differences in the production of some metabolites and in the underlying genetics of metabolism.

Novel invertebrate-killing compounds are required in agriculture and medicine to overcome resistance to existing treatments. Because insecticides and anthelmintics are discovered in phenotypic screens, a crucial step in the discovery process is determining the mode of action of hits. Visible whole-organism symptoms are combined with molecular and physiological data to determine mode of action. However, manual symptomology is laborious and requires symptoms that are strong enough to see by eye. Here, we use high-throughput imaging and quantitative phenotyping to measure Caenorhabditis elegans behavioral responses to compounds and train a classifier that predicts mode of action with an accuracy of 88% for a set of ten common modes of action. We also classify compounds within each mode of action to discover substructure that is not captured in broad mode-of-action labels. High-throughput imaging and automated phenotyping could therefore accelerate mode-of-action discovery in invertebratetargeting compound development and help to refine mode-ofaction categories.

Novel invertebrate-killing compounds are required in agriculture and medicine to overcome resistance to existing treatments. Because insecticides and anthelmintics are discovered in phenotypic screens, a crucial step in the discovery process is determining the mode of action of hits. Visible whole-organism symptoms are combined with molecular and physiological data to determine mode of action. However, manual symptomology is laborious and requires symptoms that are strong enough to see by eye. Here we use high-throughput imaging and quantitative phenotyping to measure C. elegans behavioral responses to compounds and train a classifier that predicts mode of action with an accuracy of 88% for a set of ten common modes of action. We also classify compounds within each mode of action to discover pharmacological relationships that are not captured in broad mode of action labels. High-throughput imaging and automated phenotyping could therefore accelerate mode of action discovery in invertebrate-targeting compound development and help to refine mode of action categories.