A multi-dimensional, time-lapse, high content screening platform applied to schistosomiasis drug discovery

Steven Chen,Rahul Singh,Michelle R Arkin,Jakob Dohrmann,Brian M Suzuki,Conor R Caffrey

doi:10.1038/s42003-020-01402-5

Abstract

Approximately 10% of the world’s population is at risk of schistosomiasis, a disease of poverty caused by the Schistosoma parasite. To facilitate drug discovery for this complex flatworm, we developed an automated high-content screen to quantify the multidimensional responses of Schistosoma mansoni post-infective larvae (somules) to chemical insult. We describe an integrated platform to process worms at scale, collect time-lapsed, bright-field images, segment highly variable and touching worms, and then store, visualize, and query dynamic phenotypes. To demonstrate the methodology, we treated somules with seven drugs that generated diverse responses and evaluated 45 static and kinetic response descriptors relative to concentration and time. For compound screening, we used the Mahalanobis distance to compare multidimensional phenotypic effects induced by 1323 approved drugs. Overall, we characterize both known anti-schistosomals and identify new bioactives. Apart from facilitating drug discovery, the multidimensional quantification provided by this platform will allow mapping of chemistry to phenotype.

Highlights

10% of the world’s population is at risk of schistosomiasis, a disease of poverty caused by the Schistosoma parasite
Primary screening of cultured schistosomes has often used post-infective larvae that can be obtained in their thousands to tens of thousands from vector snails for relatively little effort and cost, in contrast to adult worms that can only be harvested in low numbers from small mammals
As part of our research program to develop methods for antischistosomal drug discovery[14–16], we report a fully integrated, automated and multiparametric image-analysis platform for high-throughput phenotyping of living parasites

Summary

Introduction

10% of the world’s population is at risk of schistosomiasis, a disease of poverty caused by the Schistosoma parasite. To facilitate drug discovery for this complex flatworm, we developed an automated high-content screen to quantify the multidimensional responses of Schistosoma mansoni post-infective larvae (somules) to chemical insult. As part of our research program to develop methods for antischistosomal drug discovery[14–16], we report a fully integrated, automated and multiparametric image-analysis platform for high-throughput phenotyping of living parasites. Our approach offers key advances in method integration, including several of general utility to the drug screening/imaging community as follows: (a) automated liquid handling of 100 μm-sized organisms; (b) manipulation of the focal plane to facilitate identification of low-contrast, variable, and touching objects; (c) time-lapsed tracking to define frequencies and rates of motion; (d) a public system for storage, visualization and querying of the complex phenotypic data; and (e) use of a statistical metric (the Mahalanobis distance, dM) to compare multi-dimensional phenotypes for high-throughput screening

Methods

Results

Conclusion