(1111-B) Cell Painting & Natural Product Discovery in Chagas Disease: Image-based Morphological Profiling of Host-Parasite Model Uncovers Mechanism of Action Leading to Accelerated Therapeutics

Abstract: Chagas disease (CD), caused by the protozoan Trypanosoma cruzi (T.cruzi), represents an important public health problem in Latin America. Recently, it has become a potential emerging disease in non-endemic areas through migrating populations and climate change. With new technologies and tools now available, there are advanced drug discovery pipelines being built to urgently meet these needs.
Here, we present our workflow using Cell Painting approach and in-house custom analysis to assess the morphological profiling of parasite infection on host cells. U2OS cells and T.cruzi parasites were stained with multiplexed six fluorescent dyes designed to illuminate various subcellular components. Each component was acquired using an automated confocal microscope with 40X water objective to provide detailed features at high-resolution. With Cell Painting, the acquired images of host-pathogen interactions were analyzed to extract ~6000 features at single cell level generating large amounts of metadata. Using Python software package, we implemented an analysis pipeline including principal component analysis (PCA), distribution, clustering, and uniform manifold approximation and projection (UMAP) to quantitate morphological changes between infected and uninfected cells. As proof of concept, we tested two reference compounds with different proven actions against T.cruzi to access their anti-parasitic activity and reversion towards a non-infected state. Our analysis revealed a distinct separation between compounds highlighting differences in mode of action. We further utilized the Cell Painting approach on MEDINA’s purified natural products to uncover and classify novel promising mechanisms of action (MoA) associated to T.cruzi parasite killing.
Cell Painting is a powerful approach to quickly understand the effect of bioactive compounds on cells to unravel their potential MoA. In this study, we have established a workflow using Cell Painting approach and custom analysis solution using Python software in T.cruzi infection model. This image-based morphological profiling of natural products on infection predicts MoA and subsequently leading to improved therapeutic discoveries that could boost drug discovery programs for Chagas disease.