Implementation of an image processing protocol for phenotypic cell viability assays

• Grant number: 25/05515-6
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: June 01, 2025
• End date: December 31, 2025
• Field of knowledge: Biological Sciences - Morphology - Cytology and Cell Biology
• Principal Investigator: João Victor da Silva Guerra
• Grantee: Kayllany Lara da Silva Oliveira
• Host Institution: Centro Nacional de Pesquisa em Energia e Materiais (CNPEM). Ministério da Ciência, Tecnologia e Inovação (Brasil). Campinas , SP, Brazil

Abstract

High-content screening is a key methodology in drug discovery and the study of biological mechanisms. However, processing and analyzing the large number of images generated by these assays pose a significant challenge for researchers. This project aims to develop an automated image processing protocol for phenotypic cell viability assays using open-source tools designed to integrate high-performance computing clusters. Implemented in Python, the protocol will utilize libraries such as CellProfiler, SciPy, scikit-image, and CellPose to process fluorescence images of Vero CCL81 and HuH7.0 cells stained with Hoechst 33342. The workflow will include image preprocessing, nuclear segmentation, morphological feature extraction, and data integration. Performance will be evaluated by comparing results with the commercial Acapella/Columbus software, used as a reference. Validation will be carried out on a phenotypic screening dataset for drug discovery, involving approximately 7,700 compounds and multiple viruses. The protocol will be released as an open-source tool to promote scientific collaboration and facilitate cell viability image analysis across various research applications. (AU)