We construct phenotypic profiles of differentiated human cells such as neurons. Our goal is to better understand the overall effects of chemical compound treatments on the cells. Phenotypic profiles can suggest less biased entry points for further mechanistic studies.
The quality of protocols for differentiating human dopaminergic neurons has significantly improved, enabling the production of large batches of homogeneous neurons. Additionally, there is a rise in the use of lab automation for handling differentiated cells'reproducibility over extended periods, and of course, the exploitation of imaging-based data has become faster and more detailed. A big challenge is to ensure that phenotypic profiles are both quantifiable and reproducible.
To achieve this, it is crucial to produce homogeneous neuron batches and identify an automation-suited protocol. However, with an automated protocols, there is always a trade-off between technical feasibility and physiological relevance. Here, we found a good trade-off.
We developed a ready-to-use solution to thoroughly characterize human dopaminergic neurons using an imaging approach. The automated protocol, along with the image and data analysis workflow, will equip more scientists to create neuronal phenotypic profiles. We would like to better understand how phenotypic profiles differ between monogenetic and idiopathic forms of Parkinson's disease.
We would also like to explore the changes in phenotypic aspects when dopaminergic neurons interact with other brain cell types such as microglia, for example.
