Browsing by Subject "Peripheral blood mononuclear cell"

The aim for this project is to set up a high-content imaging pipeline for phenotypic analysis of single cells in peripheral blood mononuclear cell (PBMC) samples from healthy blood donors. The blood donors selected for the optimization experiments are known to carry specific allele variants of interest, based on an earlier FinnGen study. The main question is whether these genetic differences result in phenotypic changes in the PBMCs that can be identified by microscopic imaging and AI-guided image analysis. In this Pro Gradu work, I have optimized the pipeline of PBMC sample handling, immunostaining, and phenotypic imaging. PBMCs were gathered from healthy donors at the Blood Service Biobank. The frozen PBMC samples were thawed, and cells were plated on 384-well plates prior to immediate fixation with paraformaldehyde. The cells were then stained with fluorescent cell markers based on the Cell Painting assay (Bray et.al. 2016), followed by wide-field and confocal imaging with Opera Phenix high-content confocal microscope (FIMM High Content Imaging and Analysis unit). Novel deep learning methods are now being developed (Pitkänen group) to automatically learn phenotypes from the collected imaging data and associate them to the donor’s genotypes. We also used in-house tools for cell segmentation and further analysis as well as quality control (Paavolainen group). Primary results based on the features extracted from acquired images showed promising cell type - and donor -type specific clustering.