A PhD studentship examining the effect of high cholesterol on unconventional immune cell interactions for a better understanding of inflammation in atherosclerosis is available at Cardiff University funded by the Wales Heart Research Institute (WHRI). This studentship will be supervised by Dr Kristin Ladell (School of Medicine), Prof Dipak Ramji (School of Biosciences) and Dr. Meike Heurich (School of Pharmacy).
Aims:
To determine whether hypercholesterolaemia changes the frequency, phenotype and/or activation status of types of immune cells not found in mice in the blood of healthy individuals compared to patients with hypercholesterolaemia using multiparameter imaging analyses.
To isolate these immune cells from the blood of patients/controls and expose them to different types of fluorescently labelled cholesterol to determine the localisation of the cholesterol inside/on the surface of these cells in relation to specific receptors found in/on these cells.
To use cells engineered to express these specific cell surface receptors to examine their interaction with immune cells isolated from patients/controls before and after exposure to different types of cholesterol. This interaction could be specifically targeted with future therapies.
To assess this interaction at the biomolecular level.
You will become proficient in state-of-the-art spectral flow cytometry using a BD FACSDiscover S8 with integrated imaging (CellViewTM)) for an in-depth characterisation of the various immune cells found in the circulation of patients with hypercholesterolaemia and healthy controls. You will be trained to use various software and software algorithms for analysis of complex/large datasets and for data presentation. You will also use high-resolution fluorescent microscopy and learn several other laboratory techniques including molecular techniques such as single-cell mRNA sequencing and Biacore, which is a technique to study biomolecular interactions. You will be supported by experts in statistics, bioinformatics and clinical trials.
