Developing a lung organoid signalome for real-time analysis of senescence-associated cellular cross talk

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Cells in our body suffer damage on a daily basis, and this is particularly true in the lungs which are constantly exposed to dangerous agents in the air that we breathe. In isolation, the effect of pollution, diesel particles, tobacco smoke, allergens and viral insults may be mild, but repeated exposure over many years can lead to development of diseases which have long term effects on lung health including Idiopathic Pulmonary Fibrosis (IPF) and Chronic Obstructive Pulmonary Disease (COPD). After exposure to an insult, the cells in the lung have to decide how to respond. In younger healthy individuals, lung cells will quickly repair themselves in response to a mild insult, restoring ormal lung function. As we age, the effect of years of repeated mild injuries leads the lung cells to respond in a different way, a process called cellular senescence. Senescent cells so not divide, so they are unable to aid in the repair of the lung following even mild injury. They also do not die. Instead they remain in the lungs and release signals which encourage neighbouring cells to also become senescent. Accumulation of these senescent, defective cells appears to contribute to the development of chronic lung disease although the exact process is unclear. We will create a 3D model of the human lung which contains two of the most important lung cell types, epithelial cells and fibroblasts. These cells will be modified so that they can change colour in response to signals generated by senescent cells. We will use this model to try and understand how healthy cells in the lung respond to signals from senescent cells, and how neighbouring cells influence each other's behaviour. Understanding how senescent cells increase in number in the aging lung could help us to identify new treatment to prevent these dysfunctional cells from collecting in the lung and causing disease.