Decoding temporal epithelial signaling programs to restore homeostasis in acute lung injury

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Abstract Acute lung injury/acute respiratory distress syndrome (ALI/ARDS) is a common pulmonary syndrome with high mortality. ALI/ARDS stems from a communication breakdown between lung epithelial cells and immune cells and is a major factor in severe cases of respiratory infection, including COVID-19. Treatments for ALI/ARDS are currently limited by inadequate models of the complex relationships between signaling pathways and lung epithelial cell behavior. A core network of signaling pathways control epithelial structure and cytokine release and are an important unexploited point of intervention in ALI/ARDS via existing targeted kinase inhibitors or metabolic modulators. This core network includes NF-kB, a primary transcription factor for cytokine release and inflammation, and the kinases ERK, AKT, JNK, p38, mTOR and AMPK, which modulate cytokine production in response to cellular growth and metabolic status. Notably, this signaling network also plays a causal role in lung cancer and is involved in other diseases of the lung epithelium, including fibrosis and COPD. Our lab has developed an extensive live-cell technology platform for tracking temporal programs of signaling events – different patterns of timing, intensity, and coordination between these pathways – that govern epithelial cell fate decisions. Our overall objective is to quantitatively decode how cytokine secretion is specified by multi-kinase activity programs. Our hypothesis is that accounting for coinciding phases of signaling activity at the single cell level will significantly improve the prediction of both overall and local variability in cytokine secretion and will identify metabolic manipulations that reduce inflammation. Our approach will develop the technology needed to detect and manipulate temporal signaling programs to restore lung epithelial homeostasis in ALI/ARDS. Aim 1 will develop a high-content data-driven model correlating signaling programs to cytokine release on a cell-by-cell basis across multiple conditions. Aim 2 will develop the capacity to characterize the localized inflammatory environment in subregions of lung epithelium by examining the dynamic programs of kinase signaling in groups of 10-100 neighboring cells. In the process, we will provide proof of principle for using panels of fixed immunofluorescence markers to capture dynamic signaling patterns. Aim 3 will investigate the potential for manipulating temporal signaling programs with existing pharmacological agents, focusing on the emerging benefits of AMPK activators as a route to modulate the larger signaling network. Our multi-disciplinary team will work across the boundaries of pulmonary care, cell biology, and computational systems modeling to create a technology platform that connects modern single- cell signal transduction analysis to pressing challenges in lung disease. We anticipate that our project will identify potential new routes of intervention for ALI/ARDS, as well as revealing general concepts in cytokine signaling pathways that are broadly relevant for the treatment of lung malignancies and inflammatory disease.