Developing a bioprinted ventilated lung alveolar platform for investigating microbial interactions and influenza response

PROJECT SUMMARY / ABSTRACT Our goal is to understand how the lung microbiome regulates influenza virus infection response by developing a 3D in vitro bioprinted platform to study host-microbiome-influenza interactions in the lung alveolar space. The respiratory microbiome, encompassing hundreds of different bacterial and fungal species, has essential roles in the development of tissue-specific immunity and colonization resistance to pathogens, including viral infection. The lung and alveolar space undergo constant microbial exposure from the inhalation of oropharyngeal contents. Notably, sequencing-based studies have identified a low biomass but diverse microbial signature in healthy individuals. However, a detailed mechanistic understanding of how these diverse microbes interact with host cells to maintain lung health and contribute to viral infection susceptibility is currently lacking. Major knowledge gaps exist due to 1) the substantial biodiversity of the lung microbiome, 2) difficulties in modeling the complexity of the human lung environment, and 3) limited information about where in the lung epithelium these interactions take place and what are the cell-type specific host responses. Additionally, Current approaches lack the capacity to model host-microbe interactions in the lung at transcriptional and spatial resolution. We will overcome these limitations by developing two new technologies – a 3D bioprinted alveolar sac model and dual host-microbe spatial transcriptomics (ST) – to enhance our understanding of the host response to microbial colonization in an advanced, anatomically relevant lung model. The ability to examine which and how specific microbes interact with the lung epithelium and the effect these interactions on influenza infection would be valuable to investigate the microbiome’s role in lung health and infection response. In Aim 1, we will develop and characterize a 3D bioprinted ventilated alveolar sac model. We will then evaluate its influenza infection response using ST and single-cell RNA-sequencing. In Aim 2, we will examine how diverse respiratory microbiota condition the alveolar epithelium to affect influenza infection response. We will develop a dual ST method to simultaneously profile host transcriptional response and microbial/viral localization. We will then use this method to examine how microbial conditioning of the epithelium affects influenza infection dynamics. Together, these aims will allow us to address fundamental questions on the underlying biology of the lung microbiome and its effect on influenza response. Our success would result in two new technologies facilitating the construction of a high-resolution spatial map of the microbiome-host interactions. This advancement would enable in-depth investigations into the mechanisms of interstrain interactions, virulence regulation, and their impact on lung immune homeostasis and infection response.