Back

A novel in vitro tubular model to recapitulate features of distal airways: the bronchioid

Maurat, E.; Raasch, K.; Leipold, A.; Henrot, P.; Zysman, M.; Prevel, R.; Trian, T.; Thumerel, M.; Nassoy, P.; Berger, P.; Saliba, A.-E.; Andrique, L.; Recher, G.; Dupin, I.

2023-12-08 physiology
10.1101/2023.12.06.569771 bioRxiv
Show abstract

BackgroundAirflow limitation is the hallmark of obstructive pulmonary diseases, with the distal airways representing a major site of obstruction. Although numerous in vitro models of bronchi already exist, there is currently no culture system for obstructive diseases that reproduces the architecture and function of small airways. Here, we aimed to engineer a model of distal airways to overcome the limitations of current culture systems. MethodsWe developed a so-called bronchioid model by encapsulating human bronchial adult stem cells derived from clinical samples in a tubular scaffold made of alginate gel. ResultsThis template drives the spontaneous self-organization of epithelial cells into a tubular structure. Fine control of the level of contraction is required to establish a model of the bronchiole, which has a physiologically relevant shape and size. 3D imaging, gene expression and single-cell RNA-seq analysis of bronchioids made of bronchial epithelial cells revealed tubular organization, epithelial junction formation and differentiation into ciliated and goblet cells. Ciliary beating is observed, at a decreased frequency in bronchioids made of cells from COPD patients. The bronchioid can be infected by rhinovirus. An air-liquid interface is introduced that modulates gene expression. ConclusionHere, we provide a proof of concept of a perfusable bronchioid with proper mucociliary and contractile functions. The key advantages of our approach, such as the air-liquid interface, lumen accessibility, recapitulation of pathological features and possible assessment of clinically relevant endpoints, will make our pulmonary organoid-like model a powerful tool for preclinical studies.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.