Back

Development of a Xenopus-based assay for high-throughput evaluation of mucociliary flow

Antoniades, I.; Koulle, A.; Chatzifrangkeskou, M.; Konstantinou, T.; Skourides, P. A.

2022-07-13 cell biology
10.1101/2022.07.12.499724 bioRxiv
Show abstract

Motile cilia are organelles lining the surfaces of major organs of the human body and generate directional fluid flow. Ciliary dysfunction has been linked to an emerging class of multisystem disorders, collectively known as motile ciliopathies. Drug screening for ciliopathies is challenging due to the unavailability of high-throughput assays that can evaluate ciliary flow generation. Here, we describe the development of a unique assay that enables the direct and rapid evaluation of mucociliary flow, which simultaneously facilitates high-throughput screening of potential therapeutic agents for motile ciliopathies. The assay relies on the ability of Xenopus tadpoles to promote mixing of a two-phase differential density aqueous mixture, through the robust flow generated by the mucociliary epithelium on their epidermis. We show that the rate of phase mixing is proportional to the rate of cilia-driven flow, therefore it directly represents the effectiveness of flow generation. We also demonstrate that the assay can detect changes in ciliary flow elicited by defects in cilia, CBF modulation and rotational polarity, providing an ideal assay for the identification of CBF-modulating compounds, as potential drugs for motile ciliopathies. Importantly we use the assay to show that CBF modulating drugs can improve flow generation and could thus be used as a potential therapeutic approach in PCD patients. The assay we have developed thus represents a powerful new tool for research, as well as drug development.

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.