Assessing motile cilia coverage and beat frequency in mammalian in-vitro cell culture tissues
Cilia density, distribution and beating frequency are important parameters lung tissues, for example in diagnostics of Primary Ciliary Dyskinesia, and in the study of in vitro models, e.g. derived from induced Pluripotent Stem Cells. Video microscopy can be used to characterise these parameters, but most tools available at the moment are limited in the type of information they can provide, usually only describing the ciliary beat frequency of very small areas, while requiring human intervention and training for their use. We propose a novel and open source method to fully characterise cilia beating frequency and motile cilia coverage in an automated fashion without user intervention. We demonstrate the ability to differentiate between different coverage densities, identifying even small patches of cilia in a larger field of view, and to fully characterise the cilia beating frequency of all moving areas. We also show that the method can be used to combine multiple fields of view to better describe a sample without relying on small pre-selected regions of interest. This is released with a simple graphical user interface for file handling, enabling a full analysis of individual fields of view in a few minutes on a typical personal computer.