Comparative and practical aspects of localization-based super-resolution imaging

Chibby promotes ciliary vesicle formation and basal body docking during airway cell differentiation

Airway multiciliated epithelial cells play crucial roles in the mucosal defense system, but their differentiation process remains poorly understood. Mice lacking the basal body component Chibby (Cby) exhibit impaired mucociliary transport caused by defective ciliogenesis, resulting in chronic airway infection. In this paper, using primary cultures of mouse tracheal epithelial cells, we show that Cby facilitates basal body docking to the apical cell membrane through proper formation of ciliary vesicles at the distal appendage during the early stages of ciliogenesis. Cby is recruited to the distal appendages of centrioles via physical interaction with the distal appendage protein CEP164. Cby then associates with the membrane trafficking machinery component Rabin8, a guanine nucleotide exchange factor for the small guanosine triphosphatase Rab8, to promote recruitment of Rab8 and efficient assembly of ciliary vesicles. Thus, our study identifies Cby as a key regulator of ciliary vesicle formation and basal body docking during the differentiation of airway ciliated cells.

Test samples for optimizing STORM super-resolution microscopy

STORM is a recently developed super-resolution microscopy technique with up to 10 times better resolution than standard fluorescence microscopy techniques. However, as the image is acquired in a very different way than normal, by building up an image molecule-by-molecule, there are some significant challenges for users in trying to optimize their image acquisition. In order to aid this process and gain more insight into how STORM works we present the preparation of 3 test samples and the methodology of acquiring and processing STORM super-resolution images with typical resolutions of between 30-50 nm. By combining the test samples with the use of the freely available rainSTORM processing software it is possible to obtain a great deal of information about image quality and resolution. Using these metrics it is then possible to optimize the imaging procedure from the optics, to sample preparation, dye choice, buffer conditions, and image acquisition settings. We also show examples of some common problems that result in poor image quality, such as lateral drift, where the sample moves during image acquisition and density related problems resulting in the 'mislocalization' phenomenon.