Electron Microscopy Techniques for Investigating Structure and Composition of Hair-Cell Stereociliary Bundles

0301 basic medicine Cell and Developmental Biology 03 medical and health sciences electron microscopy QH301-705.5 cochlea SEM TEM Biology (General) hair cell stereocilia
DOI: 10.3389/fcell.2021.744248 Publication Date: 2021-10-22T07:30:11Z
ABSTRACT
Hair cells—the sensory cells of the vertebrate inner ear—bear at their apical surfaces a bundle of actin-filled protrusions called stereocilia, which mediate the cells’ mechanosensitivity. Hereditary deafness is often associated with morphological disorganization of stereocilia bundles, with the absence or mislocalization within stereocilia of specific proteins. Thus, stereocilia bundles are closely examined to understand most animal models of hereditary hearing loss. Because stereocilia have a diameter less than a wavelength of light, light microscopy is not adequate to reveal subtle changes in morphology or protein localization. Instead, electron microscopy (EM) has proven essential for understanding stereocilia bundle development, maintenance, normal function, and dysfunction in disease. Here we review a set of EM imaging techniques commonly used to study stereocilia, including optimal sample preparation and best imaging practices. These include conventional and immunogold transmission electron microscopy (TEM) and scanning electron microscopy (SEM), as well as focused-ion-beam scanning electron microscopy (FIB-SEM), which enables 3-D serial reconstruction of resin-embedded biological structures at a resolution of a few nanometers. Parameters for optimal sample preparation, fixation, immunogold labeling, metal coating and imaging are discussed. Special attention is given to protein localization in stereocilia using immunogold labeling. Finally, we describe the advantages and limitations of these EM techniques and their suitability for different types of studies.
SUPPLEMENTAL MATERIAL
Coming soon ....
REFERENCES (87)
CITATIONS (24)
EXTERNAL LINKS
PlumX Metrics
RECOMMENDATIONS
FAIR ASSESSMENT
Coming soon ....
JUPYTER LAB
Coming soon ....