Serial scanning electron microscopy of anti-PKHD1L1 immuno-gold labeled mouse hair cell stereocilia bundles

VASCilia (Vision Analysis StereoCilia): A Napari Plugin for Deep Learning-Based 3D Analysis of Cochlear Hair Cell Stereocilia Bundles

Cochlear hair cell stereocilia bundles are key organelles required for normal hearing. Often, deafness mutations cause aberrant stereocilia heights or morphology that are visually apparent but challenging to quantify. Actin-based structures, stereocilia are easily and most often labeled with phalloidin then imaged with 3D confocal microscopy. Unfortunately, phalloidin non-specifically labels all the actin in the tissue and cells and therefore results in a challenging segmentation task wherein the stereocilia phalloidin signal must be separated from the rest of the tissue. This can require many hours of manual human effort for each 3D confocal image stack. Currently, there are no existing software pipelines that provide an end-to-end automated solution for 3D stereocilia bundle instance segmentation. Here we introduce VASCilia, a Napari plugin designed to automatically generate 3D instance segmentation and analysis of 3D confocal images of cochlear hair cell stereocilia bundles stained with phalloidin. This plugin combines user-friendly manual controls with advanced deep learning-based features to streamline analyses. With VASCilia, users can begin their analysis by loading image stacks. The software automatically preprocesses these samples and displays them in Napari. At this stage, users can select their desired range of z-slices, adjust their orientation, and initiate 3D instance segmentation. After segmentation, users can remove any undesired regions and obtain measurements including volume, centroids, and surface area. VASCilia introduces unique features that measures bundle heights, determines their orientation with respect to planar polarity axis, and quantifies the fluorescence intensity within each bundle. The plugin is also equipped with trained deep learning models that differentiate between inner hair cells and outer hair cells and predicts their tonotopic position within the cochlea spiral. Additionally, the plugin includes a training section that allows other laboratories to fine-tune our model with their own data, provides responsive mechanisms for manual corrections through event-handlers that check user actions, and allows users to share their analyses by uploading a pickle file containing all intermediate results. We believe this software will become a valuable resource for the cochlea research community, which has traditionally lacked specialized deep learning-based tools for obtaining high-throughput image quantitation. Furthermore, we plan to release our code along with a manually annotated dataset that includes approximately 55 3D stacks featuring instance segmentation. This dataset comprises a total of 1,870 instances of hair cells, distributed between 410 inner hair cells and 1,460 outer hair cells, all annotated in 3D. As the first open-source dataset of its kind, we aim to establish a foundational resource for constructing a comprehensive atlas of cochlea hair cell images. Together, this open-source tool will greatly accelerate the analysis of stereocilia bundles and demonstrates the power of deep learning-based algorithms for challenging segmentation tasks in biological imaging research. Ultimately, this initiative will support the development of foundational models adaptable to various species, markers, and imaging scales to advance and accelerate research within the cochlea research community.

Mini-PCDH15 gene therapy rescues hearing in a mouse model of Usher syndrome type 1F

Usher syndrome type 1 F (USH1F), caused by mutations in the protocadherin-15 gene (PCDH15), is characterized by congenital deafness, lack of balance, and progressive blindness. In hair cells, the receptor cells of the inner ear, PCDH15 is a component of tip links, fine filaments which pull open mechanosensory transduction channels. A simple gene addition therapy for USH1F is challenging because the PCDH15 coding sequence is too large for adeno-associated virus (AAV) vectors. We use rational, structure-based design to engineer mini-PCDH15s in which 3-5 of the 11 extracellular cadherin repeats are deleted, but which still bind a partner protein. Some mini-PCDH15s can fit in an AAV. An AAV encoding one of these, injected into the inner ears of mouse models of USH1F, produces a mini-PCDH15 which properly forms tip links, prevents the degeneration of hair cell bundles, and rescues hearing. Mini-PCDH15s may be a useful therapy for the deafness of USH1F.

Deficit of PKHD1L1 in the dentate gyrus increases seizure susceptibility in mice

Epilepsy is a chronic neurological disorder featuring recurrent, unprovoked seizures, which affect more than 65 million people worldwide. Here, we discover that the PKHD1L1, which is encoded by polycystic kidney and hepatic disease1-like 1 (Pkhd1l1), wildly distributes in neurons in the central nervous system (CNS) of mice. Disruption of PKHD1L1 in the dentate gyrus region of the hippocampus leads to increased susceptibility to pentylenetetrazol-induced seizures in mice. The disturbance of PKHD1L1 leads to the overactivation of the mitogen-activated protein kinase (MAPK)/extracellular regulated kinase (ERK)-Calpain pathway, which is accompanied by remarkable degradation of cytoplasmic potassium chloride co-transporter 2 (KCC2) level together with the impaired expression and function of membrane KCC2. However, the reduction of membrane KCC2 is associated with the damaged inhibitory ability of the vital GABA receptors, which ultimately leads to the significantly increased susceptibility to epileptic seizures. Our data, thus, indicate for the first time that Pkhd1l1, a newly discovered polycystic kidney disease (PKD) association gene, is required in neurons to maintain neuronal excitability by regulation of KCC2 expression in CNS. A new mechanism of the clinical association between genetic PKD and seizures has been built, which could be a potential therapeutic target for treating PKD-related seizures.

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

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.