# Molecular Basis of Hair Cell Stereocilia Bundle Morphology

> **NIH NIH R01** · MASSACHUSETTS EYE AND EAR INFIRMARY · 2021 · $306,359

## Abstract

Project Summary: The sensory cells of the inner ear, the hair cells, carry a bundle of precisely organized
stereocilia bundles on their surface. Stereocilia are microvilli-like protrusions detecting sub-nanometer vibrations
enabling our perception of sound. This incredible sensitivity requires an ensemble of proteins, some of which
form mechanical linkages at the surface of stereocilia. These linkages have long been visualized with electron
microscopy, however, the specific function of some remain elusive. This proposal focuses on a specific novel
protein, Polycystic Kidney and Hepatic Disease 1-Like 1 (PKHD1L1), which is thought to be a major component
of the stereocilia surface coat and is hypothesized to facilitate stereocilia bundle cohesion. To understand the
spatiotemporal distribution of the protein throughout development, as well as the mechanism by which it causes
deafness when mutated, multiple high-resolution light and electron microscopy experiments using different
imaging modalities are being performed, resulting in a plethora of 2D and 3D images containing a wealth of data
which unfortunately are costly to analyze in their entirety. Often generated to answer one question, such data
sets could be shared with the scientific community for other groups to reuse for their research needs. As data
collection becomes increasingly more expensive and time consuming, more groups join in sharing their raw data
sets with the scientific community, in various formats often unsuitable for easy analysis. Advances in machine
learning for computer vision has made it feasible to automate these manual analysis tasks, however the
development of such models is heavily bottlenecked by the availability of training data which has been properly
prepared and annotated. This supplemental proposal aims to increase the availability of such training data by
annotating and depositing a wealth of imaging data in such a way that they may be readily used for the training
of machine learning models. We will annotate three types of imaging data we collect from wild-type and ko mice
to study the role of PKHD1L1 in hair cells: 1) cochlear hair cells on 3D confocal Z-stacks, 2) hair cell stereocilia
and mitochondria in our 3D focused ion beam scanning electron micrograph volumes, and finally 3) stereocilia
(in 2D) on our scanning electron micrographs of cochlear hair cell bundles. These annotations will be evaluated
by our collaborators specializing in machine learning volumetric image segmentation to help us assess data
biases, assess generalizability of our data annotation, and demonstrate the usability of the data in AI/ML
applications through mini-AI/ML applications as a proof of concept. A special attention will be given to
documenting our data and demonstrating their usability by retraining open-source machine learning algorithms
both, with the help of our collaborators, and in-house. The data, annotations, documentation, and example use
cases will be publicly hosted...

## Key facts

- **NIH application ID:** 10410746
- **Project number:** 3R01DC017166-04S1
- **Recipient organization:** MASSACHUSETTS EYE AND EAR INFIRMARY
- **Principal Investigator:** Artur Indzhykulian
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $306,359
- **Award type:** 3
- **Project period:** 2018-08-01 → 2023-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10410746

## Citation

> US National Institutes of Health, RePORTER application 10410746, Molecular Basis of Hair Cell Stereocilia Bundle Morphology (3R01DC017166-04S1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10410746. Licensed CC0.

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