By David Raible, Ph.D.
Cells transition through states as they grow, divide, and differentiate. Measuring gene transcription has proven to be a powerful method for understanding and classifying cell types. However, cells can change in ways that are not necessarily reflected in gene transcription levels.
The shape of a cell can give important clues about what it does and how it functions, so cell shape analysis offers another avenue to quantitatively characterize and classify cells. Methods to encode cell shape in an unbiased, high dimensional representation have been employed with great success to cells in culture, but most studies of cell shape in living, developing animals have relied on 2D projections of cells or representative 3D geometric features, which may not capture many aspects of cell shape in these tissues.
As published in the journal Development in January 2024, we developed a workflow to semi-automatically detect and measure the 3D shapes of cells and their nuclei in microscopic images. We used mathematical techniques (spherical harmonics and principal components analysis) to break down the complex shapes into simpler descriptive features.
The researchers used mathematical techniques to identify major shape features that distinguish sensory cell types in the zebrafish model. Credit and to see full caption and image: Hewitt, Cruz, and Raible/Development
We applied this approach to study neuromast cells of the zebrafish. Neuromasts consist of sensory hair cells, which detect water movement, and support cells. These hair cells share many molecular and cellular properties with those in the inner ear, including their propensity to be damaged by environmental insult. We found cell shape varies based on location and cell type. The distinction between hair cells and support cells accounted for much of the variation, which allowed us to train classifiers to predict cell identity from shape features.
Using genetic markers, we could separate support cells into subtypes and saw they had distinct shapes too. To investigate how loss of a neuromast cell type altered cell shape distributions, we examined Atoh1a variants of the zebrafish that lacked hair cells. These altered zebrafish lost the hair cell shape profile, but did not gain a new variant-specific cell shape.
It would be illuminating to explore other genes and signaling pathways that may pattern cell shape within neuromasts. The analysis of cell shapes can help us understand how changes in the appearance of hair cells are influenced by various genetic and drug-related alterations. Zebrafish hair cells are also able to regenerate from surrounding support cells, and future shape analysis could lead to better understanding of the underlying processes by which this occurs.
Our results demonstrate the utility of using 3D cell shape features to characterize, compare, and classify cells in a living, developing organism.
Hearing Restoration Project member David Raible, Ph.D., is the corresponding author on the Development paper written with Madeleine Hewitt, Ph.D., and Iván Cruz, Ph.D., who are both members of Raible’s University of Washington lab.
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