Researchers have observed that a small number of cells in the human body lose their ability to divide, but remain active cells. There are many unanswered questions about these “senescent cells,” including how they contribute to both chronic diseases of aging and healthy functions like wound healing. The NIH Common Fund’s Cellular Senescence Network (SenNet) is identifying and characterizing senescent cells to construct “atlases” that will show where different types of senescent cells are located within human and mouse tissues. SenNet researchers rely on multiple methods to characterize the cells, including spatial transcriptomics, which pairs imaging and genetic sequencing techniques to measure gene activity in precise locations of a tissue sample. Location plays an important role for senescent cells because they often release molecules that affect neighboring cells. However, there is a need for computational methods that can use spatial transcriptomics data to better understand unique cell features resulting from the cell’s location in the tissue. Fortunately, the NIH Common Fund’s 4D Nucleome (4DN) program has spent significant time advancing technology that combines imaging and genetic sequencing, like spatial transcriptomics, in its effort to study how the shape and arrangement of chromatin in the cell influences gene activity and consequently human health.
A research team led by Dr. Jian Ma, a member of both the SenNet and 4DN programs, developed a computational method called SPICEMIX that can analyze spatial transcriptomics data to understand cell identities in tissues containing multiple cell types, like those being collected in SenNet. Using models of the cortex region of the mouse brain, SPICEMIX matched or outperformed existing methods in identifying cell types using information about gene activity and location. SPICEMIX could identify cell types specific to a certain layer of tissue or found sparsely distributed across multiple tissue layers. These cell types are more difficult to identify using existing methods. Development of new tools like SPICEMIX brings the field closer to understanding how, when, where, and why senescent cells form in the body and how they may play a role in chronic diseases of aging.
Reference
- SPICEMIX enables integrative single-cell spatial modeling of cell identity. Chidester B, Zhou T, Alam S, Ma J. Nature Genetics. 2023 Jan;55(1):78-88. doi: 10.1038/s41588-022-01256-z. Epub 2023 Jan 9.
