MIT News breed · Science

AI-Powered Barcode Identifies Senescent Cells Non-invasively

Researchers developed a novel AI and Raman microscopy method to identify senescent cells, which accumulate with age and contribute to age-related diseases. This non-invasive technique creates a unique "barcode" for these cells.

Senescent cells stop dividing but do not die, potentially causing age-related issues. The new method combines Raman microscopy with single-cell gene expression data.

This combination identifies unique "barcodes" that flag senescent cells. The study used mouse cells, with ongoing efforts for human tissues.

The research aims to enable future diagnostics, like an endoscope identifying senescence within the body. This is part of a larger NIH initiative.

Senescence is triggered by DNA damage, leading to cell cycle arrest and altered cell metabolism and gene expression. Immune system clearance declines with age.

Previous biomarker identification methods destroyed cells. Raman microscopy is non-destructive, revealing chemical composition via light.

Integrating Raman microscopy with spatial RNA sequencing identified new markers, including increased lipid synthesis in older mouse cells.

The "barcode" uses Raman peaks linked to specific molecules. Researchers are developing a faster imaging system for larger samples and diagnostics.

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