Unmasking “zombie cells” in aging tissue with an AI-powered barcode

Amazing stuff!

"... researchers have developed a noninvasive way to detect biomarkers of senescence. Their method is based on Raman microscopy, which can reveal the biochemical composition of cells without harming them.

By combining Raman microscopy with gene expression data at single-cell resolution from the same cells, the researchers were able to identify unique “barcodes” that can be used to quickly identify senescent cells. This study was done in mouse cells, but the researchers are now working on adapting it for use with human tissue. ..."

From the abstract:

"Aging and tissue repair involve heterogeneous remodeling across transcriptional, biochemical and cellular dimensions, yet prevailing definitions rely on isolated molecular markers that obscure how these states co-evolve.

Here we present RamanOmics, a multimodal framework integrating label-free hyperspectral Raman imaging with single-nucleus RNA sequencing and spatial transcriptomics to link biochemical states with transcriptional programs at single-cell spatial resolution. Applied to young and old mouse lung and skin, RamanOmics reveals tissue-specific programs:

lung senescent cells are enriched for extracellular matrix remodeling and transforming growth factor-β signaling, whereas

skin senescence is dominated by epidermal differentiation genes (Krt10, Lor and Sbsn).

Across tissues, we identified a conserved lipid-linked Raman signature (1,131–1,135 cm−1) marking p21+ senescent cells and developed a machine learning-derived, multimodal barcode enabling nondestructive senescence identification in situ.

In a mouse wound-healing model, RamanOmics reveals reactivation of epidermal differentiation genes (Krt10, Lor and Sbsn) in senescent cells, alongside increased lipid-associated Raman signatures. Together, RamanOmics provides a tissue-agnostic framework for scalable, multimodal profiling of cellular states."

Unmasking “zombie cells” in aging tissue with an AI-powered barcode | MIT News | Massachusetts Institute of Technology "Tracking down senescent cells, which accumulate as we age, could help diagnose age-related disorders and guide researchers working on new treatments."

RamanOmics decodes the spatial vibrational–molecular architecture of senescence in aging and repair (open access)

Fig. 1: RamanOmics workflow and dynamics of gene regulation across ages and tissues.