Single-cell Raman spectroscopy as a novel platform for unveiling the heterogeneity of mesenchymal stem cells.

Abstract

Despite the significant potential of mesenchymal stem cells (MSC) therapy in clinical settings, challenges persist regarding the efficient detection of consistency and uniformity of MSC populations. Raman spectroscopy is a fast, convenient, and nondestructive technique to acquire molecular properties of biomolecules across laboratory and mass-production settings. Here we utilized Raman spectroscopy to evaluate the heterogeneity of primary MSC from varying donors, passages, and distinct culture conditions, and compared its effectiveness with conventional techniques such as flow cytometry. Although these MSC exhibited insignificant differences in morphology and surface markers in flow cytometry analysis, they could be distinctly clustered into different populations by Raman spectroscopy and the subsequent machine learning using linear discriminant analysis. Principal component analysis demonstrated limited efficiency in clustering Raman data from diverse sources, which could be enhanced through combination with support vector machine or deterministic finite automation. These findings highlight the sensitivity of Raman spectroscopy in detecting subtle differences. Moreover, the analysis of characteristic Raman peaks attributed to cellular biomolecules in MSC from passages 2 (P2) to P10 revealed a gradual decrease in the levels of nucleic acids, lipids, and proteins with increasing passages, and a significant increase in carotenoids from P8. These results suggest the potential use of Raman spectroscopy to assess cellular biochemical characteristics such as aging, with carotenoids emerging as a potential marker of cell aging. In conclusion, Raman spectroscopy demonstrates the ability to rapidly and non-invasively detect cellular heterogeneity and biochemical status, offering significant potential for quality control in stem cell therapy.