Transcriptome-aligned metabolic profiling by SERSome reflects biological changes following mesenchymal stem cells expansion.

Abstract

Background: Mesenchymal stem cells (MSCs) are widely applied in the treatment of various clinical diseases and in the field of medical aesthetics. However, MSCs exhibit greater heterogeneity limited stability, and more complex molecular and mechanistic characteristics compared to conventional drugs, making rapid and precise monitoring more challenging.

Methods: Surface-enhanced Raman spectroscopy (SERS) is an ultrasensitive, tractable and low-cost fingerprinting technique capable of identifying a wide range of molecules related to biological processes. Here, we employed SERS for reproducible quantification of ultralow concentrations of molecules and utilized spectral sets, termed SERSomes, for robust and comprehensive intracellular multi-metabolite profiling.

Results: We revealed that with increasing passage number, there is a gradual decline in cell expansion efficiency, accompanied by significant changes in intracellular amino acids, purines, and pyrimidines. By integrating these metabolic features detected by SERS with transcriptomic data, we established a correlation between SERS signals and biological changes, as well as differentially expressed genes.

Conclusion: In this study, we explore the application of SERS technique to provide robust metabolic characteristics of MSCs across different passages and donors. These results demonstrate the effectiveness of SERSome in reflecting biological characteristics. Due to its sensitivity, adaptability, low cost, and feasibility for miniaturized instrumentation throughout pretreatment, measurement, and analysis, the label-free SERSome technique is suitable for monitoring MSC expansion and offers significant advantages for large-scale MSC manufacturing.