Roadmap to highest-throughput Raman flow cytometry for biological applications

Abstract

The interrogation of single cells is revolutionizing biology by revealing heterogeneity that is masked in bulk analyses. Flow cytometry (FCM) enables high-throughput single-cell analysis but typically depends on exogenous fluorescent labels, which are time-intensive to prepare and may perturb native cellular states. In contrast, Raman scattering provides a label-free alternative with intrinsic molecular specificity. Raman flow cytometry (RFC) combines Raman scattering with FCM, merging high-throughput sample processing with detailed molecular characterization. However, the inherently weak intensity of spontaneous Raman scattering necessitates long integration times, and precise cell positioning in the laser focal volume limits linear flow velocity, resulting in lower throughput compared to conventional fluorescence-based flow cytometry (FFC). Overcoming these limitations demands a multidisciplinary approach. Recent progress in nanofabrication have facilitated the development of microfluidic chips that help address this bottleneck through precise multiphysics-based cell focusing techniques, as well as scalability achieved through parallel channel arrays or droplet systems. This review examines three principal strategies for enhancing the throughput of RFC from the perspective of modern microfluidic frameworks: (ⅰ) advanced cell focusing methods, (ⅱ) Raman signal amplification techniques, and (ⅲ) artificial intelligence (AI)-assisted spectral analysis. By synthesizing recent advances in these areas, we highlight the potential of RFC to advance high-throughput, label-free single-cell analysis in biomedical research.