Integrated optical and mechanical phenotyping platform for high-throughput single-cell analysis

Abstract

Recent advanced developments in optical microscopy allow researchers to quantify a wide range of biological phenotypes at single-cell precision. It constantly transforms the practice in clinical diagnostics, drug discovery, and biological research. Notably, the emergence of ultrafast quantitative phase imaging (QPI), that offers label-free biophysical profiling of cells, has created new opportunities to overcome the limitations of conventional cellular assays in both measurement throughput and content. It thus unveiled a new direction towards next-generation image-based single-cell analysis. In this work, we explored the potential of applying high-throughput biophysical characterisation of cells enabled by ultrafast QPI in addressing different challenges in biological research. The study on red blood cell degradation over prolonged storage was first demonstrated. Previously, storage lesion of red blood cells was manually assessed by their morphological changes using blood smear analysis. The integration of imaging flow cytometry has automated the process; however, the accuracy was still limited by the classification of morphological stages based solely on bright-field images. The development and application of QPI flow cytometry have enabled large-scale, high dimensional, label-free analysis of red blood cells. We demonstrated the ability to track the deterioration progression over a timespan of eight days based on the subtle morphological changes read out by the QPI flow cytometry platform. This novel approach has showcased the ability to translate such quantitative label-free imaging into clinical applications. The next part of this work focused on the microfluidic integration of mechanical phenotyping of cells, which enables real-time deformability cytometry, into the current imaging system. The QPI system was further re-engineered to tackle the common challenge in accurate quantification of cell deformability based on line-scan QPI operation. Specifically, this system refinement has tackled the impact of cell-size-dependent velocity on faithful image reconstruction in line scan imaging, hence the morphological feature extraction. The performance of the system was validated through the imaging of beads and cell samples. The result also suggested the possibility of incorporating multiple line scans in the current imaging system for other purposes, for example cell sorting. A feasibility study, which consists of a series of experiments, was done to investigate the capability of the integrated optical and mechanical phenotyping platform. Firstly, deformable microbeads and cancer cell lines were used to test the imaging protocol and image quality. The system demonstrated the ability to distinguish between beads (or cell types) with different stiffness and to capture multi-contrast cell images at subcellular resolution. Next, a proof-of-concept drug treatment experiment was performed. A breast cancer cell line MDA-MB-231 was treated with cytoskeletal drug Vinblastine. The results showed that the system was able to capture changes in their mechanical properties and demonstrated the ability to quantify mechanical responses to drugs through high-dimensional morphological feature analysis. To summarise, this work presents the application of high-throughput, label-free, imaging system and its integration with microfluidic deformability cytometry. This integrated platform could allow us to understand biophysical and mechanical cellular heterogeneity and uncover salient cost-effective biomarkers of health and disease - ushering in effective label-free diagnostics.