Label-free morphological profiling of immune cells : methods and applications

Abstract

The human body's immune system has two primary lines of defense, innate and adaptive. These defenses work in tandem through cellular communication to combat harmful substances. In the second stage of the immune response, T cells play a crucial role in both commanding innate cells for sustained confrontation towards pathogens while recruiting other cells, such as B cells to secrete antibodies for protection. As a result, the first immunotherapy developed, such as CAR-T, was based on the principle of invigorating the human immune system with engineered T cells to fight against cancers. One of the reasons for successfully establishing this cell-based therapy was the advancement of tools for investigating immune cell proteins and gene expressions. Nevertheless, common tools such as single-cell RNA sequencing and reverse-transcription quantitative polymerase chain reaction, require laborious work to ensure the quality of results and high cost. Fast screening of protein expressions of immune cells such as flow cytometry has the constraint of the limited number of proteins to be detected. This thesis first introduced the efforts onadopting label-free screening instruments, mainly quantitative phase imaging (QPI) for investigating immune cell properties which can greatly reduce the time for cell properties investigation without prior staining. However, the low throughput of those systems is one of the limitations for imaging experts to collect more data for studying cell morphological changes in different biological events. To compensate for this limitation, this thesis aims to explore the T cell activation progress with high-throughput, ultrafast scanning QPI imaging flow cytometry, multiplexed Asymmetric-detection Time-stretch Optical Microscopy (multiATOM), to understand if the optobiophysical profiling could be done by gathering cell optobiophysical morphological features of each cell at large scale. The thesis reported the high-resolution, single-cell images obtained from multi-ATOM were able to identify crucial optobiophysical profiles of T cells activation, between resting states and activation states, in addition to T cell subtypes (CD4+ and CD8+) profile changes from early to late stage of activation. This illustrated the unrevealed capability of applying QPI toward large-scale immunological studies in the future such as screening of efficacy-engineered T cells towards targeted cells such as cancerous cells. Nevertheless, improvement in identifying optobiophysical features changes towards biological events is necessary and thus is also another area that should be worked on in the future to allow the method to be applied in clinical practice.