Illuminating T and CAR-T cell dynamics by multiplexed imaging of single-FP biosensors

Introduction: Protein kinases function as key signaling nodes, controlling nearly every facet of cellular activity and integrating diverse stimuli to regulate complex physiological processes. Despite this, the spatiotemporal changes in different kinases, especially during cancer-immune interactions, remain poorly understood due to a lack of precise tools. Genetically encoded biosensors based on fluorescent proteins (FP) have become indispensable for dissecting intracellular signaling regulation. FRET-based biosensors, the state of the art, rely on pairs of FPs and typically occupy a broad spectral space, which restricts their ability to track multiple molecular activities simultaneously in the same cell. In contrast, the expanding toolkit of single-FP biosensors is increasingly enabling robust, ultrasensitive visualization of signaling dynamics across various living systems, including in vivo. However, the design of single-FP-based kinase biosensors, particularly for tyrosine kinases, remains largely unexplored, and their general applicability requires further validation. Additionally, developing an efficient approach for biosensor engineering is crucial. These biosensors and the multiplexed imaging platform will enable the live cell imaging of T cells or CAR-T cells when they engage with tumor cells.

Materials and

Methods: We hypothesized that the design of single-FP biosensors could be extended to develop biosensors for tyrosine kinases. To evaluate this, we constructed two prototypes: (1) the red Lck biosensor, R-LckAR, which combines an Lck-specific substrate sequence with a c-Src SH2 domain derived from the FRET-based sensor ZapLck, using cpmApple from R-Geco as the reporter unit; and (2) the green ZAP70 biosensor, ExRai-ZAPKAR, which pairs a substrate peptide from LAT (LATY191) with the Grb2 SH2 domain, known to interact with LAT pY191, using cpEGFP from ExRai-AKAR as the reporter unit. These prototypes, ExRai-ZAPKAR and R-LckAR, were transduced into Jurkat T cells, and their responses were quantified both before and after T-cell activation via anti-CD3/CD28 antibody stimulation. Additionally, recognizing the critical role of linker sequences in determining biosensor performance, we optimized ExRai-ZAPKAR by employing an evolutionary sort-seq approach. This method screened 160,000 biosensor candidates with variable linkers in mammalian cells to identify those with the best response to kinase activities.

Results, Conclusions, and Discussions: The prototypes R-LckAR and ExRai-ZAPKAR demonstrated substantial increases in fluorescence intensity and excitation ratios (480/400) upon T-cell activation. Specifically, the prototype green ZAP70 biosensor exhibited a 35% dynamic change, while the red R-LckAR showed a 10% change. The specificity of these responses was confirmed by the abolishment of signal changes upon pretreatment with the Lck inhibitor PP2 and the ZAP70 inhibitor TAK-659, validating the specificity of the biosensors. These findings underscore the potential of developing single-FP tyrosine kinase biosensors. Additionally, using the evolutionary sort-seq platform, we concurrently optimized the linkers in both biosensors. This optimization resulted in a significant enhancement in sensitivity, with some variants (e.g., Z2) showing a 300% increase in dynamic response, a marked improvement over the 35% change observed in the original versions. This confirms the efficacy of our directed evolution technique for high-throughput optimization of single-FP biosensors. Future research will focus on refining the red Lck biosensor with the library screening approach and exploring the application of these biosensors for multiplexed imaging of multiple molecular targets in single live T or CAR-T cells when they engage with tumor cell. In addition, with these sensitive live cell imaging tools, we will further explore the autoimmune disease progression mechanism with live cell imaging in vivo.

Acknowledgements (Optional): The authors would like to thank the Molecular Genomics Core at USC for the sequencing experiment. This work was supported in part by grants from NIH EB029122, GM140929, HL121365, HD107206, and CA262815, and NIH EB035649.