Supporting data for the thesis "Development of GaN microchip for label-free and scalable monitoring of single-cell dynamic behaviors"

Accurately elucidating the intricate and dynamic behaviors of cells, along with their underlying mechanisms, is crucial for advancing the understanding of fundamental biological principles, improving disease diagnostics, and accelerating drug development. Conventional population-based approaches, which emphasize general patterns across cell populations, often overlook rare events and individual cell heterogeneity. In contrast, single-cell analysis techniques can effectively address this limitation by enabling discrete observations of individual cells.However, the most popular fluorescence-based single-cell techniques face significant challenges like photobleaching, chemical invasiveness, and potential biological perturbations, making them less suitable for long-term continuous sensing. Although label-free surface plasmon resonance-based methods can overcome these constraints, they are still hindered by high dependence on bulky and costly external optical/electrical equipment for scalable measurement and large-scale deployment.To overcome these barriers, this thesis aims to develop a highly integrated, scalable biosensor capable of label-free, real-time, long-term single-cell analysis. Furthermore, through various signal transduction pathways, individual cells inherently can perceive, detect, and respond to extracellular changes, making it possible to function as a biosensor for high-sensitivity detection of the external environment (e.g., extracellular matrix, neighboring cells). Hence, this paper also focuses on how individual cells dynamically sense and respond to their surroundings, providing insights into developing cell-based single-cell sensors.

精准阐明细胞复杂且动态的行为及其内在机制，对于深化基础生物学原理的认知、提升疾病诊断水平以及加速药物研发进程均具有至关重要的意义。传统基于群体的研究方法侧重于细胞群体的共性模式，往往会忽略罕见事件与单细胞异质性（single-cell heterogeneity）。相较而言，单细胞分析技术（single-cell analysis techniques）可通过实现对单个细胞的离散式观测，有效弥补上述局限。然而，当前主流的基于荧光的单细胞技术面临诸多严峻挑战，例如光漂白（photobleaching）、化学侵入性以及潜在的生物学扰动（biological perturbations），这使得其难以适配长期连续传感场景。尽管无标记的基于表面等离子体共振（surface plasmon resonance）的方法可克服上述局限，但此类方法仍受制于对体积庞大且成本高昂的外部光学/电学设备的高度依赖，难以实现规模化测量与大规模部署。为突破上述瓶颈，本论文旨在开发一款高度集成、可扩展的生物传感器（biosensor），可实现无标记、实时、长期的单细胞分析。此外，单个细胞可通过各类信号转导通路（signal transduction pathways）固有地感知、检测并响应细胞外环境变化，这使其可作为生物传感器，实现对外部环境（例如细胞外基质（extracellular matrix）、邻近细胞）的高灵敏度检测。因此，本研究同时聚焦于单个细胞如何动态感知并响应其所处环境，以期为开发基于细胞的单细胞传感器提供理论参考。