Real-time bioluminescent detection of circulating biomarkers

项目摘要/摘要 芯片器官技术最近为研究细胞和微型器官提供了新的工具 在3D环境中模拟本地器官结构的功能。然而，在这些封闭的系统中，它 仍然很难评估这些设备中包含的活细胞的健康和功能 追溯固定和抗体染色。分泌蛋白生物标记物可能为非 侵入性地评估这些细胞的健康和功能，尽管可靠地检测这些生物标志物的工具 在实时方面还没有开发出来。我们最近应用了一种芯片上器官的方法来研究 代谢紊乱糖尿病。在健康个体中，胰岛结构分泌这种小分子 胰岛素负向调节血糖水平，这一过程在糖尿病患者中被扰乱，导致 血糖水平升高。为了在体外研究胰岛功能缺陷的机制，我们 最近将人的胰岛整合到一个3D的血管器官芯片平台中，该平台 在活体内模拟胰腺。为了充分利用这一平台，一种简单、可靠和实时的传感方法 分泌的生物标志物胰岛素是评估芯片内胰岛功能所必需的。在此，我们建议 设计、开发和验证基于受体的生物发光成像方法，以优化实时 小蛋白生物标志物的检测。具体地说，我们将利用分离的荧光素酶构造与 人胰岛素受体及其底物IRS-1用于检测胰岛素结合，使用光输出作为读出 胰岛素浓度。这些工具的敏感度和特异度将在两个方面得到广泛验证 发展阶段：静态2D培养；随后在3D芯片上仿生胰腺的应用 站台。虽然这项提议的重点是开发这些胰岛素检测工具，但我们的方法已经 静态培养和动态培养中检测其他分泌型生物标志物的广泛意义 微流控平台。

Project Summary / Abstract Organ-on-a-chip technology has recently presented new tools for studying cellular and micro-organ function within a 3D environment mimicking native organ structures. However, in these enclosed systems, it remains difficult to evaluate the health and function of live cells contained within these devices without retroactive fixation and antibody staining. Secreted protein biomarkers may provide an opportunity to non- invasively evaluate the health and function of these cells, although the tools to reliably sense these biomarkers in real-time have yet to be developed. We have recently applied an organ-on-a-chip approach to study the metabolic disorder diabetes. In healthy individuals, pancreatic islet structures secrete the small molecule insulin to negatively regulate blood glucose levels, a process that is disrupted in diabetic individuals resulting in elevated blood glucose levels. In order to study the mechanisms underlying defective islet function ex vivo, we have recently incorporated human pancreatic islets within a 3D, vascularized organ-on-a-chip platform which mimics the pancreas in vivo. To fully exploit this platform, a simple, reliable, and real-time method for sensing the secreted biomarker insulin is necessary to evaluate islet function within the chip. Here, we propose to design, develop, and validate a receptor-based, bioluminescent imaging approach to optimize the real-time detection of small protein biomarkers. Specifically, we will utilize split luciferase constructs coupled to the human insulin receptor and its substrate, IRS-1, to detect insulin binding, using light output as a read-out of insulin concentration. The sensitivity and specificity of these tools will be extensively validated in two developmental phases: static 2D culture; followed by application in a 3D, biomimetic pancreas-on-a-chip platform. While this proposal focuses on developing these tools for insulin detection, our approach has broad implications in the detection of other secreted biomarkers in both static culture and dynamic microfluidic platforms.