Platform for high-throughput biomechanical measurements using metallic islands on boron nitride nanosheets

使用氮化硼纳米片上的金属岛进行高通量生物力学测量的平台

• 批准号: 10158533
• 负责人: Darren J Lipomi
• 金额: $ 18.25万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-01 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10158533
• 关键词: Algorithms; Animals; Arrhythmia; Award; Benchmarking; Biological Assay; Biomechanics; Biomedical Engineering; Boron; Cancer Patient; Cardiac Myocytes; Cardiomyopathies; Cardiotoxicity; Cardiovascular system; Cells; Cellular biology; Cessation of life; Classification; Clinical; Data; Data Set; Detection; Development; Devices; Dilated Cardiomyopathy; Disease; Disease model; Drug Compounding; Drug Screening; Electrical Resistance; Engineering; Evaluation; Failure; Functional disorder; Health; Heart; Heart Diseases; Heart failure; Human; Human Biology; Hypertrophic Cardiomyopathy; Individual; Island; Kinetics; Maps; Measurement; Measures; Mechanics; Medicine; Membrane; Methods; Modeling; Mutation; Myopathy; Optics; Outcome; Patients; Pharmaceutical Preparations; Phenotype; Play; Process; Proteins; Relaxation; Role; Sarcomeres; Signal Transduction; Solid; Testing; Time; Tissue Engineering; Training; United States National Institutes of Health; Universities; Ursidae Family; analog; base; biomaterial compatibility; cellular engineering; chemotherapy; design; detection limit; drug development; drug discovery; experience; functional genomics; high throughput analysis; improved; induced pluripotent stem cell; innovation; instrumentation; machine learning algorithm; mechanical force; mechanical properties; metallicity; nano; nanofabrication; response; sensor; stem cells; therapeutic target; tool

SUMMARY This proposal describes a new platform for high-throughput measurement of mechanical phenomena in cells. The platform is based on a type of strain sensor comprising metallic nanoislands supported by hexagonal boron nitride. Mechanical deformation produces a change in both the electrical resistance and the optical scattering of these sensors. These processes allow the detection of deformations ≤1 ppm (≤0.0001% strain). This unprecedented level of sensitivity permits the measurement of minute forces produced by cells that cannot be measured using existing methods, and the electrical signals can be analyzed rapidly using machine-learning algorithms. While this sensor has a broad range of potential applications in cell biology, we apply it here to a ubiquitous challenge in cardiovascular medicine and drug discovery. In particular, contractile dysfunction in cardiomyocytes is associated with a range of difficult-to-treat cardiomyopathies. In drug discovery, cardiotoxicity (myopathy, arrhythmia, or both) is a leading reason for the failure of drugs during development and aftermarket launch. For some classes of drugs—especially those used in chemotherapy—up to 30% of patients experience heart disease related to their treatment. Indeed, heart failure is the second most common reason for death of cancer patients. There are currently no assays that are both predictive of cardiotoxicity and are of sufficient throughput to implement early in drug development (i.e., when safer drug leads can be selected among analogues). We propose the use of induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) bearing various disease-associated mutations as a test case of our nano-enabled biomechanical sensor. In particular, we will construct an array based on a “96-well” plate format combined with high-throughput analysis using a purpose-designed machine learning algorithm in order to measure the forces and kinetics of contractility of the cells. Such a platform would enable large-scale evaluation of disease mechanisms and accelerate therapeutic target discovery by permitting high-throughput, unbiased testing. This application offers the exciting possibility of introducing aspects of the biology of the human heart early in the discovery pipeline. More broadly, the platform we describe offers the potential of answering deep questions about mechanical phenomena in cells—“the mechanome”—which play critical roles in human health.

总结 该提案描述了一种新的平台，用于高通量测量细胞中的机械现象。 该平台基于一种应变传感器，其包括由六方硼支撑的金属纳米岛 氮化物机械变形产生的电阻和光学散射的变化， 这些传感器。这些过程允许检测≤1 ppm（≤0.0001%应变）的变形。这 前所未有的灵敏度允许测量细胞产生的微小力， 使用现有方法测量，并且可以使用机器学习快速分析电信号 算法虽然这种传感器在细胞生物学中具有广泛的潜在应用，但我们将其应用于 在心血管医学和药物发现中普遍存在的挑战。特别是， 心肌细胞的损伤与一系列难以治疗的心肌病有关。在药物发现中，心脏毒性 （肌病、心律失常或两者兼有）是药物在开发和售后市场失败的主要原因 发射对于某些类别的药物-特别是那些用于化疗-高达30%的患者的经验 与治疗有关的心脏病。事实上，心力衰竭是第二个最常见的死亡原因， 癌症患者。目前还没有既能预测心脏毒性又能充分预测 在药物开发早期实现的生产量（即，当更安全的药物先导可以选择， 类似物）。我们建议使用具有诱导性多能干细胞来源的心肌细胞（iPSC-CM）， 各种疾病相关的突变作为我们的纳米生物力学传感器的测试案例。特别是， 我们将构建一个基于“96孔”板格式的阵列，并结合高通量分析， 专门设计的机器学习算法，以测量收缩力和动力学， 细胞这样的平台将能够大规模评估疾病机制，并加速治疗。 通过允许高通量、无偏倚的测试来发现目标。这个应用程序提供了令人兴奋的可能性 在发现过程的早期引入人类心脏生物学的各个方面。更广泛地说，平台 我们描述了提供了回答关于细胞中机械现象的深层问题的潜力-“ “机械组”-在人类健康中发挥关键作用。