Combined In vitro Experimental and Computational Approaches for Predicting the Identity and Behaviour of Protein Corona-Adsorbed Nanoparticles

尽管多年来优秀的个人研究，我们预测纳米粒子(NP)在体内的行为的能力仍然有限，基于它们的工程性质。NSERC Discovery研究计划的目的是在全球范围内了解血浆蛋白质表面吸附后，NPs与不同的细胞和非细胞生物屏障之间的相互作用，并生成这些不同相互作用的预测模型。 静脉注射的NPs的工程化性质(NPs的广泛应用)与NP通过细胞外基质的运输(在退出循环后)、NP的细胞毒性和细胞摄取之间的关系是不一致的。这在一定程度上与NPs与血浆的相互作用有关，导致蛋白质日冕沉积在NP表面。在模拟生理环境的条件下，对于特定的工程NP设计特性，对NP电晕形成的动力学了解有限。然而，已经表明，NP电晕形成的动力学决定了NPs在体内的行为。 在这个研究项目中，我的团队将进行一项全面的调查，以揭示工程NP设计特性、血浆蛋白质沉积(电晕形成)的动力学以及随后通过细胞外基质和细胞相互作用的运输之间的关系。这些关系在文学中没有被描述过。我将指导和培训我的团队使用模拟动态生理环境的体外实验和机器学习方法的组合来发展这些关系。我的研究计划分为两个研究主题：从机理上理解NPs与血浆蛋白质的相互作用，以及利用体外模型和模拟算法研究蛋白质电晕吸附NPs的细胞外基质和细胞相互作用。 这些拟议的科学努力将对日冕形成的决定因素及其在核子随后行为中的作用产生关键的新见解。以前的工作还没有证明能够使用模拟动态生理环境的体外模型来分离和准确预测电晕吸附NPs的不同个体疗效终点。将这一点与机器学习方法相结合，将产生经过验证的结果，并观察到传统方法不明显的微妙关系。我们将提供新的知识，使工程师能够开发出既有效又安全的新一代核动力源。

Despite years of excellent individual investigations, our ability to predict the behaviour of nanoparticles (NPs) in the body based on their engineered properties is still limited. The aim of this NSERC Discovery research program is to develop a global understanding of the interaction of NPs with different cellular and acellular biological barriers following surface adsorption of plasma proteins, and generate predictive models of those different interactions. There is inconsistency in relating the engineered properties of NPs injected intravenously (vast applications of NPs) to either of NP transport through the extracellular matrix (after exiting the circulation), NP cytotoxicity and cell uptake of NPs. This is partly related to the interaction of NPs with the blood plasma resulting in a corona of proteins being deposited on the NP surface. There is a limited understanding of the kinetics of NP corona formation for specific engineered NP design properties in a condition simulating the physiological environment. However, it has been shown that the kinetics of NP corona formation determines the behaviour of NPs in the body. In this research program, my team will undertake a comprehensive investigation to unravel the relationships between engineered NP design properties, kinetics of plasma protein deposition (corona formation) and subsequent transport through the extracellular matrix and cell interactions. These relationships have not been described in literature. I will guide and train my team to use a combination of in vitro experiments that mimic the dynamic physiological environment, and machine learning approaches in order to develop these relationships. My research program is divided into two research themes: mechanistic understanding of the interaction of NPs with plasma proteins, and studying the extracellular matrix and cell interactions of protein corona-adsorbed NPs using in vitro models, and modelling algorithms. These proposed scientific endeavours will generate critical new insights into the determinants of corona formation and its role in the subsequent behaviour of NPs. No previous work has demonstrated an ability to separate and accurately predict the different individual efficacy end-points of corona-adsorbed NPs using in vitro models that mimic the dynamic physiological environment. Combining this with machine learning approaches will result in validated results and observation of subtle relationships that are not obvious by traditional approaches. We will provide new knowledge that will enable engineers to develop new generations of NPs that are both effective- and safe-by-design.