权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Library of protein-nanoparticle interactions: Automated sample handling and low-cost proteomics

蛋白质-纳米粒子相互作用库：自动化样品处理和低成本蛋白质组学

基本信息

批准号：
1901579
负责人：
Christine Payne
金额：
$ 39万
依托单位：
Duke University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-07-01 至 2023-06-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1901579&HistoricalAwards=false
关键词：
Library protein nanoparticle interactions Automated

项目摘要

Exposure to nanoparticles can be beneficial, such as the use of nanomedicines, or detrimental, such as the inhalation of metal oxide nanoparticles used in industrial applications. In both cases, there is a pressing need for a quantitative understanding of how nanoparticles interact with biological systems. This research will generate a library of protein-nanoparticle interactions using a carefully controlled set of nanoparticles. Experiments will focus on the interaction of nanoparticles with the proteins found in the blood stream. Use of a robot to automate experiments will increase throughput and reproducibility. The research team will use this library, which will be publicly available, to determine which proteins adsorb on the surface of nanoparticles as a function of nanoparticle diameter and surface properties and then use this library for subsequent cell-nanoparticle experiments. A major limit to generating a protein-nanoparticle library has been the cost associated with protein analysis. The research team will benchmark the use of a faster, less expensive, protein separation method to reduce costs. The use of controlled nanoparticle parameters, in combination with automated sample preparation and low-cost protein analysis, will enable the first quantitative understanding of protein-nanoparticle interactions, important for environmental and industrial nanoparticle exposure, as well as therapeutic and diagnostic applications. This research also provides an ideal training platform for students to address fundamental questions of nanoscience with advances in research automation, training that will be relevant to future academic or industry jobs.Nanoparticles used in any biological system proteins are exposed to proteins that adsorb on the surface of the nanoparticle forming a protein corona. Modification with neutral polymers can reduce this protein corona, but complete inhibition remains a challenge. Currently lacking is an ability to predict which proteins will adsorb on the surface of a specific nanoparticle. Previous work in this area has been limited by the cost of proteomics, only identifying protein-nanoparticles interactions for small sets of nanoparticles, or have carried out large-scale proteomics on a diverse array of ligands that preclude the identification of trends. This research will generate a protein corona library and then use this library to select nanoparticles for protein- and cellular-level mechanistic studies. To generate sufficient nanoparticles with controlled variation of surface parameters, the research team will automate nanoparticle functionalization using a liquid handling robot. To reduce the costs associated with generating a protein corona library, the team will reduce the time required for peptide separation using capillary electrophoresis instead of liquid chromatography. The corona library will be used to select nanoparticles for mechanistic studies to understand why complement C3 and serum albumin are enriched and under-represented, respectively, in protein coronas, and the effect of these proteins on the subsequent interaction with macrophage cells. The outcomes of this research include the protein corona library, which will be publicly available, automation of nanoparticle functionalization and sample preparation, and a detailed comparison of capillary electrophoresis and liquid chromatography separation for proteomics.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

暴露于纳米颗粒可能是有益的，例如使用纳米药物，或有害的，例如吸入工业应用中使用的金属氧化物纳米颗粒。在这两种情况下，迫切需要定量了解纳米粒子如何与生物系统相互作用。这项研究将使用一组精心控制的纳米颗粒生成蛋白质-纳米颗粒相互作用的库。实验将集中在纳米粒子与血液中发现的蛋白质的相互作用。使用机器人来自动化实验将提高通量和再现性。研究小组将使用这个库，这将是公开的，以确定哪些蛋白质吸附在纳米粒子的表面作为纳米粒子直径和表面特性的函数，然后使用这个库为后续的细胞纳米粒子实验。产生蛋白质-纳米颗粒文库的主要限制是与蛋白质分析相关的成本。研究小组将基准使用更快，更便宜的蛋白质分离方法来降低成本。使用受控的纳米颗粒参数，结合自动化样品制备和低成本蛋白质分析，将首次定量了解蛋白质-纳米颗粒相互作用，这对于环境和工业纳米颗粒暴露以及治疗和诊断应用非常重要。这项研究还为学生提供了一个理想的培训平台，以解决纳米科学的基本问题，研究自动化的进步，培训将与未来的学术或工业工作相关。在任何生物系统中使用的纳米颗粒蛋白质暴露于吸附在纳米颗粒表面的蛋白质，形成蛋白质冠。用中性聚合物修饰可以减少这种蛋白质冠，但完全抑制仍然是一个挑战。目前缺乏的是预测哪些蛋白质将吸附在特定纳米颗粒表面的能力。以前在这一领域的工作受到蛋白质组学成本的限制，仅识别小组纳米颗粒的蛋白质-纳米颗粒相互作用，或者对排除趋势识别的各种配体进行大规模蛋白质组学。这项研究将产生一个蛋白质冠库，然后使用这个库来选择蛋白质和细胞水平的机制研究的纳米粒子。为了生成足够的纳米颗粒，并控制表面参数的变化，研究团队将使用液体处理机器人自动化纳米颗粒功能化。为了降低与生成蛋白质冠状文库相关的成本，该团队将减少使用毛细管电泳而不是液相色谱分离肽所需的时间。冠库将用于选择纳米颗粒进行机制研究，以了解为什么补体C3和血清白蛋白在蛋白质冠中分别富集和代表不足，以及这些蛋白质对随后与巨噬细胞相互作用的影响。这项研究的成果包括蛋白质冠图书馆，这将是公开的，纳米粒子功能化和样品制备的自动化，以及毛细管电泳和液相色谱分离的蛋白质组学的详细比较。该奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。