Combination ribonucleic acid nanotechnologies to simultaneously study the multitude of mechanistic pathways found in complex diseases

慢性病是复杂的，很难研究。一个单一的生物异常可能会导致更多的问题，使细胞和组织容易受到更多的损害。目前，当研究人员试图研究慢性病的病因时，研究人员利用小分子来阻止或激活细胞内的某些机械过程，我们认为这些过程会导致疾病。一些进程包含多个步骤，其中一些步骤与其他进程共享，这创建了一个广泛的网络。这种重叠使得在不意外地激活另一个进程的情况下独占一个进程变得困难。此外，考虑到慢性疾病中故障过程的令人难以置信的多样性，许多感兴趣的目标缺乏能够提供控制的相应的小分子。由于缺乏有针对性的控制，我们对哪些功能不正常的细胞过程导致慢性疾病的理解存在知识差距。为了弥合这一差距并揭示疾病机理的隐藏见解，迫切需要能够控制难以捉摸的过程的新的工程工具。此外，许多疾病是由多个过程的失败引起的。因此，这些工具还必须具有同时控制多个过程的能力，才能执行有意义的研究。我们的长期愿景是发现哪些失灵的过程组合会导致慢性病。我们将利用我们在多伦多大学医学机器学习中心、生物医学工程研究所和免疫学系的跨学科地位来实现这一愿景。为了开始这些研究，我们需要新的工程工具，使我们能够精确地操纵细胞内的任何过程，以模拟疾病的发展。因此，作为我们的起点，这项发现资助计划将创造一种新的纳米技术，当应用于细胞时，可以调整任何用于研究目的的过程。然后，我们观察这些变化的结果，以了解这些过程如何影响疾病的开始和发展。这种纳米技术是以小颗粒的形式进入细胞并运送核酸的。核酸是细胞可以阅读和遵循的指令集。在纳米技术传递核酸后，细胞将遵循指令，这些指令告诉它们如何改变内部过程以模仿疾病。我们将对许多不同的核酸进行筛选，以发现哪些指令会导致疾病。这样，我们就可以一步一步地推导出导致不同疾病的序列。这项研究将促进我们对疾病为什么发生以及它们是如何发展的基本理解。在给加拿大人带来的好处方面，该项目培养了具有化学(纳米技术有机合成)、细胞生物学(大型屏幕)、分析方法(细胞观察和数据收集)和机器学习(高级疾病建模)技能的高素质人才。

Chronic diseases are complex and difficult to study. A single biological aberration can cascade into additional problems, leaving cells and tissues vulnerable to more damage. Currently, when trying to study the cause of chronic diseases, researchers make use of small molecules that can block or activate certain mechanistic processes inside cells that we believe cause disease. Some processes contain multiple steps, and some of these steps are shared with other processes, which creates an extensive network. This overlap makes it difficult to exclusively target one process without accidentally activating another one. Moreover, given the incredible diversity of malfunctioning processes in chronic diseases, many targets of interest lack a corresponding small molecule that can provide control. Because of this lack of targeted control, there is a knowledge gap in our understanding of which malfunctioning cellular processes contribute to chronic disease. To bridge this gap and reveal hidden insights into the mechanics of diseases, new engineering tools capable of controlling elusive processes are desperately needed. Furthermore, many diseases arise from the failure of multiple processes. Thus, these tools must also have the ability to control many processes at once to perform meaningful studies. Our long-term vision is to discover what combination of malfunctioning processes lead to chronic diseases. We will leverage our interdisciplinary position in the University of Toronto's Centre for Machine Learning in Medicine, Institute of Biomedical Engineering and Department of Immunology to achieve this vision. To begin these studies, we require new engineering tools that allow us to precisely manipulate any process inside a cell to mimic the progression of disease. Thus, as our starting point, this Discovery Grant program will create a new nanotechnology that, when administered to cells, can adjust any process for research purposes. We then observe the outcome of these changes to understand how these processes influence the initiation and progression of disease. This nanotechnology is in the form of small particles that enter cells and deliver nucleic acids. Nucleic acids are instruction sets that cells can read and follow. After the nanotechnology delivers the nucleic acids, the cells will follow the instructions, which tell them how to change their internal processes to mimic a disease. We will screen many different nucleic acids to discover which instruction lead to disease. In this way, we will deduce the step-by-step sequences that lead to different diseases. This research will advance our fundamental understanding of why diseases occur and how they progress. In terms of benefits to Canadians, this program creates highly qualified personnel with skills in chemistry (organic synthesis of nanotechnology), cell biology (large-scale screens), analytical methods (cell observation and data collection), and machine learning (advanced disease modelling).