RAPID: Understanding SARS-CoV2 transmission through a novel continuous monitoring system

冠状病毒SARS-CoV-2（严重急性呼吸综合征-冠状病毒-2）是COVID-19的病因，与以往已知通过呼吸道分泌物、飞沫、直接或间接接触传播的与类似冠状病毒有关的有限流行病相比，其传播率更高。最近的一项研究表明，SARS-CoV-2可以在不锈钢、塑料、玻璃和纸板等各种表面上存活数小时，这表明传播也可以通过受污染的表面发生。SARS-CoV-2是否可以通过气溶胶传播仍存在争议。因此，重要的是要了解受感染者开始脱落病毒的时间，以及他或她将感染传染给与其直接或间接接触的另一个人的时间。为了解决这些主要问题，该项目将利用一种新型的非侵入性监测系统，该系统可以提供有关疾病进展的重要信息，并利用一种经过设计的小鼠模型提供有关疾病分期、结果和传播的新见解，该模型具有人类受体，该受体是允许病毒进入人体呼吸道细胞的关键。监测系统可以持续捕捉疾病相关数据，如体温、头身距离、活动模式和呼吸声。获得的数据将用于确定与疾病发生和进展相关的有意义的模式。为了确定直接接触（DC）和间接接触（IC）之间的区别，将把感染和未感染的动物群体安置在同一个笼子（DC）中，或安置在由可渗透隔板（IC）隔开的相邻笼子中。这一新颖的信息将为进一步的研究打开大门，在那里可以调查更多的实验因素，实现更人性化的终点。此外，新的SARS-CoV-2小鼠传播模型可应用于其他传染病。这个原理验证项目的目标是在小鼠模型中通过直接或间接接触（DC或IC）产生关于SARS-CoV-2传播率、频率和疾病进展的新信息。预计获得的结果将提供基本的见解，了解感染者多久开始脱落病毒，以及他或她多久将感染传染给与他们直接或间接接触的另一个人。该项目的目标将使用表达ACE2受体的hACE2（人类血管紧张素转换酶2）转基因小鼠和设计用于多传感器数据收集的非侵入性连续监测系统（CMS）来完成，该系统可以捕获几种外部表型，包括体温、头-体距离、活动模式、呼吸声音等，以表征传染病的进展。已经开发了用于时间序列分解和分类的算法，可以识别与疾病分期相关的有意义的模式。该项目假设，新的CMS可用于更好地表征SARS-CoV-2的传播时间、频率，并研究DC和IC小鼠间传播模型的疾病进展变异性。这一假设将通过两个具体目标进行检验。第一个目标是在DC小鼠到小鼠的传播模型中量化SARS的传播时间、频率和由此产生的疾病进展动力学。实现这一目标的方法是，每个笼子里饲养两只hACE2转基因小鼠，其中一只感染SARS-CoV-2，之后对这些动物进行21天的连续监测。实时数据分析将用于确定其他未感染的hACE2小鼠的发病（病毒传播），这些小鼠与感染的小鼠一起被安置在同一笼子中并患有DC。第二个目标将量化SARS在小鼠间传播模型中的传播时间、频率和疾病进展。这一目的将通过将未感染的hACE2小鼠安置在笼子中，并将其与感染的hACE2小鼠隔开，从而实现。在这两个目标中，道德比率都将被量化。将收集安乐死动物的组织，通过组织学测量组织病毒载量，组织发病机制，并通过免疫组织化学（IHC）染色检测组织病毒抗原。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The coronavirus SARS-CoV-2 (severe acute respiratory syndrome–coronavirus-2), which is the cause of COVID-19, has a higher transmission rate compared to previous limited epidemics related to similar coronaviruses that are known to be transmitted by respiratory secretions, droplets, direct or indirect contacts. A recent study documented that SARS-CoV-2 can remain viable for several hours on various surfaces such as stainless steel, plastic, glass, and cardboards, suggesting that transmission can also happen through contaminated surfaces. Controversies remain whether SARS-CoV-2 can be transmitted through aerosols. Therefore, it is important to understand how soon an infected person starts shedding the virus, and how soon he or she transmits the infection to another person who is in direct or indirect contact with them. To address these major questions, this project will utilize a novel non-invasive monitoring system that can provide important information about the disease progression and new insights on disease staging, outcomes, and transmissions using a mouse model that has been engineered to have the human receptor that is key to allowing the virus to enter cells lining human airways. The monitoring system can continuously capture disease related data such as body temperature, head-body distance, activity patterns and breathing sounds. The data obtained will be used to identify meaningful patterns associated with disease onset and progression. To determine the difference between direct contact (DC) and indirect contact (IC), infected and uninfected animal groups will be housed in the same cage (DC) or in adjoining cages separated by a permeable partition (IC). This novel information will open the door for further studies where a greater number of experimental factors can be investigated, enabling more humane endpoints. Furthermore, the novel SARS-CoV-2 - mouse transmission models can be applied to other contagious diseases. The goal of this proof-of-principle project is to generate novel information about the SARS-CoV-2 transmission rate, frequencies and, disease progression through direct or indirect contact (DC or IC) in murine models. Results obtained are expected to provide fundamental insight into how soon an infected person starts shedding the virus, and how soon he or she transmits the infection to another person who is in direct or indirect contact with them. The project’s goal will be accomplished using hACE2 (human angiotensin-converting enzyme 2) transgenic mice expressing the ACE2 receptor and a non-invasive and continuous monitoring system (CMS) designed for multi-sensor data collection that can capture several external phenotypes, including body temperature, head-body distance, activity patterns, breathing sounds, and others to characterize infectious disease progression. Algorithms have been developed for time-series decomposition and classification that can identify meaningful patterns associated with disease staging. The project hypothesizes that the novel CMS can be used to better characterize the SARS-CoV-2 transmission time, frequencies, and to study disease progression variability between DC and IC mice-to-mice transmission models. The hypothesis will be tested with two specific aims. The FIRST aim is to quantify the SARS transmission time, frequencies, and resulting disease progression dynamics in a DC mice-to-mice transmission model. This aim will be achieved by infecting one of the two housed hACE2 transgenic mice per cage with SARS-CoV-2, after which the animals will be continuously monitored for 21 days. Real time data analysis will be used to determine disease onset (viral transmission) for other uninfected hACE2 mice, which are housed in the same cage and have DC with the infected mice. The SECOND Aim will quantify the SARS transmission time, frequencies, and disease progression in an IC mice-to-mice transmission model. This aim will be accomplished by housing uninfected hACE2 mice in cages with a permeable partition separating them from infected hACE2 mice. In both aims, the morality rate will be quantified. Tissues will be collected from euthanized animals to measure tissue viral loads, tissue pathogenesis by histology, and to detect tissue viral antigens by immunohistochemistry (IHC) staining.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.