Phenotyping the virulence of SARS-CoV-2 variants in hamsters by digital pathology and machine learning.
Phenotyping the virulence of SARS-CoV-2 variants in hamsters by digital pathology and machine learning.
复制标题
DOI：
10.1371/journal.ppat.1011589
复制
发表时间：
2023-11
期刊：
影响因子：
6.7
通讯作者：
中科院分区：
文献类型：
--
作者：
严重急性呼吸综合征冠状病毒 2 (SARS-CoV-2) 在冠状病毒病 19 (COVID-19) 大流行期间持续演变，产生了具有不同生物学特性的多种关注变体 (VOC)。随着大流行的进展，必须近乎实时地测试任何新出现的变异引起严重疾病的可能性。与之前的 VOC（如 Delta）相比，BA.1 (Omicron) 被证明是减毒的，但新出现的变体可能会重新恢复毒性表型。仓鼠已被证明是 SARS-CoV-2 发病机制的一个非常好的模型。在这里，我们的目标是开发强大的定量管道来评估 SARS-CoV-2 变体对仓鼠的毒力。我们使用多种方法，包括RNAseq、RNA原位杂交、免疫组织化学和数字病理学，包括软件辅助全切片成像和机器学习增强的下游自动分析，开发以公正的方式评估和量化病毒引起的肺部病变的方法。最初，我们使用 Delta 和 Omicron 来开发我们的实验管道。然后，我们评估了最近的 Omicron 亚谱系的毒力，包括 BA.5、XBB、BQ.1.18、BA.2、BA.2.75 和 EG.5.1。我们表明，在实验感染的仓鼠中，肺泡上皮增生和巨噬细胞浸润的准确定量代表了评估病毒诱导的肺部病理程度以及病毒毒力的有力标记。此外，使用这些管道，我们可以揭示一些 Omicron 子谱系（例如 BA.2.75 和 EG.5.1）与原始 BA.1 相比如何重新获得毒力。最后，为了最大限度地利用我们研究中报告的数字病理学管道，我们开发了一个在线存储库，其中包含可以在可变放大倍率下可视化的代表性全器官组织病理学部分（https://covid-atlas.cvr.gla.ac.uk）。总体而言，该管道可以提供公正且宝贵的数据，用于快速评估新出现的变异及其引起严重疾病的可能性。在 COVID-19 大流行期间，定期出现新的 SARS-CoV-2 变种。在大流行的这一阶段，“成功”变种所拥有的关键特征是它们能够逃避现有 SARS-CoV-2 疫苗或感染所赋予的免疫力。然而，尚不清楚新变体是否会保持 Omicron 所显示的相对较低的毒力，或者获得前 omicron 变体的毒性更强的表型。在本研究中，我们开发了软件辅助图像分析方法来定量评估实验感染 SARS-CoV-2 的仓鼠肺部病变程度。仓鼠是评估 SARS-CoV-2 毒力的绝佳动物模型。根据之前的实验，我们推断 SARS-CoV-2 变异体的毒力将与其在仓鼠中引起的肺部病变成正比。我们开发了公正的方法，旨在对整个肺切片进行成像，并量化浸润器官的免疫细胞，以及响应病毒损伤的肺细胞增殖水平。使用这些方法，我们表明，正如预期的那样，Omicron 的毒性低于 Delta 变种。 XBB 和 BQ.1.18 等其他变体的毒力与 Omicron 显示的毒力相当。然而，最近出现的变种 BA.2.75 和 EG.5.1 的毒性比 Omicron 更强，但不是 Delta。我们的方法可以对新出现的变异引起严重疾病的能力进行定量评估。
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has continued to evolve throughout the coronavirus disease-19 (COVID-19) pandemic, giving rise to multiple variants of concern (VOCs) with different biological properties. As the pandemic progresses, it will be essential to test in near real time the potential of any new emerging variant to cause severe disease. BA.1 (Omicron) was shown to be attenuated compared to the previous VOCs like Delta, but it is possible that newly emerging variants may regain a virulent phenotype. Hamsters have been proven to be an exceedingly good model for SARS-CoV-2 pathogenesis. Here, we aimed to develop robust quantitative pipelines to assess the virulence of SARS-CoV-2 variants in hamsters. We used various approaches including RNAseq, RNA in situ hybridization, immunohistochemistry, and digital pathology, including software assisted whole section imaging and downstream automatic analyses enhanced by machine learning, to develop methods to assess and quantify virus-induced pulmonary lesions in an unbiased manner. Initially, we used Delta and Omicron to develop our experimental pipelines. We then assessed the virulence of recent Omicron sub-lineages including BA.5, XBB, BQ.1.18, BA.2, BA.2.75 and EG.5.1. We show that in experimentally infected hamsters, accurate quantification of alveolar epithelial hyperplasia and macrophage infiltrates represent robust markers for assessing the extent of virus-induced pulmonary pathology, and hence virus virulence. In addition, using these pipelines, we could reveal how some Omicron sub-lineages (e.g., BA.2.75 and EG.5.1) have regained virulence compared to the original BA.1. Finally, to maximise the utility of the digital pathology pipelines reported in our study, we developed an online repository containing representative whole organ histopathology sections that can be visualised at variable magnifications (https://covid-atlas.cvr.gla.ac.uk). Overall, this pipeline can provide unbiased and invaluable data for rapidly assessing newly emerging variants and their potential to cause severe disease. New SARS-CoV-2 variants have periodically emerged throughout the COVID-19 pandemic. The key characteristic possessed by “successful” variants in this phase of the pandemic is their ability to evade the immunity conferred by existing SARS-CoV-2 vaccines or infections. However, it is not clear whether new variants will maintain the relatively low virulence shown by Omicron or acquire the more virulent phenotype of the pre-omicron variants. In this study, we developed software-assisted image analysis methods to quantitatively assess the extent of the lesions in lungs of hamsters experimentally infected with SARS-CoV-2. Hamsters are an excellent animal model to assess SARS-CoV-2 virulence. Based on previous experiments, we reasoned that the virulence of SARS-CoV-2 variants will be directly proportional to the lung lesions they cause in hamsters. We developed unbiased methods aimed to image whole lung sections, and quantify immune cells infiltrating the organ, in addition to the levels of lung cells proliferation in response to virus injury. Using these methods, we show that Omicron is, as expected, less virulent than the Delta variant. The virulence of other variants such as XBB and BQ.1.18 is comparable to that displayed by Omicron. However, the more recently emerged variants BA.2.75 and EG.5.1 are more virulent than Omicron, but not Delta. Our methods can provide a quantitative assessment of the ability of newly emerging variants to cause severe disease.
登录
查看更多内容
影响因子：
17.1
作者：
Frere, Justin J.;Serafini, Randal A.;Pryce, Kerri D.;Zazhytska, Marianna;Oishi, Kohei;Golynker, Ilona;Panis, Maryline;Zimering, Jeffrey;Horiuchi, Shu;Hoagland, Daisy A.;Moller, Rasmus;Ruiz, Anne;Kodra, Albana;Overdevest, Jonathan B.;Canoll, Peter D.;Borczuk, Alain C.;Chandar, Vasuretha;Bram, Yaron;Schwartz, Robert;Lomvardas, Stavros;Zachariou, Venetia;Tenoever, Benjamin R.
通讯作者：
Tenoever, Benjamin R.
影响因子：
4.6
作者：
Bankhead P;Loughrey MB;Fernández JA;Dombrowski Y;McArt DG;Dunne PD;McQuaid S;Gray RT;Murray LJ;Coleman HG;James JA;Salto-Tellez M;Hamilton PW
通讯作者：
Hamilton PW
影响因子：
16.6
作者：
通讯作者：
--
影响因子：
32.4
作者：
Hoagland DA;Møller R;Uhl SA;Oishi K;Frere J;Golynker I;Horiuchi S;Panis M;Blanco-Melo D;Sachs D;Arkun K;Lim JK;tenOever BR
通讯作者：
tenOever BR
影响因子：
2.3
作者：
Lin, Elisa;Fuda, Franklin;Chen, Mingyi
通讯作者：
Chen, Mingyi