A phenomics approach for antiviral drug discovery - Images, analysis pipelines and feature data

Abstract:<br><br>The current COVID-19 pandemic has highlighted the need for new and fast methods to identify novel or repurposed therapeutic drugs. Here we present a method for untargeted phenotypic drug screening of virus-infected cells, combining Cell Painting with antibody-based detection of viral infection in a single assay. We designed an image analysis pipeline for segmentation and classification of virus-infected and non-infected cells, followed by extraction of morphological properties. We show that the methodology can successfully capture virus-induced phenotypic signatures of MRC-5 human lung fibroblasts infected with Human coronavirus 229E (CoV-229E). Moreover, we demonstrate that our method can be used in phenotypic drug screening using a panel of nine host- and virus-targeting antivirals. Treatment with effective antiviral compounds reversed the morphological profile of the host cells towards a non-infected state. The method can be used in drug discovery for morphological profiling of novel antiviral compounds on both infected and non-infected cells. <br><br>Screen description: <br>The images are of MRC-5 human lung fibroblasts infected with Human coronavirus 229E (CoV-229E) and treated with a panel of nine host- and virus-targeting antivirals. Cells are labelled with five labels that characterise seven cellular components (from the "Cell Painting" assay) as well as with a Coronavirus pan monoclonal antibody combined with a secondary antibody. This experiment consists of 5 plates. Each plate has 60 wells, and 9 fields of view per well. Each field was imaged in five channels (detection wavelengths), and each channel is stored as a separate, grayscale image file in TIFF format.The channel names (w1-w5) correspond to the following stains: w1 = Hoechst 33342 (HOECHST); w2= Coronavirus pan Monoclonal Antibody (FIPV3-70) + Goat Anti-Mouse IgG H&amp;L secondary antibody (MITO); w3= Wheat Germ Agglutinin/Alexa Fluor 555 + Phalloidin/Alexa Fluor 568 (PHAandWGA); w4= SYTO 14 green (SYTO); w5= Concanavalin A/Alexa Fluor 488 (CONC)<br>Organization of files:<br>1) Raw image data:<br>- MRC5_HCoV229_Plate1.tar.gz <br>- MRC5_HCoV229_Plate2.tar.gz - MRC5_Plate3.tar.gz - MRC5_Plate4.tar.gz - MRC5_HCoV229_Plate5.tar.gz <br>2) Image analysis pipelines (CellProfiler 4.0.7):<br>Cell Profiler project with a subset of images to try out the analysis pipeline:- Example_PipelineAndData.tar.gz <br>Quality control, illumination correction and feature extraction pipelines:- AnalysisPipelines.tar.gz<br><br>3) Extracted feature data:<br>- features_MRC5_HCoV229_Plate1.tar.gz<br>- features_MRC5_HCoV229_Plate2.tar.gz- features_MRC5_Plate3.tar.gz- features_MRC5_Plate4.tar.gz- features_MRC5_HCoV229_Plate5.tar.gz<br>Metadata:<br>The file “Metadata_MRC5_HCoV229E_plate1-5.csv“ contains the metadata in CSV format, with the following fields:<br>- Plate_id: corresponds to the experimental plate<br>- Well: well allocation in the 96-well plate<br>- virus: "virus +" when cells are exposed to virus, and "virus -' for non-infected controls- Compound: name of compound<br>- Dose [μM]: dose of compound<br>For full information, see the manuscript to which this data is linked.<br>

摘要：
当前COVID-19大流行凸显了开发快速、新型方法以识别新型或再利用治疗药物的迫切需求。本研究开发了一种针对病毒感染细胞的无靶标表型药物筛选方法，将Cell Painting（细胞绘图）技术与基于抗体的病毒感染检测整合至单一实验体系中。我们设计了一套图像分析流程，用于病毒感染与未感染细胞的分割与分类，并随后提取细胞的形态学特征。我们证实该方法可成功捕获感染人冠状病毒229E（Human coronavirus 229E, CoV-229E）的MRC-5人胚肺成纤维细胞的病毒诱导表型特征。此外，我们验证了该方法可结合9种靶向宿主与病毒的抗病毒药物组合，用于表型药物筛选。经有效抗病毒化合物处理后，宿主细胞的形态学特征可恢复至未感染状态。该方法可用于药物开发领域，对感染与未感染细胞中的新型抗病毒化合物开展形态学表征。

筛选实验说明：
本数据集的图像来源于感染人冠状病毒229E（Human coronavirus 229E, CoV-229E），并经9种靶向宿主与病毒的抗病毒药物处理的MRC-5人胚肺成纤维细胞。细胞通过5种标记物进行染色，以表征7种细胞组分（来自Cell Painting实验），同时使用冠状病毒泛单克隆抗体结合二抗进行标记。本实验共包含5块检测板，每块板设有60个孔，每个孔采集9个视场。每个视场通过5个通道（检测波长）成像，每个通道以独立的灰度图像文件形式存储，格式为TIFF。
各通道名称（w1-w5）对应如下染色剂：w1 = 赫斯特33342（Hoechst 33342, HOECHST）；w2 = 冠状病毒泛单克隆抗体（FIPV3-70）+ 山羊抗小鼠IgG H&L二抗（MITO）；w3 = 小麦胚凝集素/Alexa Fluor 555 + 鬼笔环肽/Alexa Fluor 568（PHAandWGA）；w4 = SYTO 14绿色染料（SYTO）；w5 = 伴刀豆球蛋白A/Alexa Fluor 488（CONC）

文件组织：
1) 原始图像数据：
- MRC5_HCoV229_Plate1.tar.gz
- MRC5_HCoV229_Plate2.tar.gz
- MRC5_Plate3.tar.gz
- MRC5_Plate4.tar.gz
- MRC5_HCoV229_Plate5.tar.gz

2) 图像分析流程（CellProfiler 4.0.7）：
- 用于测试分析流程的Cell Profiler项目（含部分图像子集）：Example_PipelineAndData.tar.gz
- 质量控制、光照校正与特征提取流程：AnalysisPipelines.tar.gz

3) 提取的特征数据：
- features_MRC5_HCoV229_Plate1.tar.gz
- features_MRC5_HCoV229_Plate2.tar.gz
- features_MRC5_Plate3.tar.gz
- features_MRC5_Plate4.tar.gz
- features_MRC5_HCoV229_Plate5.tar.gz

元数据：
文件"Metadata_MRC5_HCoV229E_plate1-5.csv"为CSV格式的元数据，包含以下字段：
- Plate_id：对应实验板编号
- Well：96孔板中的孔位编号
- virus："virus +"表示细胞已接触病毒，"virus -"为未感染的对照组
- Compound：化合物名称
- Dose [μM]：化合物给药剂量（单位：微摩尔）
完整信息请参阅本数据集关联的研究论文。