COVID-19db linkage maps of cell surface proteins and transcription factors in immune cells.
COVID-19db linkage maps of cell surface proteins and transcription factors in immune cells.
复制标题
免疫细胞中细胞表面蛋白和转录因子的 COVID-19db 连锁图。
DOI：
10.1002/jmv.28887
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发表时间：
2023
影响因子：
12.7
通讯作者：
Osmanbeyoglu,HaticeUlku
中科院分区：
文献类型：
--
作者：
Ramjattun,Koushul;Ma,Xiaojun;Gao,Shou-Jiang;Singh,Harinder;Osmanbeyoglu,HaticeUlku
高度传染性的SARS-CoV-2及其相关疾病（COVID-19）对全球公共卫生和经济构成威胁。为了开发针对COVID-19的有效治疗方法，我们必须了解与感染和发病机制相关的宿主细胞类型、细胞状态和调节因子，例如失调的转录因子（TF）和表面蛋白，包括信号受体。为了将细胞表面蛋白与TF联系起来，我们最近开发了SPaRTAN（单细胞蛋白质组学和基于RNA的转录因子活性网络），该网络通过整合基于转录组和表位的细胞测序索引（CITE‐seq）和基因顺式调控信息的平行单细胞蛋白质组学和转录组学数据。我们将SPaRTAN应用于来自不同程度COVID-19严重程度患者和健康对照的CITE‐seq数据集，以确定宿主免疫细胞中表面蛋白和TF之间的关联。在这里，我们展示了COVID-19 db of Immune Cell States（https：//covid19db.streamlit.app/），这是一个包含细胞表面蛋白表达、SPaRTAN推断的TF活性及其与主要宿主免疫细胞类型的关联的网络服务器。这些数据包括四个高质量的COVID-19 CITE‐seq数据集，以及用于用户友好的数据分析和可视化的工具集。我们为每个数据集提供了跨主要免疫细胞类型的交互式表面蛋白和TF可视化，允许在各种患者严重程度组之间进行比较，以发现潜在的治疗靶点和诊断生物标志物。
The highly contagious SARS‐CoV‐2 and its associated disease (COVID‐19) are a threat to global public health and economies. To develop effective treatments for COVID‐19, we must understand the host cell types, cell states and regulators associated with infection and pathogenesis such as dysregulated transcription factors (TFs) and surface proteins, including signaling receptors. To link cell surface proteins with TFs, we recently developed SPaRTAN (Single‐cell Proteomic and RNA‐based Transcription factor Activity Network) by integrating parallel single‐cell proteomic and transcriptomic data based on Cellular Indexing of Transcriptomes and Epitopes by sequencing (CITE‐seq) and gene cis‐regulatory information. We apply SPaRTAN to CITE‐seq data sets from patients with varying degrees of COVID‐19 severity and healthy controls to identify the associations between surface proteins and TFs in host immune cells. Here, we present COVID‐19db of Immune Cell States (https://covid19db.streamlit.app/), a web server containing cell surface protein expression, SPaRTAN‐inferred TF activities, and their associations with major host immune cell types. The data include four high‐quality COVID‐19 CITE‐seq data sets with a toolset for user‐friendly data analysis and visualization. We provide interactive surface protein and TF visualizations across major immune cell types for each data set, allowing comparison between various patient severity groups for the discovery of potential therapeutic targets and diagnostic biomarkers.