key: cord-0278045-sjyz1wp6
authors: Wang, Xiran; Ou, Zhihua; Ding, Peiwen; Sun, Chengcheng; Wang, Daxi; Zhu, Jiacheng; Wu, Wendi; Wei, Yanan; Ding, Xiangning; Luo, Lihua; Li, Meiling; Zhang, Wensheng; Jin, Xin; Sun, Jian; Liu, Huan; Chen, Dongsheng
title: Comparative analysis of single cell lung atlas of bat, cat, tiger and pangolin
date: 2021-12-27
journal: bioRxiv
DOI: 10.1101/2021.12.26.473325
sha: e11d380d19b3ebd02215eb78695125763682a456
doc_id: 278045
cord_uid: sjyz1wp6

Horseshoe bats (Rhinolophus sinicus) might help maintain coronaviruses severely affecting human health, such as SARS-CoV and SARS-CoV-2. It has long been suggested that bats may be more tolerant of viral infection than other mammals due to their unique immune system, but the exact mechanism remains to be fully explored. During the COVID-19 pandemic, multiple animal species were diseased by SARS-CoV-2 infection, especially in the respiratory system. Herein, single-cell transcriptomic data of the lungs of a horseshoe bat, a cat, a tiger, and a pangolin were generated. The receptor distribution of twenty-eight respiratory viruses belonging to fourteen viral families were characterized for the four species. Comparison on the immune-related transcripts further revealed limited cytokine activations in bats, which might explain the reason why bats experienced only mild diseases or even no symptoms upon virus infection. Our findings might increase our understanding of the immune background of horseshoe bats and their insensitivity to virus infections.

Bats are important reservoir hosts for a myriad of viruses including coronaviruses, rabies viruses, Hendra viruses, influenza viruses, etc. They were mostly asymptomatic or only developed mild diseases during viral infections by Ebola viruses, coronaviruses, henipaviruses, etc. The immune response induced by virus infection was shown to differ between human and bat cells 1, 2 and that bats may have their unique transcripts that are not present in other mammals 3 Bats were found to have limited interferon activation due to mutation in the STING protein 4 and have contracted type I IFNα locus but constitutive IFNα expression without viral stimulation 5 . The unique immune response pathways and antiviral gene expression profile of bats, may promote their tolerance to viral infections 6 . Bats are probably the initial host of SARS-CoV-2 7,8 , the etiological virus causing COVID-19. Although the direct progenitor of SARS-CoV-2 remains unknown, its closest relative (RaTG13) has been detected in a horseshoe bat (Rhinolophus sinicus), indicating horseshoe bats as its potential reservoir hosts.

Moreover, horseshoe bats (genus Rhinolophus) were also found to harbor other groups of coronaviruses including the SARS-CoV emerged in China from 2002 to 2003 9-11 , indicating their critical role in the maintenance of human sensitive coronaviruses. Since the outbreak of COVID-19, multiple animal species have been infected and diseased by SARS-CoV-2, including pangolins, cats, tigers, etc. [12] [13] [14] [15] [16] . Herein, we conducted a comparative study using single cell transcriptomic data to elucidate the lung immune landscape of bat, cat, tiger and pangolin, which might help reveal the molecular basis for their differential immune behaviors upon infections by SARS-CoV-2.

Due to species-specific immune response upon viral infection, clinical symptoms in the lower respiratory differ among species. While bats, cats, tigers and pangolins were all permissive to SARS-CoV-2 infection, details of their biological background remain unknown. Herein, we collected lung tissues from healthy individuals of bats to generate single-nucleus libraries of lung cells, resulting in a total of 11838 pulmonary cells passing quality control (Figures 1A and 1B) . Nine major cell types were identified in the lung atlas of bats, which included alveolar type 1 cells (AT1), alveolar type 2 cells (AT2), ciliated cells, secretory cells, endothelial cells, fibroblasts, T cells, B cells and macrophages, each demonstrating the specific expression of canonical cell type markers ( Figure 1C , Table S1 ). ACE2, receptor for SARS-CoV and SARS-CoV-2, were relatively highly expressed in ciliated and secretory cells of cat and in the secretory cells of tiger. Only marginal expressions of ACE2 were observed in bat ciliated cells. However, the receptor for SARS-CoV-2, Scarb1, displayed highly specific expression in bat endothelial cells and macrophages. Another two SARS-CoV-2 receptors, Nrp1 and Axl, also showed significant cell type and species specificity. Nrp1 was largely enriched in AT1/AT2 of tigers and AT2 of bats, whereas Axl was highly expressed in fibroblasts and macrophages of bat lung, and fibroblasts of pangolin lung ( Figure 1D ).

Cytokine storm, due to uncontrolled and excessive release of pro-inflammatory cytokines, is one of the main culprits contributing to severe lung pathogenesis caused by various virus infections 17 . As a natural reservoir for zoonotic viruses, bats display no significant symptoms after virus infection thanks to its unique immunity 18 . Here, we compared the expression profiles of a variety of pro-inflammatory cytokines (IL1, IL6, TNF, interferons) and anti-inflammation cytokines (IL10, TGF beta) among distinct pulmonary cell types of bat, cat, pangolin, and tiger. Regarding anti-inflammation cytokines and corresponding receptors, no significant differences were observed among the pulmonary cells of the four species ( Figure S1 ). However, receptors for specific pro-inflammation cytokines, IL-6 (Osmr, Lifr) and interferons (IFN) (Ifngr2, Ifnar1, Ifnar2), were significantly lowly expressed in bat pulmonary cells ( Figure S1 ). Lif was suggested to be a mediator of pro-inflammation in several inflammatory disorders 19 and was lowly expressed in bat. Accumulating evidence has indicated that OSM mediates lung inflammations 20 

Bats used in this study were all male Rhinolophus sinicus (Chinese horseshoe bat) which were identified the species by the field experts, and obtained from Guangdong province, China, then dissected and stored in -80°C freezer immediately. After being isolated, the lung tissues of bats were rinsed by 1X PBS and stored in liquid nitrogen.

Subsequently, we used mechanical extraction method from previous study 23 to obtain the single nucleus and then stained using DAPI (4',6-diamidino-2-phenylindole), calculated the density of the nucleus to ensure the quality of the single nucleus RNA sequencing library construction.

The isolated nuclei were separated from lung tissue of bats and then their reactions were performed according to the manufacturer's protocol for the Chromium Single Cell 3' GEM, Library & Gel Bead Kit v3.1. Library preparation was carried out following the guidelines provided by the manufacturer, total of 2 libraries were sequenced using a compatible Illumina NovaSeq 6000 platform.

Raw sequencing data was aligned to ref genome sequence of Rhinolophus sinicus (GCF_001888835.1_ASM188883v1) and preprocessed by CellRanger 3.0.2 (10X Genomics). After obtaining the single cell gene expression matrices, we used Seurat 3.2.2 24 to perform the downstream analysis. First, genes detected in less than three cells were discarded. Then, low-quality cells in which expressed gene numbers are less than 200 were filtered out. Moreover, cells with the percentage of mitochondrial genes more than 10% were removed. After quality control, "LogNormalize" function was used to normalize and "FindVariableGenes" was used to calculate the variance scores of each gene. Then, we applied "cca" to integrate the two libraries and remove the batch effect. Following, the integrated data was scaled and principal component analysis (PCA) was performed on the corrected data. Clusters were identified using "FindClusters" function and visualized by UMAP.

Other single cell RNA sequencing data (cat, tiger, pangolin) were obtained from public 1 .

The lung cell types of bats were annotated according to the expression of canonical markers. The lung cell types of cat, tiger and pangolin were acquired from Chen et al.

We applied "FindAllMarkers" function to identify the differentially expressed genes (DEGs). P value of the significance of DEGs were calculated by default Wilcox test and adjusted using Bonferroni methods. Genes of which adjusted p value is less than 0.05 and absolute value of log fold change is more than 0.25 were defined as DEGs and used for the following analysis. R package clusterProfiler 25 was applied for GO term enrichment analysis.

To facilitate the comparation among four species, we first convert all genes of bats to the homogenous mouse genes using OrthoFinder 26 . Then we used Seurat 2 to integrate the single cell datasets of bats, cat, tiger and pangolin.

Used the integrated datasets of four species, we calculated the average expression value and the percentage of expression for known respiratory virus receptors collected from previous study 27 in various cell types. Besides, the expression patterns of cytokine genes in each cell type were also calculated using "DotPlot" function from Seurat and visualized by ggplot2 28 . 

The authors declare no competing interests.

The raw data supporting the findings of this study will be made available upon request.

The data that support the findings of this study have been deposited into CNGB Sequence Archive (CNSA) 29 T ig e r B a t C a t P a n g o li n T ig e r B a t C a t P a n g o li n T ig e r B a t C a t P a n g o li n T ig e r B a t C a t P a n g o li n T ig e r B a t C a t P a n g o li n T ig e r B a t C a t P a n g o li n T ig e r B a t C a t P a n g o li n B a t C a t P a n g o li n 

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CNSA: a data repository for archiving omics data

CNGBdb: China National GeneBank DataBase