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In 2020, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused infections worldwide. However, the correlation between the immune infiltration and coronavirus disease 2019 (COVID-19) susceptibility or severity in cancer patients remains to be fully elucidated. ACE2 expressions in normal tissues, cancers and cell lines were comprehensively assessed. Furthermore, we compared ACE2 expression between cancers and matched normal tissues through Gene Expression Profiling Interactive Analysis (GEPIA). In addition, we performed gene set enrichment analysis (GSEA) to investigate the related signaling pathways. Finally, the correlations between ACE2 expression and immune infiltration were investigated via Tumor Immune Estimation Resource (TIMER) and GEPIA. We found that ACE2 was predominantly expressed in both adult and fetal tissues from the digestive, urinary and male reproductive tracts; moreover, ACE2 expressions in corresponding cancers were generally higher than that in matched healthy tissues. GSEA showed that various metabolic and immune-related pathways were significantly associated with ACE2 expression across multiple cancer types. Intriguingly, we found that ACE2 expression correlated significantly with immune cell infiltration in both normal and cancer tissues, especially in the stomach and colon. These findings proposed a possible fecal-oral and maternal-fetal transmission of SARS-CoV-2 and suggested that cancers of the respiratory, digestive or urinary tracts would be more vulnerable to SARS-CoV-2 infection.

Being infected by SARS-CoV-2 may cause damage to multiple organs in patients, such as the lung, liver and heart. Angiotensin-converting enzyme 2 (ACE2), reported as a SARS-CoV-2 receptor, is also expressed in human male testes. This suggests a potential risk in human male reproductive system. However, the characteristics of ACE2-positive cells and the expression of other SARS-CoV-2 process-related genes are still worthy of further investigation. Here, we performed singlecell RNA seq (scRNA-seq) analysis on 853 male embryo primordial germ cells (PGCs) and 2,854 normal testis cells to assess the effects of the SARS-CoV-2 virus on the male reproductive system from embryonic stage to adulthood. We also collected and constructed the scRNA-seq library on 228 Sertoli cells from three non-obstructive azoospermia (NOA) patients to assess the effects at disease state. We found that ACE2 expressing cells existed in almost all testis cell types and Sertoli cells had highest expression level and positive cells ratio. Moreover, ACE2 was also expressed in human male PGCs. In adulthood, the level of ACE2 expression decreased with the increase of age. We also found that ACE2 positive cells had high expressions of stress response and immune activation-related genes. Interestingly, some potential SARS-CoV-2 process-related genes such as TMPRSS2, BSG, CTSL and CTSB had different expression patterns in the same cell type. Furthermore, ACE2 expression level in NOA donors’ Sertoli cells was significantly decreased. Our work would help to assess the risk of SARS-CoV-2 infection in the male reproductive system. Electronic Supplementary Material Supplementary material is available for this article at 10.1007/s11427-020-1705-0 and is accessible for authorized users.

To examine the characteristics and distribution of possible severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) target cells in the human trophectoderm (TE) and placenta.Bioinformatics analysis was performed based on published single-cell transcriptomic datasets of early TE and first- and second-trimester human placentae. We conducted the transcriptomic analysis of 4198 early TE cells, 1260 first-trimester placental cells and 189 extravillous trophoblast cells (EVTs) from 24-week placentae (EVT_24W) using the SMART-Seq2 method. In addition, to confirm the bioinformatic results, we performed immunohistochemical staining of three first-trimester, three second-trimester and three third-trimester placentae from nine women recruited prospectively to this study. We evaluated the expression of the SARS-CoV-2-related molecules angiotensin-converting enzyme 2 (ACE2) and transmembrane protease serine 2 (TMPRSS2).Via bioinformatic analysis, we identified the existence of ACE2 and TMPRSS2 expression in human TE as well as in first- and second-trimester placentae. In the human TE, 54.4% of TE1 cells, 9.0% of cytotrophoblasts (CTBs), 3.2% of EVTs and 29.5% of syncytiotrophoblasts (STBs) were ACE2-positive. In addition, 90.7% of TE1 cells, 31.5% of CTBs, 22.1% of EVTs and 70.8% of STBs were TMPRSS2-positive. In placental cells, 20.4% of CTBs, 44.1% of STBs, 3.4% of EVTs from 8-week placentae (EVT_8W) and 63% of EVT_24W were ACE2-positive, while 1.6% of CTBs, 26.5% of STBs, 1.9% of EVT_8W and 20.1% of EVT_24W were TMPRSS2-positive. Pathway analysis revealed that EVT_24W cells that were positive for both ACE2 and TMPRSS2 (ACE2 + TMPRSS2-positive) were associated with morphogenesis of branching structure, extracellular matrix interaction, oxygen binding and antioxidant activity. The ACE2 + TMPRSS2-positive TE1 cells were correlated with an increased capacity for viral invasion, epithelial-cell proliferation and cell adhesion. Expression of ACE2 and TMPRSS2 was observed on immunohistochemical staining in first-, second- and third-trimester placentae.ACE2- and TMPRSS2-positive cells are present in the human TE and placenta in all three trimesters of pregnancy, which indicates the possibility that SARS-CoV-2 could spread via the placenta and cause intrauterine fetal infection. © 2020 International Society of Ultrasound in Obstetrics and Gynecology.

Background Single-cell (sc) sequencing performs unbiased profiling of individual cells and enables evaluation of less prevalent cellular populations, often missed using bulk sequencing. However, the scale and the complexity of the sc datasets poses a great challenge in its utility and this problem is further exacerbated when working with larger datasets typically generated by consortium efforts. As the scale of single cell datasets continues to increase exponentially, there is an unmet technological need to develop database platforms that can evaluate key biological hypotheses by querying extensive single-cell datasets. Large single-cell datasets like Human Cell Atlas and COVID-19 cell atlas (collection of annotated sc datasets from various human organs) are excellent resources for profiling target genes involved in human diseases and disorders ranging from oncology, auto-immunity, as well as infectious diseases like COVID-19 caused by SARS-CoV-2 virus. SARS-CoV-2 infections have led to a worldwide pandemic with massive loss of lives, infections exceeding 7 million cases. The virus uses ACE2 and TMPRSS2 as key viral entry associated proteins expressed in human cells for infections. Evaluating the expression profile of key genes in large single-cell datasets can facilitate testing for diagnostics, therapeutics, and vaccine targets, as the world struggles to cope with the on-going spread of COVID-19 infections. Main body In this manuscript we describe REVEAL: SingleCell, which enables storage, retrieval, and rapid query of single-cell datasets inclusive of millions of cells. The array native database described here enables selecting and analyzing cells across multiple studies. Cells can be selected using individual metadata tags, more complex hierarchical ontology filtering, and gene expression threshold ranges, including co-expression of multiple genes. The tags on selected cells can be further evaluated for testing biological hypotheses. One such example includes identifying the most prevalent cell type annotation tag on returned cells. We used REVEAL: SingleCell to evaluate the expression of key SARS-CoV-2 entry associated genes, and queried the current database (2.2 Million cells, 32 projects) to obtain the results in Conclusion In this paper, we introduce the REVEAL: SingleCell database that addresses immediate needs for SARS-CoV-2 research and has the potential to be used more broadly for many precision medicine applications. We used the REVEAL: SingleCell database as a reference to ask questions relevant to drug development and precision medicine regarding cell type and co-expression for genes that encode proteins necessary for SARS-CoV-2 to enter and reproduce in cells.