scholarly journals Single-Cell RNA-seq Identifies Cell Subsets in Human Placenta That Highly Expresses Factors to Drive Pathogenesis of SARS-CoV-2

2020 ◽  
Author(s):  
Nancy Ashray ◽  
Anshul Bhide ◽  
Priyanka Chakarborty ◽  
Stacy Colaco ◽  
Anuradha Mishra ◽  
...  
Keyword(s):  
Single Cell ◽  
Human Placenta ◽  
First Trimester ◽  
Host Cells ◽  
Second Trimester ◽  
Rna Seq ◽  
Cellular Targets ◽  
Viral Budding ◽  
Differentiated Cells ◽  
Novel Coronavirus

Infection by the Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) results in the novel coronavirus disease COVID-19, which has posed a serious threat globally. Infection of SARS-CoV-2 during pregnancy is associated with complications like preterm labor and premature rupture of membranes; a proportion of neonates born to the infected mothers are also positive for the virus. During pregnancy, the placental barrier protects the fetus from pathogens and ensures healthy development. However, whether or not SARS-CoV-2 can infect the placenta is unknown. Herein, utilizing single-cell RNA-seq data, we report that the SARS-CoV-2 binding receptor ACE2 and the S protein priming protease TMPRSS2 are co-expressed by a subset of syncytiotrophoblasts (STB) in the first trimester and extra villous trophoblasts (EVT) in the second trimester human placenta. The ACE2- and TMPRSS2-positive (ACE2+TMPRSS2+) placental subsets express mRNA for proteins involved in viral budding and replication. These cells also express mRNA for proteins that interact with SARS-CoV-2 structural and non-structural proteins in the host cells. We also discovered unique signatures of genes in ACE2+TMPRSS2+ STBs and EVTs. The ACE2+TMPRSS2+ STBs are highly differentiated cells and express genes involved mitochondrial metabolism and glucose transport. The second trimester ACE2+TMPRSS2+ EVTs are enriched for markers of endovascular trophoblasts. Further, both these subtypes abundantly expressed genes in Toll like receptor pathway, the second trimester EVTs (but not first trimester STBs) are also enriched for component of the JAK-STAT pathway that drive inflammation. To conclude, herein we uncovered the cellular targets for SARS-CoV-2 entry and show that these cells can potentially drive viremia in the developing human placenta. Our results provide a basic framework towards understanding the paraphernalia involved in SARS-CoV-2 infections in pregnancy.

scholarly journals Meta-Transcriptome Detector (MTD): a novel pipeline for metatranscriptome analysis of bulk and single-cell RNAseq data

2021 ◽  
Author(s):  
Fei Wu ◽  
Yaozhong Liu ◽  
Binhua Ling
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Host Cells ◽  
Host Responses ◽  
Rna Seq ◽  
Cell Level ◽  
Gene Expressions ◽  
Rnaseq Data ◽  
Software Program ◽  
User Friendly

RNA-seq data contains not only host transcriptomes but also non-host information that comprises transcripts from active microbiota in the host cells. Therefore, metatranscriptomics can reveal gene expression of the entire microbial community in a given sample. However, there is no single tool that can simultaneously analyze host-microbiota interactions and to quantify microbiome at the single-cell level, particularly for users with limited expertise of bioinformatics. Here, we developed a novel software program that can comprehensively and synergistically analyze gene expression of the host and microbiome as well as their association using bulk and single-cell RNA-seq data. Our pipeline, named Meta-Transcriptome Detector (MTD), can identify and quantify microbiome extensively, including viruses, bacteria, protozoa, fungi, plasmids, and vectors. MTD is easy to install and is user-friendly. This novel software program empowers researchers to study the interactions between microbiota and the host by analyzing gene expressions and pathways, which provides further insights into host responses to microorganisms.

scholarly journals PROSSTT: probabilistic simulation of single-cell RNA-seq data for complex differentiation processes

2018 ◽  
Author(s):  
Nikolaos Papadopoulos ◽  
R. Gonzalo Parra ◽  
Johannes Söding
Keyword(s):  
Single Cell ◽  
Single Cells ◽  
Noise Model ◽  
Rna Seq ◽  
Enabling Technology ◽  
Differentiated Cells ◽  
Probabilistic Simulation ◽  
Lineage Tree ◽  
Lineage Trees

BackgroundSingle-cell RNA sequencing (scRNA-seq) is an enabling technology for the study of cellular differentiation and heterogeneity. From snapshots of the transcriptomic profiles of differentiating single cells, the cellular lineage tree that leads from a progenitor population to multiple types of differentiated cells can be derived. The underlying lineage trees of most published datasets are linear or have a single branchpoint, but many studies with more complex lineage trees will soon become available. To test and further develop tools for lineage tree reconstruction, we need test datasets with known trees.ResultsPROSSTT can simulate scRNA-seq datasets for differentiation processes with lineage trees of any desired complexity, noise level, noise model, and size. PROSSTT also provides scripts to quantify the quality of predicted lineage trees.Availabilityhttps://github.com/soedinglab/[email protected]

scholarly journals Single cell transcriptome research in human placenta

Reproduction ◽  
2020 ◽  
Vol 160 (6) ◽  
pp. R155-R167
Author(s):  
Hui Li ◽  
Qianhui Huang ◽  
Yu Liu ◽  
Lana X Garmire
Keyword(s):  
Single Cell ◽  
Human Placenta ◽  
Pregnancy Complications ◽  
Cell Types ◽  
Rna Seq ◽  
Structural Components ◽  
The Public ◽  
Cell Transcriptome ◽  
Areas Of Interest ◽  
Single Cell Transcriptome

Human placenta is a complex and heterogeneous organ interfacing between the mother and the fetus that supports fetal development. Alterations to placental structural components are associated with various pregnancy complications. To reveal the heterogeneity among various placenta cell types in normal and diseased placentas, as well as elucidate molecular interactions within a population of placental cells, a new genomics technology called single cell RNA-seq (or scRNA-seq) has been employed in the last couple of years. Here we review the principles of scRNA-seq technology, and summarize the recent human placenta studies at scRNA-seq level across gestational ages as well as in pregnancy complications, such as preterm birth and preeclampsia. We list the computational analysis platforms and resources available for the public use. Lastly, we discuss the future areas of interest for placenta single cell studies, as well as the data analytics needed to accomplish them.

scholarly journals Developmental landscape of  human forebrain at a single-cell level unveils early waves of oligodendrogenesis

2021 ◽  
Author(s):  
David van Bruggen ◽  
Fabio Baldivia Pohl ◽  
Christoffer Mattsson Langseth ◽  
Petra Kukanja ◽  
Hower Lee ◽  
...  
Keyword(s):  
Single Cell ◽  
Network Inference ◽  
Regulatory Mechanisms ◽  
Oligodendrocyte Precursor Cells ◽  
Second Trimester ◽  
Rna Seq ◽  
Cell Level ◽  
Human Central Nervous System ◽  
Oligodendrocyte Precursor

Oligodendrogenesis in the human central nervous system has been mainly observed at the second trimester of gestation, a much later developmental stage compared to mouse. Here we characterize the transcriptomic neural diversity in the human forebrain at post conceptual weeks (PCW) 8 to 10, using single-cell RNA-Seq. We find evidence of the emergence of a first wave of oligodendrocyte lineage cells as early as PCW 8, which we also confirm at the epigenomic level with single-cell ATAC-Seq. Using regulatory network inference, we predict key transcriptional events leading to the specification of oligodendrocyte precursor cells (OPCs). Moreover, by profiling the spatial expression of fifty key genes using In Situ Sequencing (ISS), we identify regions in the human ventral fetal forebrain where oligodendrogenesis first occurs. Our results indicate evolutionary conservation of the first wave of oligodendrogenesis between mouse and human and describe regulatory mechanisms required for human OPC specification.

scholarly journals Single-Cell RNA-seq Identifies Cell Subsets in Human Placenta That Highly Expresses Factors Driving Pathogenesis of SARS-CoV-2

2020 ◽  
Vol 8 ◽  
Author(s):  
Nancy Ashary ◽  
Anshul Bhide ◽  
Priyanka Chakraborty ◽  
Stacy Colaco ◽  
Anuradha Mishra ◽  
...  
Keyword(s):  
Single Cell ◽  
Human Placenta ◽  
Rna Seq

scholarly journals Learning common and specific patterns from data of multiple interrelated biological scenarios with matrix factorization

2018 ◽  
Author(s):  
Lihua Zhang ◽  
Shihua Zhang
Keyword(s):  
Single Cell ◽  
Matrix Factorization ◽  
Expression Profiles ◽  
Chromatin Modification ◽  
Embryonic Stem ◽  
Differential Analysis ◽  
Rna Seq ◽  
Sequencing Data ◽  
Cancer Subtypes ◽  
Differentiated Cells

AbstractHigh-throughput biological technologies (e.g., ChIP-seq, RNA-seq and single-cell RNA-seq) rapidly accelerate the accumulation of genome-wide omics data in diverse interrelated biological scenarios (e.g., cells, tissues and conditions). Data dimension reduction and differential analysis are two common paradigms for exploring and analyzing such data. However, they are typically used in a separate or/and sequential manner. In this study, we propose a flexible non-negative matrix factorization framework CSMF to combine them into one paradigm to simultaneously reveal common and specific patterns from data generated under interrelated biological scenarios. We demonstrate the effectiveness of CSMF with four applications including pairwise ChIP-seq data describing the chromatin modification map on protein-DNA interactions between K562 and Huvec cell lines; pairwise RNA-seq data representing the expression profiles of two cancers (breast invasive carcinoma and uterine corpus endometrial carcinoma); RNA-seq data of three breast cancer subtypes; and single-cell sequencing data of human embryonic stem cells and differentiated cells at six time points. Extensive analysis yields novel insights into hidden combinatorial patterns embedded in these interrelated multi-modal data. Results demonstrate that CSMF is a powerful tool to uncover common and specific patterns with significant biological implications from data of interrelated biological scenarios.

scholarly journals Bioinformatic analysis reveals that the reproductive system is potentially at risk from 2019-nCoV

2020 ◽  
Author(s):  
Jiawei Zhang ◽  
Yuqi Wu ◽  
Rui Wang ◽  
Keshi Lu ◽  
Menjiang Tu ◽  
...  
Keyword(s):  
Protein Expression ◽  
Single Cell ◽  
Potential Risk ◽  
Reproductive System ◽  
Single Cell Analysis ◽  
Bioinformatic Analysis ◽  
Host Cells ◽  
Rna Expression ◽  
Novel Coronavirus

An outbreak of a novel coronavirus, 2019-nCoV, occurred in China towards the end of 2019, and has spread rapidly ever since. Previous studies showed that some virus could affect the reproductive system and cause long-term complications. Recent studies exploring the source of 2019-nCoV using genomic sequencing have revealed that 2019-nCoV enters the host cells via the angiotensin-converting enzyme II (ACE2), the receptor that recognizes 2019-nCoV. To investigate the expression of ACE2 and to explore the potential risk of infection in the reproductive system, we performed a thorough bioinformatic analysis on data from public databases involving RNA expression, protein expression, and single-cell RNA expression studies. The analyzed data showed high levels of ACE2 mRNA and protein expression in the testis and spermatids and equal levels of ACE2 expression in the uterus and lung. Comprehensive single-cell analysis identified ACE2 expression in the lung, testis, spermatids, and uterus. In conclusion, this study revealed the potential risk associated with the 2019-nCoV infection in the reproductive system and predicted that long-term complications might have a significant impact on the prevention and management of COVID-19, the disease caused upon infection with 2019-nCoV.

scholarly journals Single-cell RNA-seq reveals the diversity of trophoblast subtypes and patterns of differentiation in the human placenta 

Cell Research ◽  
2018 ◽  
Vol 28 (8) ◽  
pp. 819-832 ◽  
Author(s):  
Yawei Liu ◽  
Xiaoying Fan ◽  
Rui Wang ◽  
Xiaoyin Lu ◽  
Yan-Li Dang ◽  
...  
Keyword(s):  
Single Cell ◽  
Human Placenta ◽  
Rna Seq

scholarly journals Single-cell RNA expression profiling shows that ACE2, the putative receptor of COVID-2019, has significant expression in nasal and mouth tissue, and is co-expressed with TMPRSS2 and not co-expressed with SLC6A19 in the tissues

2020 ◽  
Author(s):  
Chao Wu ◽  
Min Zheng
Keyword(s):  
New England ◽  
Single Cell ◽  
Host Cells ◽  
Angiotensin Converting Enzyme 2 ◽  
The Public ◽  
Putative Receptor ◽  
Nasal Swabs ◽  
Rna Expression Profiling ◽  
Significant Expression ◽  
Novel Coronavirus

Abstract A novel coronavirus (COVID-2019) was first identified in Wuhan, Hubei Province, and then spreads to the other Provinces of China. COVID-2019 was reported to share the same receptor, Angiotensin-converting enzyme 2 (ACE2), with SARS-CoV. But the infection rate of COVID-2019 is much higher than SARS-CoV. The biophysical and structural evidence showed that the COVID-2019 binds ACE2 with 10~20 times affinity than SARS-CoV. TMPRSS2 cleaves ACE2 and facilitates the entry of the virus into host cells. The presence of SLC6A19 may block the access of TMPRSS2 to the cutting site on ACE2 and weaken the entry of COVID-2019 into host cells. Here based on the public single-cell RNA-Seq datasets, we analyzed the ACE2 expression in the nasal, mouth, lung, and colon tissues. We find that the number of ACE2-expressing cells in the nasal and mouth tissues is comparable to the number of ACE2-expressing cells in the lung and colon tissues. We also find that ACE2 tends to be co-expressed with TMPRSS2 and not co-expressed with SLC6A19 in the nasal and mouth tissues. With the results, we infer that nasal and mouth tissues may be the first host cells of COVID-2019 infection. In our previous report in medRxiv and a recurrent report in New England Journal of Medicine, the COVID-2019 load tends to be higher in the nasal-swabs than in throat-swabs. We believe the roles of nasal and mouth tissues in COVID-2019 infection should be investigated, and we need to pay more attention to protect nose and mouth from COVID-2019 infection.

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