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      Single-cell RNA sequencing of SARS–CoV-2 cell entry factors in the preconceptional human endometrium

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          Abstract

          STUDY QUESTION

          Are SARS-CoV-2 canonical cell entry machinery, consisting of ACE2, TMPRSS2, NRP1 and LY6E, or alternative potential cell entry machinery, consisting of BSG, ANPEP, CD209, CLEC4G, TMPRSS4, TMPRSS11A, FURIN, CTSB, CTSL and IFITM1, expressed in the human endometrium across the menstrual cycle?

          SUMMARY ANSWER

          Analysis of cell entry factors for SARS-CoV-2 by single-cell RNA-sequencing (scRNAseq) in the preconceptional human endometrium reveals low risk of infection.

          WHAT IS KNOWN ALREADY

          Gene expression datasets from bulk endometrial tissue show no significant expression of the SARS-CoV-2 receptor ACE2 and TMPRSS2. This is in contrast to reported expression of ACE2 at the single-cell level in the decidua and trophoblast cells at the maternal–fetal interface in early pregnancy, as well as vertical transmission of SARS-CoV-2 during pregnancy.

          STUDY DESIGN, SIZE, DURATION

          This analysis of SARS-CoV-2 cell entry machinery gene expression was conducted by scRNAseq in 73 181 human endometrial cells isolated from endometrial biopsies obtained from 27 donors across the menstrual cycle.

          PARTICIPANTS/MATERIALS, SETTING, METHODS

          ScRNAseq examined the expression of genes encoding cell entry machinery for SARS-CoV-2. The raw data were from a previously published dataset.

          MAIN RESULTS AND THE ROLE OF CHANCE

          ScRNAseq analysis showed no significant expression of ACE2 in stromal or unciliated epithelial cells in any phase of the menstrual cycle. TMPRSS2 was expressed in epithelial cells during the early proliferative and mid-secretory phases. Interestingly, the expression of NRP1 was observed in both stromal and epithelial cells across all phases of the menstrual cycle, and LY6E was highly expressed in stromal cells. In the mid-secretory phase, coexpression of ACE2 and TMPRSS2 was detected in 0.07% of luminal epithelial cells. No cells simultaneously expressed ACE2, NRP1 and TMPRSS2 at the time of embryo implantation. Focusing on non-canonical cell entry machinery, BSG was highly expressed in all cell types across the menstrual cycle and may interact with CTSB or CTSL proteases, but viral infection using this machinery has not yet been confirmed.

          LARGE SCALE DATA

          All raw data in this study can be found at NCBI’s Gene Expression Omnibus (series accession code GSE111976) and Sequence Read Archive (accession code SRP135922).

          LIMITATIONS, REASONS FOR CAUTION

          Our findings at the single-cell level imply low efficiency of SARS-CoV-2 endometrial infection using canonical receptors in a cohort of healthy reproductive-age women; however, infection of endometrial cells can only be assessed in the presence of the virus. All samples were processed for scRNAseq, so no samples are remaining to analyze protein expression or spatial transcriptomics.

          WIDER IMPLICATIONS OF THE FINDINGS

          Our results offer a useful resource to guide reproductive decisions when assessing risk of endometrial infection by SARS-CoV-2 during the preconceptional period in asymptomatic COVID-19 carriers.

          STUDY FUNDING/COMPETING INTEREST(S)

          This study was jointly supported by the March of Dimes, Chan Zuckerberg Biohub and MINECO/FEDER (SAF-2015-67164-R, to C.S.) (Spanish Government), and the European Union’s Horizon 2020 Framework Programme for Research and Innovation (Grant agreement 874867). W.W. was supported by the Stanford Bio-X Graduate Bowes Fellowship and Chan Zuckerberg Biohub. F.V. was supported by the Miguel Servet Program Type II of ISCIII (CPII18/00020) and the FIS project (PI18/00957). A patent disclosure has been filed for the study with the title ‘Methods for assessing endometrial transformation’ and the global patent number ‘EP 3807648 A2’ under the inventors S.R.Q., C.S., W.W. and F.V. C.S. is the Founder and Head of the Scientific Advisory Board of Igenomix SL. S.R.Q is the Director of Mirvie. I.M. is partially employed by Igenomix SL. B.R. has no interests to declare.

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          Most cited references38

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          STAR: ultrafast universal RNA-seq aligner.

          Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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            SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor

            Summary The recent emergence of the novel, pathogenic SARS-coronavirus 2 (SARS-CoV-2) in China and its rapid national and international spread pose a global health emergency. Cell entry of coronaviruses depends on binding of the viral spike (S) proteins to cellular receptors and on S protein priming by host cell proteases. Unravelling which cellular factors are used by SARS-CoV-2 for entry might provide insights into viral transmission and reveal therapeutic targets. Here, we demonstrate that SARS-CoV-2 uses the SARS-CoV receptor ACE2 for entry and the serine protease TMPRSS2 for S protein priming. A TMPRSS2 inhibitor approved for clinical use blocked entry and might constitute a treatment option. Finally, we show that the sera from convalescent SARS patients cross-neutralized SARS-2-S-driven entry. Our results reveal important commonalities between SARS-CoV-2 and SARS-CoV infection and identify a potential target for antiviral intervention.
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              Comprehensive Integration of Single-Cell Data

              Single-cell transcriptomics has transformed our ability to characterize cell states, but deep biological understanding requires more than a taxonomic listing of clusters. As new methods arise to measure distinct cellular modalities, a key analytical challenge is to integrate these datasets to better understand cellular identity and function. Here, we develop a strategy to "anchor" diverse datasets together, enabling us to integrate single-cell measurements not only across scRNA-seq technologies, but also across different modalities. After demonstrating improvement over existing methods for integrating scRNA-seq data, we anchor scRNA-seq experiments with scATAC-seq to explore chromatin differences in closely related interneuron subsets and project protein expression measurements onto a bone marrow atlas to characterize lymphocyte populations. Lastly, we harmonize in situ gene expression and scRNA-seq datasets, allowing transcriptome-wide imputation of spatial gene expression patterns. Our work presents a strategy for the assembly of harmonized references and transfer of information across datasets.
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                Author and article information

                Journal
                Hum Reprod
                Hum Reprod
                humrep
                Human Reproduction (Oxford, England)
                Oxford University Press
                0268-1161
                1460-2350
                30 July 2021
                30 July 2021
                : deab183
                Affiliations
                [1 ]Igenomix Foundation, INCLIVA Health Research Institute , Valencia, Spain
                [2 ]Department of Bioengineering, Stanford University , Stanford, CA, USA
                [3 ]Department of Applied Physics, Stanford University , Stanford, CA, USA
                [4 ]Chan Zuckerberg Biohub , San Francisco, CA, USA
                [5 ]Department of Obstetrics & Gynecology, University of Valencia , Valencia, Spain
                [6 ]Department of Obstetrics & Gynecology, Beth Israel Deaconess Medical Center, Harvard University , Boston, MA, USA
                Author notes

                The authors consider that the first two authors should be regarded as joint First Authors.

                Correspondence address. Igenomix Foundation, INCLIVA Health Research Institute, C/Narcis de Monturiol Estarriol 11B, Valencia 46980, Spain. E-mail: carlos.simon@ 123456uv.es (C.S.) https://orcid.org/0000-0003-0902-9531; Department of Bioengineering, Stanford University, 443 Via Ortega, Stanford, CA 94305, USA. E-mail: steve@ 123456quake-lab.org (S.R.Q.) https://orcid.org/0000-0002-1613-0809
                Author information
                https://orcid.org/0000-0002-0039-9846
                https://orcid.org/0000-0002-1613-0809
                https://orcid.org/0000-0003-0902-9531
                Article
                deab183
                10.1093/humrep/deab183
                8385818
                34329437
                98b6c5ba-d447-41b1-a6d3-eb0184b381ae
                © The Author(s) 2021. Published by Oxford University Press on behalf of European Society of Human Reproduction and Embryology. All rights reserved. For permissions, please email: journals.permissions@oup.com

                This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model ( https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)

                This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections.

                History
                : 30 December 2020
                : 17 May 2021
                : 02 July 2021
                : 20 August 2021
                Page count
                Pages: 19
                Funding
                Funded by: March of Dimes, Chan Zuckerberg Biohub and MINECO/FEDER;
                Award ID: SAF- 2015-67164-R, to C.S.
                Funded by: European Union’s Horizon 2020 Framework Programme for Research and Innovation;
                Award ID: 874867
                Funded by: Stanford Bio-X Graduate Bowes Fellowship and Chan Zuckerberg Biohub;
                Funded by: Miguel Servet Program Type II of ISCIII;
                Award ID: CPII18/00020
                Funded by: FIS project;
                Award ID: PI18/00957
                Categories
                Original Article
                AcademicSubjects/MED00905
                Custom metadata
                PAP

                Human biology
                covid-19,sars-cov-2,ace2,tmprss2,nrp1,scrnaseq
                Human biology
                covid-19, sars-cov-2, ace2, tmprss2, nrp1, scrnaseq

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