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      Human Pluripotent Stem Cell-Derived Intestinal Organoids Model SARS-CoV-2 Infection Revealing a Common Epithelial Inflammatory Response

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          Abstract

          Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection leading to coronavirus disease 2019 (COVID-19) usually results in respiratory disease, but extrapulmonary manifestations are of major clinical interest. Intestinal symptoms of COVID-19 are present in a significant number of patients, and include nausea, diarrhea, and viral RNA shedding in feces. Human induced pluripotent stem cell-derived intestinal organoids (HIOs) represent an inexhaustible cellular resource that could serve as a valuable tool to study SARS-CoV-2 as well as other enteric viruses that infect the intestinal epithelium. Here, we report that SARS-CoV-2 productively infects both proximally and distally patterned HIOs, leading to the release of infectious viral particles while stimulating a robust transcriptomic response, including a significant upregulation of interferon-related genes that appeared to be conserved across multiple epithelial cell types. These findings illuminate a potential inflammatory epithelial-specific signature that may contribute to both the multisystemic nature of COVID-19 as well as its highly variable clinical presentation.

          Abstract

          In this article, Gustavo Mostoslavsky, Elke Mühlberger, and colleagues model the host response to intestinal SARS-CoV-2 infection using iPSC-derived regionally patterned intestinal organoids. Specifically, they highlight productive infection of mesenchyme-free intestinal and colonic organoids and demonstrate that they recapitulate intrinsic inflammatory transcriptomic responses to infection that have been shown in other epithelial cell types.

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          Most cited references49

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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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            Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus–Infected Pneumonia in Wuhan, China

            In December 2019, novel coronavirus (2019-nCoV)-infected pneumonia (NCIP) occurred in Wuhan, China. The number of cases has increased rapidly but information on the clinical characteristics of affected patients is limited.
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              Is Open Access

              limma powers differential expression analyses for RNA-sequencing and microarray studies

              limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
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                Author and article information

                Journal
                Stem Cell Reports
                Stem Cell Reports
                Stem Cell Reports
                The Authors.
                2213-6711
                13 April 2021
                13 April 2021
                13 April 2021
                : 16
                : 4
                : 940-953
                Affiliations
                [1 ]Center for Regenerative Medicine of Boston University and Boston Medical Center, Boston, MA 02118, USA
                [2 ]National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA 02118, USA
                [3 ]Department of Microbiology, Boston University School of Medicine, Boston, MA 02118, USA
                [4 ]Department of Physiology & Biophysics, Boston University School of Medicine, Boston, MA 02118, USA
                [5 ]The Pulmonary Center, Department of Medicine, Boston University School of Medicine, Boston, MA 02118, USA
                [6 ]Section of Gastroenterology, Department of Medicine, Boston University School of Medicine, Boston, MA 02218, USA
                Author notes
                []Corresponding author
                [∗∗ ]Corresponding author
                [7]

                These authors contributed equally

                Article
                S2213-6711(21)00099-0
                10.1016/j.stemcr.2021.02.019
                8042780
                33852884
                3fbcdab9-d657-4bbf-88e2-5d4d15ce457e
                © 2021 The Authors

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                : 29 December 2020
                : 23 February 2021
                : 24 February 2021
                Categories
                Resource

                human induced pluripotent stem cells,intestinal and colonic organoids,sars-cov-2,extrapulmonary covid-19,host response,intestinal epithelial cells

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