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      GSDME-mediated pyroptosis promotes the progression and associated inflammation of atherosclerosis

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          Abstract

          Pyroptosis, a type of Gasdermin-mediated cell death, contributes to an exacerbation of inflammation. To test the hypothesis that GSDME-mediated pyroptosis aggravates the progression of atherosclerosis, we generate ApoE and GSDME dual deficiency mice. As compared with the control mice, GSDME −/− /ApoE −/− mice show a reduction of atherosclerotic lesion area and inflammatory response when induced with a high-fat diet. Human atherosclerosis single-cell transcriptome analysis demonstrates that GSDME is mainly expressed in macrophages. In vitro, oxidized low-density lipoprotein (ox-LDL) induces GSDME expression and pyroptosis in macrophages. Mechanistically, ablation of GSDME in macrophages represses ox-LDL-induced inflammation and macrophage pyroptosis. Moreover, the signal transducer and activator of transcription 3 (STAT3) directly correlates with and positively regulates GSDME expression. This study explores the transcriptional mechanisms of GSDME during atherosclerosis development and indicates that GSDME-mediated pyroptosis in the progression of atherosclerosis could be a potential therapeutic approach for atherosclerosis.

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          Most cited references77

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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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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              clusterProfiler: an R package for comparing biological themes among gene clusters.

              Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
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                Author and article information

                Contributors
                Journal
                Nature Communications
                Nat Commun
                Springer Science and Business Media LLC
                2041-1723
                December 2023
                February 18 2023
                : 14
                : 1
                Article
                10.1038/s41467-023-36614-w
                ad1f79d0-fe28-4694-888f-5de2b95d5c85
                © 2023

                https://creativecommons.org/licenses/by/4.0

                https://creativecommons.org/licenses/by/4.0

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