0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Necroptosis of macrophage is a key pathological feature in biliary atresia via GDCA/S1PR2/ZBP1/p-MLKL axis

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Biliary atresia (BA) is a severe inflammatory and fibrosing neonatal cholangiopathy disease characterized by progressive obstruction of extrahepatic bile ducts, resulting in cholestasis and progressive hepatic failure. Cholestasis may play an important role in the inflammatory and fibrotic pathological processes, but its specific mechanism is still unclear. Necroptosis mediated by Z-DNA-binding protein 1 (ZBP1)/phosphorylated-mixed lineage kinase domain-like pseudokinase (p-MLKL) is a prominent pathogenic factor in inflammatory and fibrotic diseases, but its function in BA remains unclear. Here, we aim to determine the effect of macrophage necroptosis in the BA pathology, and to explore the specific molecular mechanism. We found that necroptosis existed in BA livers, which was occurred in liver macrophages. Furthermore, this process was mediated by ZBP1/p-MLKL, and the upregulated expression of ZBP1 in BA livers was correlated with liver fibrosis and prognosis. Similarly, in the bile duct ligation (BDL) induced mouse cholestatic liver injury model, macrophage necroptosis mediated by ZBP1/p-MLKL was also observed. In vitro, conjugated bile acid-glycodeoxycholate (GDCA) upregulated ZBP1 expression in mouse bone marrow-derived monocyte/macrophages (BMDMs) through sphingosine 1-phosphate receptor 2 (S1PR2), and the induction of ZBP1 was a prerequisite for the enhanced necroptosis. Finally, after selectively knocking down of macrophage S1pr2 in vivo, ZBP1/p-MLKL-mediated necroptosis was decreased, and further collagen deposition was markedly attenuated in BDL mice. Furthermore, macrophage Zbp1 or Mlkl specific knockdown also alleviated BDL-induced liver injury/fibrosis. In conclusion, GDCA/S1PR2/ZBP1/p-MLKL mediated macrophage necroptosis plays vital role in the pathogenesis of BA liver fibrosis, and targeting this process may represent a potential therapeutic strategy for BA.

          Related collections

          Most cited references73

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            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/.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Metascape provides a biologist-oriented resource for the analysis of systems-level datasets

              A critical component in the interpretation of systems-level studies is the inference of enriched biological pathways and protein complexes contained within OMICs datasets. Successful analysis requires the integration of a broad set of current biological databases and the application of a robust analytical pipeline to produce readily interpretable results. Metascape is a web-based portal designed to provide a comprehensive gene list annotation and analysis resource for experimental biologists. In terms of design features, Metascape combines functional enrichment, interactome analysis, gene annotation, and membership search to leverage over 40 independent knowledgebases within one integrated portal. Additionally, it facilitates comparative analyses of datasets across multiple independent and orthogonal experiments. Metascape provides a significantly simplified user experience through a one-click Express Analysis interface to generate interpretable outputs. Taken together, Metascape is an effective and efficient tool for experimental biologists to comprehensively analyze and interpret OMICs-based studies in the big data era.
                Bookmark

                Author and article information

                Contributors
                jsdr2002@126.com
                liliying@ccmu.edu.cn
                Journal
                Cell Death Dis
                Cell Death Dis
                Cell Death & Disease
                Nature Publishing Group UK (London )
                2041-4889
                1 March 2023
                1 March 2023
                March 2023
                : 14
                : 3
                : 175
                Affiliations
                [1 ]GRID grid.24696.3f, ISNI 0000 0004 0369 153X, Department of Cell Biology, Municipal Laboratory for Liver Protection and Regulation of Regeneration, , Capital Medical University, ; Beijing, 100069 China
                [2 ]GRID grid.24696.3f, ISNI 0000 0004 0369 153X, Department of Neonatal Surgery, Beijing Children’s Hospital, , Capital Medical University, National Center for Children’s Health, ; Beijing, 100045 China
                [3 ]GRID grid.16821.3c, ISNI 0000 0004 0368 8293, Institute of Precision Medicine, the Ninth People’s Hospital, , Shanghai Jiao Tong University School of Medicine, ; Shanghai, 200125 China
                [4 ]GRID grid.24696.3f, ISNI 0000 0004 0369 153X, Department of Pathology, Beijing Children’s Hospital, , Capital Medical University, National Center for Children’s Health, ; Beijing, 100045 China
                [5 ]GRID grid.24696.3f, ISNI 0000 0004 0369 153X, Department of General Surgery, Beijing Children’s Hospital, , Capital Medical University, National Center for Children’s Health, ; Beijing, 100045 China
                [6 ]GRID grid.24696.3f, ISNI 0000 0004 0369 153X, Department of Surgical Oncology, Beijing Children’s Hospital, , Capital Medical University, National Center for Children’s Health, ; Beijing, 100045 China
                Author information
                http://orcid.org/0000-0003-0470-2328
                Article
                5615
                10.1038/s41419-023-05615-4
                9977961
                36859525
                d5db843f-4c05-41f9-a560-7e0bcbc90e54
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 30 July 2022
                : 19 January 2023
                : 23 January 2023
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001809, National Natural Science Foundation of China (National Science Foundation of China);
                Award ID: 81770603
                Award ID: 81660092
                Award ID: 81970532
                Award ID: 82170622
                Award ID: 81430013
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2023

                Cell biology
                chronic inflammation,liver fibrosis
                Cell biology
                chronic inflammation, liver fibrosis

                Comments

                Comment on this article