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      Mutations that prevent caspase cleavage of RIPK1 cause autoinflammatory disease

      research-article
      1 , 2 , * , 3 , * , 3 , 3 , 3 , 1 , 1 , 2 , 3 , 1 , 4 , 5 , 6 , 3 , 1 , 2 , 1 , 2 , 1 , 2 , 7 , 7 , 8 , 9 , 1 , 2 , 1 , 10 , 11 , 3 , 3 , 12 , 3 , 3 , 1 , 2 , 1 , 2 , 1 , 3 , 3 , 9 , 1 , 2 , 1 , 3 , 3 , 3 , 3 , 3 , 13 , 14 , 15 , 1 , 2 , 1 , 2 , 11 , 9 , 8 , 10 , 1 , 2 , 7 , 3 , * , 1 , 2 , *
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          Abstract

          Receptor Interacting Protein Kinase 1 (RIPK1) is a key regulator of innate immune signalling pathways. To ensure an optimal inflammatory response, RIPK1 is post-translationally regulated by well characterised ubiquitylation and phosphorylation events, as well as caspase-8 mediated cleavage 17 . The physiological relevance of this cleavage remains unclear, though it is believed to inhibit activation of RIPK3 and necroptosis 8 . Here we show that heterozygous missense mutations p.D324N, p.D324H and p.D324Y prevent caspase cleavage of RIPK1 in humans and result in early-onset periodic fever episodes and severe intermittent lymphadenopathy, a condition we designate ‘Cleavage-resistant RIPK1-Induced Autoinflammatory’ (CRIA) syndrome. To define the mechanism for this disease we generated a cleavage-resistant Ripk1 D325A mutant mouse strain. While Ripk1 -/- mice die postnatally from systemic inflammation, Ripk1 D325A/D325A mice died during embryogenesis. Embryonic lethality was completely prevented by combined loss of Casp8 and Ripk3 but not by loss of Ripk3 or Mlkl alone. Loss of RIPK1 kinase activity also prevented Ripk1 D325A/D325A embryonic lethality, however the mice died before weaning from multi organ inflammation in a RIPK3 dependent manner. Consistently, Ripk1 D325A/D325A and Ripk1 D325A/+ cells were hypersensitive to RIPK3 dependent TNF-induced apoptosis and necroptosis. Heterozygous Ripk1 D325A/+ mice were viable and grossly normal, but were hyper-responsive to inflammatory stimuli in vivo. Our results demonstrate the importance of caspase-mediated RIPK1 cleavage during embryonic development and show that caspase cleavage of RIPK1 not only inhibits necroptosis but maintains inflammatory homeostasis throughout life.

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          Most cited references26

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          TCC: an R package for comparing tag count data with robust normalization strategies

          Background Differential expression analysis based on “next-generation” sequencing technologies is a fundamental means of studying RNA expression. We recently developed a multi-step normalization method (called TbT) for two-group RNA-seq data with replicates and demonstrated that the statistical methods available in four R packages (edgeR, DESeq, baySeq, and NBPSeq) together with TbT can produce a well-ranked gene list in which true differentially expressed genes (DEGs) are top-ranked and non-DEGs are bottom ranked. However, the advantages of the current TbT method come at the cost of a huge computation time. Moreover, the R packages did not have normalization methods based on such a multi-step strategy. Results TCC (an acronym for Tag Count Comparison) is an R package that provides a series of functions for differential expression analysis of tag count data. The package incorporates multi-step normalization methods, whose strategy is to remove potential DEGs before performing the data normalization. The normalization function based on this DEG elimination strategy (DEGES) includes (i) the original TbT method based on DEGES for two-group data with or without replicates, (ii) much faster methods for two-group data with or without replicates, and (iii) methods for multi-group comparison. TCC provides a simple unified interface to perform such analyses with combinations of functions provided by edgeR, DESeq, and baySeq. Additionally, a function for generating simulation data under various conditions and alternative DEGES procedures consisting of functions in the existing packages are provided. Bioinformatics scientists can use TCC to evaluate their methods, and biologists familiar with other R packages can easily learn what is done in TCC. Conclusion DEGES in TCC is essential for accurate normalization of tag count data, especially when up- and down-regulated DEGs in one of the samples are extremely biased in their number. TCC is useful for analyzing tag count data in various scenarios ranging from unbiased to extremely biased differential expression. TCC is available at http://www.iu.a.u-tokyo.ac.jp/~kadota/TCC/ and will appear in Bioconductor (http://bioconductor.org/) from ver. 2.13.
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            RIP3 induces apoptosis independent of pronecrotic kinase activity.

            Receptor-interacting protein kinase 3 (RIP3 or RIPK3) has emerged as a central player in necroptosis and a potential target to control inflammatory disease. Here, three selective small-molecule compounds are shown to inhibit RIP3 kinase-dependent necroptosis, although their therapeutic value is undermined by a surprising, concentration-dependent induction of apoptosis. These compounds interact with RIP3 to activate caspase 8 (Casp8) via RHIM-driven recruitment of RIP1 (RIPK1) to assemble a Casp8-FADD-cFLIP complex completely independent of pronecrotic kinase activities and MLKL. RIP3 kinase-dead D161N mutant induces spontaneous apoptosis independent of compound, whereas D161G, D143N, and K51A mutants, like wild-type, only trigger apoptosis when compound is present. Accordingly, RIP3-K51A mutant mice (Rip3(K51A/K51A)) are viable and fertile, in stark contrast to the perinatal lethality of Rip3(D161N/D161N) mice. RIP3 therefore holds both necroptosis and apoptosis in balance through a Ripoptosome-like platform. This work highlights a common mechanism unveiling RHIM-driven apoptosis by therapeutic or genetic perturbation of RIP3.
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              Cleavage of the death domain kinase RIP by caspase-8 prompts TNF-induced apoptosis.

              Although the molecular mechanisms of TNF signaling have been largely elucidated, the principle that regulates the balance of life and death is still unknown. We report here that the death domain kinase RIP, a key component of the TNF signaling complex, was cleaved by Caspase-8 in TNF-induced apoptosis. The cleavage site was mapped to the aspartic acid at position 324 of RIP. We demonstrated that the cleavage of RIP resulted in the blockage of TNF-induced NF-kappaB activation. RIPc, one of the cleavage products, enhanced interaction between TRADD and FADD/MORT1 and increased cells' sensitivity to TNF. Most importantly, the Caspase-8 resistant RIP mutants protected cells against TNF-induced apopotosis. These results suggest that cleavage of RIP is an important process in TNF-induced apoptosis. Further more, RIP cleavage was also detected in other death receptor-mediated apoptosis. Therefore, our study provides a potential mechanism to convert cells from life to death in death receptor-mediated apoptosis.
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                Author and article information

                Journal
                0410462
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                18 October 2019
                11 December 2019
                January 2020
                11 June 2020
                : 577
                : 7788
                : 103-108
                Affiliations
                [1 ]The Walter and Eliza Hall Institute, 1G Royal Parade, Parkville, Victoria 3052, Australia
                [2 ]Department of Medical Biology, University of Melbourne, Parkville, Victoria 3010, Australia
                [3 ]Inflammatory Disease Section, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
                [4 ]Centre for Innate Immunity and Infectious Diseases, Hudson Institute of Medical Research, Clayton, Victoria, 3168, Australia
                [5 ]Department of Molecular and Translational Science, Monash University, Clayton, Victoria, 3168, Australia
                [6 ]Light Imaging Section, Office of Science and Technology, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, MD 20892, USA
                [7 ]Translational Immunology Section, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, MD 20892, USA
                [8 ]Department of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, MD 20892, USA
                [9 ]Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
                [10 ]Institute for Genetics, Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD) & Center for Molecular Medicine (CMMC), University of Cologne, D-50931, Germany
                [11 ]Molecular Development of the Immune System Section and Clinical Genomics Program, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
                [12 ]Laboratory of Muscle Stem Cells and Gene Regulation, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, MD 20892, USA
                [13 ]NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
                [14 ]Division of Rheumatology, Department of Medicine, University of California San Francisco, San Francisco, CA 94143, USA
                [15 ]Division of Pulmonary and Critical Care, Department of Medicine, University of California San Francisco, San Francisco, CA 94143, USA
                Author notes
                [* ] Correspondence and requests for mouse materials should be addressed to N.L. or J.S. and for human materials to D.L.K. lalaoui@ 123456wehi.edu.au ; steven.boyden@ 123456genetics.utah.edu ; kastnerd@ 123456mail.nih.gov ; silke@ 123456wehi.edu.au
                [17]

                These authors jointly supervised this work: Daniel L. Kastner, John Silke

                Article
                EMS84659
                10.1038/s41586-019-1828-5
                6930849
                31827281
                49878cca-9f14-410f-92a9-ff912341492f

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