ABSTRACT
Enhancer of zeste 2 (Ezh2) mainly methylates lysine 27 of histone-H3 (H3K27me3) as part of the polycomb repressive complex 2 (PRC2) together with Suz12 and Eed. However, Ezh2 can also modify non-histone substrates, although it is unclear whether this mechanism has a role during development. Here, we present evidence for a chromatin-independent role of Ezh2 during T-cell development and immune homeostasis. T-cell-specific depletion of Ezh2 induces a pronounced expansion of natural killer T (NKT) cells, although Ezh2-deficient T cells maintain normal levels of H3K27me3. In contrast, removal of Suz12 or Eed destabilizes canonical PRC2 function and ablates NKT cell development completely. We further show that Ezh2 directly methylates the NKT cell lineage defining transcription factor PLZF, leading to its ubiquitination and subsequent degradation. Sustained PLZF expression in Ezh2-deficient mice is associated with the expansion of a subset of NKT cells that cause immune perturbation. Taken together, we have identified a chromatin-independent function of Ezh2 that impacts on the development of the immune system.
Subject(s)
Enhancer of Zeste Homolog 2 Protein/genetics , Enhancer of Zeste Homolog 2 Protein/metabolism , Homeostasis , Immunity/genetics , Animals , Cell Differentiation , Cell Line , Gene Expression , Humans , Kruppel-Like Transcription Factors/genetics , Kruppel-Like Transcription Factors/metabolism , Methylation , Mice , Mice, Knockout , Natural Killer T-Cells/immunology , Natural Killer T-Cells/metabolism , Promyelocytic Leukemia Zinc Finger Protein , Protein Binding , Proteolysis , Receptors, Antigen, T-Cell, alpha-beta/genetics , Receptors, Antigen, T-Cell, alpha-beta/metabolism , T-Lymphocyte Subsets/immunology , T-Lymphocyte Subsets/metabolism , Thymocytes/cytology , Thymocytes/immunology , Thymocytes/metabolismABSTRACT
BACKGROUND: Influenza is one of the oldest and deadliest infectious diseases known to man. Reassorted strains of the virus pose the greatest risk to both human and animal health and have been associated with all pandemics of the past century, with the possible exception of the 1918 pandemic, resulting in tens of millions of deaths. We have developed and tested new computer algorithms, FluShuffle and FluResort, which enable reassorted viruses to be identified by the most rapid and direct means possible. These algorithms enable reassorted influenza, and other, viruses to be rapidly identified to allow prevention strategies and treatments to be more efficiently implemented. RESULTS: The FluShuffle and FluResort algorithms were tested with both experimental and simulated mass spectra of whole virus digests. FluShuffle considers different combinations of viral protein identities that match the mass spectral data using a Gibbs sampling algorithm employing a mixed protein Markov chain Monte Carlo (MCMC) method. FluResort utilizes those identities to calculate the weighted distance of each across two or more different phylogenetic trees constructed through viral protein sequence alignments. Each weighted mean distance value is normalized by conversion to a Z-score to establish a reassorted strain. CONCLUSIONS: The new FluShuffle and FluResort algorithms can correctly identify the origins of influenza viral proteins and the number of reassortment events required to produce the strains from the high resolution mass spectral data of whole virus proteolytic digestions. This has been demonstrated in the case of constructed vaccine strains as well as common human seasonal strains of the virus. The algorithms significantly improve the capability of the proteotyping approach to identify reassorted viruses that pose the greatest pandemic risk.