CD4+CD25+ regulatory T cells (Treg) have been shown to maintain immune tolerance against self and foreign Ags, but their role in persistent viral infection has not been well-defined. In this study, we investigated whether and where CD4+CD25+ Treg contribute to the development of chronic hepatitis B (CHB). One hundred twenty-one patients were enrolled, including 16 patients with acute hepatitis B, 76 with CHB, and 29 with chronic severe hepatitis B. We demonstrated that in chronic severe hepatitis B patients, the frequencies of CD4+CD25+ Treg in both PBMC and liver-infiltrating lymphocytes were significantly increased and there was a dramatic increase of FoxP3+-cell and inflammatory cell infiltration in the liver compared with healthy controls. In CHB patients, circulating CD4+CD25+ Treg frequency significantly correlates with serum viral load. In acute hepatitis B patients, circulating CD4+CD25+ Treg frequency was initially low and with time, the profile reversed to exhibit an increased number of circulating Treg in the convalescent phase and restored to normal levels upon resolution. In PBMC taken from infected patients, depletion of CD4+CD25+ Treg led to an increase of IFN-γ production by HBV-Ag-stimulated PBMC. In addition, CD4+CD25+ Treg were capable of suppressing proliferation of autologous PBMC mediated by HBV Ags, which probably reflects the generation of HBV-Ag-specific Treg in circulation and in the liver of HBV-infected patients. Together, our findings suggest that CD4+CD25+ Treg play an active role not only in modulating effectors of immune response to HBV infection, but also in influencing the disease prognosis in patients with hepatitis B.

Type I interferon (IFN) is critical for controlling pathogen infection; however, its regulatory mechanisms in plasmacytoid cells (pDCs) still remain unclear. Here, we have shown that nucleic acid sensors cGAS-, STING-, MDA5-, MAVS-, or transcription factor IRF3-deficient mice produced high amounts of type I IFN-α and IFN-β (IFN-α/β) in the serum and were resistant to lethal plasmodium yoelii YM infection. Robust IFN-α/β production was abolished when gene encoding nucleic acid sensor TLR7, signaling adaptor MyD88, or transcription factor IRF7 was ablated or pDCs were depleted. Further, we identified SOCS1 as a key negative regulator to inhibit MyD88-dependent type I IFN signaling in pDCs. Finally, we have demonstrated that pDCs, cDCs, and macrophages were required for generating IFN-α/β-induced subsequent protective immunity. Thus, our findings have identified a critical regulatory mechanism of type I IFN signaling in pDCs and stage-specific function of immune cells in generating potent immunity against lethal YM infection.

Epigenetic factors have been implicated in the regulation of CD4+ T cell differentiation. Jmjd3 plays a role in many biological processes, but its in vivo function in T cell differentiation remains unknown. Here, we report that Jmjd3 ablation promotes CD4+ T cell differentiation into Th2 and Th17 cells in the small intestine and colon, and inhibits T cell differentiation into Th1 cells under different cytokine-polarizing conditions and in a Th1-dependent colitis model. Jmjd3 deficiency also restrains the plasticity of the conversion of Th2, Th17 or Treg cells to Th1 cells. The skewing of T cell differentiation is concomitant with changes in the expression of key transcription factors and cytokines. H3K27me3 and H3K4me3 levels in Jmjd3-deficient cells are correlated with altered gene expression through interactions with specific transcription factors. Our results identify Jmjd3 as an epigenetic factor in T cell differentiation via changes in histone methylation and target gene expression.

The kinome-wide virtual profiling of small molecules with high-dimensional structure−activity data is a challenging task in drug discovery. Here, we present a virtual profiling model against a panel of 391 kinases based on largescale bioactivity data and the multitask deep neural network algorithm. The obtained model yields excellent internal prediction capability with an auROC of 0.90 and consistently outperforms conventional single-task models on external tests, especially for kinases with insufficient activity data. Moreover, more rigorous experimental validations including 1410 kinasecompound pairs showed a high-quality average auROC of 0.75 and confirmed many novel predicted "off-target" activities. Given the verified generalizability, the model was further applied to various scenarios for depicting the kinome-wide selectivity and the association with certain diseases. Overall, the computational model enables us to create a comprehensive kinome interaction network for designing novel chemical modulators or drug repositioning and is of practical value for exploring previously less studied kinases.