Protein arginine methyltransferase 1 is required for megakaryocyte-mediated inflammatory response Free

Background: Megakaryocytes (MKs) are heterogeneous, with one subgroup known as immune MKs, which express immune regulatory transcription factors alongside other genes involved in inflammatory responses. Surface markers such as CD53 and CXCR4, combined with CD41 staining, have been used to identify immune MKs. Additionally, hematopoietic stem cells (HSC) give rise to Mks via two pathways: a stepwise differentiation through CD48⁺ intermediates and a direct pathway from HSCs which generate CD48^-Mks. Protein arginine methyltransferase 1 (PRMT1) in general is not a housekeeping gene but is activated in response to nutrients and growth factors for proliferation in mammalian cells. Our previous research has demonstrated that PRMT1 is highly expressed in immune MKs and correlates with the expression of immune response genes. Mechanistically, PRMT1 methylates RUNX1, RBM15, and DUSP4 as we reported to be key regulators for megakaryopoiesis and Mk functions. Given that immune Mks per se are very heterogeneous as shown in scRNA sequencing assays, here we report how PRMT1 determines the expansion of certain groups of immune MKs under lipopolysaccharide (LPS) challenge and in diabetes.

Methods: We generated Prmt1 conditional knockout mice (Pf4-Prmt1^fl/fl) and PRMT1 transgenic mice (Pf4-PRMT1) using the Pf4-Cre system, which specifically manipulates Prmt1 expression in Mks. Additionally, we developed a vital dye E84 (Su et al. Blood Advances 2018) to sort and culture Mks based on PRMT1 expression levels. We also used NOD mice, a spontaneous Type 1 diabetes mouse model, for Prmt1 analysis. MKs were analyzed by flow cytometry in bone marrow, peripheral blood, and spleen under steady-state and LPS-induced inflammatory conditions. MK function was assessed using colony formation assays, DQ-OVA uptake, and OT-II CD4⁺ T cell co-culture assays.

Results: PRMT1 overexpression promoted the expansion of CD48⁺CD53⁺CD41⁺CD42⁺ immune MKs in the bone marrow under steady state. After LPS stimulation, PRMT1 was essential for the expansion of CD48⁻CD53⁺ immune MKs, their mobilization to peripheral blood, and the migration of CD48⁺CD53⁺ MKs to the spleen. Pf4-PRMT1 MKs produced more colonies in standard colony formation assays, and these colonies were larger than those formed by wild-type mice, indicating that Prmt1 promotes MK's migratory capacity. Mechanistically, PRMT1 upregulates TLR4 expression and increases MHC class II intensity on immune MKs without changing the percentage of MHC-II⁺ cells. PRMT1 reduced the M6A methylation on TLR4 mRNA via RBM15 binding. PRMT1 also enhanced antigen uptake, as shown by increased DQ-OVA phagocytosis in CD48⁺CD53⁺ MKs. Functionally, PRMT1-overexpressing MKs more effectively activated OT-II CD4⁺ T cells, inducing higher IL-2 expression and promoting Th17-like polarization. These effects were absent in immune MKs from Pf4-PRMT1 ^flox/flox mice, which had normal lifespans. In addition to TLR4, MHC class 2, and CD53, immune MKs express additional surface markers that can be used to further categorize them into distinct groups, such as for migration or tissue residence. Since PRMT1 methylates DUSP4 and triggers its ubiquitylation, we also analyzed immune MKs from DUSP4^-/- mice. Essentially, immune MKs were expanded in Dusp4 knockout mice, which were highly susceptible to Leishmania infection. The PRMT1-DUSP4 axis may be crucial for self-limited immune responses, and constant activation of PRMT1 could lead to chronic inflammation, as seen in diabetes.

Conclusions: We demonstrate that CD48+CD53+CD41+CD42+ immune Mks are the key players in Mk-mediated immune responses in a PRMT1-dependent manner. They drive the development and mobilization of distinct immune MK subsets mainly through stepwise megakaryopoiesis, enhance their responsiveness to inflammatory signals, and enable their antigen-processing and presenting functions, while stress megakaryopoiesis may lack full immune functions in the CD48^- immune Mks. These data are critical for us to better understand mechanisms of inflammation and aging.