Robust adaptive immune response against Babesia microti infection marked by low parasitemia in a murine model of sickle cell disease
The intraerythrocytic parasite Babesia microti is the number 1 cause of transfusion-transmitted infection and can induce serious, often life-threatening complications in immunocompromised individuals including transfusion-dependent patients with sickle cell disease (SCD). Despite the existence of strong long-lasting immunological protection against a second infection in mouse models, little is known about the cell types or the kinetics of protective adaptive immunity mounted following Babesia infection, especially in infection-prone SCD that are thought to have an impaired immune system. Here, we show, using a mouse B microti infection model, that infected wild-type (WT) mice mount a very strong adaptive immune response, characterized by (1) coordinated induction of a robust germinal center (GC) reaction; (2) development of follicular helper T (TFH) cells that comprise ∼30% of splenic CD4+ T cells at peak expansion by 10 days postinfection; and (3) high levels of effector T-cell cytokines, including interleukin 21 and interferon γ, with an increase in the secretion of antigen (Ag)-specific antibodies (Abs). Strikingly, the Townes SCD mouse model had significantly lower levels of parasitemia. Despite a highly disorganized splenic architecture before infection, these mice elicited a surprisingly robust adaptive immune response (including comparable levels of GC B cells, TFH cells, and effector cytokines as control and sickle trait mice), but higher immunoglobulin G responses against 2 Babesia-specific proteins, which may contain potential immunogenic epitopes. Together, these studies establish the robust emergence of adaptive immunity to Babesia even in immunologically compromised SCD mice. Identification of potentially immunogenic epitopes has implications to identify long-term carriers, and aid Ag-specific vaccine development.
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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