Activation and Regulation of Blood Vδ2 T Cells Are Amplified by TREM-1+ during Active Pulmonary Tuberculosis.
Yongjian WuYin-Min FangLi DingXi LiuNgiambudulu M FranciscoJinsheng WenChunxin LiaoZhiming MaZi LiMiao LiSiqi MingTing LiuMei ZhangMinhao WuMuazzam JacobsSitang GongXi HuangPublished in: Journal of immunology (Baltimore, Md. : 1950) (2018)
Triggering receptor expressed on myeloid cells 1 (TREM-1) is a receptor mainly expressed on myeloid cells, and it plays an important role in modulating immune response against infectious agents. The function of TREM-1 on nonmyeloid cells such as Vδ2 T cells has not been characterized, and their role in pulmonary tuberculosis (TB) remains unclear. To assess the expression of TREM-1 on blood Vδ2 T cells from pulmonary TB patients and investigate its mechanism of induction, we exploited flow cytometry analysis to study the expression of TREM-1 on Vδ2 T cells from active pulmonary TB patients and control subjects. In this study we demonstrate that TREM-1 (TREM-1+) is highly expressed on Vδ2 T cells of patients with active pulmonary TB. Unlike TREM-1--expressing Vδ2 T cells, TREM-1+-producing Vδ2 T cells display APC-like phenotypes. Surprisingly, TREM-1+ signaling promotes the Ag-presenting capability of Vδ2 T cells to induce the CD4+ T cell response. TREM-1+Vδ2 T cells induced the proliferation and differentiation of naive CD4+ T cells, as well as the elimination of intracellular mycobacteria. We identified TREM-1+ (but not TREM-1-) as an Ag-presentation amplifier on human blood Vδ2 T cells, and data shed new light on the regulation of Vδ2 T cells in the phase of innate and adaptive immune responses against Mycobacterium tuberculosis infection. Targeting TREM-1+Vδ2 T cells may be a promising approach for TB therapy.
Keyphrases
- mycobacterium tuberculosis
- pulmonary tuberculosis
- immune response
- induced apoptosis
- end stage renal disease
- newly diagnosed
- dendritic cells
- pulmonary hypertension
- chronic kidney disease
- poor prognosis
- bone marrow
- stem cells
- cell cycle arrest
- machine learning
- oxidative stress
- mesenchymal stem cells
- drug delivery
- quantum dots
- diabetic rats
- binding protein
- artificial intelligence
- cell therapy
- cancer therapy
- big data