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Background: Myeloid derived suppressor cells (MDSCs) have been reported to keep elevating during sepsis. The current study was performed to investigate the immunosuppressive effect of MDSCs and their subsets with the underlying mechanisms. Methods: The immunosuppressive status was manifested by the apoptosis of splenocytes, quantity of T cells and PD-1 expression. The dynamics of quantity and PD-L1 level of MDSCs and the subsets were determined over time. The subset of MDSCs with high PD-L1 level was co-cultured with T cells to observe the suppressive effect. Results: Abdominal abscess was observed after 7 days post-sepsis. Five biomarkers related to organ functions were all significantly higher in the CLP group. The survival rate was consistent with the middle grade severity of sepsis model. Apoptosis of splenocytes increased over time during sepsis; CD4 + T cell decreased from day 1 post-sepsis; CD8+ T cells significantly reduced at day 7. The PD-1 expression in spleen was upregulated from an early stage of sepsis, and negatively related with the quantity of T cells. MDSCs were low at day 1 post-sepsis, but increased to a high level later; the dynamics of PMN-MDSC was similar to MDSCs. PD-L1 on MDSCs was highest at day 1 post-sepsis; PMN-MDSC was the main subset expressing PD-L1. The PMN-MDSC with high PD-L1 expression level extracted on day 1 after surgery from CLP mice significantly inhibited the proliferation of T cells. Conclusions: Sepsis-induced immunosuppression is initiated from a very early stage, a high expression level of PD-L1 on MDSCs and the main subset, PMN-MDSC might play a critical role suppressive role on T cells through PD-L1/PD-1 axis.
Pubmed ID: 32719675
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THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role.
View all literature mentionsAn Organization portal, Antibody supplier, Service resource,
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View all literature mentionsMus musculus with name C57BL/6J from IMSR.
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