Plasmacytoid Dendritic Cells Surveil Megakaryocyte Sialic Acid to Regulate Thrombopoiesis
Bibliographic record
Abstract
The Thomsen-Friedenreich antigen (TF-antigen) occurs during exposure of the underlying Core-1 disaccharide (Gal-beta(1,3)GalNAc) through the loss of its capping sialic acid (Sia). Exposure of the cryptic TF-antigen occurs during inflammation, during acute infections with influenza viruses or bacteria, in malignancies, and is associated with thrombocytopenia. Exposure of the TF-antigen on circulating blood cells, including platelets and red blood cells (RBC), can lead to severe thrombocytopenia or hemolysis in hemolytic uremic syndrome and other immune diseases. Recent data suggest that altered Sia may cause platelet destruction because treatment with the sialidase inhibitor Tamiflu increases platelet count in healthy and thrombocytopenic patients. In humans, genetic mutations involving Sia synthesis and transport, and atypical cell surface sialylation, unrelated to any genetic mutation, are associated with reduced platelet count, supporting the role of Sia in regulating platelet count. Immune cells, including classical dendritic cells (cDCs), plasmacytoid dendritic cells (pDCs), and subsets of T cells (CD8+, CD4+, and Treg cells) can also affect immune thrombocytopenia pathogenesis. Like many other immune cells, cDCs, and pDCs express Siglecs (sialic-acid-binding immunoglobulin-like lectins), which often contain immunoreceptor tyrosine-based inhibitory motifs (ITIMs) that act as immunosuppressors. Whether BM immune cells monitor MKs via glycan-lectin receptors, including Siglecs and Sia interactions, to control platelet production is unclear. To investigate the role of the TF-antigen in thrombopoiesis, we generated St3gal1MK-KO mice (Pf4-Cre) that display increased TF-antigen specifically in megakaryocytes (MK) and platelets. St3gal1MK-KO mice developed significant thrombocytopenia, but had normal platelet half-life, suggesting that the TF-antigen affected BM thrombopoiesis. In vitro MK maturation and proplatelet production from primary ST3Gal1MK-KO mouse BM cells were also normal, pointing to extrinsic factors in the BM environment affecting thrombopoiesis. Platelet counts of St3gal1MK-KO mice were restored to wild-type levels by 1) crossing St3gal1MK-KO mice with Jak3KO mice that have impaired of lymphoid cell development, 2) by treatment with anti-inflammatory dexamethasone, and 3) treatment with a depleting anti-CD4 antibody. Immunofluorescence staining of the St3gal1MK-KO BM revealed proplatelet structures positive for GPIba+ and the TF-antigen, being infiltrated by mononuclear cells resembling lymphocytes. We speculated that immune cells surveil megakaryocytes to control thrombopoiesis. Bulk RNAseq of CD4+ cells in St3gal1MK-KO BM confirmed a population bias for Type I interferon (IFN-I)-releasing pDCs, a cell type regulated by unique sialic acid binding lectins (Siglecs). Inhibition of IFN-I activity, by a blocking receptor antibody improved platelet counts in St3gal1MK-KO mice. Co-cultures of pDCs with MKs show inhibited pro-platelet formation when TF-antigen is present on MKs with elevated IFN-I levels. Gene set enrichment analysis of BM pDCs single cell RNASeq (scRNAseq) data further confirmed that TF-antigen exposure by MKs up-regulates IFN-I transcripts. scRNAseq also reveals a new population of immune cells with pDC transcript signature and concomitant upregulation of immunoglobulin re-arrangement gene transcripts Igkc and Ighm. In conclusion, the data shows that recognition of aberrant MK sialylation by pDCs regulates thrombopoiesis through IFN-I secretion. Disclosures No relevant conflicts of interest to declare.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".