Activated αIIbβ3 on platelets mediates flow-dependent NETosis via SLC44A2.

Platelet-neutrophil interactions are important for innate immunity, but also contribute to the pathogenesis of deep vein thrombosis, myocardial infarction and stroke. Here we report that, under flow, von Willebrand factor/glycoprotein Ibα-dependent platelet 'priming' induces integrin αIIbβ3 activation that, in turn, mediates neutrophil and T-cell binding. Binding of platelet αIIbβ3 to SLC44A2 on neutrophils leads to mechanosensitive-dependent production of highly prothrombotic neutrophil extracellular traps. A polymorphism in SLC44A2 (rs2288904-A) present in 22% of the population causes an R154Q substitution in an extracellular loop of SLC44A2 that is protective against venous thrombosis results in severely impaired binding to both activated αIIbβ3 and VWF-primed platelets. This was confirmed using neutrophils homozygous for the SLC44A2 R154Q polymorphism. Taken together, these data reveal a previously unreported mode of platelet-neutrophil crosstalk, mechanosensitive NET production, and provide mechanistic insight into the protective effect of the SLC44A2 rs2288904-A polymorphism in venous thrombosis

The role of CD8+ T cell clones in immune thrombocytopenia

Immune thrombocytopenia (ITP) is traditionally considered an antibody-mediated disease. However, a number of features suggest alternative mechanisms of platelet destruction. In this study, we use a multi-dimensional approach to explore the role of cytotoxic CD8+ T cells in ITP. We characterised patients with ITP and compared them to age-matched controls using immunophenotyping, next-generation sequencing of T cell receptor (TCR) genes, single-cell RNA sequencing, and functional T cell and platelet assays. We found that adults with chronic ITP have increased polyfunctional, terminally differentiated effector memory CD8+ T cells (CD45RA+CD62L-) expressing intracellular interferon-g, tumour necrosis factor-a, and Granzyme B defining them as TEMRA cells. These TEMRA cells expand when the platelet count falls and show no evidence of physiological exhaustion. Deep sequencing of the T cell receptor showed expanded T cell clones in patients with ITP. T cell clones persisted over many years, were more prominent in patients with refractory disease, and expanded when the platelet count was low. Combined single-cell RNA and TCR sequencing of CD8+ T cells confirmed that the expanded clones are TEMRA cells. Using in vitro model systems, we show that CD8+ T cells from patients with ITP form aggregates with autologous platelets, release interferon-g and trigger platelet activation and apoptosis through TCR-mediated release of cytotoxic granules. These findings of clonally expanded CD8+ T cells causing platelet activation and apoptosis provide an antibody-independent mechanism of platelet destruction, indicating that targeting specific T-cell clones could be a novel therapeutic approach for patients with refractory ITP

Platelet–Neutrophil Crosstalk in Thrombosis

Platelets are essential for the formation of a haemostatic plug to prevent bleeding, while neutrophils are the guardians of our immune defences against invading pathogens. The interplay between platelets and innate immunity, and subsequent triggering of the activation of coagulation is part of the host system to prevent systemic spread of pathogen in the blood stream. Aberrant immunothrombosis and excessive inflammation can however, contribute to the thrombotic burden observed in many cardiovascular diseases. In this review, we highlight how platelets and neutrophils interact with each other and how their crosstalk is central to both arterial and venous thrombosis and in COVID-19. While targeting platelets and coagulation enables efficient antithrombotic treatments, they are often accompanied with a bleeding risk. We also discuss how novel approaches to reduce platelet-mediated recruitment of neutrophils could represent promising therapies to treat thrombosis without affecting haemostasis

miRNA-mediated knockdown of GPIbα by transfection of CHO GPIb-IX cells.

<p>Representative flow cytometry histograms from CHO GPIb-IX control cells (white) and cells transfected with (A) pCMV-mi<i>GPIBA</i>-2-eGFP (green), (B) pCMV-mi<i>GPIBA</i>-3-eGFP (red), (C) pCMV-mi<i>GPIBA</i>-2+2-eGFP (orange), or (D) pCMV-mi<i>GPIBA</i>-2+3-eGFP (purple) expressing GPIbα 48h post transfection. Negative control in which no anti-GPIbα moAb 6B4 was added is depicted in each histogram in grey. Percentages of cells expressing GPIbα are indicated next to each histogram. (F) Flow cytometry analysis representing mean fluorescence intensities of each population of CHO GPIb-IX cells expressing GPIbα ± SEM (n>3). Statistical analysis was performed using Anova followed by Dunnett’s post-test (** p<0.01).</p

Morphological changes in differentiating megakaryoblastic DAMI cells.

<p>(A-C) Representative confocal images of differentiating mock transfected DAMI cells (A), DAMI cells transfected with pCMV-eGFP (note extensive eGFP fluorescence) (B) and DAMI cells transfected with pCMV-mi<i>GPIBA</i>-2+3-eGFP (C-D). Cells were stained for GPIbα (green), the actin cytoskeleton (red) and the nucleus (blue/purple). Scale bar is 25 μm. The width (W) and length (L) of the cells along two perpendicular axes used to calculate cell aspect ratios are indicated in (C). (D) GPIbα expression in untransfected (white) or pCMV-eGFP (black) or pCMV-mi<i>GPIBA</i>-2+3-eGFP (purple) transfected DAMI cells was determined by flow cytometry. DAMI transfected cells were stimulated with PMA for 48h as indicated. Data represent mean fluorescence intensities of GPIbα expression ± SEM (n>3). (E) Quantitative analysis showing cell aspect ratios (W/L) represent mean ± SEM (n >3; 20 cells analyzed per condition). Statistical analysis was performed using the unpaired Student t test (* p<0.05; *** p<0.01).</p

Knockdown of GPIb-IX reduces ristocetin induced VWF-dependent CHO GPIb-IX cell aggregation.

<p>CHO GPIb-IX cells were incubated with ristocetin without (A) or with (B-E) VWF on a rotary shaker to induce aggregate formation. Representative overlay bright field and fluorescent (GFP) images from (A-B) mock, (C) pCMV-eGFP and (D) pCMV-mi<i>GPIBA</i>-2+3-eGFP transfected cells are shown. Quantitative analysis was performed by measuring (E) the number of aggregates and (F) the aggregate size (a.u.: arbitrary units). Data represent mean ± SEM (n = 4). Statistical analysis was performed using the unpaired Student t test (* p<0.05).</p

Knockdown of GPIbα expression following transfection of CHO GPIb-IX cells with siRNA.

<p>Representative flow cytometry histograms from mock transfected cells (white) and cells transfected with (A) si<i>GPIBA</i>-1 (blue), (B) si<i>GPIBA</i>-2 (green), (C) si<i>GPIBA</i>-3 (red), (D) si<i>GPIBA</i>-2+3 (purple) and (E) si<i>GPIBA</i>-1+2+3 (black) expressing GPIbα 48h post transfection. Negative control in which no anti-GPIbα moAb 6B4 was added is depicted in each histogram in grey. Percentages of cells expressing GPIbα are indicated next to each histogram. (F) Flow cytometry analysis representing mean fluorescence intensities of each population of CHO GPIb-IX cells expressing GPIbα ± SEM (n>3). Statistical analysis was performed using Anova followed by Dunnett’s post-test (* p<0.05; ** p<0.01).</p