OC 49.1 - Procoagulant platelets have a distinct transcriptome that identifies the large GTPase dynamin as a driver in their formation

Monday, July 11, 2022

2:45 PM – 3:00 PM

Location: ExCel Center, ICC Capital Suite Room 1

Presentation Format: In-Person

Presenting Author(s)

Ibrahim Tohidi-Esfahani, BMed FRACP FRCPA

Clinical research Fellow
Department of Haematology, University College London Hospitals NHS Foundation Trust, London, UK
London, England, United Kingdom

Co-Author(s)

SW

Shane Whittaker

Research Assistant
ANZAC Research Institute, University of Sydney
Sydney, New South Wales, Australia
Christine S M Lee, PhD

Postdoctoral Research Fellow
ANZAC Research Institute, University of Sydney
Sydney, New South Wales, Australia
HC

Heather Campbell

Research assistant
ANZAC Research Institute, University of Sydney
Sydney, New South Wales, Australia
KL

Kaitao Lai

Bioinformatics Research Fellow
University of Sydney
Sydney, New South Wales, Australia
HL

Hai Po Helena Liang

Senior Postdoctoral Research Fellow
ANZAC Research Institute, University of Sydney
Sydney, New South Wales, Australia
MK

Maaike Kockx

Senior Research Fellow
ANZAC Research Institute, University of Sydney
Sydney, New South Wales, Australia
ML

Mark Larance

Group Leader
Larance Laboratory, Charles Perkins Centre, University of Sydney
Sydney, New South Wales, Australia
VC

Vivien M. Chen, Phd FRACP FRCPA

Group Leader, Staff Specialist Haematologist
ANZAC Research Institute, University of Sydney
Sydney, New South Wales, Australia

Background: The procoagulant platelet subpopulation is involved more in pathological thrombosis than haemostasis.

Aims: This study aimed to identify unique pathways through transcriptomics that predispose platelets to become procoagulant after activation, to facilitate targeting this subpopulation.

Methods: Washed platelets from healthy donors (n=6) were sorted into procoagulant (GSAO+/P-selectin+) and activated non-procoagulant (GSAO-/P-selectin+) subpopulations (Hua, Blood 2015), after thrombin 2U/mL plus collagen-related peptide 4µg/mL stimulation, using flow cytometry cell sorting. RNA was extracted, sequenced (single-end, 75 base-pair reads), with differentially expressed (DE, fold-change >/=2, false discovery rate/FDR < 0.05) genes identified using DESeq2 and edgeR tools. DE genes were input into Ingenuity Pathway Analysis (IPA). Functional validation was undertaken for candidate gene, Dynamin 1. Procoagulant platelet proportions were assessed by flow cytometry and confocal microscopy with inhibitors MiTMAB and dynasore.

Results: DESeq2 analysis yielded 1024 DE genes with a higher proportion upregulated in procoagulant platelets. Subpopulations segregated after unsupervised hierarchical clustering (Figure 1A-B). qPCR of a subset of genes (n=30) from different donors (n=10) confirmed differential expression within subpopulations. IPA identified integrin signalling, endocytosis and actin cytoskeleton-related pathways as highly enriched in procoagulant platelets (Figure 1C). Dynamin 1, involved in both endocytosis and actin rearrangement, was 4.9-fold increased (FDR < 0.05, both DE tools), confirmed by qPCR (3.4-fold increased, p< 0.01, Figure 1D). Dynamin inhibition by MiTMAB led to a dose-dependent, selective reduction in agonist-induced procoagulant platelet formation by flow cytometry (Figure 1E), and platelet “balloon” morphology by confocal microscopy (vehicle 21.6±0.7%, MiTMAB 1.7±0.3%, p=0.0003), while >99% of platelets remained activated (P-selectin+). Alternative dynamin inhibitor, dynasore, confirmed dose-dependent reduction in procoagulant platelet formation (n=6, p< 0.0001). Together, these suggest functional validation of transcriptomic differences.

Conclusion(s): The procoagulant subpopulation is transcriptionally distinct compared to activated non-procoagulant platelets. Functional validation of RNA-sequencing results by dynamin inhibition strongly suggests transcriptional differences are involved in determination of functionally distinct platelet subpopulations.