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Specific Gtpase Dynamin Isoforms Regulate Megakaryocyte Membrane Remodeling and The Formation Of Multivesicular Bodies and Microparticles

2013· article· en· W2491588201 on OpenAlexaff
Yolande Chen, Arinola Awomolo, Jorie Aardema, Michael Hession, Francisco J. González-González, Hilary Christensen, Walter H.A. Kahr, Seth J. Corey

Bibliographic record

VenueBlood · 2013
Typearticle
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsDynaminPleckstrin homology domainCell biologyBiologyGTPaseEndocytosisVesicleMembraneSignal transductionBiochemistryCell

Abstract

fetched live from OpenAlex

Abstract Cdc42 interacting protein 4 (CIP4) is a membrane-associated BAR protein, which also forms a complex via its SH3 domain with the dynamins (DNMs) and Wiskott-Aldrich Syndrome (WAS) protein. Thus, CIP4 remodels the plasma membrane and cortical actin cytoskeleton. To determine its physiological function, we generated CIP4-null mice. They displayed thrombocytopenia similar to that of WAS-null mice and have abnormal megakaryocytes (MKs) with decreased proplatelet formation and underdeveloped demarcation membrane system (DMS) (Chen et al, Blood 2013). The DMS is an extensive network of membrane tubules which serves as a membrane reservoir for proplatelet formation. The membranes are enriched for polyphosphoinositides that are docking sites for BAR proteins and for pleckstrin homology domain-containing proteins such as the dynamins. Still, the formation of the DMS is poorly understood. Dynamins are cell vesicle trafficking proteins that possess a GTPase domain. They induce neck vesicle constriction and scission from the plasma membrane. When the GTPase activity is abrogated, vesicle scission does not occur; instead, the plasma membrane invagination induced by the BAR proteins results in deep plasma membrane tubulations. Of the three dynamin isoforms, DNM3 participates in MK development including DMS formation (Reems et al, Exp Hematol 2008; Wang et al, Stem Cells Dev 2011). Moreover, a recent genome-wide association study suggested that an MK-specific DNM3 isoform might play a role in human platelet size determination (Nürnberg et al, Blood 2012). However the exact mechanism for dynamin’s participation in DMS formation is unclear. A double knockout for dynamin 1 and dynamin 3 in neurons causes accumulation of long invaginations from the plasma membrane (Ferguson and De Camilli, Nat Rev Mol Cell Biol 2012). We initially hypothesized that CIP4’s association with DNM3 contributes to the DMS development during platelet biogenesis and wanted to test for functional redundancy with other dynamins present in MKs and platelets. To determine if CIP4 interacts with dynamin in the MK lineage, we found that following either phorbol ester (PMA) or fibronectin stimulation in the human MK cell line CHRF-288, CIP4 co-precipitated with DNM3 and colocalized by confocal microscopy. To determine dynamin’s effect on membrane biophysical properties, we measured the fluorescence anisotropy, which reflects the disorder of membrane lipids due to movement and indicate membrane rigidity. Compared with controls in CHRF-288 cells, shRNA-mediated knockdown (KD) of DNM2 or DNM3 resulted in higher membrane rigidity in response to PMA. The strongest effect was seen in double KD cells with decreased fluidity by 2.6 ± 0.3%, which is similar to what was observed with CIP4 KD and is physiologically significant (Chen et al Blood 2013). KD of DNM2 resulted in aberrant morphology, greater cell diameter, and electron microscopy (EM) showed formation of new multivesicular bodies (MVBs) which are sorting compartments during α- and dense granules formation. Single DNM3 KD cells had no observable phenotype. EM imaging of DNM2 and DNM3 double KD cells revealed plasma membrane tubulation that resembles the DMS. While control CHRF-288 cells, with high DNM3 protein expression, do not have a DMS at baseline, MK cell lines Meg-01 and L8057, with respectively lower or no dynamin-3 protein expression, both have a DMS (Battinelli et al PNAS 2001; Ishida Y et al, Exp Hematol 1993). Platelet microparticles (MPs) are known to mediate a prothrombotic state in patients. Having previously found that CIP4-null mice show reduced levels of platelet MPs, we measured MPs in dynamin knockdown cell supernatant by flow cytometry and CD41/Annexin V staining. Surprisingly, we found that microparticle levels were increased 2.9-fold in DNM2 KD cells and 3.8-fold in double DNM2 and DNM3 KD cells. Our findings suggest that: 1) there is only partial functional redundancy between DNM2 and DNM3 in platelet biogenesis, 2) DNM2 controls MVB formation and MP release in MK cells, and 3) the CIP4-dynamin pathway contributes to DMS formation. It is possible that CIP4’s interaction with dynamins restrains their spatial and temporal activity to allow for long invaginations to accumulate in the DMS. Dynamin depletion might also increase surface membrane availability for MP formation. Dynamins are thus potential targets to modulate thrombotic state and platelet biogenesis. Disclosures: No relevant conflicts of interest to declare.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.009
GPT teacher head0.206
Teacher spread0.198 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2013
Admission routes1
Has abstractyes

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