Title: Piezo1 as a force-through-membrane sensor in red blood cells
Piezo1 is the stretch activated Ca2+channel in red blood cells that mediates homeostatic volume control. Here, we study the organization of Piezo1 in red blood cells using a combination of super-resolution microscopy techniques and electron microscopy. Piezo1 adopts a non-uniform distribution on the red blood cell surface, with a bias toward the biconcave ‘dimple’. Trajectories of diffusing Piezo1 molecules, which exhibit confined Brownian diffusion on short timescales and hopping on long timescales, also reflect a bias toward the dimple. This bias can be explained by ‘curvature coupling’ between the intrinsic curvature of the Piezo dome and the curvature of the red blood cell membrane. Piezo1 does not form clusters with itself, nor does it colocalize with F-actin, Spectrin, or the Gardos channel. Thus, Piezo1 exhibits the properties of a force-through-membrane sensor of curvature and lateral tension in the red blood cell. more »« less
Chen, Jinghao; Holt, Jesse R.; Evans, Elizabeth L.; Lowengrub, John S.; Pathak, Medha M.
(, PLOS Computational Biology)
Haugh, Jason M.
(Ed.)
The collective migration of keratinocytes during wound healing requires both the generation and transmission of mechanical forces for individual cellular locomotion and the coordination of movement across cells. Leader cells along the wound edge transmit mechanical and biochemical cues to ensuing follower cells, ensuring their coordinated direction of migration across multiple cells. Despite the observed importance of mechanical cues in leader cell formation and in controlling coordinated directionality of cell migration, the underlying biophysical mechanisms remain elusive. The mechanically-activated ion channel PIEZO1 was recently identified to play an inhibitory role during the reepithelialization of wounds. Here, through an integrative experimental and mathematical modeling approach, we elucidate PIEZO1’s contributions to collective migration. Time-lapse microscopy reveals that PIEZO1 activity inhibits leader cell formation at the wound edge. To probe the relationship between PIEZO1 activity, leader cell formation and inhibition of reepithelialization, we developed an integrative 2D continuum model of wound closure that links observations at the single cell and collective cell migration scales. Through numerical simulations and subsequent experimental validation, we found that coordinated directionality plays a key role during wound closure and is inhibited by upregulated PIEZO1 activity. We propose that PIEZO1-mediated retraction suppresses leader cell formation which inhibits coordinated directionality between cells during collective migration.
Jetta, Deekshitha; Bahrani Fard, Mohammad Reza; Sachs, Frederick; Munechika, Katie; Hua, Susan Z.
(, Scientific Reports)
null
(Ed.)
Abstract Adherent cells utilize local environmental cues to make decisions on their growth and movement. We have previously shown that HEK293 cells grown on the fibronectin stripe patterns were elongated. Here we show that Piezo1 function is involved in cell spreading. Piezo1 expressing HEK cells plated on fibronectin stripes elongated, while a knockout of Piezo1 eliminated elongation. Inhibiting Piezo1 conductance using GsMTx4 or Gd 3+ blocked cell spreading, but the cells grew thin tail-like extensions along the patterns. Images of GFP-tagged Piezo1 showed plaques of Piezo1 moving to the extrusion edges, co-localized with focal adhesions. Surprisingly, in non-spreading cells Piezo1 was located primarily on the nuclear envelope. Inhibiting the Rho-ROCK pathway also reversibly inhibited cell extension indicating that myosin contractility is involved. The growth of thin extrusion tails did not occur in Piezo1 knockout cells suggesting that Piezo1 may have functions besides acting as a cation channel.
Introduction: Vaso-occlusive crises (VOCs) are a leading cause of morbidity and early mortality in individuals with sickle cell disease (SCD). These crises are triggered by sickle red blood cell (sRBC) aggregation in blood vessels and are influenced by factors such as enhanced sRBC and white blood cell (WBC) adhesion to inflamed endothelium. Advances in microfluidic biomarker assays (i.e., SCD Biochip systems) have led to clinical studies of blood cell adhesion onto endothelial proteins, including, fibronectin, laminin, P-selectin, ICAM-1, functionalized in microchannels. These microfluidic assays allow mimicking the physiological aspects of human microvasculature and help characterize biomechanical properties of adhered sRBCs under flow. However, analysis of the microfluidic biomarker assay data has so far relied on manual cell counting and exhaustive visual morphological characterization of cells by trained personnel. Integrating deep learning algorithms with microscopic imaging of adhesion protein functionalized microfluidic channels can accelerate and standardize accurate classification of blood cells in microfluidic biomarker assays. Here we present a deep learning approach into a general-purpose analytical tool covering a wide range of conditions: channels functionalized with different proteins (laminin or P-selectin), with varying degrees of adhesion by both sRBCs and WBCs, and in both normoxic and hypoxic environments. Methods: Our neural networks were trained on a repository of manually labeled SCD Biochip microfluidic biomarker assay whole channel images. Each channel contained adhered cells pertaining to clinical whole blood under constant shear stress of 0.1 Pa, mimicking physiological levels in post-capillary venules. The machine learning (ML) framework consists of two phases: Phase I segments pixels belonging to blood cells adhered to the microfluidic channel surface, while Phase II associates pixel clusters with specific cell types (sRBCs or WBCs). Phase I is implemented through an ensemble of seven generative fully convolutional neural networks, and Phase II is an ensemble of five neural networks based on a Resnet50 backbone. Each pixel cluster is given a probability of belonging to one of three classes: adhered sRBC, adhered WBC, or non-adhered / other. Results and Discussion: We applied our trained ML framework to 107 novel whole channel images not used during training and compared the results against counts from human experts. As seen in Fig. 1A, there was excellent agreement in counts across all protein and cell types investigated: sRBCs adhered to laminin, sRBCs adhered to P-selectin, and WBCs adhered to P-selectin. Not only was the approach able to handle surfaces functionalized with different proteins, but it also performed well for high cell density images (up to 5000 cells per image) in both normoxic and hypoxic conditions (Fig. 1B). The average uncertainty for the ML counts, obtained from accuracy metrics on the test dataset, was 3%. This uncertainty is a significant improvement on the 20% average uncertainty of the human counts, estimated from the variance in repeated manual analyses of the images. Moreover, manual classification of each image may take up to 2 hours, versus about 6 minutes per image for the ML analysis. Thus, ML provides greater consistency in the classification at a fraction of the processing time. To assess which features the network used to distinguish adhered cells, we generated class activation maps (Fig. 1C-E). These heat maps indicate the regions of focus for the algorithm in making each classification decision. Intriguingly, the highlighted features were similar to those used by human experts: the dimple in partially sickled RBCs, the sharp endpoints for highly sickled RBCs, and the uniform curvature of the WBCs. Overall the robust performance of the ML approach in our study sets the stage for generalizing it to other endothelial proteins and experimental conditions, a first step toward a universal microfluidic ML framework targeting blood disorders. Such a framework would not only be able to integrate advanced biophysical characterization into fast, point-of-care diagnostic devices, but also provide a standardized and reliable way of monitoring patients undergoing targeted therapies and curative interventions, including, stem cell and gene-based therapies for SCD. Disclosures Gurkan: Dx Now Inc.: Patents & Royalties; Xatek Inc.: Patents & Royalties; BioChip Labs: Patents & Royalties; Hemex Health, Inc.: Consultancy, Current Employment, Patents & Royalties, Research Funding.
Willy, Nathan_M; Colombo, Federico; Huber, Scott; Smith, Anna_C; Norton, Erienne_G; Kural, Comert; Cocucci, Emanuele
(, Proceedings of the National Academy of Sciences)
Significance Clathrin-coated vesicles (CCVs) are endocytic carriers responsible for the internalization of receptor-bound ligands and extracellular fluids. CCV assembly occurs by the sequential recruitment of clathrin, adaptors, and other accessory molecules that promote curvature formation. To form, CCVs need to overcome the local plasma membrane tension that varies during cell cycle, development, and cell polarization. Using quantitative fluorescence microscopy, we demonstrate that the adaptor CALM is a major determinant of CCV formation upon membrane tension increase. Since CALM is differentially expressed, our results demonstrate that competence in clathrin-mediated endocytosis is tissue specific, providing mechanistic explanation why CALM depletion strongly affects embryo development and red blood cell differentiation with minor effects in other systems.
Ojaghi, Ashkan; Carrazana, Gabriel; Caruso, Christina; Abbas, Asad; Myers, David_R; Lam, Wilbur_A; Robles, Francisco_E
(, Proceedings of the National Academy of Sciences)
Hematological analysis, via a complete blood count (CBC) and microscopy, is critical for screening, diagnosing, and monitoring blood conditions and diseases but requires complex equipment, multiple chemical reagents, laborious system calibration and procedures, and highly trained personnel for operation. Here we introduce a hematological assay based on label-free molecular imaging with deep-ultraviolet microscopy that can provide fast quantitative information of key hematological parameters to facilitate and improve hematological analysis. We demonstrate that this label-free approach yields 1) a quantitative five-part white blood cell differential, 2) quantitative red blood cell and hemoglobin characterization, 3) clear identification of platelets, and 4) detailed subcellular morphology. Analysis of tens of thousands of live cells is achieved in minutes without any sample preparation. Finally, we introduce a pseudocolorization scheme that accurately recapitulates the appearance of cells under conventional staining protocols for microscopic analysis of blood smears and bone marrow aspirates. Diagnostic efficacy is evaluated by a panel of hematologists performing a blind analysis of blood smears from healthy donors and thrombocytopenic and sickle cell disease patients. This work has significant implications toward simplifying and improving CBC and blood smear analysis, which is currently performed manually via bright-field microscopy, and toward the development of a low-cost, easy-to-use, and fast hematological analyzer as a point-of-care device and for low-resource settings.
Vaisey, George, Banerjee, Priyam, North, Alison J, Haselwandter, Christoph A, and MacKinnon, Roderick. Piezo1 as a force-through-membrane sensor in red blood cells. Retrieved from https://par.nsf.gov/biblio/10477615. eLife 11. Web. doi:10.7554/eLife.82621.
Vaisey, George, Banerjee, Priyam, North, Alison J, Haselwandter, Christoph A, & MacKinnon, Roderick. Piezo1 as a force-through-membrane sensor in red blood cells. eLife, 11 (). Retrieved from https://par.nsf.gov/biblio/10477615. https://doi.org/10.7554/eLife.82621
Vaisey, George, Banerjee, Priyam, North, Alison J, Haselwandter, Christoph A, and MacKinnon, Roderick.
"Piezo1 as a force-through-membrane sensor in red blood cells". eLife 11 (). Country unknown/Code not available: eLife. https://doi.org/10.7554/eLife.82621.https://par.nsf.gov/biblio/10477615.
@article{osti_10477615,
place = {Country unknown/Code not available},
title = {Piezo1 as a force-through-membrane sensor in red blood cells},
url = {https://par.nsf.gov/biblio/10477615},
DOI = {10.7554/eLife.82621},
abstractNote = {Piezo1 is the stretch activated Ca2+channel in red blood cells that mediates homeostatic volume control. Here, we study the organization of Piezo1 in red blood cells using a combination of super-resolution microscopy techniques and electron microscopy. Piezo1 adopts a non-uniform distribution on the red blood cell surface, with a bias toward the biconcave ‘dimple’. Trajectories of diffusing Piezo1 molecules, which exhibit confined Brownian diffusion on short timescales and hopping on long timescales, also reflect a bias toward the dimple. This bias can be explained by ‘curvature coupling’ between the intrinsic curvature of the Piezo dome and the curvature of the red blood cell membrane. Piezo1 does not form clusters with itself, nor does it colocalize with F-actin, Spectrin, or the Gardos channel. Thus, Piezo1 exhibits the properties of a force-through-membrane sensor of curvature and lateral tension in the red blood cell.},
journal = {eLife},
volume = {11},
publisher = {eLife},
author = {Vaisey, George and Banerjee, Priyam and North, Alison J and Haselwandter, Christoph A and MacKinnon, Roderick},
}
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