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      Piezo1 activation augments sickling propensity and the adhesive properties of sickle red blood cells in a calcium‐dependent manner

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          Summary

          Haemoglobin S polymerization in the red blood cells (RBCs) of individuals with sickle cell anaemia (SCA) can cause RBC sickling and cellular alterations. Piezo1 is a mechanosensitive protein that modulates intracellular calcium (Ca 2+) influx, and its activation has been associated with increased RBC surface membrane phosphatidylserine (PS) exposure. Hypothesizing that Piezo1 activation, and ensuing Gárdos channel activity, alter sickle RBC properties, RBCs from patients with SCA were incubated with the Piezo1 agonist, Yoda1 (0.1–10 μM). Oxygen‐gradient ektacytometry and membrane potential measurement showed that Piezo1 activation significantly decreased sickle RBC deformability, augmented sickling propensity, and triggered pronounced membrane hyperpolarization, in association with Gárdos channel activation and Ca 2+ influx. Yoda1 induced Ca 2+‐dependent adhesion of sickle RBCs to laminin, in microfluidic assays, mediated by increased BCAM binding affinity. Furthermore, RBCs from SCA patients that were homo−/heterozygous for the rs59446030 gain‐of‐function Piezo1 variant demonstrated enhanced sickling under deoxygenation and increased PS exposure. Thus, Piezo1 stimulation decreases sickle RBC deformability, and increases the propensities of these cells to sickle upon deoxygenation and adhere to laminin. Results support a role of Piezo1 in some of the RBC properties that contribute to SCA vaso‐occlusion, indicating that Piezo1 may represent a potential therapeutic target molecule for this disease.

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          Trimmomatic: a flexible trimmer for Illumina sequence data

          Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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            The Sequence Alignment/Map format and SAMtools

            Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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              A framework for variation discovery and genotyping using next-generation DNA sequencing data

              Recent advances in sequencing technology make it possible to comprehensively catalogue genetic variation in population samples, creating a foundation for understanding human disease, ancestry and evolution. The amounts of raw data produced are prodigious and many computational steps are required to translate this output into high-quality variant calls. We present a unified analytic framework to discover and genotype variation among multiple samples simultaneously that achieves sensitive and specific results across five sequencing technologies and three distinct, canonical experimental designs. Our process includes (1) initial read mapping; (2) local realignment around indels; (3) base quality score recalibration; (4) SNP discovery and genotyping to find all potential variants; and (5) machine learning to separate true segregating variation from machine artifacts common to next-generation sequencing technologies. We discuss the application of these tools, instantiated in the Genome Analysis Toolkit (GATK), to deep whole-genome, whole-exome capture, and multi-sample low-pass (~4×) 1000 Genomes Project datasets.
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                Author and article information

                Contributors
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                Journal
                British Journal of Haematology
                Br J Haematol
                Wiley
                0007-1048
                1365-2141
                August 2023
                April 03 2023
                August 2023
                : 202
                : 3
                : 657-668
                Affiliations
                [1 ] Laboratory LIBM EA7424, Vascular Biology and Red Blood Cell Team University of Lyon Lyon France
                [2 ] Hematology and Transfusion Center University of Campinas Campinas Brazil
                [3 ] Sorbonne Université, CNRS, UMR 8227 LBI2M, Station Biologique de Roscoff SBR Roscoff France
                [4 ] Service de Biochimie et Biologie Moléculaire, Laboratoire de Biologie Médicale Multi‐site Hospices Civils de Lyon Lyon France
                [5 ] Erytech Pharma Lyon France
                [6 ] Institut d'Hématologique et d'Oncologique Pédiatrique, Hospices Civils de Lyon Lyon France
                [7 ] Service de Médecine Interne, Hôpital Edouard Herriot, Hospices Civils de Lyon Lyon France
                Article
                10.1111/bjh.18799
                37011913
                eed3cfb8-a874-4dc1-ae79-500e9c43e3d5
                © 2023

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