Author
Listed:
- Hanae Shimo
- Satya Nanda Vel Arjunan
- Hiroaki Machiyama
- Taiko Nishino
- Makoto Suematsu
- Hideaki Fujita
- Masaru Tomita
- Koichi Takahashi
Abstract
Oxidative stress mediated clustering of membrane protein band 3 plays an essential role in the clearance of damaged and aged red blood cells (RBCs) from the circulation. While a number of previous experimental studies have observed changes in band 3 distribution after oxidative treatment, the details of how these clusters are formed and how their properties change under different conditions have remained poorly understood. To address these issues, a framework that enables the simultaneous monitoring of the temporal and spatial changes following oxidation is needed. In this study, we established a novel simulation strategy that incorporates deterministic and stochastic reactions with particle reaction-diffusion processes, to model band 3 cluster formation at single molecule resolution. By integrating a kinetic model of RBC antioxidant metabolism with a model of band 3 diffusion, we developed a model that reproduces the time-dependent changes of glutathione and clustered band 3 levels, as well as band 3 distribution during oxidative treatment, observed in prior studies. We predicted that cluster formation is largely dependent on fast reverse reaction rates, strong affinity between clustering molecules, and irreversible hemichrome binding. We further predicted that under repeated oxidative perturbations, clusters tended to progressively grow and shift towards an irreversible state. Application of our model to simulate oxidation in RBCs with cytoskeletal deficiency also suggested that oxidation leads to more enhanced clustering compared to healthy RBCs. Taken together, our model enables the prediction of band 3 spatio-temporal profiles under various situations, thus providing valuable insights to potentially aid understanding mechanisms for removing senescent and premature RBCs.Author Summary: In order to maintain a steady internal environment, our bodies must be able to specifically recognize old and damaged red blood cells (RBCs), and remove them from the circulation in a timely manner. Clusters of membrane protein band 3, which form in response to elevated oxidative damage, serve as essential molecular markers that initiate this cell removal process. However, little is known about the details of how these clusters are formed and how their properties change under different conditions. To understand these mechanisms in detail, we developed a computational model that enables the prediction of the time course profiles of metabolic intermediates, as well as the visualization of the resulting band 3 distribution during oxidative treatment. Our model predictions were in good agreement with previous published experimental data, and provided predictive insights on the key factors of cluster formation. Furthermore, simulation experiments of the effects of multiple oxidative pulses and cytoskeletal defect using the model also suggested that clustering is enhanced under such conditions. Analyses using our model can provide hypotheses and suggest experiments to aid the understanding of the physiology of anemia-associated RBC disorders, and optimization of quality control of RBCs in stored blood.
Suggested Citation
Hanae Shimo & Satya Nanda Vel Arjunan & Hiroaki Machiyama & Taiko Nishino & Makoto Suematsu & Hideaki Fujita & Masaru Tomita & Koichi Takahashi, 2015.
"Particle Simulation of Oxidation Induced Band 3 Clustering in Human Erythrocytes,"
PLOS Computational Biology, Public Library of Science, vol. 11(6), pages 1-21, June.
Handle:
RePEc:plo:pcbi00:1004210
DOI: 10.1371/journal.pcbi.1004210
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pcbi00:1004210. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ploscompbiol (email available below). General contact details of provider: https://journals.plos.org/ploscompbiol/ .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.