Atomic force microscopy study of red blood cell membrane nanostructure during oxidation-reduction processes.
Elena KozlovaA ChernyshV SergunovaO GudkovaE ManchenkoA KozlovPublished in: Journal of molecular recognition : JMR (2018)
The morphology and functional state of red blood cells (RBCs) mainly depends on the configuration of the spectrin network, which can be broken under the influence of intoxication because of oxidation processes in the cells. Measurement of these processes is a complex problem. The most suitable and prospective method that resolves this problem is atomic force microscopy (AFM). We used AFM to study the changes in the spectrin matrix and RBC morphology during oxidation processes caused by ultraviolet (UV) irradiation in RBC suspension. The number of discocytes decreased from 98% (in control) to 12%. We obtained AFM images of the spectrin matrix in RBC ghosts. Atomic force microscopy allows for the direct observation and quantitative measurement of the disturbances in the structure of the spectrin matrix during oxidation processes in RBCs. The typical section size of the spectrin network changed from approximately 80 to 200 nm (in control) to 600 nm and even to 1000 nm after UV irradiation. An AFM study showed that incubation of RBCs with Cytoflavin® after UV irradiation preserved the forms of RBCs almost at control levels; 89% of the cells remained as discocytes. To quantify the intensity of the oxidation-reduction processes, the percentage of haemoglobin derivatives was measured. The content of methaemoglobin varied in the range of 1% to 70% during the experiments. These evidence-based studies are important for the fundamental research of interactions during redox processes in RBCs at the molecular level.
Keyphrases
- atomic force microscopy
- red blood cell
- high speed
- single molecule
- hydrogen peroxide
- induced apoptosis
- photodynamic therapy
- high resolution
- nitric oxide
- radiation therapy
- cell cycle arrest
- machine learning
- electron transfer
- radiation induced
- oxidative stress
- endoplasmic reticulum stress
- signaling pathway
- convolutional neural network