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Nanoscale detection of insulin granule sub-structures using dSTORM imaging

Hong, Yu LU (2020) FYSM60 20191
Atomic Physics
Department of Physics
Abstract
Diabetes mellitus is a global disease, mainly caused by insufficient insulin secre-
tion from pancreatic islet β-cells. Insulin is stored in the granules of islet β-cells and released in response to extracellular stimuli e.g. glucose. The state of insulin structure and maturation determines the quality of the released insulin, However, the insulin state in the granules is rarely investigated due to lack of proper methods.
Here, we hypothesize that high-resolution microscopy and appropriate image
analysis methods could be used to detect the insulin state in the granule. We used
direct stochastic optical reconstruction microscopy (dSTORM), which is a super-
resolution imaging method, to capture cellular insulin granules images and... (More)
Diabetes mellitus is a global disease, mainly caused by insufficient insulin secre-
tion from pancreatic islet β-cells. Insulin is stored in the granules of islet β-cells and released in response to extracellular stimuli e.g. glucose. The state of insulin structure and maturation determines the quality of the released insulin, However, the insulin state in the granules is rarely investigated due to lack of proper methods.
Here, we hypothesize that high-resolution microscopy and appropriate image
analysis methods could be used to detect the insulin state in the granule. We used
direct stochastic optical reconstruction microscopy (dSTORM), which is a super-
resolution imaging method, to capture cellular insulin granules images and obtain
the location of insulin molecules labelled by an insulin single-domain fluorescent antibody. The images were processed by the optimized algorithm of layering and filtering until the clusters of fluorescent dots in the images were distinguished. Then the hypothetical structures were used to scan the images to find the complete hexamer. In summary, this study provides novel method to study mature insulin crystals in the granular of islet β-cells. (Less)
Popular Abstract
Diabetes is a household disease. People with diabetes are like children who eat too much sugar and cause tooth decay in their mouths who cannot live a happy life. Unfortunately, there are so many such "children" on our earth. The World Health Organization estimates that approximately 422 million people worldwide have diabetes. Because diabetes is a metabolic disease that is prone to cardiovascular diseases, strokes and other diseases, more than 3.7 million people die directly or indirectly from diabetes each year causing serious economic losses. Insulin injection is an important method for treating diabetes. Therefore, the study of the pathogenesis of diabetes is a serious and urgent issue.

One of the causes of diabetes is that the... (More)
Diabetes is a household disease. People with diabetes are like children who eat too much sugar and cause tooth decay in their mouths who cannot live a happy life. Unfortunately, there are so many such "children" on our earth. The World Health Organization estimates that approximately 422 million people worldwide have diabetes. Because diabetes is a metabolic disease that is prone to cardiovascular diseases, strokes and other diseases, more than 3.7 million people die directly or indirectly from diabetes each year causing serious economic losses. Insulin injection is an important method for treating diabetes. Therefore, the study of the pathogenesis of diabetes is a serious and urgent issue.

One of the causes of diabetes is that the pancreas cannot produce enough insulin. Islet cells are an important part of the pancreas and have the biological function of secreting insulin. Therefore, studying the production, secretion, and distribution of insulin in islet cells is of great significance for understanding the pathogenesis of diabetes and promoting the treatment of diabetes.

In order to study islet cells, we need a super magnifying lens to observe it. Fortunately, we have "one"--Direct Stochastic Optical Reconstruction Microscopy (dSTORM). It is a super-resolution microscope as the world's highest resolution cell imaging microscope technology. By using it, we obtain nano-scale images so that the study of subcellular structure can be realized. By performing two-dimensional or three-dimensional imaging of cells, much useful information can be obtained, which will help clinicians understand the pathogenesis of diabetes. This paper will introduce this interesting research such as how to obtain samples, figures, and analysis. It's as smooth as a story. (Less)
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author
Hong, Yu LU
supervisor
organization
course
FYSM60 20191
year
type
H2 - Master's Degree (Two Years)
subject
keywords
islet β-cells, dSTORM imaging, Alexa Fluor 647
language
English
id
9006335
date added to LUP
2020-03-19 11:37:35
date last changed
2020-03-19 11:38:27
@misc{9006335,
  abstract     = {Diabetes mellitus is a global disease, mainly caused by insufficient insulin secre-
tion from pancreatic islet β-cells. Insulin is stored in the granules of islet β-cells and released in response to extracellular stimuli e.g. glucose. The state of insulin structure and maturation determines the quality of the released insulin, However, the insulin state in the granules is rarely investigated due to lack of proper methods.
Here, we hypothesize that high-resolution microscopy and appropriate image
analysis methods could be used to detect the insulin state in the granule. We used
direct stochastic optical reconstruction microscopy (dSTORM), which is a super-
resolution imaging method, to capture cellular insulin granules images and obtain
the location of insulin molecules labelled by an insulin single-domain fluorescent antibody. The images were processed by the optimized algorithm of layering and filtering until the clusters of fluorescent dots in the images were distinguished. Then the hypothetical structures were used to scan the images to find the complete hexamer. In summary, this study provides novel method to study mature insulin crystals in the granular of islet β-cells.},
  author       = {Hong, Yu},
  keyword      = {islet β-cells,dSTORM imaging,Alexa Fluor 647},
  language     = {eng},
  note         = {Student Paper},
  title        = {Nanoscale detection of insulin granule sub-structures using dSTORM imaging},
  year         = {2020},
}