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Deciphering glucocorticoid-mediated stress responses in the pancreatic beta cell using bioinformatics methods

Karagiannopoulos, Alexandros (2019) BINP52 20182
Degree Projects in Bioinformatics
Popular Abstract
Detecting gene targets of glucocorticoids in pancreatic beta cells by bioinformatics approaches

The pancreatic beta cells (β-cells) are the cells that synthesize and secrete insulin, the hormone that is responsible for controlling the blood sugar levels in the body. Studies have revealed that a certain group of drugs, called glucocorticoids (GCs), despite being widely prescribed against various pathological conditions such as autoimmune disorders, allergies and asthma, can cause temporary or long-term increase in blood sugar levels, leading to diabetes. This suggests that GCs may cause the dysfunction of β-cells, but the molecular mechanisms behind this process remain unknown.

In this project, we developed a method that makes use of... (More)
Detecting gene targets of glucocorticoids in pancreatic beta cells by bioinformatics approaches

The pancreatic beta cells (β-cells) are the cells that synthesize and secrete insulin, the hormone that is responsible for controlling the blood sugar levels in the body. Studies have revealed that a certain group of drugs, called glucocorticoids (GCs), despite being widely prescribed against various pathological conditions such as autoimmune disorders, allergies and asthma, can cause temporary or long-term increase in blood sugar levels, leading to diabetes. This suggests that GCs may cause the dysfunction of β-cells, but the molecular mechanisms behind this process remain unknown.

In this project, we developed a method that makes use of various bioinformatics tools to study the effect of GCs on β-cells.

Once GCs enter the cell, they can activate (turn on) or repress (turn off) hundreds of genes. To find out which genes are activated or repressed from GCs, we used two sets of β-cells. In one set we administered GCs and in the other we did not. Then we compared the gene profiles between the sets and detected the genes that have been activated or repressed in the first set compared to the second. These are the target genes of GCs in the pancreatic β-cells. As we wanted to discover which of these genes are more important targets of GCs, we also used publicly available data with the exact positions in the DNA that GCs can act on in many different cell types.

Combining the above-mentioned data, we managed to score the genes that are targeted by the GCs with a custom scoring system. In that way, we could distinguish the genes that are more potent targets of GCs in the pancreatic β-cells. Comparing our most potent gene targets in β-cells with other validated targets in different cell types, we observed that some of them were common, while the rest appear to be targets exclusively in the β-cells. In the future, we intend to validate some of these gene targets with experimental methods in the laboratory.

In order for the analysis to be performed in an effortless way, the whole workflow was converted into an automated process using Snakemake, a workflow management system. Moreover, with the help of a web application called Jupyter Notebook, the analysis can be carried out in an interactive way, while we can display and compare the results of the analysis at the same time.

Master’s Degree Project in Bioinformatics 60 credits 2019
Department of Biology, Lund University
Advisor: Jonathan LS Esguerra
Department of Clinical Sciences - Malmö, Lund University (Less)
Please use this url to cite or link to this publication:
author
Karagiannopoulos, Alexandros
supervisor
organization
course
BINP52 20182
year
type
H2 - Master's Degree (Two Years)
subject
language
English
id
8974072
date added to LUP
2019-04-05 14:17:33
date last changed
2019-04-05 14:17:33
@misc{8974072,
  author       = {{Karagiannopoulos, Alexandros}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Deciphering glucocorticoid-mediated stress responses in the pancreatic beta cell using bioinformatics methods}},
  year         = {{2019}},
}