Difference between revisions of "Team:BioIQS-Barcelona"
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| − | <p class="text-b">To develop <b>non-dimensional mathematical and stochastic models</b> to understand and predict the <a href="https://2018.igem.org/Team:BioIQS-Barcelona/Model | + | <p class="text-b">To develop <b>non-dimensional mathematical and stochastic models</b> to understand and predict the <a href="https://2018.igem.org/Team:BioIQS-Barcelona/Model" style="color: #032a5e; text-decoration: underline">sensor dynamics.</a></p> |
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| − | <p class="text-b">To <a href="https://2018.igem.org/Team:BioIQS-Barcelona/ | + | <p class="text-b">To <a href="https://2018.igem.org/Team:BioIQS-Barcelona/Human_Practices" style="color: #032a5e; text-decoration: underline">provide information</a> to the public to <b>clear up common misunderstandings related to celiac disease.</b></p> |
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Latest revision as of 15:08, 10 December 2018
We are the BioIQS iGEM team!
Explore our project!Welcome to our page
A brief resume:
Our project is based on the design of a personalized gluten sensor by using the common tools of synthetic biology. There are already several sensors that are able to detect gluten in the food. However, there are milestones that still have not been overcome. We propose a robust model in which the HLA-DQ protein of a patient is expressed and used as a sensor to detect specific reactive gluten epitopes.
Celiac disease (CD) is an autoimmune disorder that is closely related with HLA (Human Leukocyte Antigen), a type of cell-surface proteins that are responsible for the regulation of the inmune systems in humans.
These molecules are responsible for the correct discrimination between what is self and foreign proteins, guaranteeing the correct immune response against foreign agents that can cause infections.
Within the HLA protein family there is a subset called HLA-DQ. There are several DQ isoforms that can bind to different gluten-derived epitopes and present them to T-cells. More specifically, 25% of the general population carry the HLA-DQ haplotype that recognizes gluten-derived epitopes, but only 1% of the population suffer from celiac disease.
As a consequence of T-cell activation, an inmune response is triggered, causing damage to the enterocytes present in the small intestine.
Understanding why the inflammatory response is triggered by a certain type of T cells upon epitope presentation by HLA-DQ molecules is essential to uncover the mechanism of CD. Since the first step for the immune response activation is the recognition and binding of the gluten epitope to the HLA-DQ receptor, we developed a sensor based on this principle.
The development of a personalized sensor to detect reactive epitopes could help to better understand the disease and would also allow the screening of those foods that could potentially trigger an immune response to the patient.
Objectives
Here there are:
In our iGEM Project we will design a personalized gluten sensor through a synthetic biology approach. To do so, we decided to build a model based on the HLA expression of the patient which will be coupled to a sensor, allowing the detection of reactive gluten epitopes.
first
To obtain de HLA-DQ from scratch. That means, to extract the α and β chains from the genomic DNA of a celiac patient.
second
To express the human HLA-DQ in a bacterial or yeast cell host.
third
To develop non-dimensional mathematical and stochastic models to understand and predict the sensor dynamics.
fourth
To provide information to the public to clear up common misunderstandings related to celiac disease.