Team:Imperial College London/Tour/Page One

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|style="font-family: helvetica, arial, sans-serif;font-size:2em;color:#ea8828;" colspan="2"|Welcome to the tour!
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|colspan="2" valign="top"|'''[[Team:Imperial_College_London/The_Team | The team]]''' embarked on our iGEM project in early July, after finishing our exams and having about a week off for a bit of rest and relaxation. There have been highs, there have been lows (our '''[[Team:Imperial_College_London/Diary/Week_One | diary]]''' can give you all the details, or even our '''[[Team:Imperial_College_London/Media/Videos | video diary]]''' if you're feeling adventurous!), but it's all part of the amazing journey that is iGEM. Follow this brief tour of our project for an idea of what we got upto. Check out our '''[[Team:Imperial_College_London/Glossary | glossary]]''' if you ever feel lost.
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|colspan="2" valign="top"|We had great fun with our initial '''[[Team:Imperial_College_London/Brainstorming | brainstorming]]''' sessions, but we soon focused on an area we found interesting: biosensors. Synthetic biology has great potential for biosensors, but there are definitely a few key problems with current solutions.
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|style="font-family: helvetica, arial, sans-serif;font-size:2em;color:#ea8828;" colspan="2"|Current problems
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|colspan="2" valign="top"|'''Time - '''Current solutions can take anything from hours to weeks to generate a visible output. What if you could design a system that was capable of responding in minutes?
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'''Capability - '''Current solutions are limited to a variety of simple inputs. Basic chemicals, environmental changes, etc. What if you could detect something more complex, like a protein?
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'''Modularity - '''Current systems tend to have a fixed input/output. What if you could create a framework that allowed inputs and outputs to be mixed and matched together?
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|style="font-family: helvetica, arial, sans-serif;font-size:2em;color:#ea8828;" colspan="2" align="right"|What to detect?
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|colspan="2" valign="top"|After much deliberation, we decided that something with a strong health impact would be a good candidate for detection. But how, why, and what? This is when we brought our '''[[Team:Imperial_College_London/Human_Practices/Panel_Discussion | human practices]]''' to bear on the problem. A series of expert meetings, workshops, a panel discussion and a '''[[Team:Imperial_College_London/Safety | safety consideration]]''' later, we found our target. Parasites - hard to detect, but easy to treat. In particular we looked at the '''[[Team:Imperial_College_London/Schistosoma | schistosoma parasite]]''', a neglected tropical disease which affects over 200 million people worldwide. If we could create a cheap, easy and safe system, then it might really make a difference.
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|style="font-family: helvetica, arial, sans-serif;font-size:2em;color:#ea8828;" colspan="2"|The engineering cycle
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|colspan="2" valign="top"|With a goal in mind, what was the most efficient way to develop our project? We decided to follow the engineering design cycle. We first produced a specification based on the problems we had identified with previous biosensors, combined with ethical and logistical factors identified through the '''[[Team:Imperial_College_London/Human_Practices/Report | human practices report]]'''. Next came the fun part.
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|colspan="2" valign="top"|With our specification at the ready, how did we want to design our system? What '''[[Team:Imperial_College_London/Chassis | chassis]]''' should we use? How can we split up our project? After intense '''[[Team:Imperial_College_London/Research | research]]''' we settled on using ''B. subtilis'', and dividing the project into '''[[Team:Imperial_College_London/Modules | three modules]]'''. This makes it more powerful to use, simpler to create, and allows us to focus each module on solving an identified problem.
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|style="font-family: helvetica, arial, sans-serif;font-size:2em;color:#ea8828;" colspan="2"|Detection module
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|colspan="2" valign="top"|We decided to design a '''[[Team:Imperial_College_London/Modules/Detection | new mechanism for parasite detection]]''' - by using the proteases they release. A novel protein is bound to the cell surface, with a signalling peptide attached via a protease cleavage site. When the protease comes along, the signal peptide is released, allowing it to activate our signaling module.
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|colspan="2" valign="top"|To transduce the signal we used a '''[[Team:Imperial_College_London/Modules/Signaling | quorum sensing system]]''' of a gram positive bacterium. The two component signal transduction system taken from ''S. pneumoniae'' transfers our peptide signal into the cell, activating the fast response module.
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|style="font-family: helvetica, arial, sans-serif;font-size:2em;color:#ea8828;" colspan="2"|Fast response module
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|colspan="2" valign="top"|Our '''[[Team:Imperial_College_London/Modules/Fast_Response | fast response mechanism]]''' is based around using two enzymatic amplification steps involving a transcripted enzyme, a deactivated enzyme and a presynthesised substrate. This greatly reduces the time required for producing a recognisable output, enabling useful field testing kits.
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|style="font-family: helvetica, arial, sans-serif;font-size:2em;" colspan="3" align="right"|[[Team:Imperial_College_London/Tour/Page_Two | Carry on to part two of the tour...]]
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Latest revision as of 03:58, 28 October 2010

Welcome to the tour!
The team embarked on our iGEM project in early July, after finishing our exams and having about a week off for a bit of rest and relaxation. There have been highs, there have been lows (our diary can give you all the details, or even our video diary if you're feeling adventurous!), but it's all part of the amazing journey that is iGEM. Follow this brief tour of our project for an idea of what we got upto. Check out our glossary if you ever feel lost.
Biosensors
We had great fun with our initial brainstorming sessions, but we soon focused on an area we found interesting: biosensors. Synthetic biology has great potential for biosensors, but there are definitely a few key problems with current solutions.
Current problems
Time - Current solutions can take anything from hours to weeks to generate a visible output. What if you could design a system that was capable of responding in minutes?

Capability - Current solutions are limited to a variety of simple inputs. Basic chemicals, environmental changes, etc. What if you could detect something more complex, like a protein?

Modularity - Current systems tend to have a fixed input/output. What if you could create a framework that allowed inputs and outputs to be mixed and matched together?

What to detect?
After much deliberation, we decided that something with a strong health impact would be a good candidate for detection. But how, why, and what? This is when we brought our human practices to bear on the problem. A series of expert meetings, workshops, a panel discussion and a safety consideration later, we found our target. Parasites - hard to detect, but easy to treat. In particular we looked at the schistosoma parasite, a neglected tropical disease which affects over 200 million people worldwide. If we could create a cheap, easy and safe system, then it might really make a difference.
The engineering cycle
With a goal in mind, what was the most efficient way to develop our project? We decided to follow the engineering design cycle. We first produced a specification based on the problems we had identified with previous biosensors, combined with ethical and logistical factors identified through the human practices report. Next came the fun part.
Design
With our specification at the ready, how did we want to design our system? What chassis should we use? How can we split up our project? After intense research we settled on using B. subtilis, and dividing the project into three modules. This makes it more powerful to use, simpler to create, and allows us to focus each module on solving an identified problem.
Detection module
We decided to design a new mechanism for parasite detection - by using the proteases they release. A novel protein is bound to the cell surface, with a signalling peptide attached via a protease cleavage site. When the protease comes along, the signal peptide is released, allowing it to activate our signaling module.
Signaling module
To transduce the signal we used a quorum sensing system of a gram positive bacterium. The two component signal transduction system taken from S. pneumoniae transfers our peptide signal into the cell, activating the fast response module.
Fast response module
Our fast response mechanism is based around using two enzymatic amplification steps involving a transcripted enzyme, a deactivated enzyme and a presynthesised substrate. This greatly reduces the time required for producing a recognisable output, enabling useful field testing kits.
Carry on to part two of the tour...
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