Team:UTDallas

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==Project Description==
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The University of Texas, Dallas iGEM team will develop a new generation of biosensors for contaminants. These sensors will be engineered in bacteria and will be able to combine heterogeneous inputs, process the incoming information dynamically, and release accordingly a reporter.
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Enlisting E. Scherichia Holmes: A modular whole-cell biosensor for the detection of environmental pollutants
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We are mainly interested in producing biosensors for use in disasters such as the recent Deepwater Horizon Spill. Even though the rig was recently closed, the World Water Assessment Program (WWAP) warns of health risks associated with the presence and circulation of such pollutants. Therefore, there is an urgent need for cheap and reliable contaminant sensors.
 
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Chemical sensors can have wide-ranging environmental applications, but can be very expensive depending on the technology. On the other hand, bacterial biosensors offer a cheaper alternative to existing systems. We will use Synthetic biology to implement gene circuits responsible for combinatorial logic, feedback and noise-reduction functions in a similar manner to electronic devices.
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===Project Abstract===
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Recalcitrant pollutants such as petroleum constituents and nitrates are regularly introduced to the environment through oil spills, natural geological seepage and eutrophication. The UN’s flagship water protection initiative enumerates a host of health risks associated with these chemicals. UT Dallas iGEM addresses the eminent need to mitigate their circulation by developing novel whole-cell biosensors that can detect alkanes, aromatics and nitrates and execute combinatorial logic, feedback and noise-reduction functions inspired by synthetic biology. This work has wide ranging applications requiring a cheap chemical sensor that can dynamically process heterogeneous inputs and express a user-friendly output.
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===Track Selection===
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Top three track choices:
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#Environment
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#Foundational Advance
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#Information Processing
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We will employ molecular biology techniques to develop new and modify existing BioBricks that respond to the following contaminants:
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''Crude oil:'' Commercial oil spills release millions of gallons of toxic chemicals into the ocean, which severely implicate wildlife and their habitats. These chemicals comprise several oil fractions including light ends, naphtha, kerosene, fuel oil, PGO and residual oil fractions. Crude oil is a complex mixture of hydrocarbons consisting primarily of alkanes, cycloalkanes and aromatic hydrocarbons. The alkane series are saturated hydrocarbons with linear or branched chains. The cycloalkane series are saturated hydrocarbons that include non-aromatic rings. The aromatic series are unsaturated hydrocarbons that include six-carbon benzene rings. We will engineer novel BioBricks to convert straight-chain alkanes into aldehydes. Existing parts sensitive to aldehydes would then indicate the presence of alkanes.  We will also modify parts submitted by the Glasgow 2007 team, which are inducible by aromatic compounds benzene, toluene, ethylbenzene and xylene.
 
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''Nitrates:'' Nitrates are a common ingredient in fertilizers, whose use is widespread and often excessive. Nutrient-rich runoff enriches water sources such as lakes, rivers and aquifers with the nitrates in a process called eutrophication, which facilitates the onset of algal blooms that deprive the water of oxygen and essential nutrients. Afflicted water sources are difficult and expensive to cleanse and the process would severely implicate the native wildlife.  
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We have several options for the sensor’s output. One possibility is for each contaminant sensor to activate the transcription of a pigment protein. For example, aromatics could produce red, nitrates purple, and alkanes green. When used in conditions with multiple contaminants, this would produce a specific color. A second possibility is using logic functions in a gene network implementation. For example, the presence of aromatics OR nitrates OR alkanes produces green. We will explore both options.
 
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Latest revision as of 02:21, 28 October 2010


Enlisting E. Scherichia Holmes: A modular whole-cell biosensor for the detection of environmental pollutants


Project Abstract

Recalcitrant pollutants such as petroleum constituents and nitrates are regularly introduced to the environment through oil spills, natural geological seepage and eutrophication. The UN’s flagship water protection initiative enumerates a host of health risks associated with these chemicals. UT Dallas iGEM addresses the eminent need to mitigate their circulation by developing novel whole-cell biosensors that can detect alkanes, aromatics and nitrates and execute combinatorial logic, feedback and noise-reduction functions inspired by synthetic biology. This work has wide ranging applications requiring a cheap chemical sensor that can dynamically process heterogeneous inputs and express a user-friendly output.

Track Selection

Top three track choices:

  1. Environment
  2. Foundational Advance
  3. Information Processing