Difference between revisions of "Team:UC Davis"

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<h2> UC Davis 2015 iGEM Team</h2>
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<p>The goal of our project is to create a biosensor for the detection of triclosan. Triclosan is an antimicrobial agent that works by preventing bacteria from synthesizing fatty acids. More specifically, triclosan competitively inhibits enoyl ACP reductase (FabI), the enzyme that catalyzes the last step of fatty acid synthesis.</p>
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<p> FabI uses an electron from NADH to reduce crotonyl ACP. Because triclosan inhibits FabI from reducing crotonyl ACP, there will be higher levels of NADH in the presence of triclosan. By measuring levels of NADH, we will be able to infer levels of triclosan.
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We will mix up enoyl reductase (enzyme), crotonyl-coA (substrate), NADH (cofactor), and triclosan (inhibitor) and drop a sample onto our screen-printed electrode, which will be connected to our potentiostat.
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We will use the potentiostat to control the potential of the working electrode at a fixed value relative to the reference electrode.  The applied potential serves as the driving force for the full reduction of the electroactive species (NADH).
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It is important to note that the sample on the electrode is divided into two regions: the diffusion region and the bulk region and that the applied potential only affects the diffusion region. In this diffusion region, the current is governed by Fick’s Law of Diffusion, which states that the magnitude of current is proportional to the concentration gradient of NADH.
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When we apply the potential, all of the NADH in the diffusion region will be oxidized. Since current is proportional to concentration gradient, there will be a huge spike in current. Over time, NADH from the bulk solution will diffuse back onto the electrode, making the concentration gradient less pronounced. This mellowing out of the concentration gradient translates to a steady stating out of current.
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The steady state value of the current is proportional to the concentration of NADH in the bulk solution.
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A solution with enzyme, substrate, and NADH that is allowed to incubate for some time will have less NADH than starting out with (due to the enzyme turning over NADH). If we add triclosan into the mix, the enzyme will still use up some NADH, but it will use up less because it is inhibited. Each of these solutions will have different levels of NADH and will thus generate different current values.
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By comparing the current values, we will be able to determine how different levels of triclosan affect the magnitude of current. The idea is that for a sample of unknown triclosan, we will be able to correlate the current read out with the sample’s concentration of triclosan.
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Revision as of 21:38, 15 July 2015


Tutorial

Explore our Code

Launch!

SBiDer: Synthetic Biocircuit Developer

Abstract

Genetic circuits are often difficult to engineer, requiring months to design, build, and test each individual genetic device involved in the circuit. SBiDer, a web tool developed by the UCSD Software iGEM team, will leverage existing devices to construct a database with consideration for the function of each device interpreted as boolean logic. The data can be queried by the user through SBiDer's visual interface to explore circuit designs. Users can search for existing circuits that can be used to assemble a complex circuit. The displayed circuit's literature reference, characterization data, and images of included devices can be viewed through the built-in table. We also provide a standalone modelling Python package that can be used to model circuits given by our online webtool. SBiDer's web of information can be expanded through user-generated additions to the database to improve the efficiency of the application and the accuracy of the models.

Project Description

Problem Statement

Synthetic genetic circuits created by synthetic biologists have yielded exciting applications such as biofuels production and cancer killing bacteria. These circuits are often difficult to engineer, requiring months to design, build, and test each individual genetic device involved in the circuit. Although there are many genetic devices that have been built, re-using these devices often requires a time-consuming review of the literature. The UCSD Software iGEM team will address this challenge by creating a web-tool that leverages existing genetic devices to create complex genetic circuits. We will accomplish this by:

  1. building a comprehensive database that captures the behavior, composition, and interactions of existing genetic devices in the literature
  2. constructing and visualizing the network of all synthetic genetic circuits that can interact with one another
  3. devising algorithms to search this network for the set of genetic devices that can be used to construct a complex genetic circuit.
  4. Perform some basic validation via kinetic modelling.

Aim 1 - Building a Database

We will mine the scientific literature for existing genetic devices and then construct a database that captures device characteristics such as:

  1. composition of devices
  2. function
  3. characterization data
  4. literature reference
We will design our database by rigorously constructing an entity relationship diagram and then normalizing these relationships to construct tables for a relational database.

Aim 2 - Constructing Network of Interacting Devices

We will connect known genetic devices together via device input and outputs to create a network of devices that can interact. We define a genetic device as a DNA construct transformed into cells that can cause expression of some protein in response to stimuli (or input). We will develop a web interface to facilitate access to the complex network that we have constructed. Our Web interface makes extensive use of Cytoscape, an open source bioinformatics software package for metabolic network visualization and simulation. In addition, the interface will generate SBOL Visual Images, a standard language that is easily understood by synthetic biologists all over the world. Users can also update our database with additional devices through this interface. Using the Cynetshare framework, users can share their circuit designs

Aim 3 - Searching the Network

This interface will allow researchers to query our database network for a circuit design expressed as logical operators such as “AND”, “OR”, and “NOR”, and retrieve the subnetwork of genetic devices that satisfies the circuit design. To Perform our search we modified several traditional graph search algorithms to traverse this graph, including but not limited to Prim’s algorithm (minimum spanning tree), Dijkstra’s algorithm and a breadth-first search. Results are visualized graphically in our web interface.

UC Davis 2015 iGEM Team