Team:UC Davis/Projects

var crosstalkContent = "<br/><p class='header'>THE PROBLEM</p><div>In synthetic biology, the issue of crosstalk acts as a substantial barrier against developing fully-controlled biological systems.  Much like in the development of electrical systems where crosstalk causes harmful interference and unpredictable behavior, crosstalk prevents us from completely understanding how our biological constructs function, and quite often can affect the efficacy of these systems.  As such, it is clear that a method to computationally predict crosstalk in a given biological system would be a valuable scientific resource, and would effectively help minimize the negative effects of crosstalk.  This is where our computational tool, CPOTATo, comes in.</div><br/>Crosstalk can be attributed to several aspects of biological systems, one of which is the interaction between proteins from the synthetic circuit and proteins from the host organism.  CPOTATo takes advantage of this fact in an attempt to predict protein combinations that may cause crosstalk in various biological systems.<br/><br/>The primary reason for the crosstalk between proteins is usually the homology between them.  Consider the following abstract example:  In the chassis' system, Protein A naturally interacts with Protein B; however, Protein C, a protein produced by the synthetic circuit we wish to implant, is very homologous to Protein A.  Since Protein A and Protein C are very similar, there is a certain degree of probability that Protein C will interact with Protein B.  Therefore, unless Protein C's original purpose was to interact with Protein B, this is an undesirable interaction that may lead to unpredictable crosstalk.<br/><br/><p class='header'>APPROACH</p>CPOTATo executes several consecutive database queries to different existing databases of genomic information in order to infer any instances of crosstalk based on protein-protein relationships.  The tool relies on two inputs: the amino acid sequence of the target protein, and the target organism or chassis.  We query 3 individual databases in order to obtain the information we need: Interpro, UniprotKB and String.<br/><br/>From the Interpro database, we obtain one or more Interpro entries, each of which consists of a group of proteins homologous to our target protein.  We then use these Interpro entries as the query parameter to the UniprotKB database in order to filter out all proteins that are not produced within the chassis.  And finally, we query the String database with each of the remaining proteins to obtain the final list of interactions involving each of these homologous proteins and the target protein.<br/><br/><p class='header'>SCORES</p>The finalization of the numerical score analysis is still pending.  See the Changelog.<br/><br/><p class='header'>Changelog</p>";