Team:Wageningen UR/Backbone enzyme database

From 2013.igem.org

(Difference between revisions)
 
(7 intermediate revisions not shown)
Line 5: Line 5:
<html>
<html>
-
<div class="page-title">
+
<div class="pagina-titel">
-
     <div class="icon"><img src="http://beauvillemedia.nl/igem/morphology-icon.png" style="margin-top: 15px;"></div>
+
     <h1>Secondary Metabolite Enzyme Database</h1>
-
    <h1>Backbone enzyme database</h1>
+
    <h2>subtitle</h2>
 +
    <img src="http://beauvillemedia.nl/igem/dna.png"/>
</div>
</div>
 +
<div id="pagewrapper">
<div id="pagewrapper">
-
<h1><b> Enzyme database </h1></b>
 
-
<h3> on secondary metabolites backbone enzymes from Aspergilli </h3><br /><br />
 
-
<h2>Introduction</h2>
+
</html>
 +
 
 +
== Introduction ==
 +
<html>
<p>In general, the biosynthesis genes for fungal secondary metabolites are located in clusters. The fact that secondary metabolites are often synthesized as polymer backbones that are subsequently diversified greatly via the actions of tailoring enzymes sets the stage for combinatorial biochemistry because their biosynthesis is modular. In this combinatorial approach in which a modular system of domain shuffling can be used to generate a plethora of novel enzyme variants with new and improved functionalities. The number of permutations is extensive as there is a myriad of different domains that can be added, removed, reordered or exchanged. In order to facilitate mixing and matching of domains of these large enzymes a database for Aspergilli will be created. </p>
<p>In general, the biosynthesis genes for fungal secondary metabolites are located in clusters. The fact that secondary metabolites are often synthesized as polymer backbones that are subsequently diversified greatly via the actions of tailoring enzymes sets the stage for combinatorial biochemistry because their biosynthesis is modular. In this combinatorial approach in which a modular system of domain shuffling can be used to generate a plethora of novel enzyme variants with new and improved functionalities. The number of permutations is extensive as there is a myriad of different domains that can be added, removed, reordered or exchanged. In order to facilitate mixing and matching of domains of these large enzymes a database for Aspergilli will be created. </p>
-
<h4> Rationale </h4>
+
<h2> Rationale </h2>
<p>
<p>
 +
By recombining the different domains
 +
</p>
 +
<h2> Aim </h2>
 +
<p>
 +
Generating a secondary metabolites backbone enzyme database that contains the following information: <br />
 +
Gene sequence, gene size, introns, domains, illegal restriction sites and primary literature
</p>
</p>
-
<h4> Aim </h4>
+
<h2> Approach </h2>
<p>
<p>
 +
Two recently published articles on secondary metabolites of Aspergilli species serve as the basis for this database. Analysis of the gene clusters that are related to secondary metabolite production allowed for identification of the backbone enzymes that stand at the basis of this process. Making a list of the backbone enzymes codes from the articles allows for extraction of additional information from other sources, such as NCBI and UniProt. Using a pattern match approach allows for identification of illegal restriction sites and other scripts can be used to automatically generate a database with this information. Finally, a graphical user interface will be created to allow easy access to the database for any user. <br /><br />
 +
- D.O. Inglis et al., 2013 <i> Comprehensive annotation of secondary metabolite biosynthetic genes and gene clusters of Aspergillus nidulans, A. fumigatus, A. niger and A. oryzae.</i> BMC Microbiology Vol. 13 p. 1-23 <br />
 +
- J.F. Sanchez et al., 2012. <i> Advances in Aspergillus secondary metabolite research in the post-genomic era. </i> Nat. Prod. Rep. Vol. 29, p. 351-371
</p>
</p>
 +
<h2>Research Methods </h2>
 +
<p>
 +
Scripting will be done in python. The database will be contructed with the use of mySQL.
 +
</p>
 +
    </div>
 +
</div>
 +
</html>
<!--- Footer Template --->
<!--- Footer Template --->
{{:Team:Wageningen_UR/Templates/Page Footer}}
{{:Team:Wageningen_UR/Templates/Page Footer}}

Latest revision as of 00:08, 18 September 2013

Secondary Metabolite Enzyme Database

subtitle

Introduction

In general, the biosynthesis genes for fungal secondary metabolites are located in clusters. The fact that secondary metabolites are often synthesized as polymer backbones that are subsequently diversified greatly via the actions of tailoring enzymes sets the stage for combinatorial biochemistry because their biosynthesis is modular. In this combinatorial approach in which a modular system of domain shuffling can be used to generate a plethora of novel enzyme variants with new and improved functionalities. The number of permutations is extensive as there is a myriad of different domains that can be added, removed, reordered or exchanged. In order to facilitate mixing and matching of domains of these large enzymes a database for Aspergilli will be created.

Rationale

By recombining the different domains

Aim

Generating a secondary metabolites backbone enzyme database that contains the following information:
Gene sequence, gene size, introns, domains, illegal restriction sites and primary literature

Approach

Two recently published articles on secondary metabolites of Aspergilli species serve as the basis for this database. Analysis of the gene clusters that are related to secondary metabolite production allowed for identification of the backbone enzymes that stand at the basis of this process. Making a list of the backbone enzymes codes from the articles allows for extraction of additional information from other sources, such as NCBI and UniProt. Using a pattern match approach allows for identification of illegal restriction sites and other scripts can be used to automatically generate a database with this information. Finally, a graphical user interface will be created to allow easy access to the database for any user.

- D.O. Inglis et al., 2013 Comprehensive annotation of secondary metabolite biosynthetic genes and gene clusters of Aspergillus nidulans, A. fumigatus, A. niger and A. oryzae. BMC Microbiology Vol. 13 p. 1-23
- J.F. Sanchez et al., 2012. Advances in Aspergillus secondary metabolite research in the post-genomic era. Nat. Prod. Rep. Vol. 29, p. 351-371

Research Methods

Scripting will be done in python. The database will be contructed with the use of mySQL.