- Filamentous fungi possess a special class of genetic components known as Biosynthetic Gene Clusters (BGCs). These BGCs have a few unique properties which make them worth exploring:
- They have an evolutionary history of horizontal gene transfer, causing many filamentous fungi species to have orthologous clusters. 
- The transcription factor genes regulating the BGC tend to be within the cluster as well. 
- They encode important secondary metabolites, such as antibiotics and environmental toxins. 
- As bacteria continue to evolve antibiotic resistance, the race to discover new secondary metabolites becomes a more crucial endeavor. Meanwhile, the catalog of genetic parts for studying the filamentous fungi lacks the diversity needed to progress science forward in this race.
- Secondary metabolites are produced by complicated pathways that require many genetic parts native to filamentous fungi genomes. Not all of these parts are included in the BGCs. Therefore, moving a functional BGC from filamentous fungi to another organism requires the movement of many other parts along with it, making it very difficult to study these fungal components outside of filamentous fungi . Therefore, it is pertinent to the field of synthetic biology to build up filamentous fungi as a synthetic biology system, by expanding it’s catalog of genetic parts.
- Some major components required to expand the catalog are transcription factors and their specific binding sites. Currently, there is a large gap in the scientific knowledge of these components. Databases of transcription factor binding sites (TRANSFAC, etc.) contain very little information on filamentous fungi, and scientific literature describing consensus binding sites are difficult to come by.
- Furthermore, an analysis of past iGEM teams showed that only 7.8% of them worked with fungi, and only 0.05% worked with fungi other than Saccharomyces cerevisiae.
- In order to find and characterize transcription factors and their respective binding sites, we utilize computational methods. Specifically, we developed bioinformatics software tools to optimize the parameters of a common motif-finding software, MEME.
- MEME is part of the MEME suite, which is a collection of bioinformatics software designed to help scientists locate specific motifs from DNA sequences. MEME works by taking in a FASTA file, and outputting a position weight matrix (PWM) that represents a specific motif. After running multiple verification tests to find the best parameters for MEME (things like promoter length, amount of genes per cluster, etc.), we look in the immense library of fungal genomes provided to us by the Joint Genome Institute. Then, using our optimized pipeline, we determine a set of our most significant motifs within the genus Aspergillus. We chose this genus as a first trial, because it is currently one of the more well studied genuses in biology. Also, it contains an easily cultured BSL 1 species, Aspergillus niger.
- The resulting list of putative Aspergillus binding sites will be accompanied by an experimental design protocol to confirm their functionality. This protocol includes an Aspergillus niger procedural handbook, safety information, and follows the engineering design cycle described by iGEM.
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