Skip to main content
ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Food Quality Laboratory » Research » Publications at this Location » Publication #297302
Title: Genomic platform for efficient identification of fungal secondary metabolism genes

Author
item UMEMURA, MYCO - National Institute Of Advanced Industrial Science And Technology (NIAIST)
item KOIKE, HIDEAKI - National Institute Of Advanced Industrial Science And Technology (NIAIST)
item KAWANO, JIN - National Institute Of Advanced Industrial Science And Technology (NIAIST)
item ISHII, TOMOKO - National Institute Of Advanced Industrial Science And Technology (NIAIST)
item MIYAMURA, YUKI - National Institute Of Advanced Industrial Science And Technology (NIAIST)
item IKEGAMI, TSUTOMU - National Institute Of Advanced Industrial Science And Technology (NIAIST)
item TERAI, GORO - National Institute Of Advanced Industrial Science And Technology (NIAIST)
item KUMAGAI, T. - National Institute Of Advanced Industrial Science And Technology (NIAIST)
item TAKEDA, I. - National Institute Of Advanced Industrial Science And Technology (NIAIST)
item Yu, Jiujiang

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 7/1/2013
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Fungal secondary metabolites (SMs) are structurally diverse natural compounds, which are thought to have great potential not only for medical industry but also for chemical and environmental industries. Since expansion of sequencing microbial genomes in 1990’s, it has been known that SM genes are expanded in the microbial genomes far more than those expected before sequencing. For most of the genes, we never have information about the conditions for their expression, thus, probably 90% or more of them have remained unexamined. In order to accelerate analysis and utilization of the unaddressed useful genes, we have developed a platform comprised of NGS (next-generation sequencer), LC/MS and bioinformatics tools specialized for high throughput analysis of multiple fungal genomes. By using the platform, twelve novel fungal genomes can be sequenced within about two weeks by SOLiD 5500 XL. Our in-house pipelines allow quick and accurate analysis of genome, gene modeling, transcriptome and successive prediction of SM gene cluster. Once a compound of interest is detected by any methods including biological, chemical or physical methods, corresponding SM gene cluster can be rapidly predicted typically within a month. We have successfully determined gene clusters of kojic acid, ustiloxin B and other unknown compounds to date. A remarkable feature of our platform is the ability to detect SM gene clusters without a so-called SM core gene such as PKS, NRPS or terpene. This allows us to expand our target SM gene clusters far beyond those already examined.