Dataset Information

Refactoring the silent spectinabilin gene cluster using a plug-and-play scaffold.

ABSTRACT: Natural products (secondary metabolites) are a rich source of compounds with important biological activities. Eliciting pathway expression is always challenging but extremely important in natural product discovery because an individual pathway is tightly controlled through a unique regulation mechanism and hence often remains silent under the routine culturing conditions. To overcome the drawbacks of the traditional approaches that lack general applicability, we developed a simple synthetic biology approach that decouples pathway expression from complex native regulations. Briefly, the entire silent biosynthetic pathway is refactored using a plug-and-play scaffold and a set of heterologous promoters that are functional in a heterologous host under the target culturing condition. Using this strategy, we successfully awakened the silent spectinabilin pathway from Streptomyces orinoci. This strategy bypasses the traditional laborious processes to elicit pathway expression and represents a new platform for discovering novel natural products.

SUBMITTER: Shao Z

PROVIDER: S-EPMC4326240 | biostudies-literature | 2013 Nov

REPOSITORIES: biostudies-literature

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Refactoring the silent spectinabilin gene cluster using a plug-and-play scaffold.

Shao Zengyi Z Rao Guodong G Li Chun C Abil Zhanar Z Luo Yunzi Y Zhao Huimin H

ACS synthetic biology 20130822 11

Natural products (secondary metabolites) are a rich source of compounds with important biological activities. Eliciting pathway expression is always challenging but extremely important in natural product discovery because an individual pathway is tightly controlled through a unique regulation mechanism and hence often remains silent under the routine culturing conditions. To overcome the drawbacks of the traditional approaches that lack general applicability, we developed a simple synthetic biol ...[more]

PMID: 23968564

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Project description:Quantitative susceptibility mapping employs regularization to reduce artifacts, yet many recent denoisers are unavailable for reconstruction. We developed a plug-and-play approach to QSM reconstruction (PnP QSM) and show its flexibility using several patch-based denoisers. We developed PnP QSM using alternating direction method of multiplier framework and applied collaborative filtering denoisers. We apply the technique to the 2016 QSM Challenge and in 10 glioblastoma multiforme datasets. We compared its performance with four published QSM techniques and a multi-orientation QSM method. We analyzed magnetic susceptibility accuracy using brain region-of-interest measurements, and image quality using global error metrics. Reconstructions on glioblastoma data were analyzed using ranked and semiquantitative image grading by three neuroradiologist observers to assess image quality (IQ) and sharpness (IS). PnP-BM4D QSM showed good correlation (β = 0.84, R2 = 0.98, p < 0.05) with COSMOS and no significant bias (bias = 0.007 ± 0.012). PnP-BM4D QSM achieved excellent quality when assessed using structural similarity index metric (SSIM = 0.860), high frequency error norm (HFEN = 58.5), cross correlation (CC = 0.804), and mutual information (MI = 0.475) and also maintained good conspicuity of fine features. In glioblastoma datasets, PnP-BM4D QSM showed higher performance (IQGrade = 2.4 ± 0.4, ISGrade = 2.7 ± 0.3, IQRank = 3.7 ± 0.3, ISRank = 3.9 ± 0.3) compared to MEDI (IQGrade = 2.1 ± 0.5, ISGrade = 2.1 ± 0.6, IQRank = 2.4 ± 0.6, ISRank = 2.9 ± 0.2) and FANSI-TGV (IQGrade = 2.2 ± 0.6, ISGrade = 2.1 ± 0.6, IQRank = 2.7 ± 0.3, ISRank = 2.2 ± 0.2). We illustrated the modularity of PnP QSM by interchanging two additional patch-based denoisers. PnP QSM reconstruction was feasible, and its flexibility was shown using several patch-based denoisers. This technique may allow rapid prototyping and validation of new denoisers for QSM reconstruction for an array of useful clinical applications.

Dataset Information

Refactoring the silent spectinabilin gene cluster using a plug-and-play scaffold.

Publications

Refactoring the silent spectinabilin gene cluster using a plug-and-play scaffold.

Similar Datasets

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