RedEx: a method for seamless DNA insertion and deletion in large multimodular polyketide synthase gene clusters

Song, Chaoyi; Luan, Jing; Li, Ruijuan; Jiang, Chanjuan; Hou, Yu; Cui, Qingwen; Cui, Tianqi; Long, Tan; Ma, Zai-Chao; Tang, Ya‐Jie; Stewart, A. Francis; Fu, Jun; Zhang, Youming; Wang, Hailong

doi:10.1093/nar/gkaa956

Cited by 26 publications

(19 citation statements)

References 34 publications

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“…In order to investigate the regulatory mechanisms underlying the AD-related neural development, we applied the imputed matrix of scGNN to IRIS3 (an integrated cell-type-specific regulon inference server from single-cell RNA-Seq) and identified 21 cell-type-specific regulons (CTSR) in five cell types 45 (Fig. 5e and Supplementary Data 13 ; IRIS3 job ID: 20200626160833).…”

Section: Resultsmentioning

confidence: 99%

“…We further identified the DEGs between AD and control cells in each cluster using the same strategy and applied GSEA for pathway enrichment analysis 62 . The imputed matrix, which resulted from scGNN was then sent to IRIS3 for CTSR prediction, using the predicted cell clustering labels with merged oligodendrocytes 45 . The default parameters were served in regulatory analysis in IRIS3.…”

Section: Methodsmentioning

confidence: 99%

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scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses

et al. 2021

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Single-cell RNA-sequencing (scRNA-Seq) is widely used to reveal the heterogeneity and dynamics of tissues, organisms, and complex diseases, but its analyses still suffer from multiple grand challenges, including the sequencing sparsity and complex differential patterns in gene expression. We introduce the scGNN (single-cell graph neural network) to provide a hypothesis-free deep learning framework for scRNA-Seq analyses. This framework formulates and aggregates cell–cell relationships with graph neural networks and models heterogeneous gene expression patterns using a left-truncated mixture Gaussian model. scGNN integrates three iterative multi-modal autoencoders and outperforms existing tools for gene imputation and cell clustering on four benchmark scRNA-Seq datasets. In an Alzheimer’s disease study with 13,214 single nuclei from postmortem brain tissues, scGNN successfully illustrated disease-related neural development and the differential mechanism. scGNN provides an effective representation of gene expression and cell–cell relationships. It is also a powerful framework that can be applied to general scRNA-Seq analyses.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses

et al. 2021

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“…The final plasmid pAPI was transformed into the heterologous host S. albus and successfully produced apigenin at 0.08 mg/L ( Marín et al, 2017 ). In another case, Song et al (2020) refactored the spinosyn BGCs via RedEx to test whether the ethyl group at C-21 of spinosyn A can be replaced by butene group.…”

Section: Heterologous Expression Of Target Bgcsmentioning

confidence: 99%

Recent Advances in Silent Gene Cluster Activation in Streptomyces

Liu

Zhao

Huang

et al. 2021

Front. Bioeng. Biotechnol.

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Natural products (NPs) are critical sources of drug molecules for decades. About two-thirds of natural antibiotics are produced by Streptomyces. Streptomyces have a large number of secondary metabolite biosynthetic gene clusters (SM-BGCs) that may encode NPs. However, most of these BGCs are silent under standard laboratory conditions. Hence, activation of these silent BGCs is essential to current natural products discovery research. In this review, we described the commonly used strategies for silent BGC activation in Streptomyces from two aspects. One focused on the strategies applied in heterologous host, including methods to clone and reconstruct BGCs along with advances in chassis engineering; the other focused on methods applied in native host which includes engineering of promoters, regulatory factors, and ribosomes. With the metabolic network being elucidated more comprehensively and methods optimized more high-thoroughly, the discovery of NPs will be greatly accelerated.

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“…However, mutagenesis of modular polyketide synthases is not trivial because of the high sequence similarity between domains. Recently, the RedEx method (Song et al, 2020) and the in vitro Cas9-assisted method (Kudo et al, 2020) have been developed to accurately edit desired regions in the PKS gene on the BAC vector containing the intact large biosynthetic gene cluster which is larger than 100 kb. These new gene-editing methods and the heterologous expression system based on the artificial gene cluster established in this study will facilitate the structural derivatization of salinomycin.…”

Section: Effects Of Regulatory Genes Salj Saln and Salo In The Hetero...mentioning

confidence: 99%

Establishing an efficient salinomycin biosynthetic pathway in three heterologous Streptomyces hosts by constructing a 106‐kb multioperon artificial gene cluster

Jiang

Zhou

Sun

et al. 2021

Biotech & Bioengineering

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Salinomycin is a promising anticancer drug for chemotherapy. A highly productive biosynthetic gene cluster will facilitate the creation of analogs with improved therapeutic activity and reduced side effects. In this study, we engineered an artificial 106-kb salinomycin gene cluster and achieved efficient heterologous expression in three hosts: Streptomyces coelicolor CH999, S. lividans K4-114, and S. albus J1074. The six-operon artificial gene cluster consists of 25 genes from the native gene cluster organized into five operons and five fatty acid β-oxidation genes into one operon. All operons are driven by strong constitutive promoters. For K4-114 and J1074 harboring the artificial gene cluster, salinomycin production in shake flask cultures was 14.3 mg L −1 and 19.3 mg L −1 , respectively. The production was 1.3-fold and 1.7-fold higher, respectively, than that of the native producer S. albus DSM41398. K4-114 and J1074 harboring the native gene cluster produced an undetectable amount of salinomycin and 0.5 mg L −1 , respectively. CH999 harboring the artificial gene cluster produced 10.3 mg L −1 of salinomycin, which was 92% of the production by DSM41398. The efficient heterologous expression system based on the 106-kb multioperon artificial gene cluster established in this study will facilitate structural diversification of salinomycin, which is valuable for drug development and structure-activity studies.

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RedEx: a method for seamless DNA insertion and deletion in large multimodular polyketide synthase gene clusters

Cited by 26 publications

References 34 publications

scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses

scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses

Recent Advances in Silent Gene Cluster Activation in Streptomyces

Establishing an efficient salinomycin biosynthetic pathway in three heterologous Streptomyces hosts by constructing a 106‐kb multioperon artificial gene cluster

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