Faculty Opinions recommendation of Genome-wide high-throughput mining of natural-product biosynthetic gene clusters by phage display.

2007 ◽  
Author(s):  
Burckhard Seelig
Keyword(s):  
Phage Display ◽  
Natural Product ◽  
High Throughput ◽  
Gene Clusters ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Genome Wide

scholarly journals Genome-Wide High-Throughput Mining of Natural-Product Biosynthetic Gene Clusters by Phage Display

2007 ◽  
Vol 14 (3) ◽  
pp. 303-312 ◽  
Author(s):  
Jun Yin ◽  
Paul D. Straight ◽  
Siniša Hrvatin ◽  
Pieter C. Dorrestein ◽  
Stefanie B. Bumpus ◽  
...  
Keyword(s):  
Phage Display ◽  
Natural Product ◽  
High Throughput ◽  
Gene Clusters ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Genome Wide

scholarly journals Global analysis of adenylate-forming enzymes reveals β-lactone biosynthesis pathway in pathogenic Nocardia

2020 ◽  
Vol 295 (44) ◽  
pp. 14826-14839
Author(s):  
Serina L. Robinson ◽  
Barbara R. Terlouw ◽  
Megan D. Smith ◽  
Sacha J. Pidot ◽  
Timothy P. Stinear ◽  
...  
Keyword(s):  
Machine Learning ◽  
Natural Product ◽  
Global Analysis ◽  
Gene Clusters ◽  
Divergent Evolution ◽  
Acid Activation ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Predictive Tool ◽  
Wide Range

Enzymes that cleave ATP to activate carboxylic acids play essential roles in primary and secondary metabolism in all domains of life. Class I adenylate-forming enzymes share a conserved structural fold but act on a wide range of substrates to catalyze reactions involved in bioluminescence, nonribosomal peptide biosynthesis, fatty acid activation, and β-lactone formation. Despite their metabolic importance, the substrates and functions of the vast majority of adenylate-forming enzymes are unknown without tools available to accurately predict them. Given the crucial roles of adenylate-forming enzymes in biosynthesis, this also severely limits our ability to predict natural product structures from biosynthetic gene clusters. Here we used machine learning to predict adenylate-forming enzyme function and substrate specificity from protein sequences. We built a web-based predictive tool and used it to comprehensively map the biochemical diversity of adenylate-forming enzymes across >50,000 candidate biosynthetic gene clusters in bacterial, fungal, and plant genomes. Ancestral phylogenetic reconstruction and sequence similarity networking of enzymes from these clusters suggested divergent evolution of the adenylate-forming superfamily from a core enzyme scaffold most related to contemporary CoA ligases toward more specialized functions including β-lactone synthetases. Our classifier predicted β-lactone synthetases in uncharacterized biosynthetic gene clusters conserved in >90 different strains of Nocardia. To test our prediction, we purified a candidate β-lactone synthetase from Nocardia brasiliensis and reconstituted the biosynthetic pathway in vitro to link the gene cluster to the β-lactone natural product, nocardiolactone. We anticipate that our machine learning approach will aid in functional classification of enzymes and advance natural product discovery.

mpCRISTAR: Multiple Plasmid Approach for CRISPR/Cas9 and TAR-Mediated Multiplexed Refactoring of Natural Product Biosynthetic Gene Clusters

2019 ◽  
Vol 9 (1) ◽  
pp. 175-180 ◽  
Author(s):  
Hiyoung Kim ◽  
Chang-Hun Ji ◽  
Hyun-Woo Je ◽  
Jong-Pyung Kim ◽  
Hahk-Soo Kang
Keyword(s):  
Natural Product ◽  
Gene Clusters ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters

scholarly journals Challenges and Advances in Genome Editing Technologies in Streptomyces

Biomolecules ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 734 ◽  
Author(s):  
Yawei Zhao ◽  
Guoquan Li ◽  
Yunliang Chen ◽  
Yinhua Lu
Keyword(s):  
Natural Product ◽  
Genome Editing ◽  
Genetic Manipulation ◽  
Chemical Compounds ◽  
Gene Clusters ◽  
Future Research ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Research Focus ◽  
Experimental Conditions

The genome of Streptomyces encodes a high number of natural product (NP) biosynthetic gene clusters (BGCs). Most of these BGCs are not expressed or are poorly expressed (commonly called silent BGCs) under traditional laboratory experimental conditions. These NP BGCs represent an unexplored rich reservoir of natural compounds, which can be used to discover novel chemical compounds. To activate silent BGCs for NP discovery, two main strategies, including the induction of BGCs expression in native hosts and heterologous expression of BGCs in surrogate Streptomyces hosts, have been adopted, which normally requires genetic manipulation. So far, various genome editing technologies have been developed, which has markedly facilitated the activation of BGCs and NP overproduction in their native hosts, as well as in heterologous Streptomyces hosts. In this review, we summarize the challenges and recent advances in genome editing tools for Streptomyces genetic manipulation with a focus on editing tools based on clustered regularly interspaced short palindrome repeat (CRISPR)/CRISPR-associated protein (Cas) systems. Additionally, we discuss the future research focus, especially the development of endogenous CRISPR/Cas-based genome editing technologies in Streptomyces.

scholarly journals Genomic Assemblies of Members of Burkholderia and Related Genera as a Resource for Natural Product Discovery

2020 ◽  
Vol 9 (42) ◽  
Author(s):  
Alex J. Mullins ◽  
Cerith Jones ◽  
Matthew J. Bull ◽  
Gordon Webster ◽  
Julian Parkhill ◽  
...  
Keyword(s):  
Natural Product ◽  
Genome Mining ◽  
Genomic Analysis ◽  
Gene Clusters ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Natural Product Discovery

ABSTRACT The genomes of 450 members of Burkholderiaceae, isolated from clinical and environmental sources, were sequenced and assembled as a resource for genome mining. Genomic analysis of the collection has enabled the identification of multiple metabolites and their biosynthetic gene clusters, including the antibiotics gladiolin, icosalide A, enacyloxin, and cepacin A.

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