| Literature DB >> 31611640 |
Gaoyan Wang1, Zhiying Zhao1, Jing Ke1, Yvonne Engel2, Yi-Ming Shi2, David Robinson1, Kerem Bingol3, Zheyun Zhang1, Benjamin Bowen1,4, Katherine Louie1, Bing Wang1, Robert Evans1, Yu Miyamoto1, Kelly Cheng1, Suzanne Kosina4, Markus De Raad4, Leslie Silva1, Alicia Luhrs5, Andrea Lubbe5, David W Hoyt3, Charles Francavilla5, Hiroshi Otani1,4, Samuel Deutsch1,4,6, Nancy M Washton3, Edward M Rubin1, Nigel J Mouncey1,4, Axel Visel1,4, Trent Northen1,4, Jan-Fang Cheng1,4, Helge B Bode7,8, Yasuo Yoshikuni9,10,11,12,13.
Abstract
It is generally believed that exchange of secondary metabolite biosynthetic gene clusters (BGCs) among closely related bacteria is an important driver of BGC evolution and diversification. Applying this idea may help researchers efficiently connect many BGCs to their products and characterize the products' roles in various environments. However, existing genetic tools support only a small fraction of these efforts. Here, we present the development of chassis-independent recombinase-assisted genome engineering (CRAGE), which enables single-step integration of large, complex BGC constructs directly into the chromosomes of diverse bacteria with high accuracy and efficiency. To demonstrate the efficacy of CRAGE, we expressed three known and six previously identified but experimentally elusive non-ribosomal peptide synthetase (NRPS) and NRPS-polyketide synthase (PKS) hybrid BGCs from Photorhabdus luminescens in 25 diverse γ-Proteobacteria species. Successful activation of six BGCs identified 22 products for which diversity and yield were greater when the BGCs were expressed in strains closely related to the native strain than when they were expressed in either native or more distantly related strains. Activation of these BGCs demonstrates the feasibility of exploiting their underlying catalytic activity and plasticity, and provides evidence that systematic approaches based on CRAGE will be useful for discovering and identifying previously uncharacterized metabolites.Entities:
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Year: 2019 PMID: 31611640 DOI: 10.1038/s41564-019-0573-8
Source DB: PubMed Journal: Nat Microbiol ISSN: 2058-5276 Impact factor: 17.745