An integrated workflow for phenazine-modifying enzyme characterization. (1st July 2018)

• Record Type: Journal Article
• Authors: Coates, R Cameron; Bowen, Benjamin P; Oberortner, Ernst; Thomashow, Linda; Hadjithomas, Michalis; Zhao, Zhiying; Ke, Jing; Silva, Leslie; Louie, Katherine; Wang, Gaoyan; Robinson, David; Tarver, Angela; Hamilton, Matthew; Lubbe, Andrea; Feltcher, Meghan; Dangl, Jeffery L; Pati, Amrita; Weller, David; Northen, Trent R; Cheng, Jan-Fang; Mouncey, Nigel J; Deutsch, Samuel; Yoshikuni, Yasuo
• Is Part Of: Journal of industrial microbiology & biotechnology. Volume 45:Number 7(2018)
• Page Start: 567
• Page End: 577
• Publication Date: 2018-07-01
• Subjects: Synthetic biology -- Biosynthesis -- Phenazine -- Pathway -- Refactored -- Pathway design; Industrial microbiology -- Periodicals; 660.62
• DOI: 10.1007/s10295-018-2025-5
• Languages: English
• ISSNs: 1367-5435

Abstract

Abstract: Increasing availability of new genomes and putative biosynthetic gene clusters (BGCs) has extended the opportunity to access novel chemical diversity for agriculture, medicine, environmental and industrial purposes. However, functional characterization of BGCs through heterologous expression is limited because expression may require complex regulatory mechanisms, specific folding or activation. We developed an integrated workflow for BGC characterization that integrates pathway identification, modular design, DNA synthesis, assembly and characterization. This workflow was applied to characterize multiple phenazine-modifying enzymes. Phenazine pathways are useful for this workflow because all phenazines are derived from a core scaffold for modification by diverse modifying enzymes (PhzM, PhzS, PhzH, and PhzO) that produce characterized compounds. We expressed refactored synthetic modules of previously uncharacterized phenazine BGCs heterologously in Escherichia coli and were able to identify metabolic intermediates they produced, including a previously unidentified metabolite. These results demonstrate how this approach can accelerate functional characterization of BGCs.