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Title: Molecular Networking and Pattern-Based Genome Mining Improves Discovery of Biosynthetic Gene Clusters and their Products from Salinispora Species

Genome sequencing has revealed that bacteria contain many more biosynthetic gene clusters than predicted based on the number of secondary metabolites discovered to date. While this biosynthetic reservoir has fostered interest in new tools for natural product discovery, there remains a gap between gene cluster detection and compound discovery. In this paper, we apply molecular networking and the new concept of pattern-based genome mining to 35 Salinispora strains, including 30 for which draft genome sequences were either available or obtained for this study. The results provide a method to simultaneously compare large numbers of complex microbial extracts, which facilitated the identification of media components, known compounds and their derivatives, and new compounds that could be prioritized for structure elucidation. Finally, these efforts revealed considerable metabolite diversity and led to several molecular family-gene cluster pairings, of which the quinomycin-type depsipeptide retimycin A was characterized and linked to gene cluster NRPS40 using pattern-based bioinformatic approaches.
Authors:
 [1] ;  [1] ;  [1] ;  [1] ;  [1] ;  [1] ;  [2] ;  [2] ;  [3] ;  [2] ;  [1]
  1. Univ. of California, San Diego, CA (United States). Scripps Inst. of Oceanography
  2. Univ. of California, San Diego, CA (United States)
  3. Univ. of California, San Diego, CA (United States). Scripps Inst. of Oceanography; Univ. of California, San Diego, CA (United States)
Publication Date:
Grant/Contract Number:
AC02-05CH11231
Type:
Published Article
Journal Name:
Chemistry & Biology
Additional Journal Information:
Journal Volume: 22; Journal Issue: 4; Journal ID: ISSN 1074-5521
Publisher:
Elsevier
Research Org:
Univ. of California, San Diego, CA (United States)
Sponsoring Org:
USDOE Office of Science (SC)
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES
OSTI Identifier:
1393314
Alternate Identifier(s):
OSTI ID: 1344453

Duncan, Katherine R., Crüsemann, Max, Lechner, Anna, Sarkar, Anindita, Li, Jie, Ziemert, Nadine, Wang, Mingxun, Bandeira, Nuno, Moore, Bradley S., Dorrestein, Pieter C., and Jensen, Paul R.. Molecular Networking and Pattern-Based Genome Mining Improves Discovery of Biosynthetic Gene Clusters and their Products from Salinispora Species. United States: N. p., Web. doi:10.1016/j.chembiol.2015.03.010.
Duncan, Katherine R., Crüsemann, Max, Lechner, Anna, Sarkar, Anindita, Li, Jie, Ziemert, Nadine, Wang, Mingxun, Bandeira, Nuno, Moore, Bradley S., Dorrestein, Pieter C., & Jensen, Paul R.. Molecular Networking and Pattern-Based Genome Mining Improves Discovery of Biosynthetic Gene Clusters and their Products from Salinispora Species. United States. doi:10.1016/j.chembiol.2015.03.010.
Duncan, Katherine R., Crüsemann, Max, Lechner, Anna, Sarkar, Anindita, Li, Jie, Ziemert, Nadine, Wang, Mingxun, Bandeira, Nuno, Moore, Bradley S., Dorrestein, Pieter C., and Jensen, Paul R.. 2015. "Molecular Networking and Pattern-Based Genome Mining Improves Discovery of Biosynthetic Gene Clusters and their Products from Salinispora Species". United States. doi:10.1016/j.chembiol.2015.03.010.
@article{osti_1393314,
title = {Molecular Networking and Pattern-Based Genome Mining Improves Discovery of Biosynthetic Gene Clusters and their Products from Salinispora Species},
author = {Duncan, Katherine R. and Crüsemann, Max and Lechner, Anna and Sarkar, Anindita and Li, Jie and Ziemert, Nadine and Wang, Mingxun and Bandeira, Nuno and Moore, Bradley S. and Dorrestein, Pieter C. and Jensen, Paul R.},
abstractNote = {Genome sequencing has revealed that bacteria contain many more biosynthetic gene clusters than predicted based on the number of secondary metabolites discovered to date. While this biosynthetic reservoir has fostered interest in new tools for natural product discovery, there remains a gap between gene cluster detection and compound discovery. In this paper, we apply molecular networking and the new concept of pattern-based genome mining to 35 Salinispora strains, including 30 for which draft genome sequences were either available or obtained for this study. The results provide a method to simultaneously compare large numbers of complex microbial extracts, which facilitated the identification of media components, known compounds and their derivatives, and new compounds that could be prioritized for structure elucidation. Finally, these efforts revealed considerable metabolite diversity and led to several molecular family-gene cluster pairings, of which the quinomycin-type depsipeptide retimycin A was characterized and linked to gene cluster NRPS40 using pattern-based bioinformatic approaches.},
doi = {10.1016/j.chembiol.2015.03.010},
journal = {Chemistry & Biology},
number = 4,
volume = 22,
place = {United States},
year = {2015},
month = {4}
}