The work outlined in this proposal is designed to establish a new turnkey natural product discovery platform -- from the development of model strains and streamlined methods for the capture and bioinformatics identification of novel biosynthetic diversity, through to the expression and characterization of natural products themselves. Our efforts will culminate in the development of not only a new natural product discovery pipeline but also a series of tools/resources (optimized strains, improved cluster cloning and annotation methods, improved gene/genome editing methods for strains from natural product producing phyla, etc.) that are designed to remove existing roadblocks in the conversion of genomic DNA into natural products. Our approach strives to develop tools that will minimize the manipulations required for molecule production from DNA sequence and, thereby, maximize the potential for truly high throughput small molecule discovery pipelines. In our First Aim we will develop improved model hosts from Phyla that are traditionally associated with natural product discovery (actinomycetes, /?-proteobacteria), by empirically selecting bacterial strains that show the greatest innate tendency for natural product production. Then, using modern synthetic biology/genome editing tools and high throughput empirical cluster expression screening, we will further optimize these strains to improve their ability to transcriptionally indce and support the production of natural products from diverse collections of biosynthetic gene clusters.
The Second Aim focuses on establishing protocols for using modern genome/gene cluster editing tools (CRISPR, MAGE) in model natural product producing genera. In our Third Aim, we propose to develop a bioinformatics pipeline for identifying gene cluster families that, by gene content and/or gene organization, do not resemble any known gene cluster family (i.e. cryptic gene cluster families, CCF).
The Third Aim also establishes improved cluster cloning and annotation methods that will allow for the rapid archiving of microbial biosynthetic diversity (whether from cultured or uncultured microbes) in a single format that can be easily annotated and mined for CCFs using minimal sequencing effort. In our Fourth Aim we propose to leverage the new tools developed in Aims 1-3 to establish methods for more efficiently accessing natural products from DNA sequence.
This Aim i ncludes the establishment of an improved functional (meta)genomics platform as well as two scalable CRISPR-based, gene cluster agnostic, activation strategies that take advantage of either the in vivo or in vitro ability of the CRISPR system to simultaneously target multiple promoter regions within a cluster for transcriptional activation.
This aim also includes the development of methods for semi-automated, MS/NMR-based structural evaluation of heterologously produced natural products present in broth extracts from small-scale fermentations. Our discovery strategy provides successively more aggressive cluster induction methods and we believe, as a whole, represents a robust, comprehensive approach for accessing natural products from genomic sequence.

Public Health Relevance

This proposal is designed to develop a turnkey, natural product discovery methodology (from biodiversity to natural products) leveraging modern bioinformatics and synthetic biology to gain access to natural products from genomic DNA. The methods developed here should provide the tools necessary to access a wide variety of biologically active, medicinally relevant, natural products that, until now, have remained hidden in the environment.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01GM110714-05
Application #
9690737
Study Section
Special Emphasis Panel (ZGM1)
Program Officer
Sledjeski, Darren D
Project Start
2015-07-07
Project End
2020-04-30
Budget Start
2019-05-01
Budget End
2020-04-30
Support Year
5
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Rockefeller University
Department
Genetics
Type
Graduate Schools
DUNS #
071037113
City
New York
State
NY
Country
United States
Zip Code
10065
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