Target-based genome mining of natural products and heterologous expression in Escherichia coli : choosing and accessing the natural world's menu of potential antibiotics
Abstract/Contents
- Abstract
- Expanding genomic databases show that many microorganisms harbor polyketide synthase (PKS) gene clusters, many of which encode natural products with valuable antibacterial properties. However, identifying and accessing novel and useful PKS activities remain challenging, as many host organisms are uncultivable or do not express PKS genes in laboratory conditions, and from sequence data alone it is difficult to ascertain which gene clusters are the most promising. Here I present efforts to address these challenges. We first aimed to improve Escherichia coli as a heterologous host for production of polyketides originating from other bacteria. We studied 13 homologs of propionyl-CoA carboxylase (PCC), an essential enzyme for many PKS gene clusters. We built 13 strains of E. coli, each harboring a different PCC homolog. We observed variability in polyketide production amongst the 13 strains and identified optimal PCC homologs. Next, we leveraged commercial gene synthesis and a recently developed large DNA assembly pipeline to synthesize DNA encoding four PKS gene clusters, ranging in length from 30-40 kB and expressed them in recombinant E. coli strains. Untargeted metabolomics revealed cluster-specific compound production in two of the four strains. Follow-up experiments suggested that these compounds resulted from activity of the tailoring genes in the cluster, not the core PKS genes, and could represent modified endogenous metabolites in E. coli. This result illustrates a need for larger datasets of heterologous expression of PKSs in E. coli to more rapidly identify gene clusters resulting in novel and cluster-specific molecules. To identify PKS genes encoding clinically relevant antibiotics, we developed an automated method to identify and catalog clusters that harbor potential self-resistance genes. These genes, which are modified targets of the produced compounds, provide the cluster-harboring microorganisms a defense against the antibiotics produced by the clusters. We mined all National Center for Biotechnology Information (NCBI) nucleotide databases for known and putative antibacterial target genes from manually curated lists. With this approach, we generated a non-redundant catalog of PKS clusters harboring putative self-resistance genes. This method can be used to prioritize gene clusters producing compounds with new mechanisms of action, as well as to identify putative novel antibacterial targets.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2019; ©2019 |
| Publication date | 2019; 2019 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Vandova, Gergana Andreeva | |
|---|---|---|
| Degree supervisor | Davis, Ronald W. (Ronald Wayne), 1941- | |
| Thesis advisor | Davis, Ronald W. (Ronald Wayne), 1941- | |
| Thesis advisor | Khosla, Chaitan, 1964- | |
| Thesis advisor | Kim, Peter, 1958- | |
| Thesis advisor | Krasnow, Mark, 1956- | |
| Degree committee member | Khosla, Chaitan, 1964- | |
| Degree committee member | Kim, Peter, 1958- | |
| Degree committee member | Krasnow, Mark, 1956- | |
| Associated with | Stanford University, Department of Biochemistry. |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Gergana Vandova. |
|---|---|
| Note | Submitted to the Department of Biochemistry. |
| Thesis | Thesis Ph.D. Stanford University 2019. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2019 by Gergana Andreeva Vandova
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
Also listed in
Loading usage metrics...