A chemistry-first approach to uncovering novel natural products from a proprietary strain collection of rare and unexplored bacteria
Lead Research Organisation:
University of Nottingham
Department Name: Sch of Chemistry
Abstract
This project is a new collaboration, combining the expertise in the O'Neill lab in high throughput molecular networking and genome mining and the unique strain library and industrial experience in Bactobio to take a chemistry-first approach in discovering novel natural products for application in pharmaceutical or agritech industries.
The key enabling technology for this research is mass-spectrometry based molecular networking, enhanced with machine learning algorithms, operated through the GNPS platform. This analyses complex cell extracts and identifies which compounds to focus research efforts on, avoiding compound rediscovery. In the O'Neill lab we have used this technique to analyse 146 bacterial species, identifying 15 families of natural products, and we recently discovered a new family of cyclic lipopetides.
The key enabling technology for this research is mass-spectrometry based molecular networking, enhanced with machine learning algorithms, operated through the GNPS platform. This analyses complex cell extracts and identifies which compounds to focus research efforts on, avoiding compound rediscovery. In the O'Neill lab we have used this technique to analyse 146 bacterial species, identifying 15 families of natural products, and we recently discovered a new family of cyclic lipopetides.
People |
ORCID iD |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| BB/T008369/1 | 30/09/2020 | 29/09/2028 | |||
| 2886339 | Studentship | BB/T008369/1 | 30/09/2023 | 29/09/2027 |