Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Mass spectrometry-guided genome mining as a tool to uncover novel natural products

Sigrist, Renata, Paulo, Bruno S., Angolini, Célio F. F. and Gonzaga De Oliveira, Luciana 2020. Mass spectrometry-guided genome mining as a tool to uncover novel natural products. Journal of Visualized Experiments 157 , e60825. 10.3791/60825

Full text not available from this repository.

Abstract

A mass spectrometry-guided genome mining protocol is established and described here. It is based on genome sequence information and LC-MS/MS analysis and aims to facilitate identification of molecules from complex microbial and plant extracts. The chemical space covered by natural products is immense and widely unrecognized. Therefore, convenient methodologies to perform wide-ranging evaluation of their functions in nature and potential human benefits (e.g., for drug discovery applications) are desired. This protocol describes the combination of genome mining (GM) and molecular networking (MN), two contemporary approaches that match gene cluster-encoded annotations in whole genome sequencing with chemical structure signatures from crude metabolic extracts. This is the first step towards the discovery of new natural entities. These concepts, when applied together, are defined here as MS-guided genome mining. In this method, the main components are previously designated (using MN), and structurally related new candidates are associated with genome sequence annotations (using GM). Combining GM and MN is a profitable strategy to target new molecule backbones or harvest metabolic profiles in order to identify analogues from already known compounds.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Chemistry
Publisher: MyJove Corporation
ISSN: 1940-087X
Last Modified: 14 Nov 2022 16:06
URI: https://orca.cardiff.ac.uk/id/eprint/153716

Actions (repository staff only)

Edit Item Edit Item