Enhanced correlation-based linking of biosynthetic gene clusters to their metabolic products through chemical class matching.

ABSTRACT:

Background

It is well-known that the microbiome produces a myriad of specialised metabolites with diverse functions. To better characterise their structures and identify their producers in complex samples, integrative genome and metabolome mining is becoming increasingly popular. Metabologenomic co-occurrence-based correlation scoring methods facilitate the linking of metabolite mass fragmentation spectra (MS/MS) to their cognate biosynthetic gene clusters (BGCs) based on shared absence/presence patterns of metabolites and BGCs in paired omics datasets of multiple strains. Recently, these methods have been made more readily accessible through the NPLinker platform. However, co-occurrence-based approaches usually result in too many candidate links to manually validate. To address th

SUBMITTER: Louwen JJR 

PROVIDER: S-EPMC9869629 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature