Optimized experimental workflow for tandem mass spectrometry molecular networking in metabolomics

Abstract

New omics sciences generate massive amounts of data, requiring to be sorted, curated, and statistically analyzed by dedicated software. Data-dependent acquisition mode including inclusion and exclusion rules for tandem mass spectrometry is routinely used to perform such analyses. While acquisition parameters are well described for proteomics, no general rule is currently available to generate reliable metabolomic data for molecular networking analysis on the Global Natural Product Social Molecular Networking platform (GNPS). Following on from an exploration of key parameters influencing the quality of molecular networks, universal optimal acquisition conditions for metabolomic studies are suggested in the present paper. The benefit of data pre-clustering before initiating large datasets for GNPS analyses is also demonstrated. Moreover, an efficient workflow dedicated to Agilent Technologies instruments is described, making the dereplication process easier by unambiguously distinguishing isobaric isomers eluted at different retention times, annotating the molecular networks with chemical formulas, and giving access to semi-quantitative data. This specific workflow foreshadows future developments of the GNPS platform.

Extending compound identification for molecular network using the LipidXplorer database independent method: A proof of concept using glycoalkaloids from Solanum pseudoquina A. St.‐Hil.

“…The latest development in structure elucidation and database matching is molecular networking, a visualisation tool designed to address structure elucidation of different compounds based on MS 2 spectra similarity. It is done online using the Global Natural Products Social Molecular Network (GNPS) web service that also provides comparison of experimental MS spectra to freely available databases for direct compound identification . The molecular networks (MNs) are generated calculating the cosine similarities between MS fragmentograms and connects precursor mass labelled nodes accordingly.…”

“…It is done online using the Global Natural Products Social Molecular Network (GNPS) web service that also provides comparison of experimental MS spectra to freely available databases for direct compound identification. [5][6][7][8][9][10] The molecular networks (MNs) are generated calculating the cosine similarities between MS fragmentograms and connects precursor mass labelled nodes accordingly. The size of the network depends on cosine threshold values settled.…”

Mass spectrometry-based metabolomics approach in the isolation of bioactive natural products

“…Therefore, the absence of a class of structurally-related active compounds could hinder the dereplication process. In this case, it could result in nodes that do not link to other groups (self-loop) 15 . Moreover, even when no hits are found in the databank, the organization in clusters (with similar fragmentation profiles) performed by GNPS facilitates analyzing the results and dereplication process.…”

Metabolômica Microbiana: Inovações E Aplicações

“…121 Na plataforma GNPS (gnps.ucsd.edu) é possível carregar os dados de MS/MS online e gerar o molecular networking, podendo ser visualizado na plataforma ou utilizando softwares como o Cytoscape. 142 O MN foi aplicado na elucidação estrutural de diversos metabólitos provenientes de comunidades microbianas multiespécies sintéticas. Nesse caso, os metabólitos conhecidos das culturas individuais auxiliaram na descoberta de diferentes metabólitos presentes nas co-culturas.…”