Automatic differential analysis of NMR experiments in complex samples

TL;DR

This paper introduces Plasmodesma, an automated software tool for processing and analyzing large sets of NMR experiments in complex samples, facilitating natural product discovery and metabolomics.

Contribution

The paper presents a novel, fully automated program for processing diverse NMR data, enabling unsupervised analysis of complex mixtures in natural product research.

Findings

Successfully detected small amounts of artemisinin in plant extracts

Generated spectral fingerprints for complex mixtures

Demonstrated utility in natural product discovery

Abstract

Liquid state NMR is a powerful tool for the analysis of complex mixtures of unknown molecules. This capacity has been used in many analytical approaches: metabolomics, identification of active compounds in natural extracts, characterization of species, and such studies require the acquisition of many diverse NMR measurements on series of samples. While acquisition can easily be performed automatically, the number of NMR experiments involved in these studies increases very rapidly and this data avalanche requires to resort to automatic processing and analysis. We present here a program that allows the autonomous, unsupervised processing of a large corpus of 1D, 2D and DOSY experiments from a series of samples acquired in different conditions. The program provides all the signal processing steps, as well as peak-picking and bucketing of 1D and 2D spectra, the program and its components are fully available. In an experiment mimicking the search of an active species in natural extract, we use it for the automatic detection of small amounts of artemisin added to a series of plant extracts, and for the generation of the spectral fingerprint of this molecules. This program called Plasmodesma is a novel tool which should be useful to decipher complex mixtures, particularly in the discovery of biologically active natural products from plants extracts, but can also in drug discovery or metabolomics studies.