Development of an NMR-Based Platform for the Direct Structural Annotation of Complex Natural Products Mixtures

Abstract

The development of new "omics" platforms is having a significant impact on the landscape of natural products discovery. However, despite the advantages that such platforms bring to the field, there remains no straightforward method for characterizing the chemical landscape of natural products libraries using two-dimensional nuclear magnetic resonance (2D-NMR) experiments. NMR analysis provides a powerful complement to mass spectrometric approaches, given the universal coverage of NMR experiments. However, the high degree of signal overlap, particularly in one-dimensional NMR spectra, has limited applications of this approach. To address this issue, we have developed a new data analysis platform for complex mixture analysis, termed MADByTE (Metabolomics and Dereplication by Two-Dimensional Experiments). This platform employs a combination of TOCSY and HSQC spectra to identify spin system features within complex mixtures and then matches spin system features between samples to create a chemical similarity network for a given sample set. In this report we describe the design and construction of the MADByTE platform and demonstrate the application of chemical similarity networks for both the dereplication of known compound scaffolds and the prioritization of bioactive metabolites from a bacterial prefractionated extract library.

Figure 1.

MADByTE Workflow. Following raw data acquisition and standard processing steps (Fourier transform, linear prediction, reconstruction phase correction, supervised peak picking; yellow box) Two stages of analysis are performed: Per-sample processing (blue box) constructs spin system features (SSF) for each sample independently from each set of spectra. After each sample is processed, the sample comparison step (green box) calculates the correlation matrix relating each spin system by similarity. The correlation matrix is then used to generate the three network outputs (Outputs 1, 2, and 3).

Figure 2.

The graphical user interface (GUI). A) Analysis setup window, including user-modifiable parameters and lists of optional reference spectra for inclusion in analysis. B) Native NMR plotting for spectral review, including options for viewing both 1D spectra and points derived from HSQC and TOCSY processing. C) Network results view, including interactive tools that allow users to highlight nodes of interest and display the NMR signals used for their construction. D) Example of network filtration based on spin system size, performed using the bottom slider, to include only spin system features containing a defined number of spin system members.

Figure 3.

Full association network of examples from standards reference set. Shared spin systems (colored node borders) were mapped back to common structural elements (corresponding color) by comparison to published chemical shift assignments. For example, the central cluster of macrocyclic compounds azithromycin (3), erythromycin (4), and roxithromycin (5) contains spin systems from the cladinose sugar (blue border) and a portion of the macrocyclic core (pink border). A complete version of this network including all reference compounds is available in the Supporting Information (Figure S5).

Figure 4.

Full annotation network illustrating extract prefractions containing spiked reference compounds (green, gold, and pink nodes), spin system features (grey nodes), and pure compound reference data (blue nodes; erthromycin (4), mupirocin (9), and novobiocin (10))

Figure 5.

Identification of novobiocin in natural products library prefractions. A) Hybrid network of 85 extract prefractions and reference compounds. B) Expanded region from panel A showing node connections between novobiocin (10) and extract prefractions 1565C and 1565D. C) Expansions of TOCSY and HSQC spectra showing resonances responsible for node connections in panel B. D) HRMS spectra of novobiocin peak at 4.36 min. E) Extracted ion chromatograms for novobiocin (m/z 613.2378) in prefractions 1565C and 1565D, compared to novobiocin standard.

Figure 6.

A) Full association network for natural products extract library. Extract nodes color coded by bioactivity profile. B) Expansion of high activity region (dashed box in panel A), highlighting shared spin system features between prefractions (grey nodes marked with asterisks). C) Expansions of TOCSY spectra for active prefractions and bioactive component collismycin A (11). Shared spin system features highlighted in pink. D) Integration of the NMR data for collismycin A (11) (teal node) and subsequent reprocessing verified a match between the spin system features of the bioactive component and the spin system features from the original prefractions.