1D "Spikelet" Projections from Heteronuclear 2D NMR Data-Permitting 1D Chemometrics While Preserving 2D Dispersion.

Maryam Tabatabaei Anaraki,Myrna Simpson,Martine Monnette,André Simpson,Ronald Soong,Wolfgang Bermel,Rudraksha Dutta Majumdar

doi:10.3390/metabo9010016

Maryam Tabatabaei Anaraki, Myrna Simpson + Show 5 more

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https://doi.org/10.3390/metabo9010016

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Abstract

Nuclear magnetic resonance (NMR) spectroscopy is a powerful tool for the non-targeted metabolomics of intact biofluids and even living organisms. However, spectral overlap can limit the information that can be obtained from 1D 1H NMR. For example, magnetic susceptibility broadening in living organisms prevents any metabolic information being extracted from solution-state 1D 1H NMR. Conversely, the additional spectral dispersion afforded by 2D 1H-13C NMR allows a wide range of metabolites to be assigned in-vivo in 13C enriched organisms, as well as a greater depth of information for biofluids in general. As such, 2D 1H-13C NMR is becoming more and more popular for routine metabolic screening of very complex samples. Despite this, there are only a very limited number of statistical software packages that can handle 2D NMR datasets for chemometric analysis. In comparison, a wide range of commercial and free tools are available for analysis of 1D NMR datasets. Overtime, it is likely more software solutions will evolve that can handle 2D NMR directly. In the meantime, this application note offers a simple alternative solution that converts 2D 1H-13C Heteronuclear Single Quantum Correlation (HSQC) data into a 1D “spikelet” format that preserves not only the 2D spectral information, but also the 2D dispersion. The approach allows 2D NMR data to be converted into a standard 1D Bruker format that can be read by software packages that can only handle 1D NMR data. This application note uses data from Daphnia magna (water fleas) in-vivo to demonstrate how to generate and interpret the converted 1D spikelet data from 2D datasets, including the code to perform the conversion on Bruker spectrometers.

Highlights

Heteronuclear 2D Nuclear magnetic resonance (NMR) provides superior spectral dispersion over one-dimensional (1D) datasets.The 1D 1 H spectra have been reported to have a peak capacity of ~3000, while that of 2D 1 H-13 C approaches 2,000,000 [1]
This becomes very important for the metabolomics studies of very complex samples that show poor resolution in 1D NMR
The question becomes: is it possible to preserve all the information from a 2D 1 H-13 C Heteronuclear Single Quantum Correlation (HSQC) spectrum while generating a standard 1D format compatible with chemometrics and statistical packages? In the present application note, we describe the generation of such a format—1D spikelet—and demonstrate its applicability using both principal component analysis (PCA) and quantile plots as examples

Summary

Introduction

The 1D 1 H spectra have been reported to have a peak capacity of ~3000, while that of 2D 1 H-13 C approaches 2,000,000 [1]. This becomes very important for the metabolomics studies of very complex samples that show poor resolution in 1D NMR (due to a combination of magnetic susceptibility distortions and sample complexity). Stable 13 C isotopic labeling [9,10,11,12] of organisms or live cells [13,14,15], has emerged as powerful approaches to overcome poor resolution and resonance overlap. In most of these studies 1D NMR, such as 13 C NMR, is commonly acquired, as chemometric software packages that directly handle 2D NMR data are still limited [16,17,18,19]

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