Dolphin: a tool for automatic targeted metabolite profiling using 1D and 2D (1)H-NMR data.

Area of Science:

• Metabolomics
• Nuclear Magnetic Resonance (NMR) Spectroscopy
• Computational Biology

Background:

• Nuclear magnetic resonance (NMR) metabolomics faces challenges in high-throughput, automated, and reproducible analysis of large spectral datasets.
• Current software for metabolite matching and quantification in NMR spectra is largely manual, leading to inconsistencies and low-resolution results.

Purpose of the Study:

• To introduce Dolphin, a novel software package for automated metabolite quantification in NMR metabolomics.
• To overcome the limitations of 1D (1)H-NMR spectra by utilizing 2D NMR techniques for enhanced reliability and accuracy.

Main Methods:

• Dolphin employs a fully automated approach for quantifying target metabolites across multiple samples.
• It leverages 2D J-resolved NMR spectroscopy for improved signal dispersion and consistent signal position detection.
• The software utilizes 2D NMR spectra to gather additional information on neighboring signals for enhanced quantification accuracy.

Main Results:

• Dolphin demonstrated more accurate targeted profiling results compared to two established NMR metabolomics approaches.
• The software provides a fully automated and high-throughput processing solution for NMR metabolomics data.
• Enhanced reliability and confidence in metabolite matching were achieved through the use of 2D NMR signal dispersion.

Conclusions:

• Dolphin offers a significant advancement in NMR metabolomics by providing automated, high-throughput, and accurate metabolite quantification.
• The software's reliance on 2D NMR techniques addresses key limitations of existing manual and 1D-based methods.
• Dolphin enhances the reproducibility and confidence of metabolic profiling in complex biological mixtures.