A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets

Metabolites

William J. Carreer¹  Robert M. Flight¹ 

[1] Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY 40536, USA;

关键词: stable isotope tracing;    stable isotope-resolved metabolomics;    Fourier transform mass spectrometry;    multi-isotope natural abundance correction;    analytical derivation;    parallelization;   

DOI  :  10.3390/metabo3040853

来源: mdpi

【 摘 要 】

New metabolomics applications of ultra-high resolution and accuracy mass spectrometry can provide thousands of detectable isotopologues, with the number of potentially detectable isotopologues increasing exponentially with the number of stable isotopes used in newer isotope tracing methods like stable isotope-resolved metabolomics (SIRM) experiments. This huge increase in usable data requires software capable of correcting the large number of isotopologue peaks resulting from SIRM experiments in a timely manner. We describe the design of a new algorithm and software system capable of handling these high volumes of data, while including quality control methods for maintaining data quality. We validate this new algorithm against a previous single isotope correction algorithm in a two-step cross-validation. Next, we demonstrate the algorithm and correct for the effects of natural abundance for both ¹³C and ¹⁵N isotopes on a set of raw isotopologue intensities of UDP-N-acetyl-D-glucosamine derived from a ¹³C/¹⁵N-tracing experiment. Finally, we demonstrate the algorithm on a full omics-level dataset.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.