Correcting for natural isotope abundance and tracer impurity in MS-, MS/MS- and high-resolution-multiple-tracer-data from stable isotope labeling experiments with IsoCorrectoR

Paul Heinrich,Rainer Spang,Paul Kuerner,Peter J Oefner,Katja Dettmer,Lisa Ellmann,Christian Kohler

doi:10.1038/s41598-018-36293-4

Abstract

Experiments with stable isotope tracers such as 13C and 15N are increasingly used to gain insights into metabolism. However, mass spectrometric measurements of stable isotope labeling experiments should be corrected for the presence of naturally occurring stable isotopes and for impurities of the tracer substrate. Here, we analyzed the effect that such correction has on the data: omitting correction or performing invalid correction can result in largely distorted data, potentially leading to misinterpretation. IsoCorrectoR is the first R-based tool to offer said correction capabilities. It is easy-to-use and comprises all correction features that comparable tools can offer in a single solution: correction of MS and MS/MS data for natural stable isotope abundance and tracer impurity, applicability to any tracer isotope and correction of multiple-tracer data from high-resolution measurements. IsoCorrectoR’s correction performance agreed well with manual calculations and other available tools including Python-based IsoCor and Perl-based ICT. IsoCorrectoR can be downloaded as an R-package from: http://bioconductor.org/packages/release/bioc/html/IsoCorrectoR.html.

Highlights

In a B-cell line with an inducible Myc-allele, a substantial upregulation of glutamine usage for TCA cycle intermediates and amino acids could be detected upon inducing Myc[6]
Data from stable isotope tracer experiments and data to be employed in metabolic flux analysis should not be used without appropriate data correction
Metabolites that have incorporated the impure tracer will contribute to signals of lower than expected mass in mass spectrometry

Summary

Introduction

In a B-cell line with an inducible Myc-allele, a substantial upregulation of glutamine usage for TCA cycle intermediates and amino acids could be detected upon inducing Myc[6]. It is mandatory to correct for natural stable isotope abundance prior to data interpretation/ modeling[4,7] Another aspect to be considered concerns tracer (im-)purity. There are already a few tools available for the correction of data from stable isotope labeling experiments. MS-X-Corr (Matlab) is capable of correcting MS and MS/MS data for natural isotope abundance, but not for tracer impurity. IsoCorrectoR, which is introduced here, is the first R-based tool for the correction of data from stable isotope labeling experiments. In contrast to IsoCor and ICT, IsoCorrectoR can handle labeling experiments employing multiple tracers such as 13C and 15N simultaneously, which have become feasible with the introduction of high-resolution mass spectrometers (e.g., the Orbitrap)[13,14]. Multi-tracer experiments require the correction of data for natural isotope abundance, as implemented in the Python-based tool PyNAC. In the contrast to PyNAC, IsoCorrectoR can correct multi-tracer data for tracer impurities, which is critical (see results section)[14,15]

Methods

Results

Conclusion