Evaluation of Accurate Mass and Relative Isotopic Abundance Measurements in the LTQ-Orbitrap Mass Spectrometer for Further Metabolomics Database Building

Abstract

Recently, high-resolution mass spectrometry has been largely employed for compound identification, thanks to accurate mass measurements. As additional information, relative isotope abundance (RIA) is often needed to reduce the number of candidates prior to tandem MS(n). Here, we report on the evaluation of the LTQ-Orbitrap, in terms of accurate mass and RIA measurements for building further metabolomics spectral databases. Accurate mass measurements were achieved in the ppm range, using external calibration within 24 h, and remained at <5 ppm over a one-week period. The experimental relative abundances of (M+1) isotopic ions were evaluated in different data sets. First of all, 137 solutions of commercial compounds were analyzed by flow injection analysis in both the positive and negative ion modes. It was found that the ion abundance was the main factor impacting the accuracy of RIA measurements. It was possible to define some intensity thresholds above which errors were systematically <20% of their theoretical values. The same type of results were obtained with analyses from two biological media. Otherwise, no significant effect of ion transmission between the LTQ ion trap and the Orbitrap analyzer on RIA measurement errors was found, whereas the reliability of RIA measurements was dramatically improved by reducing the mass detection window. It was also observed that the signal integration method had a significant impact on RIA measurement errors, with the most-reliable results being obtained with peak height integrations. Finally, automatic integrations using the data preprocessing software XCMS and MZmine gave results similar to those obtained by manual integration, suggesting that it is relevant to use the RIA information in automatic elemental composition determination software from metabolomic peak tables.

Computational mass spectrometry for metabolomics: Identification of metabolites and small molecules

“…Extensive experimental determination (and optimization) of the mass accuracy and RIA for oa-TOF instruments have been performed [13,14]. For Orbitrap instruments, mass accuracy and dependency upon ion intensities were recently evaluated by Xu et al [15]. Here, the mass accuracy was characterized as less than 5 ppm with external calibration (although much lower values have been reported elsewhere), and RIA was found to be less than 20%.…”

“…The current FT-ICR-MS instruments with superconducting 12 Tesla (or stronger) magnets can easily exceed a resolution of 300,000 in routine measurements, and allow one to resolve the isotopic fine-structure of the individual 13 C, 15 N for the first isotope peak, or 18 O and 34 S isotopes. Deriving the elemental composition is then much simplified, and can be achieved by calculating the individual ratios to the monoisotopic peak [16].…”

Non-targeted screening approaches for contaminants and adulterants in food using liquid chromatography hyphenated to high resolution mass spectrometry

“…Higher resolving power is beneficial for complex sample matrices, especially if compounds are present in trace amounts [62]. An increase in resolving power can result in greater isotopic errors [63,64]; however, the error was below 5% for an Orbitrap instrument with 140,000 resolving power when the monoisoptopic peak abundance was sufficiently high [58]. In Orbitrap instruments, resolving power is related to scan speed.…”

Profiling of Genetically Modified Organisms Using Omics Technologies

“…Fourier transform ion-cyclotron (FT-ICR-MS) provides the highest mass resolution and accuracy, and enables the determination of the elemental compositions of metabolites, which facilitates annotation procedures for unknown compounds [95]. Direct infusion analysis of plant extract without a previous separation and/or derivatization can be achieved, however, its use is very restricted due to the equipment cost, the difficulties in hardware handling and the extremely large amount of data generated.…”