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Characterization of the Spectral Accuracy of an Orbitrap Mass Analyzer Using Isotope Ratio Mass Spectrometry

NCJ Number
Analytical Chemistry Volume: 90 Issue: 3 Dated: 2018 Pages: 1897-1906
Date Published
10 pages

To investigate the effects of different ion populations on an Orbitrap's spectral accuracy (SA) and mass measurement accuracy (MMA), a solution of caffeine, the tetrapeptide MRFA, and ultramark was analyzed using a Q Exactive Plus across eight distinct automatic gain control (AGC) targets, and the same compounds from the same lot numbers were also individually analyzed using isotope ratio mass spectrometry (IRMS) to accurately determine the isotopic abundance of 13C, 15N, and 34S.


Infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) source coupled to the Q Exactive Plus has been extensively used in untargeted mass spectrometry imaging (MSI) analyses of biological tissue sections. Although the Orbitrap is a high-resolution and accurate-mass (HRAM) mass analyzer, these attributes alone cannot be used for the reliable identification of unknown analytes observed in complex biological matrices. Spectral accuracy (SA) is the ability of the mass spectrometer to accurately measure the isotopic distributions which, when used with high mass measurement accuracy (MMA), can facilitate the elucidation of a single elemental composition. The current project demonstrated that at optimum absolute ion abundances, the Orbitrap can be used to accurately count carbons, nitrogens, and sulfurs in samples with varying masses. In addition, absolute monoisotopic ion abundances required for high SA were empirically determined by using the expected (IRMS) and experimental (Orbitrap) isotopic distributions to calculate the Pearson chi-square test. These thresholds for absolute ion abundances can be used in untargeted MSI studies to shorten an identification list by rapidly screening for isotopic distributions whose absolute ion abundances are high enough to accurately estimate the number of atoms. (publisher abstract modified)

Date Published: January 1, 2018