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.2024 Apr 9;96(14):5478-5488.
doi: 10.1021/acs.analchem.3c05576. Epub 2024 Mar 26.

Tandem Mass Spectrometry across Platforms

Affiliations

Tandem Mass Spectrometry across Platforms

Corey Hoang et al. Anal Chem..

Abstract

PubChem serves as a comprehensive repository, housing over 100 million unique chemical structures representing the breadth of our chemical knowledge across numerous fields including metabolism, pharmaceuticals, toxicology, cosmetics, agriculture, and many more. Rapid identification of these small molecules increasingly relies on electrospray ionization (ESI) paired with tandem mass spectrometry (MS/MS), particularly by comparison to genuine standard MS/MS data sets. Despite its widespread application, achieving consistency in MS/MS data across various analytical platforms remains an unaddressed concern. This study evaluated MS/MS data derived from one hundred molecular standards utilizing instruments from five manufacturers, inclusive of quadrupole time-of-flight (QTOF) and quadrupole orbitrap "exactive" (QE) mass spectrometers by Agilent (QTOF), Bruker (QTOF), SCIEX (QTOF), Waters (QTOF), and Thermo QE. We assessed fragment ion variations at multiple collisional energies (0, 10, 20, and 40 eV) using the cosine scoring algorithm for comparisons and the number of fragments observed. A parallel visual analysis of the MS/MS spectra across instruments was conducted, consistent with a standard procedure that is used to circumvent the still prevalent issue of mischaracterizations as shown for dimethyl sphingosine and C20 sphingosine. Our analysis revealed a notable consistency in MS/MS data and identifications, with fragment ions'm/z values exhibiting the highest concordance between instrument platforms at 20 eV, the other collisional energies (0, 10, and 40 eV) were significantly lower. While moving toward a standardized ESI MS/MS protocol is required for dependable molecular characterization, our results also underscore the continued importance of corroborating MS/MS data against standards to ensure accurate identifications. Our findings suggest that ESI MS/MS manufacturers, akin to the established norms for gas chromatography mass spectrometry instruments, should standardize the collision energy at 20 eV across different instrument platforms.

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Conflict of interest statement

The authors declare no competing financial interest.

Figures

Figure 1
Figure 1
Comparative analysis of cosine scoresfrom MS/MS spectra acrossmultiple instrument platforms. (A,B) Cosine similarity scores obtainedfrom the MS/MS data of 100 molecular standards. Five different platformswere evaluated: Waters, SCIEX, Thermo, Bruker, and Agilent, with thelatter serving as a control. The scores were calculated at four collisionenergy levels: 0, 10, 20, and 40 eV. The dashed line in (B) representsthe average. (C) MS/MS data of γ-Glu-Leu (20 eV) and (D) probenecid(20 eV) provide examples of MS/MS data with high (0.93) and low (0.63)cosine scores.
Figure 2
Figure 2
Comparison of collision energies across platforms. TheMS/MS dataat 20 eV most consistently allowed for identifications across thedifferent platforms. Comparative analysis of molecular standards observedacross the different collision energies demonstrated (left) in thecolor-coded plot depicts the 100 standards with very light green depictingno match, light green depicting one instrument match, medium greentwo instrument matches, and dark green three instrument matches. Thetop Venn diagrams depict the hit observations at the different collisionenergies for Bruker, Thermo, and SCIEX as compared to those of Agilent.Waters data assessment was limited to manual inspection, and thereforea comprehensive analysis was not included here. The MS/MS data forstructurally distinct dimethyl sphingosine (Bruker and Thermo) andC20-sphingosine (Agilent) which have the same elemental compositiondepict the potential of misidentification (respective cosine scoresare 0.998 and 0.993) based on relatively small variations in fragmention intensity.
Figure 3
Figure 3
MS/MS datagenerated on the protease inhibitor Z-FA-FMK.
Figure 4
Figure 4
MS/MS data generated on the endogenous lipid metabolitesphingosine.
Figure 5
Figure 5
MS/MS data generated on the endogenous lipid metaboliteN-oleoyl ethanolamine.
Figure 6
Figure 6
MS/MS data generated on atrazine mercapurate, glutathione-derivedmetabolite of atrazine, an herbicide.
Figure 7
Figure 7
MS/MS data generated on the endogenous lipid metaboliteN-oleoyl glycine.
Figure 8
Figure 8
MS/MS data generated on the drug molecule BTZ043.
Figure 9
Figure 9
MS/MS data generated on caffeine.
See this image and copyright information in PMC

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