Collision-energy resolved ion mobility characterization of isomeric mixtures

Abstract

Existing instrumental resolving power limitations in ion mobility spectrometry (IMS) often restrict adequate characterization of unresolved or co-eluting chemical isomers. Recently, we introduced a novel chemometric deconvolution approach that utilized post-IM collision-induced dissociation (CID) mass spectrometry (MS) data to extract "pure" IM profiles and construct CID mass spectra of individual components from a mixture containing two IM-overlapped components [J. Am. Soc. Mass Spectrom., 2012, 23, 1873-1884]. In this manuscript we extend the capabilities of the IM-MS deconvolution methodology and demonstrate the utility of energy resolved IM deconvolution for successful characterization of ternary and quaternary isomer mixtures with overlapping IM profiles. Furthermore, we show that the success of IM-MS deconvolution is a collision-energy dependent process where different isomers can be identified at various ion fragmentation collision-energies. Details on how to identify a single collision-energy or suitable collision-energy ranges for successful characterization of isomer mixtures are discussed. To confirm the validity of the proposed approach, deconvoluted IM and MS spectra from IM overlapped analyte mixtures are compared to IM and MS data from individually run mixture components. Criteria for "successful" deconvolution of overlapping IM profiles and extraction of their corresponding pure mass spectra are discussed.

Determination of ion mobility collision cross sections for unresolved isomeric mixtures using tandem mass spectrometry and chemometric deconvolution

“…To check the validity of the deconvolution, we compared constructed CID mass spectra for each peptide from deconvolution of the data in Figure 1 to CID mass spectra of individually analyzed peptides (supporting information, Figure S2). The degree of similarity between deconvoluted and pure CID mass spectra were assessed using a previously described matching score ( R ) algorithm: 46 $$R=1-\frac{{\displaystyle {\sum }_{\mathrm{bold-italicm}=\mathrm{bold1}}^{\mathit{n}}\left|{\mathit{x}}_{\mathit{m}}-\mathrm{bold-italicx}{\prime }_{\mathit{m}}\right|}}{{\displaystyle {\sum }_{\mathrm{bold-italicm}=\mathrm{bold1}}^{\mathit{n}}\left({\mathit{x}}_{\mathit{m}}-\mathrm{bold-italicx}{\prime }_{\mathit{m}}\right)}}$$where n is the total number of fragment ion m/z values, m , with x m and x ′ m as fragment ion intensities (for a given value of m ) for pure and deconvoluted spectra, respectively. R values of 0 and 1 indicate no correlation and a perfect match, respectively.…”

“…R values of 0 and 1 indicate no correlation and a perfect match, respectively. 46 An R value of ≥0.75 was considered a “successful” threshold for our deconvolution. 46 Calculated R values for all deconvoluted reverse peptide isomer CID mass spectra were >0.86.…”

“…46 An R value of ≥0.75 was considered a “successful” threshold for our deconvolution. 46 Calculated R values for all deconvoluted reverse peptide isomer CID mass spectra were >0.86. Moreover, cross-validation matching scores ( R′ ) were calculated by comparing the deconvoluted CID mass spectra for each peptide isomer with the reference spectrum for the non-matching isomer.…”

“…Therefore, multiple calibration profiles would have to be generated to calculate CCSs for IM-unresolved species deconvoluted using different collision-energies. 46 Hence, it would be advantageous to correct ATs of deconvoluted IM profiles and fit them to a “conventional” low-energy CCS calibration plot.…”

“…TWIM-MS experiments were performed as previously described 37,39,42–44,46 using Synapt G1 (for the pentapeptide binary mixture) and G2-S (for the hexapeptide quaternary mixture) systems (Waters Corporation, Milford, MA, USA). Experimental details on collection of TWIM-MS data reported in this manuscript are included in the supporting information, Table S1.…”