Lipid Calibration Strategies for Ion Mobility Separations

Lipid Collision Cross Section Calibration Strategies for High Resolution SLIM-based Traveling Wave Ion Mobility Separations

Project Overview

Lipid Extract CCS Calibration

Calibrant Selection

Lipids and lipid-like species are structurally diverse biomolecules important in many biological processes. Isomeric species are prevalent, and their analyses is currently limited by the availability of structurally-selective analytical techniques. 1 Ion mobility (IM) has shown utility for the structural discrimination of isomeric species, and recent developments in traveling wave IM (TWIM) separations based on structures for lossless ion manipulation (SLIM) have yielded improved separations of lipids, including cis/trans and double bond positional isomers. 2 IM-derived collision cross section (CCS) values have been used as a molecular descriptor, and with high resolution SLIM-based IM, there is unexplored potential in CCS calibration for these measurements. Here, we evaluate CCS calibration strategies and considerations for high resolution SLIM-based lipid measurements.

Structurally similar calibrants have been used in TWIMS CCS calibration to achieve lower biases as compared to drift tube values. 6 Here, identified features from PC and PE extract data with a single arrival time distribution and high abundance across all replicates were selected as calibrants to recalibrate the CCS values of the PC and PE features. The results highlight the importance of not only structural similarity, but also arrival time range for CCS calibration. ATM covers the full arrival time range of the analytes and results in a relatively consistent bias. However, when using a polynomial equation, calibrants used to calibrate CCS values outside of their arrival time range (extrapolation) result in higher biases. Although calibration with the power equation does allow for extrapolation, the average bias of ATM calibrated values (not extrapolated) is higher (3.6%) than that of the polynomial (2.9%).

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Instrumentation

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Time-of-flight Mass Spectrometer (6546, Agilent )

Analyte Bias: 3 rd Order Polynomial Equation

Total lipid extracts of three subclasses (phosphocholine, PC; phosphoethanolamine, PE; and glucosylceramide, GlcCer) were prepared at 10 µg/mL in 1:2 CHCl 3 :MeOH and analyzed using the MOBILion SLIM-TWIM platform in triplicate over three days. Feature m/z and arrival time measurements were extracted using IM-MS Browser. CCS values were calibrated from these measurements using Agilent Tune Mix (ATM) acquired under the same instrumental conditions on the same day. An overview of the conformation space of the calibrated CCS values is shown above.

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A prototype high resolution SLIM-TWIM IM-MS was used for this study (details above). This instrument incorporates a 13-meter serpentine TWIM pathlength for high-resolution IM separations, integrated with a commercial quadrupole time- of-flight mass spectrometer (6546 QTOF, Agilent). Data was acquired in positive mode, and TW separation parameters were chosen for optimal resolving power based on previous studies at 20 kHz frequency and 40 V pp amplitude. 3 A liquid chromatography system (1290 Infinity II, Agilent) was used to introduce samples into the IM-MS using flow injection analysis at a flow rate of 0.01 mL/min.

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CCS Calibration Strategies

Lipid features were compared to compounds of each class reported in the Compendium to assign identifications. CCS values for identified features with a single arrival time distribution (i.e., no peak splitting) were compared to their Compendium values to assess bias in the calibrated measurements. The results are shown above.

Conclusions and Future Directions

Collision cross section values can be calibrated for SLIM-TWIM arrival time measurements using known reference values for calibrant ions. The reference values are converted to reduced CCS (CCS’) using reduced mass (µ) and charge (z) in the following equation:

CCS Calibration Using a 3rd Order Polynomial Fit y = Ax 3 +Bx 2 +Cx+D

• When calibrated with ATM, the average CCS bias for lipid features was 2.7% based on comparable reference values from the CCS Compendium. • The reproducibility of the MOBILion SLIM-TWIM system is high, with all feature RSD under 1% for arrival time measurements and under 0.4% for calibrated CCS values. • Structurally similar calibrants may reduce CCS bias within comparable arrival time ranges. Extrapolation of calibration equations is not advisable when using polynomial fits. • High reproducibility in calibrated CCS values, as shown here, will allow for the implementation of correction factors to increase accuracy of lipid calibrations. • Development of calibration strategies with low bias and high precision will allow CCS calibration and cataloging of new features revealed with high resolution SLIM-TWIM instrumentation.

SLIM-TWIM Reproducibility

𝐂𝐂𝐒 ! = 𝐂𝐂𝐒 𝐳 𝛍

Reproducibility of the lipid measurements was assessed over the three days of replicates using relative standard deviation (RSD) expressed as a percent. The average RSD of the calibrated CCS values (0.16%) was found to be lower than that of the corresponding arrival times (0.44%). Additionally, the spread of these RSD values was narrower for the calibrated CCS values as compared to the arrival times, shown below. This supports the use of calibrated CCS values in high-resolution databases for method validation and species identification.

Reference CCS’ values for calibrant ions are then plotted against their experimental arrival times and fit with a nonlinear regression model (left). Here, a 3 rd order polynomial fit is used, as this equation has shown low CCS bias in previous studies. 3,4

Inter-day Measurement Reproducibility

References and Acknowledgments

Unified CCS Compendium GlcCer, PC, and PE Lipids

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This work was supported in part by resources provided by the Center for Innovative Technology at Vanderbilt University. MOBILion is the exclusive licensee of the SLIM technology for commercialization purposes. JAM is a member of the Scientific Advisory Board for MOBILion Systems and certifies that contributions are scientifically objective and are not influenced by his SAB participation. 1. Rustam, Y. H.; Reid, G. E. Anal. Chem. 2018 , 90 (1), 374–397. 2. Wojcik, R.; Webb, I. K.; Deng, L.; Garimella, S. V. B.; Prost, S. A.; Ibrahim, Y. M.; Baker, E. S.; Smith, R. D. Int. J. Mol. Sci. 2017 , 18 (1), 1–12. 3. May, J. C.; Leaptrot, K. L.; Rose, B. S.; Moser, K. L. W.; Deng, L.; Maxon, L.; DeBord, D.; McLean, J. A. J. Am. Soc. Mass Spectrom. 2021 , 32 (4), 1126–1137. 4. Li, A.; Conant, C. R.; Zheng, X.; Bloodsworth, K. J.; Orton, D. J.; Garimella, S. V. B.; Attah, I. K.; Nagy, G.; Smith, R. D.; Ibrahim, Y. M. Anal. Chem. 2020 , 92 (22), 14976–14982. 5. Picache, J. A.; Rose, B. S.; Balinski, A.; Leaptrot, K. L.; Sherrod, S. D.; May, J. C.; McLean, J. A. Chem. Sci. 2019 , 10 (4), 983– 993. 6. Hines, K. M., May, J. C., McLean, J. A.,; Xu, L. Anal. Chem. 2016 , 88 (14), 7329–7336.

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Advances in standardization of CCS reporting has allowed the curation of high-precision databases, such as the Unified CCS Compendium, a repository of drift tube CCS values. 5 Values in the Compendium can be used as reference values with which to compare calibrated SLIM- TWIM CCS values. Additionally, compounds in the Compendium may find utility as application-specific calibrant sets. Here, CCS values are calibrated for features in total lipid extracts of three subclasses. CCS values for these subclasses are represented in the Compendium (right) and are used as reference values for calibration and comparison.

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