Extractables, Leachables, and Contact Materials: The Invaluable Benefit of Ion Mobility-Enhanced Mass Spectrometry Libraries

Significance of the Topic

The identification and characterization of extractables and leachables (E&L) from packaging and contact materials is critical for ensuring the safety and quality of food, pharmaceuticals, and consumer products. Regulatory requirements demand rigorous screening of compounds that may migrate from plastics, polymers, and additive formulations into sensitive matrices. Traditional mass spectrometry libraries rely on accurate mass, retention time, and product ion data, but complex matrices can yield false positives. Incorporating ion mobility separation and collision cross section (CCS) values adds an orthogonal dimension of specificity, reducing false detection rates and increasing confidence in compound identification.

Study Objectives and Overview

This work aimed to develop and verify a comprehensive ultraperformance liquid chromatography–ion mobility–mass spectrometry (UPLC-IM-MS) library of certified reference mixes of E&L compounds in positive and negative electrospray modes. The library includes retention times, precursor and product ion m/z values, and TWCCS_N2 values. A non-targeted screening approach used this library to analyze two food commodities—orange cordial and blackcurrant with apple cordial—spiked with known E&L standards, to verify the library’s specificity and practical utility.

Methodology and Instrumentation

Sample Preparation:

• Orange cordial and blackcurrant/apple cordial diluted 1:10 in water.
• Spiking concentration: 100 pg/µL of selected E&L standards in ES+ and ES– modes.

UPLC Conditions:

• System: Waters ACQUITY UPLC I-Class.
• Column: ACQUITY Cortecs C18, 2.1×100 mm, 1.6 µm, 50 °C.
• Mobile phases: A = water + 1 mM ammonium acetate + 0.1% formic acid; B = methanol.
• Flow rate: 0.3 mL/min; injection: 10 µL; sample temp: 6 °C.

MS and IMS Conditions:

• Instrument: Waters SYNAPT XS, ionization ES+ and ES–.
• Acquisition: m/z 50–1 200, 10 Hz, HDMSE mode with collision energy ramp (20–50 eV).
• IMS: traveling wave separation, helium and nitrogen buffer gas, drift times recorded for CCS calculation.
• Lock mass: Leucine enkephalin (m/z 556.2766).

Main Results and Discussion

The constructed UPLC-IM-MS library contains over 20 E&L small molecules characterized by retention time (±0.1 min), accurate precursor and product ion masses (<5 ppm error), and TWCCS_N2 values (ΔCCS_N2 <2%). Verification in spiked orange cordial and blackcurrant/apple cordial revealed:

• Successful identification of all spiked standards in ES+ and ES– modes with retention time errors <0.1–0.2 min and CCS deviations <1–2%.
• Detection of ubiquitous plastic additives (e.g., triphenylphosphate, Irgafos 168 derivatives) in blanks and matrices, demonstrating the library’s ability to differentiate genuine sample components from background contamination.
• Identification of triacetin (E1518) in orange cordial, linked to glycerol ester of wood rosin emulsifier, through MS and CCS matching.
• Dual‐mode detection of D-sorbitol (E420) in blackcurrant/apple cordial, correlating with natural fruit constituents.
• Recognition of fatty acids (elaidic and arachidic acids) in orange cordial, indicating both matrix constituents and common laboratory contaminants; IMS CCS data distinguished isomeric species.

Ion mobility separation enhanced spectral clarity, isolating precursor and product ions and providing an extra identification marker via CCS in cases where product ions were absent.

Benefits and Practical Applications

• Additional specificity through TWCCS_N2 reduces false-positive identifications in complex matrices.
• Improved confidence in non-targeted screening workflows for food safety, pharmaceutical packaging, and consumer goods QA/QC.
• Compatibility of retention time, MS, and CCS data with existing MS assays and software (e.g., UNIFI) for automated library matching.

Future Trends and Possibilities

• Expansion of E&L libraries to include broader chemical classes (e.g., oligomers, degradation products, and advanced polymer additives).
• Interlaboratory CCS reproducibility studies to standardize values across platforms and ensure transferability.
• Application of cyclic ion mobility for high-resolution separation of isomeric contaminants.
• Integration with machine learning and AI-driven identification tools to accelerate unknown component elucidation.
• Extension of workflows to environmental, cosmetic, and biomedical implant analyses for comprehensive risk assessment.

Conclusion

A robust UPLC-IM-MS library of extractables and leachables incorporating CCS values was developed and verified using spiked food commodities. Ion mobility separation provided an orthogonal dimension that enhanced identification specificity, reduced false positives, and facilitated confident non-targeted screening in complex matrices. The methodology supports regulatory compliance and practical safety assessments in multiple industries.

Reference

1. FDA. Code of Federal Regulations Title 21. 2000.
2. EU Regulation 1935/2004/EC. Official Journal of the European Union. 2004.
3. EU Regulation 2023/2006/EC. Official Journal of the European Union. 2006.
4. EU Regulation 10/2011/EU. Official Journal of the European Union. 2011.
5. EU Regulation 1907/2006/EC. Official Journal of the European Union. 2006.
6. EU Regulation 2009/49/EC. Official Journal of the European Union. 2009.
7. EU Directive 87/357/EEC. Official Journal of the European Union. 1987.
8. Dzumana Z, et al. Anal. Chim. Acta. 2015;863:29–40.
9. Pérez-Ortega P, et al. Talanta. 2016;160:704–712.
10. Pérez-Ortega P, et al. Food Anal. Methods. 2017;10:1216–1244.
11. Romero-González R. Anal. Methods. 2015;7:7193–7201.
12. Coscollà C, et al. J. Chromatogr. A. 2014;1368:132–142.
13. Sjerps RMA, et al. Water Res. 2016;93:254–264.
14. Pringle SD, et al. Int. J. Mass Spectrom. 2014;26:1–12.
15. Giles K, et al. Rapid Commun. Mass Spectrom. 2004;18:2401.
16. McCullagh M, et al. Phytochem. Anal. 2019;30(4):1–13.
17. McCullagh M, et al. Anal. Chem. 2018;90:4585–4595.
18. McCullagh M, et al. Phytochem. Anal. 2019;30(4):1–13.
19. Goscinny S, McCullagh M, Eppe G. Rapid Commun. Mass Spectrom. 2019;33(S2):1–15.
20. Nye LC, et al. J. Chromatogr. A. 2019;1602:386–396.
21. McCullagh M, et al. Talanta. 2021;221:121311.
22. Righetti L, et al. J. Agric. Food Chem. 2020;68(39):10937–10943.
23. Goshawk J, Barknowitz G, McCullagh M. Waters White Paper. 2020.
24. Yang Y, et al. J. Agric. Food Chem. 2016;64(41):7866–7873.
25. Hermabessiere L, et al. Sci. Total Environ. 2020;749:141651.
26. Jungmin L. Food Chem. 2015;166:616–622.
27. Cheng YY, Yu JZ. Atmosphere. 2020;11(10):1120.
28. Nordby HE, Nagy S. Phytochemistry. 1971;10(3):615–619.
29. Lamine M, et al. J. Food Meas. Charact. 2019;13(3):2211–2217.
30. Khan FA, et al. Life Sci. J. 2013;10(10s):205–209.