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Exploring Charge-Detection Mass Spectrometry on Chromatographic Time Scales
Lisa Strasser1, Florian Füssl1, Tomos E Morgan1,2
1Characterisation and Comparability Laboratory, NIBRT - the National Institute for Bioprocessing Research and Training, Foster Avenue, Mount Merrion, Blackrock Co, Dublin A94 X099, Ireland.
Charge-detection mass spectrometry (CDMS) can now be performed with online liquid chromatography. This advancement allows for rapid and accurate mass determination of complex protein mixtures, even with short acquisition times.
Area of Science:
- Analytical Chemistry
- Biochemistry
- Mass Spectrometry
Background:
- Charge-detection mass spectrometry (CDMS) directly measures ion charge and mass-to-charge ratio.
- CDMS is valuable for complex samples like heterogeneous macromolecules and mixtures where other methods fail.
- Current CDMS methods typically require long acquisition times (tens of minutes to hours).
Purpose of the Study:
- To investigate the feasibility of CDMS analysis on shorter timescales compatible with liquid chromatography.
- To assess the performance of online liquid chromatography-coupled CDMS for complex biological samples.
Main Methods:
- Coupling size exclusion chromatography (SEC) with CDMS for online separation and mass analysis.
- Analyzing mixtures of transferrin and β-galactosidase, followed by complex glycoprotein and Fc-fusion protein characterization.
- Establishing a correlation between the number of CDMS spectra and mass accuracy.
Main Results:
- Successful identification of transferrin and β-galactosidase using CDMS spectra from single chromatographic runs (140-180 spectra per protein).
- Demonstrated applicability to complex samples: α-1-acid glycoprotein and etanercept were identified with chromatograph peak widths of ~3 min (~200 spectra).
- Established a relationship between CDMS spectra count and achievable mass accuracy.
Conclusions:
- CDMS is compatible with online liquid chromatography, enabling rapid analysis of complex mixtures.
- This hyphenated technique significantly reduces analysis time while maintaining confident identification of proteins.
- The approach is suitable for characterizing highly complex glycoproteins and fusion proteins, expanding CDMS applications.
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