Wavelet Transform for Frequency-Division Multiplex Mass Spectrometry Combined With High-Performance Liquid
Hiroki Suzuki1, Yoshinori Iiguni1, Shinya Kitagawa1
1Department of Life Science and Applied Chemistry, Graduate School of Engineering, Nagoya Institute of Technology, Nagoya, Japan.
Journal of Separation Science
|March 26, 2026
Summary
Frequency-division multiplexing mass spectrometry (FDM-MS) with wavelet transform (WT) processing enhances analytical throughput. This method enables simultaneous sample analysis by effectively separating multiplexed chromatograms, improving efficiency in HPLC-MS workflows.
Area of Science:
- Analytical Chemistry
- Spectrometry
- Chromatography
Background:
- Frequency-division multiplexing mass spectrometry (FDM-MS) combined with multiple high-performance liquid chromatographs (HPLCs) increases analytical throughput by enabling simultaneous analysis of multiple samples.
- In FDM-MS, chromatograms from individual HPLCs are modulated at specific frequencies and observed as a mixed chromatogram in a single mass spectrometer, necessitating effective signal extraction methods.
Purpose of the Study:
- To investigate a novel signal extraction approach using wavelet transform (WT) for FDM HPLC-MS, replacing the traditional Fourier transform (FT) method.
- To evaluate the effectiveness of WT in resolving individual chromatograms from mixed signals while preserving analyte elution times and suppressing interference.
Main Methods:
- Mixed chromatograms from FDM HPLC-MS were processed using wavelet transform (WT), generating two-dimensional scalograms.
- Individual chromatograms were extracted by analyzing signal intensity profiles along lines corresponding to modulation frequencies within the scalograms.
- Complex Morlet wavelet parameters were optimized (B = 3.5, C = 1.5) to mitigate interference peaks, and internal standards were employed for quantitative analysis.
Main Results:
- WT processing successfully resolved individual chromatograms based on modulation frequencies, closely matching original chromatograms.
- Optimized WT parameters effectively suppressed interference peaks arising from broad spectra.
- Signal intensity dependency on modulation frequency was observed, but the introduction of internal standards enabled accurate quantitative comparisons across simultaneously analyzed samples.
Conclusions:
- Wavelet transform-based signal processing is an effective method for FDM HPLC-MS, enabling the simultaneous analysis of multiple samples and significantly improving analytical throughput.
- The WT approach offers a viable alternative to FT for chromatogram extraction in multiplexed HPLC-MS systems.
- The successful implementation of WT processing, coupled with internal standards, validates its utility for high-throughput quantitative analysis in complex chromatographic separations.
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