Improving Suspect Compound Identification in Comprehensive Two-Dimensional Liquid Chromatography High-Resolution Mass Spectrometry Data Workflows

A team of scientists from the University of Copenhagen (Copenhagen, Denmark) has created a two-step workflow to extract pure mass spectra from comprehensive two-dimensional liquid chromatography high-resolution mass spectrometry (LC×LC–HRMS) data (1). The study was published in the journal Analytical Chemistry.

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Data processing workflows for LC×LC–HRMS operated in data-independent acquisition (DIA) are restricted compared to one-dimensional (1D) methods (1). The complexity of the data in two-dimensional LC arises from the extensive information obtained across the two chromatographic dimensions and the high-resolution mass spectra generated. Scientists require dedicated data analysis and visualization software (2). In 1D-LC, the separation occurs along a single retention time axis, making data processing more straightforward. Consequently, new strategies are required to extract cleaner mass spectra and enhance compound identification reliability.

The team combined mass filtering (MF) and multivariate curve resolution (MCR) to create the workflow, called MF + MCR, which enhances the extraction of pure mass spectra and improves the identification of trace-level compounds in complex matrices. The mass filtering step groups ions that belong to the same compound based on their elution profile similarities in both the first and second dimensions. The second step, multivariate curve resolution, deconvolutes the filtered data to address potential coelution issues. This can help to resolve overlapping chromatographic peaks, particularly in DIA mode where fragment ions can be ambiguous.

To assess the effectiveness of MF + MCR, the researchers tested the workflow on pulsed elution-LC×LC–HRMS data from a wastewater effluent extract. The results were compared to three alternative mass spectra extraction methods: i) peak apex (PAM) (a traditional approach that selects mass spectra at the apex of chromatographic peaks); ii) mass filtering (MF) alone; and iii) MCR without prior MF. The MF + MCR workflow was able to identify 25 suspect compounds, compared to 23, 16, and 10 detected by MF, MCR, and PAM, respectively.

The team highlighted the importance of preprocessing before MCR. The nine suspect compounds that MCR on its own was unable to identify, but MF + MCR successfully detected, had low total signal contributions relative to the total ion chromatogram (TIC). Moreover, the spectral purity of mass spectra extracted using MF + MCR was statistically superior to those obtained via PAM (p-value = 0.003) and MCR alone (p-value = 0.04) in a spiked blank sample. This reinforces the importance of utilizing elution profiles across both chromatographic dimensions to refine mass spectral data.

The MF + MCR workflow extracts cleaner mass spectra, improves compound identification at trace levels, and outperforms conventional workflows. For those scientists working in environmental analysis, the workflow can assist in the detection of trace contaminants in complex matrices such as wastewater effluents.

References

(1) Schneide, P.-A.; Kronik, O. M. Signal Processing Workflow for Suspect Screening in LC × LC-HRMS: Efficient Extraction of Pure Mass Spectra for Identification of Suspects in Complex Samples Using a Mass Filtering Algorithm. Anal. Chem. 2025, 97 (2), 1180–1189. DOI: 10.1021/acs.analchem.4c04288

(2) Pirok, B. W. J.; Stoll, D. R.; Schoenmakers, P. J. Recent Developments in Two-Dimensional Liquid Chromatography: Fundamental Improvements for Practical Applications. Anal. Chem. 2018, 91 (1), 240–263. DOI: 10.1021/acs.analchem.8b04841