Charge State Assignment Using m/z Bin Grouping in Mass Spectrometry
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Solution Overview
Problem
Mass spectrometry techniques face challenges in accurately determining the charge state of ions due to peak overlapping issues, especially in top-down protein analysis, where extensive overlap of product ions limits sequence coverage and conventional algorithms struggle with severe spectral overlap.
Innovation Solution
A method and system for assigning charge states in mass spectrometry that involve generating detector response profiles, grouping m/z bins based on similarity, and using additional separation domain data, such as retention time or ion mobility, to simplify mass spectra and improve charge state determination through algorithms like PCA, k-means clustering, or pattern recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional mass spectrometry algorithms are used for charge state assignment, then the process is simple and fast, but the accuracy deteriorates due to peak overlapping in complex spectra
Solution Approach 1:
The patent segments the complex mass spectrum into multiple charge state-specific spectra by detecting characteristic patterns of isotopic distributions and fragment ion relationships. Each charge state is analyzed separately, resolving the overlapping peaks that plague conventional single-spectrum analysis. This segmentation transforms an intractable complex spectrum into multiple simpler, charge-state-resolved spectra.
Solution Approach 2:
The patent introduces additional analytical dimensions beyond simple m/z intensity by analyzing the relationships between precursor ions and fragment ions across multiple spectra. By examining co-elution patterns, isotopic distribution shapes, and fragment ion mass differences in a multi-dimensional space, the system can disambiguate overlapping peaks that appear identical in traditional two-dimensional mass spectra.
2Measurement precision
If higher mass resolution mass spectrometers (FT-ICR or orbitrap) are used, then peak resolution improves, but the ability to deconvolve heavily overlapped peaks in top-down protein analysis still fails
Solution Approach 1:
The patent introduces fragment ion relationships as an intermediary mechanism to resolve peak overlaps. By analyzing the mass differences between precursor ions and their fragment ions, and by tracking how these relationships persist across multiple detected spectra, the system can assign charge states even when direct precursor ion peaks are obscured by overlapping signals from other ions.
Solution Approach 2:
The system employs iterative feedback by using initially assigned charge states to guide subsequent assignments. The charge state assignments from easily identifiable ions are used to interpret more complex overlapping regions, which in turn refine the overall charge state distribution model. This feedback loop progressively improves deconvolution reliability across the entire spectrum.
Data Source
AI summary
A method for assigning charge state in mass spectrometry includes receiving a detector response signal corresponding to a plurality of ion arrival events. The detector response signal includes information related to individual ion responses generated by a detector for each ion arrival event. Detector response profiles are generated for mass-to-charge (m/z) bins of a mass spectrum generated from the ion arrival events based on the detector response signal. The m/z bins are grouped into a plurality of groups based on a similarity of the detector response profiles of the m/z bins. A charge state is assigned to one or more features based on the groups of m/z bins.