m/z Range Partitioning for High-Dynamic-Range Mass Scans
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Solution Overview
Problem
Current mass spectrometry systems face limitations in achieving high dynamic range and signal-to-noise ratios, particularly in analyzing biological samples where high-abundance species dominate, leading to poor detection of lower-abundance species due to space-charge effects and limited dynamic range in ion trap-based analyzers.
Innovation Solution
The method involves partitioning the mass-to-charge (m/z) range into dynamic m/z sub-ranges based on ion abundance, allowing for sequential injection and collective mass analysis, which dynamically adjusts the allocation of injection times to prioritize lower-abundance regions, enabling improved detection and reducing the dominance of high-abundance species.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single full mass spectrometry scan is performed with automatic gain control, then the total ion current is controlled within a target range, but the dynamic range is limited and lower-abundance species cannot be detected due to dominance by high-abundance species
Solution Approach 1:
The full m/z scan range is divided into multiple sequential windows, each analyzed separately. This segmentation allows independent optimization of injection time for each window, enabling high-abundance species in early windows to be captured without limiting the detection of low-abundance species in later windows, thereby increasing overall dynamic range
Solution Approach 2:
The injection time is made dynamic and adaptive by adjusting it based on the total ion current observed in each sequential window. This dynamic adjustment allows the system to allocate more injection time to windows containing low-abundance species while maintaining appropriate ion counts in windows with high-abundance species, optimizing signal-to-noise ratio across the entire spectrum
2Quantity of substance
If the injection time is determined by automatic gain control based on total ion current, then the number of ions in the trap is controlled, but the injection time is dominated by high-abundance species resulting in poor detection of low-abundance species
Solution Approach 1:
By segmenting the full scan into sequential windows and analyzing them in order, the system captures high-abundance species in early windows before they dominate the AGC calculation for subsequent windows. This allows low-abundance species in later windows to receive adequate injection time and detection sensitivity
Solution Approach 2:
The sequential window approach performs preliminary capture of high-abundance species in early windows, preventing them from overwhelming the AGC mechanism in subsequent windows. This preliminary action ensures that low-abundance species are not suppressed by the presence of dominant high-abundance species
Data Source
AI summary
Methods for acquiring mass spectral data of a sample across at least a portion of an m/z range include receiving mass spectral data of the sample across the m/z range. The m/z range is partitioned into one or more sets of m/z sub-ranges, each set comprising one or more m/z sub-ranges, by dividing the m/z range into a plurality of m/z bins, determining an indication of ion abundance for each m/z bin, based on the mass spectral data, and forming an m/z sub-range of the one or more sets of m/z sub-ranges by assigning m/z bins having ion abundances that correspond to at least a threshold degree to the formed m/z sub-range. A mass analysis is performed on the sample for each set of m/z sub-ranges, thereby acquiring one or more partial mass spectral data sets.