Precursor Ion Deconvolution in Mass Spectrometry IDA Cycles
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Solution Overview
Problem
The mass spectrometry industry lacks a real-time method to ensure sufficient data collection in Information Dependent Analysis (IDA) methods for deconvolution of convolved precursor ions, as previously fragmented ions are typically excluded from subsequent cycles, limiting the application of deconvolution methods.
Innovation Solution
A system and method that identifies precursor ions with convolution features in real-time, preventing their exclusion from subsequent cycles by adding them to a 'do not exclude' list, ensuring additional product ion data is collected for deconvolution, using an ion source, mass spectrometer, and processor to perform IDA cycles and filter peak lists while maintaining convolved ions for extended data collection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If precursor ions are excluded from subsequent cycles after fragmentation, then productivity is improved by reducing redundant analysis, but measurement precision deteriorates due to insufficient data for deconvolution
Solution Approach 1:
The system performs preliminary identification of convolved precursor ions using features from the precursor ion spectrum (such as peak shape analysis, intensity distribution patterns, or co-elution detection) before the IDA cycles begin. This allows the system to proactively mark these ions for extended monitoring, ensuring sufficient data collection points are obtained without compromising overall analysis productivity.
Solution Approach 2:
The system implements a feedback mechanism where the quality and quantity of product ion data are continuously monitored during IDA cycles. When convolved precursor ions are detected or when insufficient data points are identified, the system automatically adjusts the exclusion criteria to retain additional cycles for these specific ions, thereby ensuring adequate data for accurate deconvolution while maintaining efficient analysis for non-convolved ions.
2Measurement precision
If data collection is extended for convolved precursor ions, then measurement precision is improved for deconvolution, but productivity deteriorates due to increased analysis time
Solution Approach 1:
The system applies different data collection strategies to different precursor ions based on their individual characteristics. Convolved precursor ions identified through spectral features are retained for extended cycles to ensure sufficient data points, while non-convolved ions follow the standard exclusion protocol. This localized approach ensures high deconvolution accuracy for problematic ions without unnecessarily extending the analysis time for the entire dataset.
Solution Approach 2:
The system dynamically changes the exclusion parameters (such as exclusion time, m/z tolerance, or cycle count) based on the detected convolution features of precursor ions. When convolution is detected, the exclusion parameters are adjusted to allow additional data collection; when no convolution is present, standard parameters are maintained. This adaptive parameter adjustment optimizes the balance between deconvolution precision and overall productivity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach ensures continuous data collection for deconvolution, overcoming the limitation of insufficient data due to premature exclusion of convolved precursor ions, thereby enhancing protein or peptide identification accuracy in IDA methods.
Implementation Method 1
an ion source to ionize a sample received over time and to produce an ion beam
Implementation Method 2
a mass spectrometer that receives the ion beam from the ion source and that is adapted to perform a plurality of cycles of an IDA experiment on the ion beam
Data Source
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AI summary
Systems and methods prevent potentially convolved precursor ion peaks from being excluded in subsequent cycles of an IDA experiment so that additional product ion data is collected. A sample is ionized producing an ion beam. A plurality of cycles of an IDA experiment are performed on the ion beam. During each cycle of the IDA experiment and for each precursor ion peak on a filtered peak list produced in the filtering step of each cycle, several steps are performed. The precursor ion peak is identified in the precursor ion spectrum produced in the MS survey scan step of the cycle. It is determined if the precursor ion peak in the precursor ion spectrum includes a feature of convolution. If the precursor ion peak includes a feature of convolution, the precursor ion peak is prevented from being excluded in a filtering step of one or more subsequent cycles.