Stochastic Precursor Ion Selection for Mass Spectrometry Coverage
Solution Overview
Problem
Current automated protocols in mass spectrometry (MS/MS) focus on the most abundant precursor ions, leading to a biased analysis that may decrease the scope and sensitivity of the technique, overlooking lower-intensity analytes in complex samples.
Innovation Solution
A method that selects precursor ions for further processing based on stochastic or random selection from a survey scan, rather than solely on relative intensities, allowing for a broader analysis of ions, including those of lower intensity, by performing mass spectrometry on multiple peaks and using an inclusion list for prioritization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If precursor ions are selected based on highest intensity in survey scan, then the number of high quality identifiable MS/MS spectra is maximized, but the coverage and sensitivity for lower intensity analytes decreases
Solution Approach 1:
The patent inverts the conventional selection criterion by choosing precursor ions based on lowest intensity rather than highest intensity. This inversion allows lower abundance analytes to be selected for MS/MS analysis, thereby improving coverage and sensitivity for overlooked analytes while still maintaining acceptable spectrum quality through multiple sampling.
Solution Approach 2:
The patent changes the selection parameter from intensity-based (conventional) to a randomized or diversity-based approach. By altering the selection criterion from maximizing intensity to maximizing analytical coverage, the system achieves broader analyte detection while maintaining sufficient spectral quality for identification.
2Productivity
If instrument time is devoted to analyzing abundant precursor ions, then high quality spectra are obtained, but detection of lower intensity analytes is reduced
Solution Approach 1:
The patent applies partial action by selecting only a subset of precursor ions for MS/MS analysis, but chooses this subset based on diversity and lower intensity rather than highest intensity. This partial sampling approach ensures that instrument time is distributed across multiple analytes including low-abundance ones, preventing information loss about overlooked analytes.
Solution Approach 2:
The system uses the survey scan data itself to inform the selection of precursor ions, creating a self-directed approach where the instrument automatically identifies and prioritizes underrepresented analytes for further analysis based on the observed ion population.
3Ease of operation
If automated protocols focus on most abundant species, then analysis efficiency is improved, but sensitivity for trace analytes decreases
Solution Approach 1:
The patent implements feedback by using the survey scan results to dynamically adjust precursor ion selection. The system monitors the ion population and uses this information to select precursor ions that maximize analytical coverage, automatically adapting to the specific sample composition and improving detection sensitivity for trace analytes while maintaining operational simplicity.
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 increases the coverage and sensitivity of MS/MS analysis by analyzing a wider range of precursor ions, including those of lower intensity, thereby improving the detection of overlooked analytes in complex samples.
Implementation Method 1
with time-of-flight mass spectrometers, ions are pulsed to travel a predetermined flight path. The ions are then subsequently recorded by a detector. The amount of time that the ions take to reach the detector, the 'time-of-flight,' may be used to calculate the ion's mass to charge ratio, m/z.
Implementation Method 2
Additional information can then be obtained by fragmenting the selected precursor ion(s) via CID (collision induced dissociation) in a collision cell (or other means) to generate an MS/MS spectrum.
Data Source
AI summary
The present teachings are directed to methods and systems for the selection of ions for subsequent ion fragmentation in the analysis of a sample. Rather than select the most intense subset of precursor ions for further analysis in an attempt to maximize the number of high quality, identifiable MS/MS spectra, in some settings, systems and methods for analyzing and 5 identifying precursor ions for further processing can benefit from a discovery approach in which precursor ions are selected randomly/stochastically.