Targeted Mass Spectrometry Collision Energy Selection
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Solution Overview
Problem
In data-dependent acquisition (DDA) mass spectrometry, determining the optimum collision energy for thousands of precursor ions is challenging, leading to compromised sensitivity in targeted quantification due to the lack of reference standards and the need to scan collision energy over a range to ensure fragmentation.
Innovation Solution
A method involving chromatographic separation and mass analysis of precursor and product ions, where operational parameters like collision energy are varied during sequential acquisition periods, and the spectral data is stored and interrogated to determine target operational parameter values for optimal signal intensity or signal-to-noise ratio, ensuring precise fragmentation and enhanced sensitivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If collision energy is scanned over a predetermined range during targeted MS-MS data acquisition, then fragmentation is ensured, but sensitivity during targeted quantification is compromised
Solution Approach 1:
The patent performs a preliminary DDA experiment where collision energy is scanned over a range to identify precursor ions and determine their fragmentation characteristics. This preliminary action provides the information needed to select optimal fixed collision energy values for subsequent targeted quantification, eliminating the need to scan collision energy during the actual quantification analysis.
Solution Approach 2:
The patent changes the collision energy parameter from a scanned variable during targeted quantification to a fixed value selected based on preliminary DDA data. By determining the optimal collision energy for each precursor ion in advance through DDA, the system can use fixed energy values that maximize sensitivity while ensuring adequate fragmentation.
2Adaptability or versatility
If DDA is used to analyze thousands of precursor ions without reference standards, then broad coverage is achieved, but determining optimal collision energy for each precursor ion becomes challenging
Solution Approach 1:
The patent uses feedback from the DDA experiment to inform the targeted quantification setup. The DDA data provides information about precursor ions present in the sample and their fragmentation patterns, which feeds back into determining the optimal collision energy values for each precursor ion in the subsequent targeted analysis.
Solution Approach 2:
The system performs self-characterization by using the DDA data to automatically determine the optimal collision energy for each precursor ion without requiring external reference standards. The method serves itself by generating the necessary optimization information from the initial discovery experiment.
3Measurement precision
If method development stage uses reference standards with loop-injection under different mass spectrometer conditions, then optimum settings are determined, but time is consumed and chromatographic retention time information is not obtained
Solution Approach 1:
The patent merges the method development function into the initial DDA experiment itself. Instead of performing separate method development injections with reference standards, the DDA experiment on the actual sample serves both as discovery and as the basis for determining optimal analysis conditions, combining multiple functions into a single experimental run.
Solution Approach 2:
The DDA experiment serves multiple functions simultaneously: it identifies precursor ions, determines their fragmentation patterns, provides chromatographic retention time information, and establishes the basis for selecting optimal collision energy values. This multi-functional approach eliminates the need for separate method development steps.
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 optimizes sensitivity for target precursor-to-product transitions by determining the optimal collision energy and operational parameters, resulting in improved signal intensity and reduced noise, enhancing the accuracy of mass spectrometry analysis.
Implementation Method 1
mass analyzing each of the separated precursor ions, and/or product ions derived therefrom, during a plurality of sequential acquisition periods
Implementation Method 2
the value of one or more operational parameter of the spectrometer is varied such that it has different values during the different acquisition periods, and wherein the spectral data obtained for a given ion varies depending on the value of said operational parameter
Data Source
AI summary
A method of mass spectrometry is disclosed comprising: a) providing temporally separated precursor ions; b) mass analyzing separated precursor ions, and/or product ions derived therefrom, during a plurality of sequential acquisition periods, wherein the value of an operational parameter of the spectrometer is varied during the different acquisition periods; c) storing the spectral data obtained in each acquisition period along with its respective value of the operational parameter; d) interrogating the stored spectral data and determining which of the spectral data for a precursor ion or product ions meets a predetermined criterion, and determining the value of the operational parameter that provides this mass spectral data as a target operational parameter value; and e) mass analyzing again the precursor or product ions whilst the operational parameter is set to the target operational parameter value.