Mass Spectral Feature Assembly for Accurate Compound Identification
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Solution Overview
Problem
Existing methods for processing mass spectral data face challenges in correctly assembling multiple m/z signals from single compounds, due to issues like intrinsic charge identification, inconsistent adduct type assignment, and misidentification of in-source fragments.
Innovation Solution
The method involves detecting features in MS1 mass spectra, grouping them by retention time, and using MS2 or MSN data to identify compounds and resolve conflicts in ion type assignments and relationships, thereby assembling features into clusters representing single compounds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple m/z signals are assembled based on retention time alone, then the processing speed is improved, but the accuracy of compound identification deteriorates due to incorrect assignment of intrinsic charges, adducts, and in-source fragments
Solution Approach 1:
The patent introduces MSN mass spectral data as an intermediary to mediate between retention time grouping and compound identification. By using fragmentation patterns from MSN spectra as an additional matching criterion, the system resolves ambiguities in assigning m/z signals to compounds, particularly for distinguishing intrinsic charges, adducts, and in-source fragments that have similar retention times but different fragmentation characteristics.
Solution Approach 2:
The patent changes the parameter set used for assembly from solely retention time to a combined set of retention time and mass spectral data (fragmentation patterns). This parameter expansion allows the system to maintain processing efficiency while significantly improving identification accuracy by adding a second dimension of discrimination.
2Quantity of substance
If all m/z signals are assigned to potential compounds, then the sensitivity of detection is improved, but the reliability of identification deteriorates due to false positives from incorrect assembly
Solution Approach 1:
The patent uses MSN mass spectral data as an intermediary verification layer between initial signal detection and final compound identification. The fragmentation patterns serve as a mediator to confirm or reject potential compound assignments, reducing false positives while maintaining sensitivity for true detections.
Solution Approach 2:
The patent replaces the mechanical/algorithmic retention time matching system with a more sophisticated identification system that incorporates spectral library matching and fragmentation pattern analysis. This substitution maintains the initial sensitivity of detection while adding a reliability filter through spectral comparison.
3Device complexity
If traditional assembly methods are used without MSN data, then the device complexity is reduced, but the measurement precision of compound identification deteriorates
Solution Approach 1:
The patent makes the mass spectrometer perform multiple functions: it collects both retention time information and MSN mass spectral data during a single analysis run. This multi-functionality allows the system to improve identification accuracy without requiring additional analytical devices or separate measurement steps, thereby limiting the increase in overall device complexity.
Solution Approach 2:
The patent performs preliminary collection and organization of MSN spectral data during the initial analysis phase, before the assembly and identification steps. This preliminary action prepares the fragmentation pattern data in advance, making it readily available for accurate compound assembly without adding significant complexity to the processing workflow.
Data Source
AI summary
A method of processing mass spectral data is provided. The mass spectral data includes a plurality of MS1 mass spectra and a plurality of MSN mass spectra each having a respective associated retention time. A group of features is detected in the plurality of MS1 mass spectra, each feature of the group having a respective mass, and the features of the group having corresponding retention times. The method includes, for each of one or more features of the group: submitting a corresponding MSN mass spectrum to a mass spectral search engine in order to obtain an identification result for that feature, and determining a candidate ion type for the feature based on a mass difference between the mass associated with the feature and an expected mass from the identification result. The method also includes identifying one or more compounds based on the group of features and the candidate ion type(s).