Mass Spectral Deconvolution for Reproducible Biological Identification
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Solution Overview
Problem
Mass spectrometry techniques face challenges in reproducibility due to instrumental and environmental factors, leading to irreproducibility in identifying microorganisms and other biological agents, particularly due to sensitivity drift and mass discrimination, which complicates the analysis of complex mixtures and requires frequent recalibration, making it costly and time-consuming.
Innovation Solution
A method involving deconvolution of mass spectral data to combine peaks representing different charge states, adducts, and chemical interactions, followed by comparison with a library reference set of deconvoluted data from known samples, to improve the accuracy and reproducibility of mass spectral identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If mass spectrometry is used to identify microorganisms and biological agents, then identification capability is provided, but reproducibility deteriorates due to instrumental and environmental factors causing spectral drift
Solution Approach 1:
The patent transforms the mass spectral data by applying mathematical transformations to convert m/z values into mobility values, effectively changing the parameter space. This transformation corrects for spectral drift by normalizing the data, allowing reproducible identification across different instruments and conditions while maintaining the identification capability provided by mass spectrometry
2Measurement precision
If frequent recalibration is performed to maintain measurement accuracy, then spectral accuracy is improved, but time consumption and cost increase
Solution Approach 1:
The patent applies a preliminary mathematical transformation to the mass spectral data that inherently corrects for drift and eliminates the need for frequent recalibration. By transforming the data into a standardized reference frame beforehand, the system maintains spectral accuracy without requiring repeated calibration procedures, thus saving time and resources
3Measurement precision
If deconvolution is applied to combine peaks representing different charge states and adducts, then identification accuracy is improved, but data processing complexity increases
Solution Approach 1:
The patent merges multiple peaks representing different charge states and adducts into a unified transformed spectrum by applying mathematical transformations. This combining process integrates the information from various ion forms into a single standardized representation, improving identification accuracy while the systematic approach to merging keeps the processing complexity manageable
Data Source
AI summary
A method for reproducibly analyzing mass spectra from different sample sources is provided. The method deconvolutes the complex spectra by collapsing multiple peaks of different molecular mass that originate from the same molecular fragment into a single peak. The differences in molecular mass are apparent differences caused by different charge states of the fragment and/or different metal ion adducts and/or reactant products of one or more of the charge states. The deconvoluted spectrum is compared to a library of mass spectra acquired from samples of known identity to unambiguously determine the identity of one or more components of the sample undergoing analysis.