AI Article Synopsis

  • Comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS) is used for analyzing complex biological samples like Daphnia magna.
  • Different chemometric methods were compared to enhance the speed and efficiency of non-targeted metabolomic profiling, leading to a proposed workflow that integrates data compression and modeling techniques (MCR-ALS).
  • The study successfully identified 80 metabolites from D. magna, and the research outlines optimal column configurations for improved data processing and metabolomic analysis.

Article Abstract

Comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS) is a powerful tool for separation and identification of analytes in complex natural samples. In this paper, different chemometric methods were compared for fast non-targeted GC×GC-TOFMS metabolomic profiling of the crustaceous species Daphnia magna and a general chemometric strategy and workflow is proposed. The strategy proposed in this work combined the compression of GC×GC-TOFMS data matrices in the retention time direction using wavelets and the appropriate column-wise data matrix augmentation arrangement, and its modeling by Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS). Using the proposed strategy, eighty different D. magna metabolites were resolved and identified. After calculation of the peak capacities of different columns and peak area changes of these metabolites, the best instrumental configuration and column combination for the GC×GC-TOFMS metabolomic study of D. magna are proposed and discussed. The procedure described in this work can be applied as a general method for untargeted GC×GC-TOFMS data processing and metabolomic profiling.

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Source
http://dx.doi.org/10.1016/j.chroma.2017.01.052DOI Listing

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