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Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
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Biogenic Solution Map Based on the Definition of the Metabolic Correlation Distance between 4-Dimensional

Ren-Qi Wang1, Ye Geng1, Juan-Na Song1

  • 1School of Food and Biological Engineering, College of Bioresources Chemical and Materials Engineering, Shaanxi University of Science & Technology, Xi'an 710021, People's Republic of China.

Analytical Chemistry
|May 2, 2023
PubMed
Summary

This study introduces a novel "biogenic solution map" for classifying biological solutions using a 4-dimensional (4D) fingerprinting technique. This method accurately characterizes complex solutions and defines their taxonomic relationships, aiding in species identification.

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Area of Science:

  • Biochemistry
  • Cheminformatics
  • Systems Biology

Background:

  • Accurate classification of biogenic solutions is crucial for predicting characteristics and applications.
  • Directly determining similarities and differences in molecular compositions of biogenic solutions presents a significant scientific challenge.
  • Existing methods lack a standardized approach for organizing and visualizing the diversity of biogenic solutions.

Purpose of the Study:

  • To develop a standard and visualizable ontology, the "biogenic solution map", for organizing and classifying biogenic solutions.
  • To enable accurate characterization and hierarchical structuring of complex biogenic solutions.
  • To provide a method for explicitly defining species of unknown biogenic solutions and illustrating their intrinsic correlations and variations.

Main Methods:

  • Development of a novel 4-dimensional (4D) fingerprinting method using data-independent acquisition (DIA) data sets from untargeted metabolomics.
  • Calculation of a generic parameter, metabolic correlation distance, based on averaged similarities between 4D fingerprints of sample groups.
  • Hierarchical organization of biogenic solutions into a map defining "species", "genus", and "family" based on metabolic correlation distance.

Main Results:

  • The 4D fingerprinting method enables accurate characterization of complex biogenic solutions.
  • The "biogenic solution map" successfully organizes multifarious classes of biogenic solutions into a hierarchical structure.
  • Metabolic correlation distance effectively defines taxonomic ranks (species, genus, family) for biogenic solutions.
  • The map accurately illustrates intrinsic correlations and subtle variations among different biogenic solutions.
  • Samples prepared by alternative protocols can exhibit distinct metabolic compositions and be classified into different genera.

Conclusions:

  • The developed "biogenic solution map" provides a powerful and visualizable tool for the classification and understanding of biogenic solutions.
  • The 4D fingerprinting method and metabolic correlation distance offer a robust approach for defining taxonomic relationships in complex biological mixtures.
  • This framework facilitates the explicit identification of unknown biogenic solution species and reveals subtle compositional differences, even between samples of the same analyte prepared differently.