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Mass Spectrometry: Complex Analysis01:21

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Mass spectrometry is an important technique for the identification of pure compounds. However, it has some limitations for the analysis of complex mixtures, often due to excessive fragmentation making the spectrum too complicated to decipher. Mass spectrometry can be combined with suitable separation methods in sequence, forming hyphenated methods, which are useful in the analysis of complex mixtures.
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The resolution of a mass spectrometer depends on the efficiency of separating ions with different ion masses. The mass of an atom is approximated to the sum of the masses of protons and neutrons inside, considering the masses of protons and neutrons as equal. However, the masses of the proton (1.6726 × 10−24 g) and neutron (1.6749 × 10−24 g) are not truly equal. There is a minor error in the expression of atomic masses relative to the simplest atom of hydrogen. For...
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Related Experiment Video

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Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain
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Untargeted Comprehensive Two-Dimensional Liquid Chromatography Coupled with High-Resolution Mass Spectrometry

Meritxell Navarro-Reig1,2, Joaquim Jaumot1, Anna Baglai2

  • 1Department of Environmental Chemistry, IDAEA-CSIC , Jordi Girona 18-26, 08034 Barcelona, Spain.

Analytical Chemistry
|June 24, 2017
PubMed
Summary
This summary is machine-generated.

A new chemometric strategy enhances the analysis of complex two-dimensional liquid chromatography-high-resolution mass spectrometry (LC × LC-HRMS) data. This method effectively analyzes rice metabolism under varying environmental conditions, revealing significant metabolic changes.

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Area of Science:

  • Chemometrics
  • Metabolomics
  • Analytical Chemistry

Background:

  • Two-dimensional liquid chromatography-high-resolution mass spectrometry (LC × LC-HRMS) generates complex datasets.
  • Efficient data analysis is crucial for extracting meaningful biological information from untargeted metabolomics studies.

Purpose of the Study:

  • To propose a novel chemometric strategy for analyzing LC × LC-HRMS data.
  • To demonstrate the feasibility of this approach in an untargeted metabolomics study of rice.

Main Methods:

  • A data compression strategy involving regions of interest (ROI) selection and wavelet transforms.
  • Application of multivariate curve resolution alternating least squares (MCR-ALS) to compressed data from multiple samples.
  • Development of an untargeted LC × LC-HRMS method using hydrophilic interaction liquid chromatography (HILIC) and reversed-phase liquid chromatography (RPLC) columns.

Main Results:

  • The proposed method successfully resolved 154 metabolites from 15 families in rice samples.
  • 139 metabolites were identified using high-resolution mass spectrometry (HRMS) spectra.
  • Statistical analysis confirmed significant impacts of watering and harvest time on rice metabolism.

Conclusions:

  • The developed chemometric strategy provides an effective tool for analyzing complex LC × LC-HRMS data.
  • Environmental factors significantly influence rice metabolism, offering biochemical insights.
  • This approach facilitates deeper understanding of plant metabolomics.