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Related Concept Videos

Tandem Mass Spectrometry01:21

Tandem Mass Spectrometry

Tandem mass spectrometry is a technique that uses multiple mass analyzers in series to obtain a higher selectivity and reduce chemical noise during analyte detection. Instruments with multiple analyzers separated by an interaction cell enable secondary fragmentation and selected study of the fragment ions.Secondary fragmentations occur in the interaction cell and can be induced by various factors. Fragmentation induced by collision with inert gases, such as N2, Ar, He, etc., is called...
Mass Spectrometry: Molecular Fragmentation Overview01:20

Mass Spectrometry: Molecular Fragmentation Overview

The ionization of a molecule into a molecular ion inside the mass spectrometer causes instability in the molecule's structure due to the loss of an electron. This eventually leads to the fragmentation or breaking of some bonds in the molecule. The fragmentation occurs predominantly at specific bonds to yield relatively stable fragments.
One type of fragmentation pattern is the cleavage of a single bond in the molecular ion. The cleavage leads to a radical and a cation. The cleavage can occur at...
Mass Spectrometry: Aromatic Compound Fragmentation01:23

Mass Spectrometry: Aromatic Compound Fragmentation

Upon ionization, aromatic compounds generate a molecular ion that is observed as a prominent peak in their mass spectra. For example, the molecular ion peak for benzene appears at a mass-to-charge ratio of 78, while toluene is observed at a mass-to-charge ratio of 92. The molecular ion benzene is highly stable and does not readily undergo further fragmentation due to the significant amount of energy required to disrupt the aromatic stability of the benzene ring. In contrast, the molecular ion...
Mass Spectrometry: Carboxylic Acid, Ester, and Amide Fragmentation01:01

Mass Spectrometry: Carboxylic Acid, Ester, and Amide Fragmentation

The fragmentation patterns observed for compounds such as carboxylic acids, esters, and amides in the mass spectra include ⍺-cleavage and McLafferty rearrangement. Fragmentation by ⍺-cleavage preferentially occurs at the carbon-carbon bond at the ⍺-position next to the carboxylic group to generate a neutral radical and a cation. Long chain compounds with hydrogen at their γ-carbon undergo McLafferty rearrangement to give a radical cation and a neutral alkene.
For example, the fragmentation of...
Mass Spectrometry: Branched Alkane Fragmentation01:29

Mass Spectrometry: Branched Alkane Fragmentation

This lesson delves into the mass spectrometry of branched alkane fragmentation. Branched alkanes possess secondary or tertiary carbon atoms, which generate relatively stable carbocations if the cleavage occurs at the branching point. The high stability of carbocations drives the instant fragmentation of branched alkanes. Accordingly, the branched alkane's molecular ion peak is very weak or invisible in the mass spectra, especially in comparison to a linear alkane.
Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...

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An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome
05:35

An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome

Published on: September 20, 2022

Computing fragmentation trees from metabolite multiple mass spectrometry data.

Kerstin Scheubert1, Franziska Hufsky, Florian Rasche

  • 1Chair for Bioinformatics, Friedrich-Schiller-Universität Jena, Jena, Germany. kerstin.scheubert@uni-jena.de

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|November 1, 2011
PubMed
Summary
This summary is machine-generated.

High-throughput small molecule identification using mass spectrometry (MS) is crucial. This study introduces a novel method using MS(n) data to compute fragmentation trees, improving de novo identification accuracy.

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An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome
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Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry (UPLC-HRMS)
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Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry (UPLC-HRMS)

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Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures
09:38

Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures

Published on: January 7, 2019

Area of Science:

  • Computational chemistry
  • Bioinformatics
  • Analytical chemistry

Background:

  • Metabolite identification from genomic data is not feasible, necessitating high-throughput methods.
  • Mass spectrometry (MS) with fragmentation techniques is standard for small molecule analysis, but automated data analysis remains limited.
  • Fragmentation trees have emerged as a promising tool for MS data analysis.

Purpose of the Study:

  • To leverage multi-stage mass spectrometry (MS(n)) data for enhanced fragmentation tree computation.
  • To introduce and analyze the computational complexity of the Colorful Subtree Closure problem for this task.
  • To develop and evaluate an efficient algorithm for constructing fragmentation trees.

Main Methods:

  • Utilizing MS(n) data to compute fragmentation trees.
  • Formalizing the problem as the Colorful Subtree Closure problem on vertex-colored graphs.
  • Developing an exact dynamic programming algorithm parameterized by the number of colors.
  • Evaluating the algorithm's performance on a dataset of 45 reference compounds.

Main Results:

  • Demonstrated negative results concerning the tractability and approximability of the Colorful Subtree Closure problem.
  • Presented a practical and efficient dynamic programming algorithm for fragmentation tree construction.
  • Showed that using MS(n) data significantly improves the quality of constructed fragmentation trees compared to MS² measurements.

Conclusions:

  • MS(n) data enhances the accuracy of de novo small molecule identification through improved fragmentation tree construction.
  • The proposed computational framework and algorithm offer a viable solution for automated analysis of complex MS data.
  • This work advances the field of metabolomics by providing better tools for identifying unknown small molecules.