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Related Concept Videos

Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

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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.
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Mass spectrometry is a powerful characterization technique that can identify and separate a wide variety of compounds ranging from chemical to biological entities, based on their mass-to-charge ratio (m/z). The instruments that allow this detection, known as mass spectrometers, have three components: an ion source, a mass analyzer, and a detector. These spectrometers differ based on the nature of their ion source and analyzers.Matrix-assisted laser desorption ionization (MALDI) is a commonly...
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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...
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An unknown compound can be established by identifying the molecular ion peak in the mass spectrum. The molecular ion peak is often weak or absent due to the predominance of fragmentation in high-energy electron beams. In such cases, a soft-energy electron beam can be used to scan the spectrum to enhance the intensity of the molecular ion peak. Additionally, chemical ionization, field ionization, and desorption ionization spectra are used to obtain a relatively intense molecular ion peak.To...
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Detection of Protein Ubiquitination Sites by Peptide Enrichment and Mass Spectrometry
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Dinosaur: A Refined Open-Source Peptide MS Feature Detector.

Johan Teleman1,2, Aakash Chawade1, Marianne Sandin1

  • 1Department of Immunotechnology, Lund University , 223 83 Lund, Sweden.

Journal of Proteome Research
|May 26, 2016
PubMed
Summary
This summary is machine-generated.

Dinosaur, a new tool for mass spectrometry (MS)-based proteomics, enhances peptide feature detection and chimeric spectra identification. It achieves 98% feature detection, improving upon existing algorithms for complex biological samples.

Keywords:
algorithmchimeric spectraelectrospray ionizationfeature detectionmass spectrometryproteomicssoftware

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Area of Science:

  • Proteomics
  • Mass Spectrometry
  • Bioinformatics

Background:

  • Label-free quantification in bottom-up mass spectrometry (MS)-based proteomics relies on peptide features.
  • High complexity of biological samples leads to feature intermingling, complicating detection.
  • Existing feature detection algorithms face challenges with compatibility, computation time, and high-resolution data.

Purpose of the Study:

  • To develop a faster and more versatile tool for peptide feature detection in MS proteomics.
  • To improve the robustness and performance of feature detection algorithms.
  • To enhance the identification of chimeric spectra and characterization of sample complexity.

Main Methods:

  • Development of a new tool named Dinosaur for feature detection.
  • Implementation of quality-control plots, termed 'plot trail', for algorithm sampling.
  • Algorithmic improvements based on plot trail evaluation.

Main Results:

  • Dinosaur achieved 98% feature detection on a benchmark dataset, surpassing other tested algorithms (max 96%).
  • The tool demonstrated increased speed and versatility compared to existing methods.
  • Reimplementation of a chimeric spectra identification workflow using Dinosaur increased identification rates from 26% to 32%.

Conclusions:

  • Dinosaur offers improved performance and robustness for peptide feature detection in MS proteomics.
  • The tool enhances the identification of chimeric spectra, aiding complex sample analysis.
  • Dinosaur is an open-source, operating-system-independent solution available for broader research use.