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Related Concept Videos

Peptide Identification Using Tandem Mass Spectrometry01:33

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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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Advanced Precursor Ion Selection Algorithms for Increased Depth of Bottom-Up Proteomic Profiling.

Simion Kreimer1, Mikhail E Belov2, William F Danielson2

  • 1Barnett Institute of Chemical and Biological Analysis, Northeastern University , Boston, Massachusetts 02115, United States.

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|August 30, 2016
PubMed
Summary

Advanced algorithms improve proteomic profiling by excluding previously fragmented precursors in mass spectrometry. This approach identifies significantly more peptides and low-abundance proteins, enhancing coverage in complex samples.

Keywords:
DDALC−MS retention time alignmentdata-dependent acquisitiondynamic exclusionindexed exclusionproteomics

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Area of Science:

  • Proteomics
  • Mass Spectrometry
  • Biochemistry

Background:

  • Conventional TopN data-dependent acquisition (DDA) in LC-MS/MS has limitations in sampling rate, leading to underrepresentation of low-abundance precursors.
  • Repeated analyses in DDA show marginal improvements in sample coverage due to redundant precursor sampling.

Purpose of the Study:

  • To develop and apply advanced precursor ion selection algorithms to overcome limitations in conventional TopN DDA.
  • To enhance the depth of proteomic profiling in complex samples like HeLa cell lysate.

Main Methods:

  • Development of advanced precursor ion selection algorithms.
  • Application of these algorithms in bottom-up LC-MS/MS analysis of HeLa cell lysate.
  • Utilizing an automatically aligned exclusion list to exclude previously fragmented precursors.

Main Results:

  • Reduced overlap of identified peptides to approximately 10% between replicates.
  • Achieved a 29% increase in peptide identifications beyond the saturation level of conventional TopN DDA.
  • Identified several hundred low-abundance protein groups not detected by conventional methods.

Conclusions:

  • Advanced precursor ion selection algorithms significantly enhance proteomic profiling depth compared to conventional TopN DDA.
  • Exclusion strategies, particularly of previously fragmented high-abundance peptides, enable deeper exploration of the proteome.
  • The developed approach shows potential for further improvements in identifying low-abundance proteins and increasing overall proteomic coverage.