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Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
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Improving qualitative and quantitative performance for MS(E)-based label-free proteomics.

Nicholas J Bond1, Pavel V Shliaha, Kathryn S Lilley

  • 1Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge CB2 1GA, United Kingdom.

Journal of Proteome Research
|March 21, 2013
PubMed
Summary
This summary is machine-generated.

Synapter software enhances proteome analysis by combining high-definition MS(E) and MS(E) data. This tool improves peptide identification and quantitation accuracy for mass spectrometry data independent acquisition.

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Area of Science:

  • Proteomics
  • Mass Spectrometry
  • Bioinformatics

Background:

  • Label-free quantitation using data independent acquisition (DIA) mass spectrometry is increasingly popular due to its technical reproducibility.
  • High-definition MS(E) (HDMS(E)) data, acquired using instruments with ion mobility separation, offers deeper proteome coverage and more confident peptide identifications than standard MS(E).
  • Standard MS(E) provides a higher dynamic range for quantitation compared to HDMS(E).

Purpose of the Study:

  • To develop and present synapter, a versatile software tool for evaluating data independent acquisition results from Waters instruments.
  • To demonstrate the utility of synapter in combining HDMS(E) and MS(E) data for improved proteome analysis.
  • To provide additional functionalities for users analyzing DIA data, including false discovery rate estimation and data filtering.

Main Methods:

  • Development of the synapter software tool.
  • Utilizing synapter to process and integrate data from HDMS(E) and MS(E) acquisitions.
  • Implementing features for false discovery rate estimation, peptide match filtering, and missing value imputation within synapter.

Main Results:

  • Synapter successfully combines HDMS(E) and MS(E) data, achieving the deeper proteome coverage of HDMS(E) and the accurate quantitation of MS(E) for high-intensity peptides.
  • The software provides essential tools for data quality assessment and refinement, such as FDR estimation and filtering options.
  • Synapter integrates with existing tools, facilitating the combination of peptide quantitation into protein quantitation.

Conclusions:

  • Synapter is an effective tool for maximizing the benefits of both HDMS(E) and MS(E) data in mass spectrometry-based proteome analysis.
  • The software enhances data evaluation, offering improved proteome coverage, confident identifications, and accurate quantitation.
  • Synapter's integration capabilities and additional features make it a valuable asset for researchers working with DIA mass spectrometry data.