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Characterization of proteome profile data of chemicals based on data-independent acquisition MS with SWATH method

NAR Genomics and Bioinformatics, ISSN: 2631-9268, Vol: 5, Issue: 1, Page: lqad022
2023
  • 1
    Citations
  • 0
    Usage
  • 4
    Captures
  • 1
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    1
  • Captures
    4
  • Mentions
    1
    • News Mentions
      1
      • News
        1

Most Recent News

Reports on Proteome Findings from University of Tokyo Provide New Insights (Characterization of proteome profile data of chemicals based on data-independent acquisition MS with SWATH method)

2023 MAR 29 (NewsRx) -- By a News Reporter-Staff News Editor at NewsRx Life Science Daily -- New research on proteome is the subject of

Article Description

Transcriptomic data of cultured cells treated with a chemical are widely recognized as useful numeric information that describes the effects of the chemical. This property is due to the high coverage and low arbitrariness of the transcriptomic data as profiles of chemicals. Considering the importance of posttranslational regulation, proteomic profiles could provide insights into the unrecognized aspects of the effects of chemicals. Therefore, this study aimed to address the question of how well the proteomic profiles obtained using data-independent acquisition (DIA) with the sequential window acquisition of all theoretical mass spectra, which can achieve comprehensive and arbitrariness-free protein quantification, can describe chemical effects. We demonstrated that the proteomic data obtained using DIA-MS exhibited favorable properties as profile data, such as being able to discriminate chemicals like the transcriptomic profiles. Furthermore, we revealed a new mode of action of a natural compound, harmine, through profile data analysis using the proteomic profile data. To our knowledge, this is the first study to investigate the properties of proteomic data obtained using DIA-MS as the profiles of chemicals. Our 54 (samples) × 2831 (proteins) data matrix would be an important source for further analyses to understand the effects of chemicals in a data-driven manner.

Bibliographic Details

Ishiguro, Hiromu; Mizuno, Tadahaya; Uchida, Yasuo; Sato, Risa; Sasaki, Hayate; Nemoto, Shumpei; Terasaki, Tetsuya; Kusuhara, Hiroyuki

Oxford University Press (OUP)

Biochemistry, Genetics and Molecular Biology; Computer Science; Mathematics

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