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Area of Science:

  • Proteomics
  • Systems Biology
  • Mass Spectrometry

Background:

  • High-throughput analysis of complex proteomes is crucial for systems biology.
  • Existing methods can be time-consuming for large sample sets.

Purpose of the Study:

  • To develop and validate a high-throughput mass spectrometry (MS) proteomics method.
  • To apply this method for analyzing drug effects in a preclinical model.

Main Methods:

  • Integration of narrow-window data-independent acquisition (nDIA) with short-gradient micro-flow chromatography.
  • Achieved profiling of >240 samples per day.
  • Analysis of 507 mouse tissue samples treated with L-asparaginase (ASNase) or its mutant.

Main Results:

  • Identified 6,201 and 7,466 human proteins with 1- and 2-min gradients, respectively.
  • Generated a quantitative profile of 11,472 proteins after drug treatment.
  • Confirmed ASNase impact on amino acid metabolism, suppressed anticoagulants and cholesterol metabolism, and revealed tissue-specific dysregulated pathways.

Conclusions:

  • The optimized high-throughput proteomics method significantly accelerates systems-level analysis.
  • Enables generation of biological insights and clinically actionable hypotheses from preclinical models.