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Sample multiplexing for targeted pathway proteomics in aging mice.

Qing Yu1, Haopeng Xiao1,2, Mark P Jedrychowski1,2

  • 1Department of Cell Biology, Harvard Medical School, Boston, MA 02115.

Proceedings of the National Academy of Sciences of the United States of America
|April 26, 2020
PubMed
Summary
This summary is machine-generated.

We developed Tomahto software for targeted proteomics, enabling sensitive, high-throughput protein quantification across many samples. This approach reveals tissue-specific aging effects, highlighting roles in metabolism and inflammation.

Keywords:
Tomahtoisobaric labelingreal-time instrument controltargeted pathway proteomicstissue-specific aging

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Area of Science:

  • Proteomics
  • Systems Biology
  • Biochemistry

Background:

  • Pathway proteomics quantifies protein expression in cellular processes.
  • Targeted tandem mass tags enable multiplexing for high-throughput protein quantification.
  • Complex experiments require robust software for precise control and data acquisition.

Purpose of the Study:

  • Introduce Tomahto, a novel software strategy for controlled targeted sample multiplexing in proteomics.
  • Implement and validate Tomahto on the Orbitrap Tribrid mass spectrometer platform.
  • Enable sensitive, high-throughput quantification of hundreds of proteins across numerous biological samples.

Main Methods:

  • Tomahto software monitors data streams and inserts optimized MS2 and MS3 scans in real time via API.
  • Utilizes targeted tandem mass tags for sample multiplexing.
  • Applies the strategy to quantify 260 proteins/520 peptides across 90 samples from young and old mice.

Main Results:

  • Achieves sensitivity comparable to or better than deep fractionation with minimal sample input (~10 µg).
  • Quantifies hundreds of proteins accurately and sensitively in a high-throughput manner.
  • Identified tissue-specific aging effects, particularly highlighting inflammation and metabolism in white adipose tissue.

Conclusions:

  • Tomahto provides complete control over targeted sample multiplexing experiments.
  • The approach enables sensitive, high-throughput proteomic analysis for exploring biological processes like aging.
  • Validated through comparison with global proteome surveys, offering a valuable community resource.