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Adapting an Isobaric Tag-Labeled Yeast Peptide Standard to Develop Targeted Proteomics Assays
Kevin D Dong1, Ernst W Schmid1, Ryan D Bomgarden2
1Department of Cell Biology, Harvard Medical School, Boston, Massachusetts 02115, United States.
Journal of Proteome Research
|November 27, 2023
Summary
This study introduces a TKO11 standard as a test assay for goDig targeted proteomics, enabling quantitative profiling of hundreds of proteins. The developed yeast library and guide facilitate goDig implementation for researchers.
Area of Science:
- Proteomics
- Biochemistry
- Molecular Biology
Background:
- Targeted proteomics offers a hypothesis-driven method for analyzing specific protein sets or pathways.
- goDig is a quantitative, targeted tandem mass tag (TMT)-based assay for measuring relative protein abundance differences in unfractionated mixtures.
- Implementing goDig presents challenges including required software, libraries, and the lack of a readily available test assay.
Purpose of the Study:
- To establish a standardized test assay for the goDig targeted proteomics platform.
- To create a proteome-wide goDig yeast library for quantitative profiling.
- To provide a guide for goDig implementation using the TKO11 standard.
Main Methods:
- Repurposing the commercially available TKO11 standard as a goDig test assay.
- Building a proteome-wide goDig yeast library.
- Quantifying protein expression across Gene Ontology (GO) categories and comparing to a gold-standard dataset.
Main Results:
- Successfully established the TKO11 standard as a functional goDig test assay.
- Generated a comprehensive goDig yeast library enabling quantification of hundreds of proteins.
- Demonstrated goDig's utility by comparing yeast protein expression data to a gold-standard dataset.
Conclusions:
- The TKO11 standard serves as an effective goDig test assay, simplifying implementation.
- The developed yeast library and quantification guide provide a template for goDig assays in other species.
- This work lowers the barrier for researchers to adopt and utilize goDig for targeted proteomics studies.

