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Identification of Protein Interacting Partners Using Tandem Affinity Purification

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Published on: February 25, 2012

Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions.

Maxim Shatsky¹, Ming Dong², Haichuan Liu³

¹From the ‡Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720;

Molecular & Cellular Proteomics : MCP

|April 22, 2016

Summary

This study introduces a quantitative tagless mass spectrometry method to accurately identify protein-protein interactions (PPIs). The new approach validates existing bacterial interactomes and discovers novel PPIs with high confidence, improving upon previous methods.

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Identification of Protein Interaction Partners in Mammalian Cells Using SILAC-immunoprecipitation Quantitative Proteomics

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Published on: July 6, 2014

Area of Science:

Proteomics
Bioinformatics
Molecular Biology

Background:

Identifying protein-protein interactions (PPIs) with low false discovery rates (FDR) is crucial but challenging.
Previous bacterial interactomes derived from affinity purification-mass spectrometry (AP-MS) showed variable accuracy.
Accurate PPI identification is essential for understanding cellular mechanisms.

Purpose of the Study:

To develop and validate a quantitative tagless mass spectrometry method for identifying and validating PPIs.
To assess the accuracy of existing bacterial interactomes and discover novel PPIs de novo.
To evaluate the reliability of data from quantitative tagless screens in human cell extracts.

Main Methods:

Employed a quantitative tagless mass spectrometry approach using iTRAQ (isobaric tags for relative and absolute quantitation) coupled with orthogonal chromatography.
Assayed 5273 fractions from a four-step fractionation of a *Desulfovibrio vulgaris* protein extract, detecting 1242 proteins.
Integrated tagless copurification data with genomic colocalization for high-confidence PPI identification.

Main Results:

Protein partners from *D. vulgaris* and *Escherichia coli* AP-MS interactomes copurified similarly to benchmark PPI datasets.
Existing bacterial interactomes copurified 2- to 20-fold less frequently compared to the study's validated PPIs.
Identified 200 high-confidence *D. vulgaris* PPIs, showing strong validation and overlap with AP-MS data.
Estimated novel PPIs from human cell extract screens had an FDR of at least 85% with minimal overlap.

Conclusions:

A quantitative tagless method effectively validates and identifies PPIs with high confidence.
Careful data analysis is critical to minimize FDR in tagless PPI discovery.
The developed method offers a robust approach for accurate interactome mapping in bacteria and potentially other organisms.