Influence of Protein Abundance on High-Throughput Protein-Protein Interaction Detection

Abstract

Experimental protein-protein interaction (PPI) networks are increasingly being exploited in diverse ways for biological discovery. Accordingly, it is vital to discern their underlying natures by identifying and classifying the various types of deterministic (specific) and probabilistic (nonspecific) interactions detected. To this end, we have analyzed PPI networks determined using a range of high-throughput experimental techniques with the aim of systematically quantifying any biases that arise from the varying cellular abundances of the proteins. We confirm that PPI networks determined using affinity purification methods for yeast and Escherichia coli incorporate a correlation between protein degree, or number of interactions, and cellular abundance. The observed correlations are small but statistically significant and occur in both unprocessed (raw) and processed (high-confidence) data sets. In contrast, the yeast two-hybrid system yields networks that contain no such relationship. While previously commented based on mRNA abundance, our more extensive analysis based on protein abundance confirms a systematic difference between PPI networks determined from the two technologies.

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Document Details

Document Type
Technical Report
Publication Date
Jun 05, 2009
Accession Number
ADA501325

Entities

People

  • Anders Wallqvist
  • Jaques Reifman
  • Joseph Ivanic
  • Xueping Yu

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Application Software
  • Biomedical Research
  • Data Sets
  • Detection
  • Environment
  • Escherichia Coli
  • Gene Expression
  • Information Science
  • Liquid Chromatography
  • Mass Spectrometry
  • Mass Spectroscopy
  • Materials
  • Mrna
  • Network Science
  • Protein-Protein Interactions
  • Statistical Analysis
  • Throughput

Fields of Study

  • Biology

Readers

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  • Computational Modeling and Simulation
  • Neural Network Machine Learning.