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Differential analysis of combinatorial protein complexes with CompleXChange.

Thorsten Will1,2, Volkhard Helms3

  • 1Center for Bioinformatics, Saarland University, Campus E2.1, Saarbrücken, 66123, Germany.

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|June 5, 2019
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Summary
This summary is machine-generated.

This study introduces CompleXChange, a new computational pipeline for analyzing protein complexomes. It enables whole-genome scale differential analysis of protein assemblies, revealing insights beyond individual protein quantification.

Keywords:
Differential analysisDifferential protein complex analysisMonocytesProtein complex abundance estimationTranscription factor complexes

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Area of Science:

  • Proteomics
  • Systems Biology
  • Bioinformatics

Background:

  • Multiprotem complexes are crucial for cellular functions, yet quantitative analysis of their abundance (complexomes) is lacking.
  • Existing methods quantify individual proteins, not their assemblies, limiting differential analysis of macromolecular complexes.
  • Large-scale transcriptomic and proteomic data exist, but quantitative complexome data is missing, hindering biological insights.

Purpose of the Study:

  • To develop a computational pipeline for differential analysis of protein complexes on a whole-genome scale.
  • To infer complex abundances from available protein and gene expression data.
  • To enable quantitative analysis of the complexome, addressing a gap in current systems biology approaches.

Main Methods:

  • Developed a novel pipeline for differential analysis of protein complexes.
  • Utilized predicted or manually assigned complexes and inferred complex abundances.
  • Applied the pipeline on a whole-genome scale for comprehensive analysis.

Main Results:

  • The CompleXChange algorithm demonstrated improved accuracy and efficiency over previous methods using simulated data.
  • The method proved robust against false positives in human monocyte and lymphoblastoid samples.
  • Identified deregulated complexomes not fully explained by individual protein analysis, highlighting novel biological information.

Conclusions:

  • CompleXChange enables whole-genome scale analysis of protein complexome deregulation by integrating diverse data.
  • The tool provides a valuable resource for understanding cellular mechanisms at the complex level.
  • Freely available software and resources facilitate broader adoption and research in complexome analysis.