Analysis-Driven Experimentation

A Novel, Directed Shotgun Proteomics Workflow Allows to Target Specific Areas of a Proteome

The comprehensive analysis of proteins is an important pre-requisite to understand cellular processes in a systems biology context. Yet to date, not even a relatively “simple” prokaryotic proteome has been completely annotated.

As a first step towards reaching a more complete annotation of proteomes with reduced levels of redundancy , in collaboration with Dr. Erich Brunner from the Center for Model Organism Proteomes (C-MOP), we have developed a novel, directed shotgun proteomics workflow (Fig. 1). This workflow relies on liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis of complex samples, also termed “Shotgun Proteomics”, since it is far less biased against identifying membrane and low abundant proteins than 2-D gel-based approaches.

Central part of the novel workflow is an iterative feedback loop between experimentation and thorough bioinformatics and statistic analysis of the proteins identified by these experiments, which we term analysis-driven experimentation (ADE) (Fig. 1). We compare the distributions of the physiochemical and functional properties of the identified proteins to the corresponding distributions of all predicted proteins in the proteome, and identify protein categories that are underrepresented in our set of identified proteins. The identified biases allow to modify the protocols for subsequent experiments such that the underrepresented protein categories are specifically targeted. This iterative ADE feedback strategy allows to minimize the high redundancy of protein identifications typical for shotgun proteomics projects. In the specific application for the Drosophila full proteome coverage project, it has enabled to reach an unprecedented proteome coverage.

While we demonstrated the efficiency of the approach in a series of shotgun proteomics experiments targeting the Drosophila proteome, the methods are of general validity and are easily applied to other proteomes and other technologies.

Misc

• Publication
• Center for Model Organims Proteomes (C-MOP)
• Pressemitteilung der Universität Zürich

Contact

Ralph Schlapbach