PhosFox: a bioinformatics tool for peptide-level processing of LC-MS/MS-based phosphoproteomic data

Area of Science:

• Biochemistry
• Proteomics
• Bioinformatics

Background:

• Mass spectrometry-based phosphoproteomics identifies thousands of phosphopeptides and proteins.
• Downstream data analysis is a bottleneck, often requiring laborious manual steps.

Purpose of the Study:

• To develop and implement automated software for phosphoproteomic data analysis.
• To facilitate efficient and in-depth comparisons of phosphoproteins.

Main Methods:

• Developed PhosFox software for peptide-level processing of phosphoproteomic data.
• Supported data from multiple protein identification search algorithms (Mascot, Sequest, Paragon).
• Enabled qualitative and quantitative phosphoproteomics with multiple group comparisons.

Main Results:

• PhosFox enables cross-comparison of identification results from different search algorithms.
• The software detects uniquely phosphorylated peptides and proteins between samples.
• Distinguishes differences in phosphorylation sites within proteins across samples.
• Demonstrated utility with qualitative (human keratinocytes) and quantitative (rat kidney medulla) datasets.

Conclusions:

• PhosFox facilitates efficient, in-depth phosphoprotein comparisons in case-control settings.
• The open-source, extendable implementation supports widespread application use cases.