Integrative identification of Arabidopsis mitochondrial proteome and its function exploitation through protein interaction network

Jian Cui, Jinghua Liu, Yuhua Li, Tieliu Shi

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

Abstract

Mitochondria are major players on the production of energy, and host several key reactions involved in basic metabolism and biosynthesis of essential molecules. Currently, the majority of nucleus-encoded mitochondrial proteins are unknown even for model plant Arabidopsis. We reported a computational framework for predicting Arabidopsis mitochondrial proteins based on a probabilistic model, called Naive Bayesian Network, which integrates disparate genomic data generated from eight bioinformatics tools, multiple orthologous mappings, protein domain properties and co-expression patterns using 1,027 microarray profiles. Through this approach, we predicted 2,311 candidate mitochondrial proteins with 84.67% accuracy and 2.53% FPR performances. Together with those experimental confirmed proteins, 2,585 mitochondria proteins (named CoreMitoP) were identified, we explored those proteins with unknown functions based on protein-protein interaction network (PIN) and annotated novel functions for 26.65% CoreMitoP proteins. Moreover, we found newly predicted mitochondrial proteins embedded in particular subnetworks of the PIN, mainly functioning in response to diverse environmental stresses, like salt, draught, cold, and wound etc. Candidate mitochondrial proteins involved in those physiological acitivites provide useful targets for further investigation. Assigned functions also provide comprehensive information for Arabidopsis mitochondrial proteome.

Original languageEnglish
Article numbere16022
JournalPLoS ONE
Volume6
Issue number1
DOIs
StatePublished - 2011
Externally publishedYes

Fingerprint

Dive into the research topics of 'Integrative identification of Arabidopsis mitochondrial proteome and its function exploitation through protein interaction network'. Together they form a unique fingerprint.

Cite this