mSystems. 2017 Jun 6;2(3). pii: e00019-17. doi: 10.1128/mSystems.00019-17. eCollection 2017 May-Jun.

The Protein Interactome of Streptococcus pneumoniae and Bacterial Meta-interactomes Improve Function Predictions.

Wuchty S1,2,3,4, Rajagopala SV5, Blazie SM5, Parrish JR6, Khuri S1,2, Finley RL Jr6, Uetz P7.

Author information

Abstract

The functions of roughly a third of all proteins in Streptococcus pneumoniae, a significant human-pathogenic bacterium, are unknown. Using a yeast two-hybrid approach, we have determined more than 2,000 novel protein interactions in this organism. We augmented this network with meta-interactome data that we defined as the pool of all interactions between evolutionarily conserved proteins in other bacteria. We found that such interactions significantly improved our ability to predict a protein's function, allowing us to provide functional predictions for 299 S. pneumoniae proteins with previously unknown functions. IMPORTANCE Identification of protein interactions in bacterial species can help define the individual roles that proteins play in cellular pathways and pathogenesis. Very few protein interactions have been identified for the important human pathogen S. pneumoniae. We used an experimental approach to identify over 2,000 new protein interactions for S. pneumoniae, the most extensive interactome data for this bacterium to date. To predict protein function, we used our interactome data augmented with interactions from other closely related bacteria. The combination of the experimental data and meta-interactome data significantly improved the prediction results, allowing us to assign possible functions to a large number of poorly characterized proteins.

KEYWORDS:

functional prediction; protein-protein interactions

PMID: 28744484 PMCID: PMC5513735 DOI: 10.1128/mSystems.00019-17