title: A global network-based protocol for functional inference of hypothetical proteins in Synechocystis sp. PCC 6803.
abstract: Functional inference of hypothetical proteins (HPs) is a significant task in the post-genomic era. We described here a network-based protocol for functional inference of HPs using experimental transcriptomic, proteomic, and protein-protein interaction (PPI) datasets. The protocol includes two steps: i) co-expression networks were constructed using large proteomic or transcriptomic datasets of Synechocystis sp. PCC 6803 under various stress conditions, and then combined with a Synechocystis PPI network to generate bi-colored networks that include both annotated proteins and HPs; ii) a global algorithm was adapted to the bi-colored networks for functional inference of HPs. The algorithm ranked the associations between genes/proteins with known GO functional categories, and assumed that the top one ranked HP for each GO functional category might have a function related to the GO functional category. We applied the protocol to all HPs of the model cyanobacterium Synechocystis, and were able to assign putative functions to 122 HPs that have never been functionally characterized previously. Finally, the functional inference was validated by the known biological information of operon, and results showed that more than 70% HPs could be correctly validated. The study provided a new protocol to integrate different types of OMICS datasets for functional inference of HPs, and could be useful in achieving new insights into the Synechocystis metabolism.
authors.affiliation: Laboratory of Synthetic Microbiology, School of Chemical Engineering & Technology, Tianjin University, Tianjin 300072, PR China; Key Laboratory of Systems Bioengineering, Ministry of Education of China, Tianjin 300072, PR China; SynBio Platform, Collaborative Innovation Center of Chemical Science & Engineering, Tianjin, PR China.
authors.forename: Lianju
authors.initials: L
authors.lastname: Gao
authors.affiliation: Laboratory of Synthetic Microbiology, School of Chemical Engineering & Technology, Tianjin University, Tianjin 300072, PR China; Key Laboratory of Systems Bioengineering, Ministry of Education of China, Tianjin 300072, PR China; SynBio Platform, Collaborative Innovation Center of Chemical Science & Engineering, Tianjin, PR China.
authors.forename: Guangsheng
authors.initials: G
authors.lastname: Pei
authors.affiliation: Laboratory of Synthetic Microbiology, School of Chemical Engineering & Technology, Tianjin University, Tianjin 300072, PR China; Key Laboratory of Systems Bioengineering, Ministry of Education of China, Tianjin 300072, PR China; SynBio Platform, Collaborative Innovation Center of Chemical Science & Engineering, Tianjin, PR China.
authors.forename: Lei
authors.initials: L
authors.lastname: Chen
authors.affiliation: Laboratory of Synthetic Microbiology, School of Chemical Engineering & Technology, Tianjin University, Tianjin 300072, PR China; Key Laboratory of Systems Bioengineering, Ministry of Education of China, Tianjin 300072, PR China; SynBio Platform, Collaborative Innovation Center of Chemical Science & Engineering, Tianjin, PR China. Electronic address: wwzhang8@tju.edu.cn.
authors.forename: Weiwen
authors.initials: W
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D001426:Bacterial Proteins / Q000235:genetics* / Q000502:physiology*; D020869:Gene Expression Profiling; D015964:Gene Expression Regulation, Bacterial; D009876:Operon; D060066:Protein Interaction Maps; D020543:Proteome / Q000032:analysis; D040901:Proteomics / Q000379:methods; D013312:Stress, Physiological; D046939:Synechocystis / Q000235:genetics / Q000378:metabolism*
chemical_list: D001426:Bacterial Proteins; D020543:Proteome
keywords: Global algorithm; Hypothetical proteins; Network; Operon; Synechocystis