Computational Inference of Regulatory Pathways in Microbes: an Application to Phosphorus Assimilation Pathways in Synechococcus sp. WH8102

Zhengchang Su[1] (zhx@csbl.bmb.uga.edu)
Phuongan Dam[1] (phd@csbl.bmb.uga.edu)
Xin Chen[2] (xinchen@cs.ucr.edu)
Victor Olman[1] (olman@csbl.bmb.uga.edu)
Tao Jiang[2] (jiangt@cs.ucr.edu)
Brian Palenik[3] (palenikB@ucsd.edu)
Ying Xu[1](xyn@csbl.bmb.uga.edu)

[1]Department of Biochemistry and Molecular Biology, University of Georgia at Athens, and Computational Biology Institute, Oak Ridge National Laboratory
[2]Department of Computer Science and Engineering, University of California at Riverside
[3]Scripps Institute of Oceanography, University of California at San Diego


Abstract

We present a computational protocol for inference of regulatory and signaling pathways in a microbial cell, through literature search, mining “high-throughput” biological data of various types, and computer-assisted human inference. This protocol consists of four key components: (a) construction of template pathways for microbial organisms related to the target genome, which either have been extensively studied and/or have a significant amount of (relevant) experimental data, (b) inference of initial pathway models for the target genome, through combining the template pathway models and target genome-specific information, (c) refinement and expansion of the initial pathway models through applications of various data mining tools, including phylogenetic profile analysis, inference of protein-protein interactions, and prediction of transcription factor binding sites, and (d) validation and refinement of the pathway models using pathway-specific experimental data or other information. To demonstrate the effectiveness of this procedure, we have applied it to the construction of the phosphorus assimilation pathways in cyanobacterium sp. WH8102. We present, in this paper, a model of the core components of this pathway.

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Japanese Society for Bioinformatics