Dataset Information

Using Sub-Network Combinations to Scale Up an Enumeration Method for Determining the Network Structures of Biological Functions.

ABSTRACT: Deduction of biological regulatory networks from their functions is one of the focus areas of systems biology. Among the different techniques used in this reverse-engineering task, one powerful method is to enumerate all candidate network structures to find suitable ones. However, this method is severely limited by calculation capability: due to the brute-force approach, it is infeasible for networks with large number of nodes to be studied using traditional enumeration method because of the combinatorial explosion. In this study, we propose a new reverse-engineering technique based on the enumerating method: sub-network combinations. First, a complex biological function is divided into several sub-functions. Next, the three-node-network enumerating method is applied to search for sub-networks that are able to realize each of the sub-functions. Finally, complex whole networks are constructed by enumerating all possible combinations of sub-networks. The optimal ones are selected and analyzed. To demonstrate the effectiveness of this new method, we used it to deduct the network structures of a Pavlovian-like function. The whole Pavlovian-like network was successfully constructed by combining robust sub-networks, and the results were analyzed. With sub-network combination, the complexity has been largely reduced. Our method also provides a functional modular view of biological systems.

SUBMITTER: Xi JY

PROVIDER: S-EPMC5161363 | biostudies-other | 2016

REPOSITORIES: biostudies-other

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Using Sub-Network Combinations to Scale Up an Enumeration Method for Determining the Network Structures of Biological Functions.

Xi J Y JY Ouyang Q Q

PloS one 20161216 12

Deduction of biological regulatory networks from their functions is one of the focus areas of systems biology. Among the different techniques used in this reverse-engineering task, one powerful method is to enumerate all candidate network structures to find suitable ones. However, this method is severely limited by calculation capability: due to the brute-force approach, it is infeasible for networks with large number of nodes to be studied using traditional enumeration method because of the com ...[more]

PMID: 27992476

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Project description:Root selection of their associated microbiome composition and activities is determined by the plant's developmental stage and distance from the root. Total gene abundance, structure and functions of root-associated and rhizospheric microbiomes were studied throughout wheat growth season under field conditions. On the root surface, abundance of the well-known wheat colonizers Proteobacteria and Actinobacteria decreased and increased, respectively, during spike formation, whereas abundance of Bacteroidetes was independent of spike formation. Metagenomic analysis combined with functional co-occurrence networks revealed a significant impact of plant developmental stage on its microbiome during the transition from vegetative growth to spike formation. For example, gene functions related to biofilm and sensorial movement, antibiotic production and resistance and carbons and amino acids and their transporters. Genes associated with these functions were also in higher abundance in root vs. the rhizosphere microbiome. We propose that abundance of transporter-encoding genes related to carbon and amino acid, may mirror the availability and utilization of root exudates. Genes related to antibiotic resistance mechanisms were abundant during vegetative growth, while after spike formation, genes related to the biosynthesis of various antibiotics were enriched. This observation suggests that during root colonization and biofilm formation, bacteria cope with competitor's antibiotics, whereas in the mature biofilm stage, they invest in inhibiting new colonizers. Additionally, there is higher abundance of genes related to denitrification in rhizosphere compared to root-associated microbiome during wheat growth, possibly due to competition with the plant over nitrogen in the root vicinity. We demonstrated functional and phylogenetic division in wheat root zone microbiome in both time and space: pre- and post-spike formation, and root-associated vs. rhizospheric niches. These findings shed light on the dynamics of plant-microbe and microbe-microbe interactions in the developing root zone.

Dataset Information

Using Sub-Network Combinations to Scale Up an Enumeration Method for Determining the Network Structures of Biological Functions.

Publications

Using Sub-Network Combinations to Scale Up an Enumeration Method for Determining the Network Structures of Biological Functions.

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