Automated network generation and analysis of biochemical reaction pathways using RING.

This paper describes how Rule Input Network Generator (RING), a network generation computational tool, can be adopted to generate a variety of complex biochemical reaction networks. The reaction language incorporated in RING allows representation of chemical compounds in biological systems with various structural complexity. Complex molecules such as oligosaccharides in glycosylation pathways can be described using a simplified representation of their monosaccharide building blocks and glycosidic bonds. The automated generation and topological network analysis features in RING also allow for: (1) constructing biochemical reaction networks in a rule-based manner, (2) generating graphical representations of the networks, (3) querying molecules containing a particular structural pattern, (4) finding the shortest synthetic pathways to a user-specified species, and (5) performing enzyme knockout to study their effect on the reaction network. Case studies involving three biochemical reaction systems: (1) Synthesis of 2-ketoglutarate from xylose in bacterial cells, (2) N-glycosylation in mammalian cells, and (3) O-glycosylation in mammalian cells are presented to demonstrate the capabilities of RING for robust and exhaustive network generation and the advantages of its post-processing features.

Fine-Scale Biogeography and the Inference of Ecological Interactions Among Neutrophilic Iron-Oxidizing Zetaproteobacteria as Determined by a Rule-Based Microbial Network.

Hydrothermal vents, such as those at Lo'ihi Seamount and the Mariana Arc and back-arc, release iron required to support life from the Earth's crust. In these ecosystems, bacteria and archaea can oxidize the released iron and therefore play an important role in the biogeochemical cycles of essential nutrients. These organisms often form microbial mats, and the primary producers in these communities can support diverse higher trophic levels. One such class of bacteria are the Zetaproteobacteria. This class of bacteria oxidize iron and commonly produce extracellular iron oxyhydroxide matrices that provide architecture to the microbial mats, so they are considered foundational members of the community and ecosystem engineers. Zetaproteobacteria are responsible for the majority of iron-oxidation in circumneutral, marine, low-oxygen environments. To study the composition of these communities, microbial mats were collected using a biomat sampler, which allows for fine-scale collection of microbial mats. DNA was then extracted and amplified for analysis of the SSU rRNA gene. After quality control and filtering, the SSU rRNA genes from Mariana Arc and Lo'ihi Seamount microbial mat communities were compared pairwise to determine which site exhibits a greater microbial diversity and how much community overlap exists between the two sites. In-depth analysis was performed with the rule-based microbial network (RMN) algorithm, which identified a possible competitive relationship across oligotypes of a cosmopolitan Zetaproteobacteria operational taxonomic unit (OTU). This result demonstrated the ecological relevance of oligotypes, or fine-scale OTU variants. The oligotype distributions of the cosmopolitan ZetaOTUs varied greatly across the Pacific Ocean. The competitive relationship between dominant oligotypes at Lo'ihi Seamount and the Mariana Arc and back-arc may be driving their differential distributions across the two regions and may result in species divergence within a cosmopolitan ZetaOTU. This implementation of the RMN algorithm can both predict directional relationships within a community and provide insight to the level at which evolution is occurring across ecosystems.