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. 2013 Dec 27;7:142.
doi: 10.1186/1752-0509-7-142.

Rapid Construction of Metabolic Models for a Family of Cyanobacteria Using a Multiple Source Annotation Workflow

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Free PMC article

Rapid Construction of Metabolic Models for a Family of Cyanobacteria Using a Multiple Source Annotation Workflow

Thomas J Mueller et al. BMC Syst Biol. .
Free PMC article

Abstract

Background: Cyanobacteria are photoautotrophic prokaryotes that exhibit robust growth under diverse environmental conditions with minimal nutritional requirements. They can use solar energy to convert CO2 and other reduced carbon sources into biofuels and chemical products. The genus Cyanothece includes unicellular nitrogen-fixing cyanobacteria that have been shown to offer high levels of hydrogen production and nitrogen fixation. The reconstruction of quality genome-scale metabolic models for organisms with limited annotation resources remains a challenging task.

Results: Here we reconstruct and subsequently analyze and compare the metabolism of five Cyanothece strains, namely Cyanothece sp. PCC 7424, 7425, 7822, 8801 and 8802, as the genome-scale metabolic reconstructions iCyc792, iCyn731, iCyj826, iCyp752, and iCyh755 respectively. We compare these phylogenetically related Cyanothece strains to assess their bio-production potential. A systematic workflow is introduced for integrating and prioritizing annotation information from the Universal Protein Resource (Uniprot), NCBI Protein Clusters, and the Rapid Annotations using Subsystems Technology (RAST) method. The genome-scale metabolic models include fully traced photosynthesis reactions and respiratory chains, as well as balanced reactions and GPR associations. Metabolic differences between the organisms are highlighted such as the non-fermentative pathway for alcohol production found in only Cyanothece 7424, 8801, and 8802.

Conclusions: Our development workflow provides a path for constructing models using information from curated models of related organisms and reviewed gene annotations. This effort lays the foundation for the expedient construction of curated metabolic models for organisms that, while not being the target of comprehensive research, have a sequenced genome and are related to an organism with a curated metabolic model. Organism-specific models, such as the five presented in this paper, can be used to identify optimal genetic manipulations for targeted metabolite overproduction as well as to investigate the biology of diverse organisms.

Figures

Figure 1
Figure 1
Comparison of the percentage of non-exchange reactions without associated genes between the five models and five curated models, iCyt773, iSyn731 [10], iCce806 [11], iAF1260 [28], and the Synechocystis PCC 6803 model developed by Knoop et al. [37]. The model-organism correlations are iCyt773 and iCce806: Cyanothece ATCC 51142, iSyn731 and Knoop et al.: Synechocystis PCC 6803, and iAF1260: Escherichia coli K-12 MG1655.
Figure 2
Figure 2
Comparison of reaction similarity to phylogenetic relationships: (A) Venn diagram comparing the number of reactions each model shares with the iCyt773 model (B) Similarity matrix for the five models. See Methods for description of the similarity calculation done to compare reactions between two models. Both model names and organism numbers are included.
Figure 3
Figure 3
Comparison of fermentative butanol pathway enzymes present in each of the five species: The enzymes highlighted are present in the organism’s reconstruction along with the associated reaction. Listed e-values are for BLAST searches between the genes of the five species and the associated gene in Clostridium acetobutylicum and the adhA gene in Synechocystis 6803. EC-gene relationships: 2.3.1.9: CA_C2873, 1.1.1.36: CA_C2708, 4.2.1.17: CA_C2712, 1.3.99.2: CA_C2711, 1.2.1.10: CA_P0035, 1.1.1.-: slr1192.
Figure 4
Figure 4
Workflow for development of draft models: These models are developed from a sequenced genome and curated genome scale model of related organism. The right hand side outlines the steps required to evaluate the reactions in iCyt773 for their presence in the other organisms. The steps to retrieve gene annotations and resolve any conflicts are shown on the left hand side. The steps in gray were automated, whereas the manually performed step, the resolution of conflicting annotations, is shown in white.

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