A Data Integration and Visualization Resource for the Metabolic Network of Synechocystis sp. PCC 6803  

Abstract

Data integration is a central activity in systems biology. The integration of genomic, transcript, protein, metabolite, flux, and computational data yields unprecedented information about the system level functioning of organisms. Often, data integration is done purely computationally, leaving the user with little insight in addition to statistical information. In this article, we present a visualization tool for the metabolic network of Synechocystis sp. PCC 6803, an important model cyanobacterium for sustainable biofuel production. We illustrate how this metabolic map can be used to integrate experimental and computational data for Synechocystis sp. PCC 6803 systems biology and metabolic engineering studies. Additionally, we discuss how this map, and the software infrastructure that we supply with it, can be used in the development of other organism-specific metabolic network visualizations. In addition to the Python console package VoNDA (http://vonda.sf.net), we provide a working demonstration of the interactive metabolic map and the associated Synechocystis sp. PCC 6803 genome-scale stoichiometric model, as well as various ready-to-visualize microarray data sets, at http://f-a-m-e.org/synechocystis.

Chirality Matters: Synthesis and Consumption of the d -Enantiomer of Lactic Acid by Synechocystis sp. Strain PCC6803

“…D-Lactic acid is consumed by wild-type Synechocystis cultured under mixotrophic conditions, while L-lactic acid is not used. In a recent computational metabolic network analysis (40), based on a genome-scale model of wild-type Synechocystis, the only annotated route involving lactic acid [from dihydroxyacetone-phosphate via methylglyoxal, (R)-S-lactoylglutathione, and lactic acid to pyruvate] did not show any flux under the conditions tested (continuous-light and day/night cycles) and thus appears nonessential for (optimal) growth. According to this scheme, the metabolite D-lactic acid resides between pyruvate and lactoylglutathione, linked by the reversible putative Slr1556 lactate dehydrogenase, and the unidirectional (R)-S-lactoylglutathione hydrolase that is exclusively active in the direction toward lactic acid.…”

Metabolic enzyme cost explains variable trade-offs between microbial growth rate and yield

“…These five EFMs and an experimentally determined flux distribution (denoted exp [32]; for calculations see Supplementary Text S4.1) are marked by colors in Figure 2(b) and listed in Table 1 and we refer to them as focal EFMs. Their full flux maps (produced using software from [33]) can be found in the SI section S5.2. As an example, the map for max-gr is also included in Figure 2(a).…”

Cyanobacteria as Chassis for Industrial Biotechnology: Progress and Prospects

“…Recently, a visual representation of the metabolic network of Synechocystis 6803 called FAME was produced (), which can incorporate experimental and computational data. FAME can be used as an aid to engineer the metabolic pathway of Synechocystis 6803 for the production of a range of high value products and biofuels [81]. …”

“…One example is focusing research on discovering the cause behind the inability of certain cyanobacterial strains to naturally transform with exogenous DNA, which could be enabled by incorporating a competence gene, like comF of Synechocystis 6803 [136], or silencing certain nucleases genes. in silico modeling, utilising flux balance analysis and systems biology, is a promising route for production pathway optimisation of select strains [81]. This is valid for strains with well-annotated genomes, like Synechocystis 6803, which makes achieving industrial-scale feasibility possible perhaps in the “near” future.…”