Genome-Scale Reconstruction and Analysis of the Metabolic Network in the Hyperthermophilic Archaeon Sulfolobus Solfataricus

Thomas Ulas,Bettina Siebers,Dietmar Schomburg,S. Alexander Riemer,Melanie Zaparty,John Parkinson

doi:10.1371/journal.pone.0043401

Abstract

We describe the reconstruction of a genome-scale metabolic model of the crenarchaeon Sulfolobus solfataricus, a hyperthermoacidophilic microorganism. It grows in terrestrial volcanic hot springs with growth occurring at pH 2–4 (optimum 3.5) and a temperature of 75–80°C (optimum 80°C). The genome of Sulfolobus solfataricus P2 contains 2,992,245 bp on a single circular chromosome and encodes 2,977 proteins and a number of RNAs. The network comprises 718 metabolic and 58 transport/exchange reactions and 705 unique metabolites, based on the annotated genome and available biochemical data. Using the model in conjunction with constraint-based methods, we simulated the metabolic fluxes induced by different environmental and genetic conditions. The predictions were compared to experimental measurements and phenotypes of S. solfataricus. Furthermore, the performance of the network for 35 different carbon sources known for S. solfataricus from the literature was simulated. Comparing the growth on different carbon sources revealed that glycerol is the carbon source with the highest biomass flux per imported carbon atom (75% higher than glucose). Experimental data was also used to fit the model to phenotypic observations. In addition to the commonly known heterotrophic growth of S. solfataricus, the crenarchaeon is also able to grow autotrophically using the hydroxypropionate-hydroxybutyrate cycle for bicarbonate fixation. We integrated this pathway into our model and compared bicarbonate fixation with growth on glucose as sole carbon source. Finally, we tested the robustness of the metabolism with respect to gene deletions using the method of Minimization of Metabolic Adjustment (MOMA), which predicted that 18% of all possible single gene deletions would be lethal for the organism.

Highlights

In recent years an increase of the use of genome-scale computer models for the reconstruction and prediction of cellular metabolic properties can be observed
With growing availability of genomes across the three domains of life, genome-scale reconstructions of metabolic networks are available for a number of organisms such as Escherichia coli (Bacteria) [1], Methanosarcina acetivorans (Archaea) [2], and Arabidopsis thaliana (Eukaryota) [3]
Reconstruction of the S. solfataricus model The initial model was created pathway by pathway from the genome annotation and manually completed to allow the production of all biomass constituents. This metabolic reconstruction of S. solfataricus was based on published annotations of the S. solfataricus P2 genome, different biochemical databases including KEGG [18], MetaCyc [19], BRENDA [20], Sulfolobus-specific literature, and experimental data generated in our lab

Summary

Introduction

In recent years an increase of the use of genome-scale computer models for the reconstruction and prediction of cellular metabolic properties can be observed. Metabolic reconstruction starts with a full genome annotation of a particular organism, in particular the prediction of enzymes and transporters, and the addition of enzyme-catalyzed reactions. To date there are only two models of archaeal organisms available (Methanosarcina barkeri [7] and Methanosarcina acetivorans [2]), in contrast to the numerous published models of Bacteria and Eukaryota (http:// gcrg.ucsd.edu). Both M. barkeri and M. acetivorans are mesophilic anaerobic methanogens, which are very closely related to each other (same genus) and belong to the phylum Euryarchaeota. As an interesting and experimentally characterized representative of the Archaea, Sulfolobus solfataricus was modeled in this work

Methods

Results

Conclusion