Genome-scale metabolic network reconstruction and in silico flux analysis of the thermophilic bacterium Thermus thermophilus HB27

Abstract

Background: Thermus thermophilus, an extremely thermophilic bacterium, has been widely recognized as a model organism for studying how microbes can survive and adapt under high temperature environment. However, the thermotolerant mechanisms and cellular metabolism still remains mostly unravelled. Thus, it is highly required to consider systems biological approaches where T. thermophilus metabolic network model can be employed together with high throughput experimental data for elucidating its physiological characteristics under such harsh conditions.

Results: We reconstructed a genome-scale metabolic model of T. thermophilus, iTT548, the first ever large-scale network of a thermophilic bacterium, accounting for 548 unique genes, 796 reactions and 635 unique metabolites. Our initial comparative analysis of the model with Escherichia coli has revealed several distinctive metabolic reactions, mainly in amino acid metabolism and carotenoid biosynthesis, producing relevant compounds to retain the cellular membrane for withstanding high temperature. Constraints-based flux analysis was, then, applied to simulate the metabolic state in glucose minimal and amino acid rich media. Remarkably, resulting growth predictions were highly consistent with the experimental observations. The subsequent comparative flux analysis under different environmental conditions highlighted that the cells consumed branched chain amino acids preferably and utilized them directly in the relevant anabolic pathways for the fatty acid synthesis. Finally, gene essentiality study was also conducted via single gene deletion analysis, to identify the conditional essential genes in glucose minimal and complex media.

Conclusions: The reconstructed genome-scale metabolic model elucidates the phenotypes of T. thermophilus, thus allowing us to gain valuable insights into its cellular metabolism through in silico simulations. The information obtained from such analysis would not only shed light on the understanding of physiology of thermophiles but also helps us to devise metabolic engineering strategies to develop T. thermophilus as a thermostable microbial cell factory.

Figure 1

Distribution of reactions and genes across various metabolic subsystems in i TT548.

Figure 2

Metabolic organization and biomass composition of T. thermophilus and E. coli. (A) General features of the iTT548 in comparison with E. coli iAF1260 GSMM (Feist et al. 2007), (B) Central metabolic network of T. thermophilus, (C) amino acid composition (mol%) and (D) fatty acid composition (mol%). The numbers in the Venn diagram represents the enzymes in each organism. The common and unique pathways of T. thermophilus are highlighted with blue and red backgrounds, respectively. The number of unique and common enzymes was identified using the EC numbers. The biomass data for E. coli was obtained from iAF1260 GSMM. See supplementary 1 for metabolite and enzyme abbreviations used in the network diagram.

Figure 3

Batch fermentation profile of optical density and various nutrients in glucose minimal and complex medium. (A) Profiles of optical density and residual concentrations of the glucose, acetate and lactate in glucose minimal medium, (B) optical density and residual concentrations of glucose, trehalose, lactate and acetate in complex medium, (C) concentrations of amino acids which were rapidly consumed in complex media and (D) amino acids which were not completely consumed. Highlighted regions correspond to exponential growth phases of the cultures and the corresponding nutrient consumption/secretion profiles were used for in silico simulations.

Figure 4

Comparison of in silico growth rate with experimentally observed growth rate during exponential phase of the cell culture in glucose minimal medium.

Figure 5

Distribution of essential genes in T. thermophilus metabolic subsystems. Black, grey and white colors indicate the completely-, conditionally- and non-essential genes, respectively. The numbers within the parenthesis represent the number of genes in each subsystem.

Figure 6

Influence of temperature on T. thermophilus biomass composition. (A) amino acid composition (mol%) at 70°C and 45°C and (B) fatty acid composition (mol%) at 70°C and 40°C.