Genome-Scale Metabolic Modeling of Archaea Lends Insight into Diversity of Metabolic Function

Abstract

Decades of biochemical, bioinformatic, and sequencing data are currently being systematically compiled into genome-scale metabolic reconstructions (GEMs). Such reconstructions are knowledge-bases useful for engineering, modeling, and comparative analysis. Here we review the fifteen GEMs of archaeal species that have been constructed to date. They represent primarily members of the Euryarchaeota with three-quarters comprising representative of methanogens. Unlike other reviews on GEMs, we specially focus on archaea. We briefly review the GEM construction process and the genealogy of the archaeal models. The major insights gained during the construction of these models are then reviewed with specific focus on novel metabolic pathway predictions and growth characteristics. Metabolic pathway usage is discussed in the context of the composition of each organism's biomass and their specific energy and growth requirements. We show how the metabolic models can be used to study the evolution of metabolism in archaea. Conservation of particular metabolic pathways can be studied by comparing reactions using the genes associated with their enzymes. This demonstrates the utility of GEMs to evolutionary studies, far beyond their original purpose of metabolic modeling; however, much needs to be done before archaeal models are as extensively complete as those for bacteria.

Figure 1

Diversity of archaeal models. A visualization of the diversity of archaeal genome-scale metabolic models as related by phylogeny. The figure is adapted from Elkins et al. [27] where the maximum-likelihood tree was constructed using 33 conserved ribosomal proteins and three largest RNA polymerase subunits. Highlighted species indicate that genome-scale metabolic models have been constructed for that organism. Although not shown in this adapted figure, a Methanobrevibacter smithii model within the Euryarchaeota has also been constructed. While numerous models have been constructed for Euryarchaeota, the Crenarchaeota are severely underrepresented.

Figure 2

Genealogy of archaeal models. A diagram showing the evolution/genealogy of archaeal models since the reconstruction of M. jannaschii in 2004. Each box represents a single metabolic model and includes the species name, the name of the model, and the percentage of protein coding genes (where available) that are incorporated in the model. The sole representative of the Crenarchaeota kingdom [28] is highlighted in orange.

Figure 3

Methanogenesis pathway framework. (a) The basic structure of methanogenesis showing where the major growth substrates across all methanogens enter the pathway. The simplest methanogens are only capable of growing on CO₂/H₂ and/or formate while the most complex methanogens are also capable of methylotrophic and acetotrophic growth. H₄S/MPT stands for tetrahydrosarcinapterin (H₄SPT) and tetrahydromethanopterin (H₄MPT). The former is found exclusively in Methanosarcinales whereas the latter is found in all other methanogens. (b) The hypothesized methanogenesis pathways for M. hungatei (iMhu428) [21]. Although it cannot use acetate as an energy source, the pathway to take up acetate is still present to shuttle it into gluconeogenesis. (c) The hypothesized methanogenesis pathway for M. acetivorans (iST807) [29]. The conventional CO₂ reduction pathway is only run in reverse as this methanogen cannot metabolize CO₂. (d) The hypothesized methanogenesis pathway for M. barkeri (iAF692) [19] which bears great resemblance to that of M. acetivorans. The major differences between the two organisms' methanogenesis pathways lie in the electron transport chain (ETC). The specific pathways for each methanogen follow the same topological structure as the general methanogenesis illustration. Red circles are metabolites while green diamonds signify enzymatic reactions of the pathway.

Figure 4

Growth characteristics of M. acetivorans models. The models were simulated using experimental growth substrate uptakes of MeOH:20, Acetate:7, and CO:11.6 mmol/gDCW/hr. Since experimental TMA uptake rates were not available, it was set to 6.77 mmol/gDCW/hr across all the models. This value was determined by fitting iST807 to experimental growth rates on TMA. iVS941 gave unrealistically large growth yields and therefore the values were omitted from the growth yield plot for a clearer display of the other models' performances. iVS941 also did not predict any methane production under the given growth conditions. Experimental growth rates are from [–40]. Experimental growth yields are from [–42]. Experimental CH₄ production rates are from [, –44].

Figure 5

Conservation of metabolic reactions. A map showing the extent of conservation for the reactions of the M. acetivorans model iST807 (as encoded in the gene-protein-reaction associations (GPRs) of the model). Nodes represent either a metabolite or reaction and edges indicate the dependencies between reactions and metabolites. Reactions on the blue end of the spectrum are facilitated by enzymes that are conserved in relatively few of the 221 archaea in the database while reactions in red are facilitated by highly conserved enzymes. Reactions with thin grey lines are not associated with genes. To assess conservation, the db_evaluateReactionsFromGpr.py functionality of the ITEP software [45] was used. It computes homologous genes to those in the GPRs of each reaction in iST807. The ITEP function was executed with the “or” option enabled to identify whether any of the enzymes (or enzymatic subunits) annotated as facilitating the reactions were encoded in the organism.

Figure 6

Fraction of conserved reactions. Grouping of the information shown in Figure 5 by metabolic subsystem (as annotated in iST807). The overall height of each bar indicates the total fraction of reactions in the metabolic subsystem that are conserved, while the height of individual portions of each bar indicates the relative conservation of reaction in the subsystem from that organism. The 221 archaea were grouped by taxonomic order, yielding 12 distinct groups as seen in the legend. Metabolic subsystems labels are color coded: amino acid metabolism subsystems in blue, vitamin and cofactor metabolism subsystems in green, central metabolism subsystems in red, and other categories in black.

Figure 7

Diversity and phylogeny of metabolic models. (a) The uniqueness of the reactions in each of the metabolic models. Here, we define uniqueness to be the fraction of 221 archaea that do not have the reaction currently present in the respective model; higher uniqueness means fewer of the organisms contain the genes coding enzymes that are annotated by the GPRs of the specified models. The presence of the genes is computed using ITEP as discussed in Figure 5. (b) A phylogenetic tree computed based on similarity to the M. acetivorans model iST807. This tree is based on the ITEP results discussed in Figure 5.