The human metabolic reconstruction Recon 1 directs hypotheses of novel human metabolic functions

Abstract

Background: Metabolic network reconstructions formalize our knowledge of metabolism. Gaps in these networks pinpoint regions of metabolism where biological components and functions are "missing." At the same time, a major challenge in the post genomic era involves characterisation of missing biological components to complete genome annotation.

Results: We used the human metabolic network reconstruction RECON 1 and established constraint-based modelling tools to uncover novel functions associated with human metabolism. Flux variability analysis identified 175 gaps in RECON 1 in the form of blocked reactions. These gaps were unevenly distributed within metabolic pathways but primarily found in the cytosol and often caused by compounds whose metabolic fate, rather than production, is unknown. Using a published algorithm, we computed gap-filling solutions comprised of non-organism specific metabolic reactions capable of bridging the identified gaps. These candidate solutions were found to be dependent upon the reaction environment of the blocked reaction. Importantly, we showed that automatically generated solutions could produce biologically realistic hypotheses of novel human metabolic reactions such as of the fate of iduronic acid following glycan degradation and of N-acetylglutamate in amino acid metabolism.

Conclusions: The results demonstrate how metabolic models can be utilised to direct hypotheses of novel metabolic functions in human metabolism; a process that we find is heavily reliant upon manual curation and biochemical insight. The effectiveness of a systems approach for novel biochemical pathway discovery in mammals is demonstrated and steps required to tailor future gap filling algorithms to mammalian metabolic networks are proposed.

Figure 1

Automated gap filling of RECON 1 using the SMILEY algorithm. A) A simplified metabolic network. Reactions that are able to carry flux are shown in blue. Reactions unable to carry flux (red) are blocked and are caused by a root no-consumption metabolite (a in 1) and a root no-production metabolite (b in 2). Dead end metabolites can cause multiple blocked reactions refferred to as a cascade of blocked reactions. Reactions 2 and 3 occur in a blocked cascade caused by b. Note that c is a blocked intermediate but not a root-no production metabolite. B) The SMILEY algorithm identified reactions in the metabolic reaction matrix S (e.g. RECON 1) that were unable to carry flux under steady state conditions and then computed resolving reactions found in either U or X that needed to be added to S in order to restore flux through the blocked reaction. C) SMILEY solutions were categorised based on the resolving reactions required to restore flux. A category I reversal solution, if added to the network shown in A, only restores flux through reaction 1. The category II solution, addition of a novel metabolic reaction, restores flux through reactions 1, 2 and 3. The category III transport solution restores flux through reactions 2 and 3 only. SMILEY can suggest multiple solutions for a blocked reaction.

Figure 2

Characterisation of blocked reactions in RECON 1. A) Classification of blocked reactions in RECON 1 depending on their causative dead-end metabolite. B) The cellular distribution of dead-end metabolites, blocked reactions, and blocked reaction cascades within cellular compartments accounted for in RECON 1. C) The metabolic pathway distribution of the 175 blocked reactions investigated. D) The distribution of BiGG database confidence scores for the blocked reactions investigated. 3 = biochemical and or genetic evidence, 2 = physiological evidence or evidence from a nonhuman mammalian cell, 1 = modelling evidence, 0 = unevaluated.

Figure 3

Characterisation of gap filling solutions proposed by SMILEY. A) The number of SMILEY solutions proposed for each blocked reaction was not even, suggesting that it is easier to incorporate some dead-end metabolites into RECON 1 over others. Approximately 49% of the blocked reactions had a single proposed solution while 29% could be circumvented in a highly dynamic manner with twenty proposed solutions. B) 85% of the blocked reactions had SMILEY solutions composed of less than three resolving reactions.

Figure 4

Blocked reactions have different SMILEY solutions depending upon their metabolic origin and were validated with experimental evidence. Blocked reactions were resolved by connecting their corresponding blocked metabolite back into RECON 1. A shows the number of blocked reactions resolved with each solution category and, directly below in B, the metabolic pathway distribution of the blocked reactions having that particular SMILEY solution. Some blocked reactions, such as those involved in amino acid metabolism, are easily bypassed using functionalities already described in the KEGG database. Others, such as those involved in glycan biosynthesis, can only be solved by transporting their causative dead-end metabolite out of the system. C) Proposed solutions were validated by comparing category I solutions to experimentally reported enzyme directionalities. Similarly, we investigated whether category II solutions were gene associated in humans and whether the dead-end metabolites, to which the category III solutions applied, have been detected in human biofluids.

Figure 5

Category I solution for the blocked reaction ADPMAN. ADP-mannose (boxed in red) is a root no-production metabolite within RECON 1. The SMILEY solution (green arrow) involved reversal of the blocked reaction ADPMAN (red arrow). This appears plausible as an enzyme catalysing such a reaction (EC 3.7.7.28) has been described in various mammals [39] along with the finding that mannose-1-phosphate guanylyltransferase (EC 2.7.7.13) is known to be reversible and accept sugar donors other than GTP [40].

Figure 6

Category III solution for five blocked reactions occurring in dermatan sulfate degradation. Iduronic acid (idour, boxed in red) was identified as a root no-consumption metabolite in dermatan sulfate degradation in the lysosome. Flux was restored through the blocked reactions (red arrows) by addition of an extracellular transport function for idour (green arrow). Review of the literature indicates that this SMILEY generated hypothesis is biologically plausible. See text for details.

Figure 7

Category II solution for blocked reactions in peroxisomal fatty acid degradation. The blocked reactions (red arrows) are all catalysed by acetyl-CoA-acyltransferase (EC 2.3.1.16). The SMILEY solutions (green arrows) for each of the five blocked reactions generated a complete degradation pathway for saturated fatty acids in the peroxisome starting with stearoyl-CoA (StCoa) and ending in octanoyl-CoA (OcCoa) through stepwise removal of two carbons from the acyl chain. Abbreviations are as described in the BiGG database [18]. Enzyme commission numbers of all reactions are shown. Metabolites and reactions in blue are not blocked. The number of carbons of each fatty acid-CoA derivative is indicated. The results show that the SMILEY algorithm is capable of generating plausible solutions to blocked reactions in human metabolism. The resolving reactions suggested by SMILEY correspond to well-characterised reactions involved in the β-oxidation of fatty acids [50,79].

Figure 8

Category II solutions to three blocked reactions in urea metabolism. Flux was restored through the blocked reaction AGPRim by the addition of two resolving reactions (EC 2.7.2.8 and EC 2.6.1.11) which couple AGPRim to the blocked reactions ACGSm and ACODA through the consumption and production of their dead-end metabolites, N-acetylglutamate and N-acetylornithine, respectively. We found no evidence that could rule out this gap filling hypotheses. The S1 solutions to the blocked reactions ACGSm and ACODA were identical and involved inter-conversion of the dead-end metabolites of these reactions by glutamate N-acetyltransferase (EC 2.3.1.35). As opposed to the solution for AGPRim, we did not find any indications that reactions similar to EC 2.3.1.35 are found in humans.