Comparative genome sequence analysis has become the predominant tool for genome-scale reconstruction of the metabolic network of microorganisms. Frequently, however, due to incomplete annotation or undocumented functional genes, there are gaps and uncertainties within the metabolic network that need to be resolved experimentally. These limitations get in the way of a comprehensive understanding of their metabolism and interfere with the creation of quantitative genome-scale models of metabolism. This hinders the ability to rationally modulate metabolism for biotechnological or medical purposes.
Here, we used 13
C-labeled tracer experiments to elucidate the in vivo
function of the TCA cycle and other primary metabolic pathways in C. acetobutylicum
. In contrast to the prevailing hypothesis, we found that this organism has a complete, albeit bifurcated, TCA cycle; oxaloacetate flows to succinate both through citrate/α-ketoglutarate and via malate/fumarate. Although there is currently no gene annotated as citrate synthase in C. acetobutylicum
, our data revealed the presence of a citrate synthase with Re
-stereospecificity. An Re
-citrate synthase has recently been identified in Clostridium kluyveri
as the product of a gene predicted to encode isopropylmalate synthase (17
). The corresponding protein in C. acetobutylicum
, CAC0970, has a 64% amino acid sequence identity and is one candidate for the Re
-citrate synthase in this organism. While aconitase and isocitrate dehydrogenase were not annotated when the genome sequence of C. acetobutylicum
was first released (23
), the genes CAC0971 and CAC0971 are now annotated as such in the Kyoto Encyclopedia of Genes and Genomes (KEGG). The products of these genes, however, have not yet been characterized in C. acetobutylicum
or in any other clostridia. The α-ketoglutarate dehydrogenase complex is missing in the C. acetobutylicum
genome, but it has been hypothesized that a putative 2-oxoacid ferredoxin oxidoreductase (CAC2458) could catalyze succinyl-CoA formation from α-ketoglutarate (23
). There are still no candidate genes encoding fumarate reductase/succinate dehydrogenase or succinyl-CoA synthetase.
Initially defined by a set of broad phenotypic characteristics such as rod-like morphology, Gram-positive cell walls, endospore formation, and strict anaerobic metabolism, Clostridium
is one of the most heterogeneous bacterial genera (5
). In a sequence-based species tree, there are a number of independent and deeply branching sublines within the Clostridium
subdivision, which also includes many nonclostridial species (4
). Among the clostridia, C. kluyveri
shows a unique metabolism; it grows anaerobically on ethanol and acetate as sole energy sources (27
). Only about half of the genes in C. kluyveri
show more than 60% similarity in C. acetobutylicum
). The similarities that we observe between C. acetobutylicum
and C. kluyveri
regarding the oxidative production of α-ketoglutarate and one-carbon metabolism (as discussed further below) are therefore noteworthy.
In both the initial genome sequencing and a subsequent genome-scale reconstruction of the C. acetobutylicum metabolic network, it was proposed that α-ketoglutarate is synthesized from oxaloacetate by running the TCA cycle reductively. It was argued that a reductive TCA cycle would be favored given the low redox potential of the internal anaerobic environment of C. acetobutylicum. It is therefore intriguing that C. acetobutylicum synthesizes α-ketoglutarate exclusively oxidatively. The reasons for this remain unclear, but the conversion of α-ketoglutarate into succinyl-CoA appears to be irreversible in this organism; although succinate is readily synthesized via α-ketoglutarate, there is no back-flux from succinate to α-ketoglutarate, even under conditions in which there is ample production of succinate by the reductive TCA cycle (as when cells are grown in the presence of aspartate). The irreversibility is expected if this reaction is catalyzed by a yet-to-be-identified α-ketoglutarate dehydrogenase but not if it is catalyzed, as previously proposed, by a reversible 2-oxoacid ferredoxin oxidoreductase.
Given that α-ketoglutarate is synthesized solely via citrate, succinate becomes a metabolite of limited biosynthetic value. The benefit of maintaining two different routes for its production is therefore unclear. A possibility is that a bifurcated TCA cycle ending in succinate plays a role in cellular redox balance. However, the rate of succinate excretion (~4 μmol/h/g cells [dry weight]) is very low compared to that of other fermentation products such as acetate and butyrate (~4 mmol/h/g cells [dry weight]) (see Fig. S6 in the supplemental material). Another possibility is that this particular arrangement of the TCA cycle facilitates the utilization of certain amino acids as nitrogen sources. For example, when C. acetobutylicum is grown in glutamate or aspartate as the sole nitrogen source, large amounts of α-ketoglutarate or oxaloacetate are produced during deamination. While a fraction of these carbon skeletons may be used for biosynthetic purposes, most must be discarded. Their conversion to succinate, and subsequent excretion, provides a short and rapid route. These hypotheses are consistent with the data obtained from our experiments with [13C]glutamate and [13C]aspartate.
In most organisms, glycine is synthesized from serine, producing a C1
unit during the process. Glycine, in turn, can also be used to produce a C1
unit. In contrast, in C. acetobutylicum
, the major route (~90%) for the production of glycine is via threonine. This necessitates C1
unit production from a precursor other than serine, and we found that C1
units are derived predominantly (~90%) from the carboxyl group of pyruvate. A related situation has been observed in C. kluyveri
, in which 67% of glycine is formed from threonine and 33% from serine, and about 25% of C1
units are synthesized from serine and 75% from CO2
). The production of C1
units from the carboxyl group of pyruvate (oxidation state, +3) can be viewed as a reductive pathway while their production from the methylene group of serine or glycine (oxidation state, −1) can be considered an oxidative pathway. For example, using serine as the source for C1
units, the production of 10-formyl-tetrahydrofolate (used in purine biosynthesis) is accompanied by the production of one NADH; using glycine, two NADHs are produced. However, no NADH is produced when pyruvate is used as the source of C1
units for the production of 10-formyl-tetrahydrofolate. Therefore, for an anaerobic bacterium such as C. acetobutylicum
, it makes sense to derive C1
units from the carboxyl group of pyruvate. Also, the capacity to produce C1
units both reductively and oxidatively suggests that the relative utilization of these pathways may be yet another way to control cellular redox balance.
Our observations strengthen the notion that pyruvate constitutes a pivotal metabolic crossroads in C. acetobutylicum, linking the TCA cycle, amino acid biosynthesis pathways, one-carbon metabolism, and acid/solvent-producing pathways. It therefore represents a control point that could be exploited to improve biofuel production. For example, decreasing the activity of pyruvate carboxylase should decrease the flux of pyruvate into the TCA cycle and associated amino acid biosynthesis pathways and increase pyruvate flux into acetyl-CoA and solvent production.
The dynamic isotope labeling approach (kinetic flux profiling) that we use here is different from the steady-state isotopic approach (metabolic flux analysis) recently used in similar contexts (6
). One major advantage of our approach is that it provides absolute fluxes throughout the network instead of just ratios of fluxes at branch points. Additional advantages include easy data deconvolution and short labeling time. The quantitative modeling technique used in this study is generally applicable for the identification of metabolic fluxes from dynamic isotope tracer experiments (22
). In addition to providing a quantitative understanding of the target metabolic networks, we have shown its ability to discriminate among competing network structures that produce qualitatively indistinguishable labeling patterns. Moreover, given the appropriate input data, the general nonlinear identification strategy can also be employed for the construction of dynamic models that reflect the regulation of metabolic fluxes (8
). Such dynamic models can enable a more comprehensive understanding and rational engineering of metabolic networks. In the case of C. acetobutylicum
, for example, a model of dynamic regulation could be used to design genetic and nutrient perturbations that enhance solvent and/or biohydrogen production.
This study represents the first in vivo experimental characterization of the TCA cycle and central metabolism in C. acetobutylicum and exemplifies the potential of dynamic isotope tracer studies and quantitative flux modeling in complementing genome-based metabolic network reconstruction.