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Detailed profiling of carbon fixation of in silico synthetic autotrophy with reductive tricarboxylic acid cycle and Calvin-Benson-Bassham cycle in Esherichia coli using hydrogen as an energy source

Carbon fixation is the main route of inorganic carbon in the form of CO2 into the biosphere. In nature, RuBisCO is the most abundant protein that photosynthetic organisms use to fix CO2 from the atmosphere through the Calvin-Benson-Bassham (CBB) cycle. However, the CBB cycle is limited by its low catalytic rate and low energy efficiency. In this work, we attempt to integrate the reductive tricarboxylic acid and CBB cycles in silico to further improve carbon fixation capacity. Key heterologous enzymes, mostly carboxylating enzymes, are inserted into the Esherichia coli core metabolic network to assimilate CO2 into biomass using hydrogen as energy source. Overall, such a strain shows enhanced growth yield with simultaneous running of dual carbon fixation cycles. Our key results include the following. (i) We identified two main growth states: carbon-limited and hydrogen-limited; (ii) we identified a hierarchy of carbon fixation usage when hydrogen supply is limited; and (iii) we identified the alternative sub-optimal growth mode while performing genetic perturbation. The results and modeling approach can guide bioengineering projects toward optimal production using such a strain as a microbial cell factory.


Introduction
Carbon fixation is the main route of inorganic carbon in the form of CO 2 into the biosphere. Photoautotrophs such as plants, algae and cyanobacteria fix about 300 gigatons of CO 2 from the atmosphere annually through photosynthesis [1]. Six carbon fixation pathways in nature that assimilate CO 2 into cells have been identified and reviewed and the physiological roles of the central carboxylating enzymes have been discussed [2][3][4]. Efforts are also made to identify synthetic carbon fixation pathways using a computational approach [5,6]. In particular, Milo's group has searched over a database of~5000 enzymes for possible carbon fixation pathways and analyzed their performance and thermodynamic feasibility [5]. Attempts from heterologous Ribulose 1,5-bisphosphate carboxylase/oxygenase (RuBisCO) expression to facilitate growth in Escherichia coli (E. coli) have been made [7][8][9] and reviewed [10]. Recently, Antonovsky, et al. have also created a nonnative CBB cycle in E. coli to achieve hemi-autotrophic growth [11].
They employed adaptive laboratory evolution in xylose-limited chemostat to fine tune branching out of an intermediate metabolite in the CBB cycle to satisfy the kinetic requirements of the autocatalyic cycle [12]. Consequently, a fully-functional CBB pathway completely changes the trophic mode of E. coli. More importantly, the modularity of the design points to a direct path to replace the TCA-cycle-based energy module with energy harvesting molecular machinery [10]. A follow-up study elucidated the genetic basis and found the minimal set of mutations needed for a fully functional CBB cycle [13]. In vitro carbon fixation cycles with high kinetic rates under aerobic condition have also been demonstrated [14].
In nature, RuBisCO is the most abundant protein that photosynthetic organisms use to fix CO 2 from the atmosphere. The CBB cycle is often limited by its low catalytic rate but attempts to improve its performance have very marginal success [15,16]. In fact, the enzyme displays Pareto optimality with a trade-off between the enzyme catalytic rate and CO 2 specificity, possibly because of the difficulty in binding the featureless CO 2 molecules [16]. In this work, we address another naturally-existing carbon fixation cycle, namely the reductive tricarboxylic acid (TCA) cycle and attempt to integrate these two cycles into a single micro-organism, as shown in Fig. 1. In nature, the reductive TCA cycle plays a special role in carbon fixation because it is the most efficient pathway in terms of ATP consumption per CO 2 molecules fixed and runs near the thermodynamic edge [17].
In this study, we have chosen E. coli as it is still most genetically malleable micro-organism and the predicted strain can be readily realized using genetic engineering. We have chosen hydrogen as a convenient energy source, but the results obtained here can also be generalized to other energy sources. There are a few reasons to use hydrogen as an energy source. First, E. coli possesses innate hydrogenases that readily convert hydrogen to serve as reducing power and energy source of electrons for biosynthesis [18]. In comparison, to use light as an energy source, light harvesting machinery must be heterologously expressed, which is extremely challenging. Moreover, recent technological advances have enabled efficient electrosynthesis of hydrogen by combining semi-conductor based photovoltaic cells and highly efficient catalysts, which has made hydrogen a favorable and efficient energy source [19].
Constraint-based flux balance analysis has been extensively used to compute the growth yield and secretion of desired metabolic products [20,21]. To evaluate the feasibility of running a dual carbon fixation cycle, we identify and insert the necessary heterologous enzyme into a core metabolic network [22] and use constraint-based flux balance analysis to evaluate the resulting performance. We decided to use the core model instead of the genome-scale model of E. coli, as the core model is more generic and not too specific to E. coli; this may facilitate more general conclusions for other chassis microorganisms with similar central metabolisms. We employ constraint-based modeling to enable reliable predictions of how the CO 2 assimilation pathway integrates into the rest of the background metabolic network.

The model
In this study, we insert heterologous enzymes into the E. coli core metabolism model [22]. Because key carboxylating enzymes and hygrogenase are oxygen-sensitive, we only consider in silico growth under anaerobic conditions. To complete the non-native CBB cycle, we investigate the recent hemi-autotrophy strain [11] and inserted RuBisCO and phosphoribulokinase (prk) enzymes. The kinase prk enables the phosphorylation of ribulose-5-phosphate to yield ribulose-1,5-bisphosphate (RuBP), the substrate of RuBisCO. Upon expression of prk and RuBisCO, ribulose-5-phosphate is readily phosphorylated to yield RuBP and is subsequently converted to 3-phosphoglycerate, which enables completion of the non-native CBB cycle. To completely reverse the existing TCA cycle, we identify two irreversible reactions within the TCA cycle and choose to insert 2-oxoglutarate:ferredoxin oxidoreductase (OGOR) and ATP citrate lyase (ACL). In addition, because pyruvate oxidoreductase (POR) is normally considered part of the reductive TCA cycle [3], we also insert it to maximize the overall potential capacity for carbon fixation. Because glyoxylate shunt is part of the TCA cycle in E. coli, we also include the glyoxylate assimilation pathway [23] via 2-phosphoglycerate (2 PG). Consequently, glyoxylate can be a potential cycle product from the combination of the rTCA cycle and anaplerotic reactions. 2 PG is the connecting intermediate from glyoxylate shunt to glyconeogenesis. ATP maintenance requirements for non-growth-associated maintenance (NGAM) and growth-associated maintenance (GAM) are also included. The core biomass objective function uses an NGAM of 8.39 mmol ATP/(gDW h) and a GAM of 59.81 mmol ATP/gDW.

Constraint-based flux balance analysis
The constraint-based flux balance is given by a linear optimization problem.
S is the stoichiometric matrix and v is the flux vector. Z = f T v is the objective function. lb i and ub i are the lower and upper bound of the ith component of the flux vector, v, respectively [20,21]. Flux balance analysis was used to compute the growth rate given a set of constraints on the bottleneck reaction. The COBRA toolbox is used to the solve linear optimization problem. The biomass reaction with coefficients from the literature [24] is also included and serves as the objective function. In silico, the network successfully assimilates CO 2 with the dual carbon fixation cycle.

Electron uptake reaction
In our model, we assume that hydrogen is used as an electron donor and nitrate is used as a terminal electron acceptor. The electron transport chain details are shown in Fig. 2. In the context of chemiosmotic theory, all these seemingly complicated reactions in the electron transport chain aim to generate excessive proton motive force for pumping protons out of cells to drive ATPase and various other energy-linked processes [24]. Overall, the necessary proton motive force is provided by a pair of reactions in the electron transport chainhydrogen:menaquinone oxidoreductase and menaquinol:nitrate oxidoreductase. The reactions are given by Such a strategy of electron reversal is used by E. coli when the NADH supply is inadequate [24]. Additionally, we insert a heterologous enzyme or cytosolic or membrane-bound NADP + -reducing hydrogenase [25][26][27][28] as the auxiliary electron pathway.
The reducing power via cofactor ferredoxin can be provided by favin reductase (FR), which converts reducing power from NADH.

Profiling the autotrophic growth with hydrogen uptake
To understand the dual carbon fixation cycle, we fix the upper bound of flux of key enzymes -RuBisCO for the CBB cycle and OGOR and ACL for the rTCA cycle -as 1 mmol.gDW −1 .hr −1 . The growth rates for single and dual cycles as hydrogen uptake is varied are plotted in Fig. 3. The growth rate generally shows three distinct regions: (1) no growth, (2) hydrogen-limited state, and (3) carbon-limited state, as depicted in Fig. 3(b). The region of no growth is due to the failure of the energy supply to satisfy the ATP maintenance requirement. Beyond this region, as hydrogen increases, the growth rate shows a consistent increase until a plateau is reached. For simplicity, we plot one line in the hydrogen-limited state for Fig. 3(b), 3(c) and 3(d). In general, growth rate versus hydrogen curves could be multiple line segments in the region of hydrogen-limited state. Such multiple line segments indicate multiple phenotypes [21]. The region with a consistent increase and the plateau are identified as hydrogen-limited and carbon-limited states, respectively. At low hydrogen levels, the growth rate is limited by the hydrogen supply, which is a source of both energy and reducing power. When hydrogen is amply supplied, the growth rate is limited by the maximal flux of carboxylating enzymes. The efficiency difference between rTCA and CBB cycles is manifested in the different growth rates (biomass) with respect to hydrogen shown in Fig. 3(c). Note that the height of the plateau in Fig. 3(c) is related to the enzyme capacity of carboxylating enzymes, namely RuBisCO and OGOR. Equal enzyme capacity for RuBisCO and OGOR is assumed in Fig. 3(c). Close examination of the growth rate for dual and rTCA cycles reveals an overlapping region, shown in Fig. 3(d). In this overlapping region, only the rTCA cycle runs evenly, though both enzymes -RuBisCO and prkare needed to run the CBB cycle. Henceforth, we establish that the growth rate versus hydrogen uptake shows a hierarchy of usage in the carbon fixation cycle. In other words, at low hydrogen levels, the rTCA cycle will be fully used with no carboxylation in the CBB cycle as it is more energetically favorable to run only on the rTCA cycle. When hydrogen is amply supplied, both cycles will be used to maximally supply carbon because the inorganic carbon supply becomes a limiting factor.

Profiling the autotrophic growth with flux of carboxylating enzymes
Next, we conduct the profiling while varying the flux of two key carboxylating enzymes, RuBisCO and OGOR. The growth rate versus flux of RuBisCO and OGOR at various hydrogen uptake levels is displayed in Fig. 4. At very low hydrogen uptake (H 2 = −8 mmol⋅gDW −1 hr −1 ) corresponding to a hydrogen-limited state, there is a clear plateau in the region of dual carbon fixation, shown in Fig. 4(a). At very high hydrogen uptake (H 2 = −50 mmol⋅ gDW −1 hr −1 ) corresponding to a carbon-limited state, hydrogen is not a limiting factor for growth and there is no plateau. Profiling with hydrogen flux of carboxylating enzymes (Fig. 4) again shows two distinct states (carbonlimited and energy-limited). We can extend this distinction to different carboxylating enzyme capacity ratios and compare the maximal growth rate for single and dual cycles, as shown in Table 1. For the carbonlimited state (H 2 = −50 mmol.gDW −1 .hr −1 ), when hydrogen is amply supplied, the growth rate of the dual cycle exceeds that of the single cycle. For the hydrogen-limited state (H 2 = −8 mmol.gDW −1 .hr −1 ), the growth rate of dual cycle shows no enhancement compared with the single cycle when hydrogen is inadequately supplied.

Robustness analysis of dual carbon fixation
Varying a single parameter over a range of values and computing the objective for the linear optimization problem is termed robustness analysis [20,21]. Robustness analysis gives a much broader view of the optimal properties of a metabolic network. To demonstrate the usefulness of our strain, we can also carry out robustness analysis. In such a study, the upper bound of the selected reaction is varied and the corresponding growth rate is computed. For the data displayed in Fig. 5, we constrain the upper bound of RuBisCO, OGOR, and ACL reaction to 1 mmol⋅gDW −1 hr −1 for the central condition for the robustness study unless otherwise stated and the lower bound of hydrogen uptake is set to −50 mmol⋅gDW −1 hr −1 . Several interesting features are summarized. For OGOR, the curve shows multiple linear segments and therefore multiple phenotypes, as depicted in Fig. 5(b). In Fig. 5(f), when the flux of ferredoxin reductase reaches zero, the growth rate decreases to that of the CBB cycle only and rTCA is effectively shut off. This is reasonable because ferrodoxin is needed for the OGOR reaction in the rTCA cycle.

Alternative suboptimal growth mode
One interesting observation of the robustness study is that no knockout of the single heterologous enzyme in the simulation is lethal (Fig. 5). (To simulate the knockout of any enzyme, the corresponding reaction or reactions can simply be constrained to carry zero flux. By setting both the upper and lower bounds of a reaction to 0 mmol.gDW −1 hr −1 , a reaction is essentially knocked out, and is restricted from carrying flux.) This prompts us to perform a series of multiple enzyme knockout in the simulation to determine the viability and identify alternative suboptimal growth modes. The result is shown in Fig. 6. As a comparison, Fig. 6(a) shows a typical scenario of rTCA cycle, in which four carboxylating enzymes (POR, OGOR, isocitrate dehydrogenase, and phosphoenolpyruvate carboxylase) fix CO 2 and acetyl-CoA serves as the cycle product. There is one important caveat as we progressively remove heterologous enzymes in various combinations. When POR is knocked out, the glyoxylate shunt starts to emerge as shown in Fig. 6(b). When ACL is further removed, the strain shows viability (Fig. 6(c)). As the ACL reaction that provides a route to complete the rTCA cycle is removed, we expect complete disruption of the rTCA cycle because of its removal. The flux balance analysis result is somewhat surprising. Most flux (> 10% of the upperbound flux of OGOR) is concentrated on a cycle of four metabolites comprising  Table 1 Growth rate summary for single and dual carbon fixation for different enzyme capacity ratios and states. For the carbon-limited state, the results show that dual carbon fixation cycle enhances the growth rate. Growth rates of the dual cycle are higher than those of the single cycle. For the hydrogen-limited state, the dual cycle shows no growth rate enhancement. For the carbon-limited state, the lower bound of hydrogen uptake is set to −50 mmol.gDW −1 .hr −1 . For the hydrogenlimited state, the lower bound of hydrogen uptake is set to be −8 mmol.gDW −1 . hr −1 .  Fig. 6(c) is replotted in Fig. 6(d) to highlight that the four-metabolite cycle stands out and is no longer embedded within the rTCA cycle and the remaining enzymes in the existing TCA cycle play a role in completing the replenishment of intermediates drained for biosynthesis of biomass. Such a carbon fixation cycle is a metabolic shortcut of rTCA cycle and the enzyme isocitrate lyase bypasses the remaining rTCA cycle [5]. Moreover, one important feature is that glyxolate, a C2 compound, emerges as the only product of the carbon fixation cycle.
Here for the first time, we demonstrate its seamless integration with existing core metabolism of E. coli. We also find that one heterologous enzyme (OGOR) alone in the central metabolism will convert E. coli to grow in silico with such a four metabolite cycle.

Discussion
We have successfully constructed an in silico strain that can assimilate CO 2 using hydrogen for energy with dual carbon fixation cycles. By inserting heterologous enzymes, E. coli, a normally obligate heterotroph, is converted to a chemolithotroph using both inorganic carbon and energy source for growth. In terms of electron uptake and ATP generation, our strain is similar to chemolithotrophs such as hydrogen bacteria. These bacteria generate ATP by transporting electrons from reduced forms of the inorganic compound to a terminal electron acceptor. In heterotrophic growth, organic carbon sources such as glucose are supplied for growth as both a carbon and energy source. In our strain, the inorganic carbon source (in our case, CO 2 ) is decoupled from the energy source (hydrogen). The decoupling makes it possible to use their uptake as an independent parameter to profile the autotrophic growth. Indeed, when we vary the hydrogen (energy source) uptake, we discover that the strain shows hierarchy of usage of carbon fixation cycle and two distinct states -carbon-limited and energy-limited. With both cycles running to assimilate CO 2 , it is possible to enhance growth rates provided that hydrogen is amply supplied.
Another implication is that only a few heterologous enzymes are needed to enable E. coli to grow autotrophically. Such a conclusion again shows the plasticity of metabolism and seems to be conceptually consistent with a recent finding that only five mutations are needed to create a non-native CBB cycle [13]. This point is most evident in the caveat that we find as we progressively remove heterologous enzymes. We find that one heterologous enzyme (OGOR) alone in the central metabolism will enable E. coli to grow with a four-metabolite cycle as depicted in Fig. 6(d). In other words, a previously-proposed short carbon fixation cycle [5], comprising only four metabolites, is seamlessly integrated. Such a cycle is a metabolic shortcut of rTCA cycle.
Finally, we comment on the experimental realization of our strain using a synthetic biology approach. One underlying assumption for constraint-based flux balance analysis is to use biomass as an objective and maximize the growth rate. Such flux balance analysis identifies key enzymes for such metabolic rewiring and provides the genetic basis for rational metabolic engineering design. However, if one naively heterologously expresses the enzymes, one cannot expect to achieve optimized growth on the first attempt. Because our model does not account for kinetic or regulation effects, a finely-tuned flux distribution might be required to balance the rate of sugar uptake by biosynthetic pathways branching from the CBB cycle with the rate of sugar biosynthesis from CO 2 fixation. The kinetic requirements of such a balance are detailed in recent theoretical analysis [12]. Laboratory evolution in a specially-designed bioreactor with a hydrogen gaseous environment [29] may provide a route to explore such multivariate fine-tuning required for operating such a non-native cycle.

Author contribution
CCH and SCL contributed to conceptulation and analysis of the data. HTYC and YTY. contributed to the computation, analysis of the data, and manuscript writing and editing. TYH contributed to computation, supervision and fund acquisition.

Note
The authors declare no competing financial interests. The red cross symbol (x) indicates that the corresponding enzyme is knocked out in the simulation. The black dash arrows indicates no flux from Cisacon to citrate and from isocitrate to cis-acon. (d) Replot of (c) to highlight a four-metabolite cycle comprising succinate, isocitrate, succinyl-CoA and 2-ketoglutarate. Part of the existing rTCA cycle serves as an anaplerotic reaction to replenish the intermediates of this four-metabolite cycle drained for biosynthesis. Glyoxylate serves as the only cycle product. Abbreviations: 2 PG, D-glycerate-2-phophate; Fum, fumarate; Mal, Malate; OAA, oxaloacetate; PEP, phosphoenolpyruvate; ACL, ATP citrate lyase; POR, pyruvate oxidoreductase. Cis-acon, cis-aconitate; OGOR, 2-oxoglutarate:ferredoxin oxidoreductase.