Metabolic Flux Analysis of the Mixotrophic Metabolisms in the Green Sulfur Bacterium Chlorobaculum tepidum

Abstract

The photosynthetic green sulfur bacterium Chlorobaculum tepidum assimilates CO₂ and organic carbon sources (acetate or pyruvate) during mixotrophic growth conditions through a unique carbon and energy metabolism. Using a ¹³C-labeling approach, this study examined biosynthetic pathways and flux distributions in the central metabolism of C. tepidum. The isotopomer patterns of proteinogenic amino acids revealed an alternate pathway for isoleucine synthesis (via citramalate synthase, CimA, CT0612). A ¹³C-assisted flux analysis indicated that carbons in biomass were mostly derived from CO₂ fixation via three key routes: the reductive tricarboxylic acid (RTCA) cycle, the pyruvate synthesis pathway via pyruvate:ferredoxin oxidoreductase, and the CO₂-anaplerotic pathway via phosphoenolpyruvate carboxylase. During mixotrophic growth with acetate or pyruvate as carbon sources, acetyl-CoA was mainly produced from acetate (via acetyl-CoA synthetase) or citrate (via ATP citrate lyase). Pyruvate:ferredoxin oxidoreductase converted acetyl-CoA and CO₂ to pyruvate, and this growth-rate control reaction is driven by reduced ferredoxin generated during phototrophic growth. Most reactions in the RTCA cycle were reversible. The relative fluxes through the RTCA cycle were 80∼100 units for mixotrophic cultures grown on acetate and 200∼230 units for cultures grown on pyruvate. Under the same light conditions, the flux results suggested a trade-off between energy-demanding CO₂ fixation and biomass growth rate; C. tepidum fixed more CO₂ and had a higher biomass yield (Y_X/S, mole carbon in biomass/mole substrate) in pyruvate culture (Y_X/S = 9.2) than in acetate culture (Y_X/S = 6.4), but the biomass growth rate was slower in pyruvate culture than in acetate culture.

Introduction

Chlorobaculum tepidum is a representative green sulfur bacterium that is ecologically significant in global cycling of carbon, nitrogen, and sulfur (1, 2). The C. tepidum genome has been sequenced, and the genetic tools for creating C. tepidum mutant strains have been developed to make transposon-based mutations or targeted gene disruptions, which offer great potential to engineer C. tepidum for future applications (3). The annotated genome reveals unique aspects in carbon and energy metabolism in C. tepidum. Instead of using the Calvin-Benson cycle for CO₂ assimilation as in most photosynthetic organisms, C. tepidum captures energy from light and uses it along with electrons, primarily derived from oxidation of sulfur compounds, to drive the reductive tricarboxylic acid cycle (RTCA)³ for synthesis of building block molecules (3). C. tepidum can grow mixotrophically with acetate or pyruvate as the organic carbon source (2). Although recent research has been performed on the carbon and energy metabolism of C. tepidum (4, 5), rigorous quantification of the metabolic pathway activities has not yet been achieved. To provide quantitative readout of the metabolic functions and regulatory mechanisms, this study has performed ¹³C-assisted metabolic flux analysis of C. tepidum in the following steps: 1) growing cultures of C. tepidum with ¹³C-labeled acetate or pyruvate, 2) using gas chromatography (GC)-MS to measure the resulting labeling pattern in key metabolites, and 3) deciphering in vivo metabolisms via a flux model (6). Isotopic labeling and metabolic flux analysis have been developed to identify the active biosynthesis pathways (7–10) and measure the global enzymatic reaction rates (11, 12). The cell-wide quantification of intracellular metabolism can bridge the gap between genome annotations and final metabolic outputs and has been applied for characterizing numerous environmental microorganisms, including Escherichia coli (13, 14), Saccharomyces cerevisiae (15, 16), Bacillus subtilis (17), Geobacter metallireducens (18), Shewanella oneidensis (19), and Synechocystis sp. (20)., etc. This paper reports on the first studies of the fluxomics of mixotrophic metabolism in the green sulfur bacteria and provides complementary information to previous genomic and proteomic studies.

EXPERIMENTAL PROCEDURES

¹³C-labeled Experiments

C. tepidum cultures were grown anaerobically at temperatures ranging from 46–50 °C in low intensity light (100 ± 10 micromoles/m²/s). The medium composition (1 liter) was Na₂EDTA-2H₂O (0.015 g), MgSO₄-7H₂O (0.22 g), CaCl₂-2H₂O (0.08 g), NaCl (0.45 g), NH₄Cl (0.45 g), Na₂S₂O₃-5H₂O (2.6 g), KH₂PO₄ (0.57 g), MOPS buffer (2.4 g), trace element stock (1.2 ml), vitamin B₁₂ stock (0.08 mg), NaHCO₃ (2.3 g), and Na₂S-9H₂O (0.8 g). All chemicals were purchased from Sigma-Aldrich. The carbon source for the trace experiments was [1-¹³C]acetate (purity > 98%, 0.83 g/liter) or [2-¹³C] acetate (purity > 98%, 0.83 g/liter) for cultures growing on acetate, or [3-¹³C]pyruvate (purity > 98%, 1.1 g/liter) for cultures growing on pyruvate. The ¹³C-labeled acetate and pyruvate were purchased from Cambridge Isotope Laboratories. Cell growth was monitored at A₆₂₅. 1% cultures (100-fold dilution) in the exponential growth phase were used to inoculate fresh media with ¹³C-labeled substrates. To reduce the effect of nonlabeled carbon from the initial stock, cells were subcultured twice in the same labeled medium. Biomass was sampled at two time points (4-h interval) in the middle exponential growth phase, and the labeling patterns of proteinogenic amino acids in the biomass were measured. The invariability of amino acid labeling during the two time points confirmed the pseudo-steady-state metabolism in tracer experiments.

Metabolites and Isotopomer Analysis

The amount of pyruvate and acetate during the growth period was determined by enzymatic assays (21–23). For GC-MS measurement of amino acid labeling, the biomass was harvested by centrifugation and hydrolyzed using 6 m HCl (24 h at 100 °C) (19, 24). The amino acids were derivatized in 0.2 ml of tetrahydrofuran and 0.2 ml of N-(tert-butyl dimethylsilyl)-N-methyl-trifluoroacetamide (Sigma-Aldrich). A gas chromatograph (Hewlett-Packard model 7890A; Agilent Technologies) equipped with a DB5-MS column (J&W Scientific, Folsom, CA) and a mass spectrometer (model 5975C; Agilent Technologies) were used for analyzing metabolite labeling profiles. Four types of charged fragments were detected by GC-MS for all of the amino acids (see Table 1 and Fig. 1); the [M-57]⁺ or [M-15]⁺ group (containing unfragmented amino acids); and the [M-159]⁺ or [M-85]⁺ group (containing amino acids that had lost an α-carboxyl group). For each type of fragments, the labeling patterns were represented by M₀, M₁, M₂, etc, which were fractions of unlabeled, singly labeled, and doubly labeled amino acids. The effects of natural isotopes on isotopomer labeling patterns were corrected by previously reported algorithms (25). To compare the relative contributions of carbon substrates and CO₂ to mixotrophic biomass synthesis, the substrate utilization ratio R was calculated based on the labeling patterns of unfragmented amino acid X (e.g. alanine) (7),

where R ratio reflects the carbon flux ratio of labeled carbon substrate to unlabeled CO₂ for producing the corresponding amino acid X (mol carbon from substrate/mol carbon from CO₂); M_iis the GC-MS isotopomer fraction for a given amino acid. C is the total number of carbon atoms in the amino acid molecule. V_sub is the uptake of ¹³C-labeled organic substrates, V_CO2 is the uptake of CO₂; 0.98 is the purity of the labeled carbon substrate, 0.01 is the natural abundance of ¹³C, m is the total number of carbons in the substrate molecule, and n is the total number of labeled carbons in the substrate molecule.

TABLE 1.

Isotopic labeling patterns in amino acids from Chlorobaculum tepidum

The S.D. for GC-MS measurement were based on the duplicate experiments (n = 2), with an S.D. below 2%.

Carbon source	Amino acids	Fragments	M0	M1	M2
[1-13C]Acetate
	Ala	[M-57]+	0.45	0.54	0.01
		[M-159]+	0.44	0.53	0.03
	Gly	[M-57]+	0.54	0.46	0.00
		[M-85]+	0.54	0.46
	Ser	[M-57]+	0.46	0.52	0.02
		[M-159]+	0.47	0.53	0.00
	Leu	[M-159]+	0.21	0.43	0.33
	Ile	[M-159]+	0.21	0.43	0.33
	Asp	[M-57]+	0.64	0.35	0.01
		[M-159]+	0.65	0.34	0.01
	Glu	[M-57]+	0.63	0.33	0.04
		[M-159]+	0.63	0.33	0.04
	Phe	[M-57]+	0.11	0.29	0.36
		[M-159]+	0.12	0.30	0.36
[2-13C]Acetate
	Ala	[M-57]+	0.43	0.56	0.01
		[M-159]+	0.42	0.54	0.04
	Gly	[M-57]+	0.94	0.06	0.00
		[M-85]+	0.95	0.05
	Ser	[M-57]+	0.44	0.55	0.01
		[M-159]+	0.45	0.55	0.00
	Leu	[M-159]+	0.13	0.25	0.36
	Ile	[M-159]+	0.14	0.25	0.36
	Asp	[M-57]+	0.61	0.38	0.00
		[M-159]+	0.62	0.37	0.00
	Glu	[M-57]+	0.62	0.35	0.03
		[M-159]+	0.63	0.34	0.03
	Phe	[M-57]+	0.13	0.26	0.36
		[M-159]+	0.14	0.26	0.35
	His	[M-57]+	0.16	0.35	0.36
		[M-159]+	0.28	0.48	0.22
[3-13C]Pyruvate
	Ala	[M-57]+	0.67	0.32	0.01
		[M-159]+	0.65	0.30	0.05
	Gly	[M-57]+	0.96	0.04	0.00
		[M-85]+	0.97	0.03
	Ser	[M-57]+	0.71	0.28	0.01
		[M-159]+	0.71	0.28	0.01
	Leu	[M-159]+	0.47	0.38	0.12
	Ile	[M-159]+	0.47	0.39	0.12
	Asp	[M-57]+	0.82	0.17	0.00
		[M-159]+	0.83	0.15	0.01
	Glu	[M-57]+	0.75	0.20	0.05
		[M-159]+	0.76	0.20	0.04
	Phe	[M-57]+	0.38	0.41	0.17
		[M-159]+	0.38	0.40	0.18
	His	[M-57]+	0.46	0.41	0.11
		[M-159]+	0.56	0.34	0.08

FIGURE 1.

Citramalate pathway for isoleucine biosynthesis in C. tepidum (using [2-¹³C]acetate and NaHCO₃ as carbon sources). The asterisks indicate the positions of labeled carbon. The dashed lines indicate inactive pathways.

Metabolic Flux Analysis

The pathway map of C. tepidum was generated based on genome annotation from the KEGG database (Kyoto Encyclopedia of Genes and Genomes) and transcription analysis of several key pathways (26). The simplified pathway map includes the reductive tricarboxylic acid cycle, CO₂-anaplerotic pathway, gluconeogenesis pathway, and pentose phosphate pathway (supplemental Fig. S1 and Table S1). The development of a pseudo-steady-state flux model has been discussed before (19, 27, 28). In brief, the substrate (acetate or pyruvate) uptake rate was measured and normalized to 100 units. The biomass production was determined based on our previous paper (26). The biomass composition for macromolecules such as protein and fatty acids was assigned based on that of E. coli (13). The fluxes to biomass pools were loosely constrained by the estimated dry cell weight (DCW) and biomass compositions. These fluxes were used as initial inputs to the isotopomer model and optimized by isotopomer labeling information (Table 1 and supplemental Table S2). The remaining unknown intracellular fluxes were determined by reaction stoichiometry and atom/isotopomer mapping matrices in an iterative scheme (supplemental Table S3). The reaction reversibility was calculated using the exchange coefficient (18),

where v_i^exch is the exchange flux defined as the smaller of the forward and backward fluxes, and exch_i is the exchange coefficient with the range of 0–1. (If the reaction is irreversible, exch_i is 0; if the reaction is “freely” reversible, exch_i is close to 1.) The flux combinations were searched to minimize of the objective function (19),

where v_n are the unknown fluxes to be optimized in the program, M_i is the measured MS data, N_i is the corresponding model-simulated MS data, and δ_i is the corresponding S.D. in GC-MS data (1∼2%). The unknown metabolic fluxes were searched to minimize ϵ. The model was solved by IPOPT (Interior Point Optimizer), which is a software package for large-scale nonlinear optimization. To avoid getting trapped in a local optimal minimum, multiple initial guesses (>100) were used for model calculation to obtain the global solution.

To estimate the confidence interval for the calculated fluxes, a Monte Carlo approach was employed (14). In brief, the isotopomer concentration data sets were generated by adding 2% of normally distributed measurement noise to actual measured isotopomer data. The same optimization routine was used to estimate flux distribution from these data sets. Confidence limits for each flux value were obtained from the probability distribution of calculated fluxes resulting from the simulated data sets (n = 100). To determine the requirements of cellular metabolism for energy and reducing power, the relative consumption rates of ATP, NADH, NADPH, and ferredoxin were quantified based on the flux distributions in the central metabolic pathways and biomass synthesis rates.

Calculation of Biomass Yield

The biomass yield (mol of carbon in biomass/mol of substrate) was calculated based on the substrate uptake rates (mol of substrate/liter/h) and biomass growth rates (g DCW/liter/h). The molecular formula for C. tepidum was assumed to be CH_1.8O_0.5N_0.2P_0.02 (molecular weight (MW) ≈ 25.5) (29). The biomass yield was calculated by (yield = biomass growth rate (g/liter/h)/molecular weight of biomass (g/mol))/substrate uptake rate (mol/liter/h).

RESULTS AND DISCUSSION

Carbon Utilization during Mixotrophic Growth

During exponential growth with pyruvate and acetate, C. tepidum had the growth rates of 0.12 h⁻¹ and 0.17 h⁻¹, respectively. In the trace experiments, the labeled carbons were detected in all amino acids (Table 1), suggesting utilization of acetate or pyruvate to synthesize all building blocks. Table 2 shows the ratio of carbon utilization (organic carbon versus CO₂) for mixotrophic synthesis of proteinogenic amino acids. For acetate culture, the substrate utilization ratio for Ala (precursor, pyruvate) was 0.60, which indicated that carbons in pyruvate were mainly derived from labeled acetate. Pyruvate is the precursor for both the gluconeogenesis pathway and the pentose phosphate pathway, so the R ratios (Equation 1) of Ser and Phe are similar to that of alanine. The substrate utilization ratio of His was high (0.96) for culture with [2-¹³C]acetate because the His precursor C1 pool (N⁵,N¹⁰-methylene-tetrahydrofolate) was highly labeled. This carbon was derived from acetate by following route [2-¹³C]acetate → [3-¹³C]pyruvate → [3-¹³C]Ser → [¹³C]C1 pool.

TABLE 2.

Carbon substrate utilization ratios in amino acids from Chlorobaculum tepidum

The carbon source utilization ratio (organic substrate/CO₂ fixation) for amino acid synthesis was calculated according to Equation 1.

Amino acids	Carbon sources
	[1-13C]acetate + NaHCO3	[2-13C]acetate + NaHCO3	[3-13C]pyruvate + NaHCO3
Ala	0.60	0.60	0.48
Ser	0.58	0.58	0.42
Asp	0.20	0.22	0.12
Glu	0.18	0.18	0.21
His	NAa	0.96	0.38
Phe	0.62	0.64	0.26

^a Isotopomer labeling pattern for histidine was not detected under [1-¹³C]acetate + NaHCO₃ due to the weak signal to noise ratio in GC-MS.

In the mixotrophic culture with acetate, the R ratios for aspartate and glutamate (∼0.2) were significantly lower than the other amino acids. Aspartate and glutamate were synthesized from the RTCA cycle, so the small R values indicated that the unlabeled CO₂ was the dominant carbon source for synthesizing metabolites in the RTCA cycle. In pyruvate culture, the substrate utilization ratios of amino acids (Ala, Phe, Ser, and Asp) were all lower than in acetate culture, indicating a higher contribution of CO₂ to synthesize building blocks.

Analysis of Amino Acid Biosynthesis Pathways

Growing in a completely defined medium, C. tepidum was able to synthesize all amino acids from CO₂ and organic carbon sources using the annotated pathways. Interestingly, the labeling patterns of Leu and Ile from tracer experiments were found to be identical, which indicated that the two amino acids shared the same precursors. Ile is commonly synthesized via threonine ammonia-lyase, with Thr and pyruvate as the precursors, whereas Leu is synthesized from pyruvate and acetyl-CoA. In the [2-¹³C]acetate trace experiment, both Thr and pyruvate are singly labeled, which could lead only to doubly labeled Ile, instead of the triply labeled Ile detected by GC-MS. Such an observation is consistent with the fact that a gene encoding threonine ammonia-lyase has not been annotated in the genome of C. tepidum. On the other hand, an alternative pathway for Ile biosynthesis (i.e. threonine-independent pathway) has been recently identified in several bacteria (8, 9, 24, 30), where Ile is synthesized from acetyl-CoA and pyruvate (i.e. using the same precursors as Leu) through the formation of citramalate as the intermediate (Fig. 1). A search in the genome of C. tepidum for the gene for citramalate synthase (CimA) as found in Geobacter (9) returned a high identity for CT0612 (∼52%), supporting the presence of the citramalate pathway for Ile synthesis.

Central Carbon Metabolic Pathways

The genome annotation from the KEGG database indicates that 1) pyruvate:ferredoxin oxidoreductase (porA, CT1628) converts pyruvate to acetyl-CoA (an end product from RTCA cycle); 2) phosphoenolpyruvate is derived from pyruvate via pyruvate phosphate dikinase (CT1682), and 3) phosphoenolpyruvate is fed into the TCA cycle via the CO₂-anaplerotic pathway (Fig. 2). The fraction of nonlabeled Asp (M₀ = 0.64, Table 1) was much higher than that of Ala (M₀ = 0.45, Table 1) in trace experiments with [1-¹³C]acetate, which indicated that nonlabeled oxaloacetate was also generated through CO₂ fixation via the RTCA cycle. Furthermore, similar labeling patterns of Ala (precursor, pyruvate) and Ser (precursor, glycerate-3-P) confirmed that the carbon flux through the gluconeogenesis pathway was mainly from pyruvate.

FIGURE 2.

Metabolic flux distribution in C. tepidum. A, net flux distribution in acetate growth conditions (based on [2-¹³C]acetate culture). B, net flux distribution in pyruvate growth conditions. The S.D. and exchange coefficients are marked by flux ± S.D. and < exchange coefficient >, respectively. The inactive pathways are marked with dashed lines. The calculated biomass yield (moles of carbon in biomass/mol of substrate): pyruvate culture (Y_X/S = 9.2); acetate culture (Y_X/S = 6.4). S7P, sedoheptulose-7-phosphate; SUCC, succinate; SUCCoA, succinyl-CoA; Xu5P, xylulose-5-phosphate; 3PG, 3-phosphoglycerate; 6PG, 6-phosphogluconate; AC, intracellular acetate; ACCOA, acetyl-coenzyme A; AC.ext, extracellular acetate; AKG, α-ketoglutarate; CIT, citrate; E4P, erythrose-4-phosphate; F6P, fructose-6-phosphate; FBP, fructose 1,6-bisphosphate; FNR, ferredoxin-NAD(P)⁺ reductase; FUM, fumarate; G6P, glucose-6-phosphate; GAP, glyceraldehyde 3-phosphate; ICIT, isocitrate; MAL, malate; OAC, oxaloacetate; PEP, phosphoenolpyruvate; PYR, intracellular pyruvate; PYR.ext, extracellular pyruvate; R5P, ribose-5-phosphate; Ru5P, ribulose-5-phosphate; PP, pentose phosphate.

The flux analysis results are shown in Fig. 2. In general, predicted labeling patterns of all amino acids were good matches with the measured isotopomer data (Fig. 3). Under acetate growth conditions, acetyl-CoA could be generated from acetate uptake or as the end product through the RTCA cycle. Fluxes through pyruvate:ferredoxin oxidoreductase, the RTCA cycle, and the CO₂-anaplerotic pathway were ∼152, 80–100, and ∼30 units, respectively (Fig. 2). Meanwhile, the flux ratio of the gluconeogenesis pathway to the RTCA cycle was close to 1:1. The oxidative pentose phosphate pathway (glucose-6-phosphate → 6-phosphogluconate → ribulose-5-phosphate) was inactive under our experimental conditions. Compared with mixotrophic growth with acetate, the flux distribution during pyruvate growth demonstrated different patterns. In general, the fluxes into the RTCA cycle and CO₂-anaplerotic pathway were much higher (200–230 units and ∼50 units, respectively), and thus, more CO₂ was fixed. The flux ratio of the gluconeogenesis pathway to the RTCA cycle was reduced to 1:2, whereas acetyl-CoA was generated only from the RTCA cycle. The oxidative pentose phosphate pathway was not active (flux < 1 unit) under pyruvate mixotrophic growth (or acetate mixotrophic growth).

FIGURE 3.

Model quality test for acetate metabolism (A) and pyruvate metabolism (B). ●, alanine; ○, serine; ▾, aspartate, Δ, glutamate; ■, leucine; □, histidine; ♢, phenylalanine; and ♦, glycine.

In the mixotrophic cultures grown on acetate or pyruvate, most reactions in the RTCA cycle were freely reversible (with an exchange coefficient close to 1). The reversibility is consistent with the physiological free energy changes in the RTCA cycle, where the standard Gibbs free energy for most reactions of the TCA cycle is positive so that the magnitude of the reaction equilibrium constants is small (31). Furthermore, pyruvate:ferredoxin oxidoreductase catalyzes a reversible reaction between pyruvate and acetyl-CoA (pyruvate + CoA + 2Fd_ox ↔ acetyl-CoA + CO₂ + 2Fd_red + 2H⁺). (Fd_red indicates reduced ferredoxin, and Fd_ox indicates oxidized ferredoxin.) However, metabolic flux analysis of the mixotrophic metabolism indicates that the net flux of this enzymatic reaction was from acetyl-CoA to pyruvate (32). The direction of the pyruvate:ferredoxin oxidoreductase pathway indicates that the reduced ferredoxin from phototrophic processes made the reaction for pyruvate synthesis thermodynamically favorable.

Energy Metabolism of C. tepidum

The mixotrophic metabolism of C. tepidum consumes energy harvested from light. Because the oxidative pentose phosphate pathway and normal TCA cycle are not fully functional, the energy (NADPH and NADH) generation mainly depends on the light reactions. Based on the metabolic flux distribution and previous measurement of the absolute uptake rates of carbon substrates and biomass growth (26), the light energy harvested for central metabolism and biomass growth was approximately quantified (Fig. 4). In general, the photons absorbed by pigments (e.g. bacteriochlorophylls) initiate the electron flow and oxidize sulfide. The electrons are used to reduce ferredoxin and generate NAD(P)H (2, 3). Concomitant with the oxidation of the reduced ferredoxin, the essential cofactors for energy metabolism (i.e. NADPH and NADH) are mainly generated by ferredoxin-NAD(P)⁺ reductase (2, 33). Meanwhile, the oxidation of sulfide also creates a proton motive force for ATP production. The generated ATP, cofactors, and reduced ferredoxin then become the “driver” for the mixotrophic metabolism and the RTCA cycle for energy-demanding CO₂ fixation. Fig. 4 shows that the ATP, NADH, and NADPH fluxes into biomass and the RTCA cycle are stronger in acetate-grown cultures than in pyruvate-grown cultures, supporting a higher growth rate during mixotrophic growth with acetate. On the other hand, the calculated biomass yield (mol of carbon in biomass/mol of substrate) was higher for pyruvate culture (Y_X/S = 9.2) than for acetate (Y_X/S = 6.4), based on our previous experiments (26), which is consistent with the fact that the normalized fluxes through RTCA are higher in pyruvate culture than acetate culture. Accordingly, pyruvate metabolism has more CO₂ fixation (but slower growth rate).

FIGURE 4.

Proposed energy metabolism in C. tepidum. A, energy requirement (mmol/g DCW/h) in acetate growth conditions. B, energy requirement (mmol/g DCW/h) in pyruvate growth conditions. The intracellular energy metabolism was quantified in the framed figures based on the relative flux distributions. (Detailed calculations can be found in supplemental Table S4, A and B). Arrows pointing to the framed figure indicated the energy demand of intracellular metabolism. Arrows pointing to biomass indicate the energy demand of biomass accumulation. Arrows pointing from light indicated the entire energy harvested by C. tepidum. The light reaction produces reduced ferredoxin and ATP. NADPH and NADH are mainly generated by ferredoxin-NAD(P)⁺ reductase. Biomass (protein) synthesis can also generate a small amount of NADH, as indicated in the figure. SUCC, succinate; SUCCoA, succinyl-CoA; 3PG, 3-phosphoglycerate; ACCOA, acetyl-coenzyme A; AC.ext, extracellular acetate; AKG, α-ketoglutarate; CIT, citrate; FNR, ferredoxin-NAD(P)⁺ reductase; FUM, fumarate; ICIT, isocitrate; MAL, malate; OAC, oxaloacetate; PEP, phosphoenolpyruvate; PYR, intracellular pyruvate; KGOR, 2-ketoglutarate ferredoxin oxidoreductase; Fd_red, reduced ferredoxin; Fd_ox, oxidized ferredoxin; PP, pentose phosphate.