Abstract
Acetate is a major by-product of glycolytic metabolism in Escherichia coli and many other microorganisms. It has long been considered a toxic waste compound that inhibits microbial growth, but this counterproductive auto-inhibition, which represents a major problem in biotechnology, has puzzled the scientific community for decades. Recent studies have revealed that acetate is also a co-substrate of glycolytic nutrients and a global regulator of E. coli metabolism and physiology. However, most of these insights were obtained at high glycolytic flux and little is known about the role of acetate at lower glycolytic fluxes, conditions that are nevertheless frequently experienced by E. coli in natural, industrial and laboratory environments. Here, we used a systems biology strategy to investigate the mutual regulation of glycolytic and acetate metabolism. Computational and experimental results demonstrate that reducing the glycolytic flux enhances co-utilization of acetate and glucose through the Pta-AckA pathway. Enhanced acetate metabolism compensates for the reduction in glycolytic flux and eventually buffers carbon uptake so that acetate, far from being toxic, actually enhances E. coli growth under these conditions. The same mechanism of increased growth was also observed on glycerol and galactose, two nutrients with a natively low glycolytic flux. Therefore, acetate makes E. coli more robust to glycolytic perturbations and is a valuable nutrient, with a beneficial effect on microbial growth. Finally, we show that some evolutionarily conserved design principles of eukaryotic fermentative metabolism are also present in bacteria.
Significance Statement Acetate, a by-product of glycolytic metabolism in many microorganisms including Escherichia coli, is traditionally viewed as a toxic waste compound. Here, we demonstrate that this is only the case at high glycolytic fluxes. At low glycolytic fluxes in contrast, acetate acts as a co-substrate of glycolytic nutrients and boosts E. coli growth. Acetate also improves E. coli’s robustness to glycolytic perturbations. We clarify the functional relationship between glycolytic and acetate metabolisms, show that acetate is a beneficial co-substrate of glycolytic nutrients used by E. coli in bioprocesses and in the gut, and provide insights into the underlying biochemical and regulatory mechanisms.
Introduction
Metabolism is the fundamental biochemical process that converts nutrients into energy and cellular building blocks. The preferred nutrients of many organisms are glycolytic substrates, such as glucose, which are oxidized into pyruvate by glycolysis. In the presence of oxygen, pyruvate can then be fully oxidized into carbon dioxide and water via respiratory pathways involving the tricarboxylic acid (TCA) cycle and oxidative phosphorylation. When oxygen is limiting, pyruvate is incompletely oxidized through non-respiratory pathways, and fermentation by-products are released into the environment. Despite fermentation being less efficient than respiration, fermentation by-products are still released in the presence of oxygen by most microorganisms, including bacteria (1), yeasts (2) and mammalian cells (3).
Acetate is one of the most common by-products of glycolytic metabolism in Escherichia coli and many other microorganisms (1, 4, 5). The established view is that acetate and other fermentation by-products are toxic and inhibit microbial growth (4-14). Why E. coli should produce a self-toxic by-product is an intriguing question, particularly since E. coli’s natural environment, the gut, is acetate-rich. Several explanations for the toxic effect of acetate have been proposed, the classical one being the uncoupling effect of organic acids (8), with acetic acid freely diffusing through the membrane before dissociating intracellularly into acetate and a proton due to its low pKa, and the energy required to expel the excess protons from the cell to maintain pH homeostasis being detrimental to growth. Another hypothesis is that the presence of acetate in the cytoplasm may affect the anion balance of the cell (9), reducing the pool of other anions – primarily glutamate – available to maintain osmotic pressure and electroneutrality and thereby impeding cell function. Acetate has also been reported to inhibit a step in the methionine biosynthesis pathway (10), reducing the intracellular methionine pool and concomitantly increasing the concentration of the toxic intermediate homocysteine. Finally, acetate may modulate the accumulation of acetyl-phosphate (15, 16), an intermediate of the acetate pathway and a signaling metabolite that can phosphorylate and acetylate enzymes and regulatory proteins with broad physiological consequences. However, none of these studies conclusively explain how acetate inhibits microbial growth (13). The physiological role of fermentation under aerobic conditions also remains unclear, especially since it leads to the accumulation of toxic by-products at the expense of biomass production.
Acetate overflow and its impact on E. coli are also important issues in biotechnology, where acetate is both produced from glycolytic carbon sources and found in many renewable resources (4, 5, 17-19). As well as inhibiting growth, acetate production diverts carbon that could otherwise be used to synthesize biomass or valuable compounds. Acetate therefore decreases the productivity of bioprocesses. Since acetate is only produced at high glucose uptake rates (20-22), a common approach to reduce acetate overflow is to limit glucose uptake by process engineering (e.g. glucose-limited chemostat or fed-batch culture) or by metabolic engineering (e.g. deletion of glucose transporters) (5, 7, 23-27). The utilization of acetate in combination with glycolytic substrates could alleviate growth inhibition and allow acetate to act as both a renewable carbon source and a relevant (co-)substrate for bioproducts that are derived from acetyl-CoA (5, 26, 28, 29). However, despite decades of attempts to reduce its accumulation and improve its utilization, acetate is still considered a major problem in biotechnology (7, 13, 24, 27).
Recently, we found that acetate can also act as a co-substrate for glycolytic carbon sources such as glucose, fucose and gluconate (12), and is therefore more than just a waste by-product. The switch between acetate production and consumption was found to be determined thermodynamically by the acetate concentration itself. Acetate is also a global regulator of E. coli metabolism and physiology (30). These observations suggest an alternative rationale for acetate toxicity, namely that the inhibition of growth and glucose uptake may result from coordinated downregulation of the expression of most central metabolic genes (glucose uptake systems, glycolysis, TCA cycle) and ribosomal genes. To date, the role of acetate as a co-substrate and regulator of glycolytic metabolism has only been investigated under high glycolytic flux, and little is known about the response of E. coli to acetate at low glycolytic fluxes, conditions that are nevertheless commonly experienced by this bacterium in its natural, industrial and laboratory environments (31-39).
In this study, we took a systems biology approach to clarify the interplay between glycolytic and acetate metabolism in E. coli. We used a kinetic model of E. coli metabolism to generate hypotheses on the relationships between glycolytic, acetate and growth fluxes. We validated model predictions experimentally, explored the underlying biochemical and regulatory mechanisms on glucose, and extended our findings to two other glycolytic nutrients.
Results
Model-driven hypotheses on the interplay between glucose and acetate metabolism in Escherichia coli
We explored the functional relationship between glycolytic and acetate metabolism in Escherichia coli using a coarse-grained kinetic model coupling glucose and acetate metabolism with growth (Figure 1A) (30). The model included two compartments, six compounds, and six reactions representing (i) glucose uptake and its conversion into acetyl-CoA by glycolysis, (ii) acetyl-CoA utilization in the TCA cycle and anabolic growth pathways, and (iii) the reversible conversion of acetyl-CoA into acetate via phosphotransacetylase (Pta), acetate kinase (AckA), and acetate exchange between the cell and its environment. Acetate utilization via acetylCoA synthetase (Acs), which is not active when glucose is present (12), is not included in the model. This model has been extensively validated and shown to have good predictive capabilities (30). We used it to simulate the response of glycolytic, acetate and growth fluxes to different degrees of glycolytic limitation by progressively reducing the activity (i.e. Vmax) of the glycolytic pathway – and thereby the glycolytic flux – from 100 % to 20 % of its initial value. Since glycolytic and acetate fluxes are both determined by the concentration of acetate (12, 13, 30), these simulations were carried out over a broad range of acetate concentrations (from 0.1 to 100 mM).
The results obtained (Figure 1B-D) highlight the strong bidirectional interplay between glycolytic and acetate metabolism, which eventually modulate growth. Glucose uptake and acetate flux both respond nonlinearly to perturbations (Figure 1B-C). According to the model, increasing the acetate concentration inhibits glycolysis (Figure 1B) and reverses the acetate flux (Figure 1C) over the full range of glycolytic fluxes, as previously reported at the highest glucose uptake rate (30). The acetate concentration at which the flux reversal occurs appears to depend on the glycolytic flux (Figure 1C). Reducing the glycolytic flux lowers acetate production when acetate is a by-product of glucose metabolism, but seems to enhance acetate utilization when acetate is a co-substrate of glucose (Figure 1C). Finally, the glycolytic flux and the acetate concentration both have a strong, nonlinear effect on the growth rate (Figure 1D). At maximal glycolytic activity, the predictions of the model are consistent with the established deleterious effect of acetate on microbial growth (Figure 1D). However, the model also predicts that at lower glycolytic flux, increasing the acetate concentration should boost E. coli growth (Figure 1D). We present these model-driven hypotheses in detail in the following sections along with experimental results collected for validation. Note that the data obtained in this study were not used to build or calibrate the model and therefore represent independent tests of its predictions and inferred hypotheses.
Enhanced acetate utilization at low glycolytic flux buffers carbon uptake
At low acetate concentrations, acetate production is predicted to increase with the glycolytic flux (Figure 1C), in line with the relationship observed in glucose-limited chemostat experiments (20-22) and in a set of mutants with different levels of glucose uptake (23). In contrast, when the acetate concentration is high, such that it is co-consumed with glucose, acetate utilization is expected to decrease when the glycolytic flux increases (Figure 1C). This response implies, as suggested previously (30) but never verified experimentally, that the control exerted by glycolysis on the acetate flux is non-monotonic.
To test this hypothesis, we measured growth, glucose uptake, and acetate fluxes in E. coli K-12 MG1655 grown on 15 mM glucose and increased the concentration of the glycolytic inhibitor methyl α-D-glucopyranoside (αMG, an analogue of glucose that is taken up and phosphorylated but not metabolized by glycolysis) (40, 41) (Figure 2A-C). Experiments were carried out without acetate and with 30 mM acetate. Results confirm that αMG inhibits glucose uptake under both conditions (Figure 2A). In the absence of acetate, the acetate (production) flux decreased when the αMG concentration was increased (Figure 2B), as expected based on the positive control exerted by glycolysis on the acetate flux. In contrast, in the presence of 30 mM acetate, increasing the αMG concentration increased the acetate uptake flux (Figure 2B). These results are consistent with the predictions of the model and demonstrate that glycolysis controls the acetate flux in a non-monotonic manner. The control exerted by glycolysis on acetate metabolism thus depends on the concentration of acetate itself.
Total carbon uptake decreased when the αMG concentration was increased in the absence of acetate (Figure 2D), but remained stable in the presence of acetate despite a ∼2-fold reduction in glucose uptake (between 5.7 and 3.3 mmol·gDW-1·h-1 with 30 mM acetate; Figure 2A). A strong, nonlinear relationship between glucose uptake and acetate flux was observed in all experiments (Figure 2E), which was reflected in the contribution of acetate to the total carbon uptake of E. coli (Figure 2F). At the maximal glucose uptake rate, acetate production represented a 10 % loss in carbon. However, when glucose uptake was below 7 mmol·gDW-1·h-1, acetate was co-utilized with glucose and contributed positively to the carbon balance (up to 50 % at a glucose uptake rate of 3.3 mmol·gDW-1·h-1; Figure 2F). Because acetate compensates for the drop in glucose uptake, the growth rate was less sensitive to glycolytic perturbations in the presence of acetate than in the absence of acetate (Figure 2C). These results highlight the coupling between glycolytic and acetate fluxes in E. coli, with acetate buffering carbon uptake at low glycolytic flux, thereby improving the robustness of E. coli growth to glycolytic perturbations.
The glycolytic flux determines the acetate concentration threshold at which the acetate flux reverses
As already reported at maximal glucose uptake rates (12, 30), the acetate concentration threshold at which the acetate flux switches between production and consumption is about 10 mM. However, this threshold is predicted to depend on the glycolytic flux (Figure 1C). According to the model, the switch should occur at an acetate concentration of 3.9 mM when the glycolytic activity is 60 % of its maximum value, and at a concentration of just 0.7 mM when the glycolytic activity is reduced to 20 % of the maximum. This suggests that the glycolytic flux determines the role of acetate as a co-substrate or by-product of glycolytic metabolism.
We tested this hypothesis by measuring acetate fluxes in E. coli grown on glucose (15 mM) plus acetate (from 0.1 to 100 mM) at different concentrations of αMG (0, 20, 40 or 100 mM, Figure 3. As previously observed at full glycolytic activity (12-14, 30), acetate production decreased at 0 mM αMG when the acetate concentration was increased (Figure 3), and the acetate flux reversed at a concentration of ∼8 mM, resulting in co-consumption of glucose and acetate. This threshold concentration gradually decreased when the glycolytic flux was reduced (from 2 mM acetate at 20 mM αMG to below 0.1 mM acetate at 40 or 100 mM αMG). In keeping with the predictions of the model, these results demonstrate that the acetate concentration threshold at which the acetate flux reverses depends on the glycolytic flux. It therefore follows that when the glycolytic flux is limited, acetate is utilized as a co-substrate at lower acetate concentrations. These results also confirm that inhibiting glycolysis enhances acetate utilization over the full range of acetate concentrations tested here, further validating the unusual control patterns identified above, and generalizing their functional relevance for acetate concentrations spanning three orders of magnitude.
Acetate enhances E. coli growth at low glycolytic flux
Acetate is considered toxic for microbial cells, but the model predicts this might not always be the case. At full glycolytic activity, the model predicts that maximal growth should occur at low acetate concentrations, with the growth rate remaining above 95 % of the maximum only at acetate concentrations below 12 mM (Figure 1D). In agreement with the reported toxicity of acetate, the growth rate then monotonously decreases for acetate concentrations above 12 mM. However, when the glycolytic flux is reduced, maximal growth is predicted to occur at high acetate concentrations (Figure 1D). For instance, when the glycolytic activity is reduced to 20 %, the growth rate is expected to be maximal at an acetate concentration of 28 mM, and should remain above 95 % of the maximum over a broad range of acetate concentrations (between 12 and 86 mM). According to the model therefore, acetate should enhance E. coli growth at low glycolytic flux.
To test this prediction, we measured the growth rate of E. coli on glucose (15 mM) with acetate (0.1 to 100 mM) in the presence of 100 mM αMG to inhibit glycolysis (Figure 4). The data measured in the absence of αMG (30) are shown for comparison. At maximal glycolytic flux, the growth rate decreased monotonically with the acetate concentration, but this relationship became non-monotonic when glycolysis was inhibited. In this case, the growth rate was lower in the absence of acetate than at high acetate concentrations (0.28 ± 0.02 h-1 with acetate < 0.5 mM versus 0.34 ± 0.01 h-1 with 60 mM acetate). As predicted by the model therefore, acetate appears to be beneficial rather than toxic to E. coli when the glycolytic flux is reduced. The growth rate was slightly lower at 100 mM acetate (0.30 ± 0.03 h-1) than at 60 mM acetate, but the similar growth rates observed across the concentration range demonstrate that acetate is not toxic when the glycolytic flux is low, even at high concentrations.
At low glycolytic flux, acetate activates E. coli metabolism and growth at the transcriptional level
At high glycolytic flux, it has been proposed (30) that the apparent “toxicity” of acetate is due to its inhibition of most metabolic genes – including those for the glucose phosphotransferase system (PTS), glycolysis and TCA cycle. Acetate also increases the expression of genes related to stress responses and downregulates genes related to transport, energy biosynthesis and mobility for instance. To determine if acetate has a similar regulatory effect at low glycolytic flux, we compared the transcriptomes of E. coli grown on glucose (15 mM) plus acetate (0, 10, 50 or 100 mM) in the presence of αMG (100 mM), with those measured in the absence of αMG at the same acetate concentrations (30).
We observed that contrary to what occurs at maximal glycolytic flux (0 mM αMG) acetate did not trigger a stress response at low glycolytic flux (100 mM αMG) (Figure 6A). Conversely, acetate increased gene expression for the respiratory chain and some biosynthetic processes (ribonucleotide monophosphate biosynthesis, amino acid production). Other hallmarks of the effect of acetate at maximal glycolytic flux such as the inhibition of mobility-related gene expression were not observed either at low glycolytic flux. The activation of glutamate catabolism, the repression of transport related genes, and the repression of carbohydrate transport and catabolism were among the few similarities between the responses to acetate at high and low glycolytic flux.
At the metabolic level, acetate-driven inhibition of the expression of central metabolic genes (PTS, TCA and glycolytic enzymes) and growth machinery (ribosomal proteins) was not observed at low glycolytic flux (Figure 6B). In fact, expression of most of these genes (47/65) was slightly higher in the presence of 50 mM acetate and 100 mM αMG, whereas at maximal glycolytic flux it was lower at these acetate concentrations for a similar proportion (46/65). When the glycolytic flux was inhibited, ptsG expression, which controls glucose uptake (42), was 70 % higher at 10 and 50 mM acetate. The expression of most glycolytic genes was 15 to 110 % higher at 50 mM acetate, while the expression of TCA cycle genes remained stable. Regarding acetate metabolism, the expression of pta and ackA was slightly higher at 10 and 50 mM acetate, while alternative acetate utilization via Acs was inhibited by acetate (5-fold reduction in expression at 100 mM). Finally, expression of genes encoding ribosomal proteins (rpl, rpm and rps operons) was increased by 57 % on average at 50 mM acetate and 48 % on average at 100 mM acetate (Dataset S1).
These results indicate that the stress response and lower metabolic activity triggered by acetate at high glycolytic flux do not occur at low glycolytic flux. In this situation, acetate enhances the expression of ribosomal and central metabolic genes, in line with its positive effect on growth. This is the opposite of what is observed at high glycolytic flux, demonstrating that the regulatory role of acetate is largely determined by the glycolytic flux.
Acetate-enhanced growth is supported by the Pta-AckA pathway
According to the model (Figure 1A), the bidirectional Pta-AckA pathway (acetate consumption or production) explains by itself how acetate promotes E. coli growth, without the need for Acs (acetate consumption only). To confirm this hypothesis, we measured the growth rates of E. coli K-12 BW25113 wild-type and of Δpta and Δacs isogenic mutant strains cultivated on 15 mM glucose plus 100 mM αMG, with or without 10 mM acetate. The effect of acetate was quantified as the relative change in growth rate induced. As a control, the wild-type strain was also grown in the absence of αMG, and as expected, acetate reduced the growth of the wild-type strain in the absence of αMG (-6 ± 1 %). In contrast, in the presence of αMG, acetate increased the growth of the wild-type strain (+9 ± 2 %) and of the Δacs strain (+8 ± 1 %). The beneficial effect of acetate on growth was not observed in the Δpta strain, whose growth rate decreased slightly but significantly (-6 ± 1 %). These results confirm that the beneficial effect of acetate on E. coli growth at low glycolytic flux is mediated by the Pta-AckA pathway, with no involvement of Acs in this phenomenon.
Acetate boosts growth of E. coli on glycerol and galactose
Assuming that the beneficial impact of acetate on E. coli growth stems from the tight interplay of glycolytic and acetate fluxes, this should be independent of the nature of the carbon source, implying that acetate should boost E. coli growth on glycolytic substrates with low glycolytic flux, such as glycerol and galactose (43). And indeed, wild-type E. coli growth was enhanced on both glycerol (+7 ± 1 %) and galactose (+52 ± 1 %) in the presence of 10 mM acetate. Similar levels of enhancement were observed for the Δacs strain (+8 ± 1 % on glycerol; +53 ± 5 % on galactose), but not for the Δpta strain (-8 ± 2 % on glycerol; +2 ± 12 % on galactose). These results demonstrate that acetate promotes E. coli growth on galactose and glycerol. As observed for glucose, the growth enhancement is mediated exclusively by the Pta-AckA pathway, with no involvement of Acs. These results extend and generalize our findings to glycolytic carbon sources other than glucose, without the use of an inhibitor.
Discussion
Following a systems biology approach, we used a kinetic model of E. coli metabolism to generate a comprehensive map of the functional relationship between glycolytic and acetate metabolisms and predict their combined impact on E. coli growth. In agreement with the predictions of the model, experimental results revealed a strong interplay between acetate and glycolytic fluxes in E. coli, with wide-ranging physiological consequences for the cells. Despite its established toxicity for microbial growth, we found that acetate improves the robustness of E. coli to glycolytic perturbations, and even boosts growth when the glycolytic flux is low.
Previous studies of the glycolytic control of acetate metabolism were carried out in the absence of acetate. In this situation, as observed here, glycolysis as a positive effect on acetate production. However, our results also reveal that in the presence of acetate, glycolysis negatively affects acetate utilization. Glycolytic control of the acetate flux is thus determined by the concentration of acetate itself. Because of this non-monotonous control pattern, reduced glycolytic flux increases acetate uptake and lowers the acetate concentration threshold at which acetate is co-consumed with glucose, with the overall effect of increasing acetate utilization by E. coli. This demonstrates that the metabolic status of acetate as a by-product or co-substrate of glycolytic carbon sources is determined both by the concentration of acetate (12, 30) and the glycolytic flux, and thus by the availability of glycolytic nutrients. This mechanism is exclusively mediated by the Pta-AckA pathway and its role and activity are determined by the nutritional conditions experienced by E. coli. The Pta-AckA pathway can therefore be seen as a metabolic valve that integrates information on the nutritional environment of the cells to rapidly adjust the acetate flux depending on the availability of glycolytic substrates and acetate. Our results indicate that these properties, which emerge simply from the distribution of control throughout the network, buffers the total carbon uptake flux and makes E. coli more robust to changes in the nutritional environment.
When the glycolytic flux is low, enhanced acetate utilization promotes E. coli growth, demonstrating that acetate can be beneficial to E. coli, even at high concentrations. Whereas 100 mM acetate has been shown to inhibit growth by ∼50 % at maximal glucose uptake rates (7, 12, 13), we observed that acetate at concentrations up to 60 mM had a positive effect on growth at low glucose uptake rates. The positive effect of acetate on E. coli growth at (artificially) low glucose uptake rates was confirmed on glycerol and galactose, two other glycolytic substrates with a naturally low glycolytic flux. Since the impact of acetate on growth is partly determined by the glycolytic flux, this metabolic by-product is not toxic per se. Importantly, these results also weaken several hypotheses that have been proposed to explain the apparent “toxicity” of acetate for microbial growth. Indeed, perturbations of the proton gradient, of the anion composition of the cell, or of methionine biosynthesis, would have a monotonic impact on growth. The results of this study indicate that mechanisms that only explain growth inhibition at high glycolytic flux are inadequate. The slight but global activating effect of acetate on the transcriptome at low glycolytic flux, which correlates with the growth response, also contrasts with its inhibitory effect at high glycolytic flux. The regulatory effect of acetate on E. coli metabolism is therefore more complex than previously suggested (30) and should be investigated further.
Although it was not initially developed to address the questions of this study, the kinetic model used here successfully predicts the observed interplay between glycolytic and acetate metabolisms, as well as the beneficial effect of acetate on E. coli growth at low glycolytic flux. Since the model does not account for the activation by acetate of the expression of glucose uptake, glycolytic, and ribosomal genes, this suggests that transcriptional activation by acetate may not be crucial for the flux response of E. coli. The metabolic network may indeed directly sense and integrate the availability of glucose and acetate to coordinate glucose and acetate fluxes, as already reported for the coordination other metabolic processes (44-46). In keeping with this hypothesis, our results support the concept of acetate flux being thermodynamically controlled by acetate itself (12). Metabolic regulation is thus (at least partly) responsible for the interplay between acetate and glycolytic flux. The precise regulatory program driven by acetate remains to be identified.
Acetate concentrations in the gut range from 30 to 100 mM (12) and glycolytic nutrients, such as glycerol and galactose (39, 47, 48), are generally scarce. Given the established inhibition of microbial growth by acetate, these high acetate levels were considered detrimental to E. coli colonization. Our results indicate that acetate, far from being toxic, may in fact be beneficial to E. coli in this environment. Acetate enhances E. coli growth when glycolytic substrates are limiting and may therefore facilitate its colonization and survival in the gut. Moreover, acetate stabilizes growth when the glycolytic flux is perturbed by temporary nutrient shortages, which are frequent in the gut. We suggest that the underlying regulatory mechanism may therefore be optimal for E. coli in its natural environment. Our results also call for the role of acetate in the gut to be reconsidered, since it represents a valuable and abundant resource that may benefit E. coli and other microorganisms.
In biotechnology, developing efficient strategies to overcome the negative effects of acetate requires understanding what controls the acetate flux and how in turn acetate controls microbial metabolism. By addressing these two needs, our findings should immediately help design bioprocesses with reduced acetate overflow and accelerate the development of mixed feed processes in which acetate is utilized alongside glucose or other glycolytic substrates. Current strategies are mainly based on increasing Acs activity to (re)use acetate present in the feedstock, provided as a co-substrate or produced by the Pta-AckA pathway. Given the Pta-AckA pathway produces one ATP and Acs consumes two ATPs, strategies based on activating the Pta-AckA-Acs cycle are highly energy-consuming (20). Strategies involving the Pta-AckA pathway alone are inherently less costly for the cell. Our results show that the Pta-AckA pathway enables efficient co-utilization of acetate and glycolytic substrates (glucose, glycerol, galactose) in E. coli by itself, with a positive effect on growth. The comprehensive understanding of the relationship between glycolytic and acetate metabolisms provided by this study may also represents a valuable guide to increase the productivity of valuable products synthesized from acetate-derived AcCoA (49, 50).
E. coli is not the only microorganism that co-consumes glucose with fermentation by-products. Saccharomyces cerevisiae can co-consume ethanol and glucose (51, 52), and mammalian cells co-consume lactate with glucose (53-56). Our findings may thus be generalizable to other microorganisms. Glycolytic control of fermentative pathways has indeed been observed in virtually all microorganisms. Our results explain why co-consumption of ethanol with glucose in yeast requires a reduction in glucose uptake (51). A similar relationship between glycolytic and lactate fluxes has also been reported in vitro in mammalian cells (57), with the switch between lactate production and utilization being determined by the glycolytic flux. It has been suggested that lactate rather than glucose is the primary circulating energy source in the human body (54, 56). Our study demonstrates that similarly to lactate, acetate is not a deleterious waste product but a valuable nutrient that can be shuttled between cells. The reversible Pta-AckA pathway enables uncoupling of glycolysis from the TCA cycle, indicating that this evolutionarily conserved design principle of eukaryotic metabolism (52) is also present in bacteria. As a nutrient and global regulator of microbial metabolism, acetate plays a major role in cellular, microbial community and host-level carbon and energy homeostasis.
Materials and Methods
Strains
Escherichia coli K-12 MG1655 was chosen as the model wild-type strain. Δpta and Δacs mutants were constructed from wild-type E. coli K-12 BW25113 from the KEIO collection (58) after kanamycin cassette removal (59). The genes pta and acs were individually deleted by CRISPR-Cas9 genome editing using the method and plasmids described in Wei et al. (60). pta deletion was confirmed by genome sequencing and acs deletion by PCR.
Growth conditions
E. coli was grown in M9 minimal media (61) supplemented with 15 mM glucose, 15 mM galactose, or 30 mM glycerol. Sodium acetate (prepared as a 1.6 M solution at pH 7.0) and methyl α-D-glucopyranoside (αMG, prepared as a 1.2 M solution) were added up to the required concentrations. The cells were grown in shake flasks at 37 °C and 200 rpm, in 50 mL of medium. Growth was monitored by measuring the optical density (OD) at 600 nm using a Genesys 6 spectrophotometer (Thermo, USA). Biomass concentrations were determined using a conversion factor of 0.37 gDW/L/OD unit (62).
Transcriptomics experiments
Cells were grown in M9 medium with 15 mM glucose, 100 mM αMG, and 0, 10, 50, or 100 mM acetate. Sample preparations and transcriptomics analyses were carried out as described by Millard et al. (30). Three independent replicates were analyzed for each condition. The transcriptomics data can be downloaded from the ArrayExpress database (www.ebi.ac.uk/arrayexpress) under accession number E-MTAB-11717. Transcriptomics data in the absence of glycolytic inhibition (ArrayExpress database accession number E-MTAB-9086 (30)) were measured under the exact same conditions but without αMG.
Metabolomics experiments
Extracellular concentrations of glucose and acetate were quantified in 180 µL of filtered broth (0.2 μm syringe filter, Sartorius, Germany) by 1D 1H-NMR on a Bruker Avance 500 MHz spectrometer equipped with a 5-mm z-gradient BBI probe (Bruker, Germany), as described previously (30).
Flux calculation
Glucose uptake, acetate and growth rates were calculated from glucose, acetate and biomass concentration–time profiles using PhysioFit (v1.0.2, https://github.com/MetaSys-LISBP/PhysioFit) (63).
Kinetic modelling
We used Millard et al.’s kinetic model of E. coli (30). available from the Biomodels database (https://www.ebi.ac.uk/biomodels) (64) under identifier MODEL2005050001. Simulations were carried out as described in the main text, using COPASI (65) (v4.34) with the CoRC package (66) (COPASI R Connector v0.11, https://github.com/jpahle/CoRC) in R (v4.1.3, https://www.r-project.org). The scripts used to perform the simulations and to generate the figures are provided in the Supporting information (Software S1) and at https://github.com/MetaSys-LISBP/glucose_acetate_interplay.
Statistical analyses
Comparisons between strains or conditions were performed using Student’s t-tests with two-tailed distributions. The scripts used to perform the calculations are provided in the Supporting information (Software S1) and at https://github.com/MetaSys-LISBP/glucose_acetate_interplay.
Acknowledgments
The authors thank MetaboHub-MetaToul (Metabolomics and Fluxomics facilities, Toulouse, France, http://www.metatoul.fr), part of the French National Infrastructure for Metabolomics and Fluxomics (http://www.metabohub.fr/) funded by the ANR (MetaboHUB-ANR-11-INBS-0010), for access to NMR facilities. The authors are grateful to Edith Vidal and Abdulrahman Khabbaz for help with the growth experiments, and the following INSA Toulouse students for help with the growth and transcriptomics experiments: Lola Blayac, Arno Bruel, Alexis Charbinat, Romane Ducloux, Justine Dumas-Perdriau, Solène Frapard, Sophie Germain, Benjamin Jung, Oliver Larrousse, Nicolas Papadopoulos, Marine Rodeghiero, Leyre Sarrias and Auriane Thomas. The authors also thank the Département Génie Biologique of INSA Toulouse and the Département MICA of the INRAE for ongoing support, and Guy Lippens and Jean-Charles Portais for insightful discussions on the manuscript.