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Significance The Calvin cycle is the most important carbon fixation pathway in the biosphere. However, its carboxylating enzyme Rubisco also accepts oxygen, thus producing 2-phosphoglycolate. Phosphoglycolate salvage pathways were extensively studied in photoautotrophs but remain uncharacterized in chemolithoautotrophs using the Calvin cycle. Here, we study phosphoglycolate salvage in the chemolithoautotrophic model bacterium Cupriavidus necator H16. We demonstrate that this bacterium mainly reassimilates 2-phosphoglycolate via the glycerate pathway. Upon disruption of this pathway, a secondary route, which we term the malate cycle, supports photorespiration by completely oxidizing 2-phosphoglycolate to CO2. While the malate cycle was not previously known to metabolize 2-phosphoglycolate in nature, a bioinformatic analysis suggests that it may support phosphoglycolate salvage in diverse chemoautotrophic bacteria., Carbon fixation via the Calvin cycle is constrained by the side activity of Rubisco with dioxygen, generating 2-phosphoglycolate. The metabolic recycling of phosphoglycolate was extensively studied in photoautotrophic organisms, including plants, algae, and cyanobacteria, where it is referred to as photorespiration. While receiving little attention so far, aerobic chemolithoautotrophic bacteria that operate the Calvin cycle independent of light must also recycle phosphoglycolate. As the term photorespiration is inappropriate for describing phosphoglycolate recycling in these nonphotosynthetic autotrophs, we suggest the more general term “phosphoglycolate salvage.” Here, we study phosphoglycolate salvage in the model chemolithoautotroph Cupriavidus necator H16 (Ralstonia eutropha H16) by characterizing the proxy process of glycolate metabolism, performing comparative transcriptomics of autotrophic growth under low and high CO2 concentrations, and testing autotrophic growth phenotypes of gene deletion strains at ambient CO2. We find that the canonical plant-like C2 cycle does not operate in this bacterium, and instead, the bacterial-like glycerate pathway is the main route for phosphoglycolate salvage. Upon disruption of the glycerate pathway, we find that an oxidative pathway, which we term the malate cycle, supports phosphoglycolate salvage. In this cycle, glyoxylate is condensed with acetyl coenzyme A (acetyl-CoA) to give malate, which undergoes two oxidative decarboxylation steps to regenerate acetyl-CoA. When both pathways are disrupted, autotrophic growth is abolished at ambient CO2. We present bioinformatic data suggesting that the malate cycle may support phosphoglycolate salvage in diverse chemolithoautotrophic bacteria. This study thus demonstrates a so far unknown phosphoglycolate salvage pathway, highlighting important diversity in microbial carbon fixation metabolism.

Flamholz and Shih explain how photosynthetic organisms on earth have evolved carbon dioxide concentrating mechanisms to contend with an increased abundance of oxygen in the atmosphere. This critical innovation has occurred numerous times and comes in two basic flavors.

Coenzymes distribute a variety of chemical moieties throughout cellular metabolism, participating in group (e.g., phosphate, acyl) and electron transfer. For a variety of reactions requiring acceptors or donors of specific resources, there often exist degenerate sets of molecules (e.g., NAD(H) and NADP(H)) that carry out similar functions. Although the physiological roles of various coenzyme systems are well established, it is unclear what selective pressures may have driven the emergence of coenzyme redundancy. Here we use genome-wide metabolic modeling approaches to decompose the selective pressures driving enzymatic specificity for either NAD(H) or NADP(H) in the metabolic network ofEscherichia coli. We found that few enzymes are thermodynamically constrained to using a single coenzyme, and in principle, a metabolic network relying on only NAD(H) is feasible. However, structural and sequence analyses revealed widespread conservation of residues that retain selectivity for either NAD(H) or NADP(H), suggesting that additional forces may shape specificity. Using a model accounting for the cost of oxidoreductase enzyme expression, we found that coenzyme redundancy universally reduces the minimal amount of protein required to catalyze coenzyme-coupled reactions, inducing individual reactions to strongly prefer one coenzyme over another when reactions are near thermodynamic equilibrium. We propose that protein minimization generically promotes coenzyme redundancy, and that coenzymes typically thought to exist in a single pool (e.g., CoA) may exist in more than one form (e.g., dephospho-CoA).Significance statementMetabolism relies on a small class of molecules (coenzymes) that serve as universal donors and acceptors of key chemical groups and electrons. Although metabolic networks crucially depend on structurally redundant coenzymes (e.g., NAD(H) and NADP(H)) associated with different enzymes, the criteria that led to the emergence of this redundancy remain poorly understood. Our combination of modeling, and structural and sequence analysis indicates that coenzyme redundancy is not essential for metabolism, but rather an evolved strategy promoting efficient usage of enzymes when biochemical reactions are near equilibrium. Our work suggests that early metabolism may have operated with fewer coenzymes, and that adaptation for metabolic efficiency may have driven the rise of coenzyme diversity in living systems.

Many photosynthetic organisms employ a CO2concentrating mechanism (CCM) to increase the rate of CO2fixation via the Calvin cycle. CCMs catalyze ≈50% of global photosynthesis, yet it remains unclear which genes and proteins are required to produce this complex adaptation. We describe the construction of a functional CCM in a non-native host, achieved by expressing genes from an autotrophic bacterium in anEscherichia colistrain engineered to depend on rubisco carboxylation for growth. Expression of 20 CCM genes enabledE. colito grow by fixing CO2from ambient air into biomass, with growth in ambient air depending on the components of the CCM. Bacterial CCMs are therefore genetically compact and readily transplanted, rationalizing their presence in diverse bacteria. Reconstitution enabled genetic experiments refining our understanding of the CCM, thereby laying the groundwork for deeper study and engineering of the cell biology supporting CO2assimilation in diverse organisms.

Carbon fixation via the Calvin cycle is constrained by the side activity of Rubisco with dioxygen, generating 2-phosphoglycolate. The metabolic recycling of 2-phosphoglycolate, an essential process termed photorespiration, was extensively studied in photoautotrophic organisms, including plants, algae, and cyanobacteria, but remains uncharacterized in chemolithoautotrophic bacteria. Here, we study photorespiration in the model chemolithoautotroph Cupriavidus necator (Ralstonia eutropha) by characterizing the proxy-process of glycolate metabolism, performing comparative transcriptomics of autotrophic growth under low and high CO2 concentrations, and testing autotrophic growth phenotypes of gene deletion strains at ambient CO2. We find that the canonical plant-like C2 cycle does not operate in this bacterium and instead the bacterial-like glycerate pathway is the main photorespiratory pathway. Upon disruption of the glycerate pathway, we find that an oxidative pathway, which we term the malate cycle, supports photorespiration. In this cycle, glyoxylate is condensed with acetyl-CoA to give malate, which undergoes two oxidative decarboxylation steps to regenerate acetyl-CoA. When both pathways are disrupted, autotrophic growth is abolished at ambient CO2. We present bioinformatic data suggesting that the malate cycle may support photorespiration in diverse chemolithoautotrophic bacteria. This study thus demonstrates a so-far unknown photorespiration pathway, highlighting important diversity in microbial carbon fixation metabolism.

Significance The k cat values of enzymes are important for the study of metabolic systems. However, the current use of k cat presents major difficulties, as values for most enzymes have not been experimentally measured, and experimentally available values are often measured under nonphysiological conditions, thereby casting doubt on the relevance of k cat under in vivo conditions. We present an approach that utilizes omics data to quantitatively analyze the relationship between in vitro k cat values and the maximal catalytic rate of enzymes in vivo. Our approach offers a high-throughput method to obtain enzyme kinetic constants, which reflect in vivo conditions, and are useful for more accurate and complete cellular metabolic models.

Rubisco is the primary carboxylase of the Calvin cycle, the most abundant enzyme in the biosphere, and one of the best-characterized enzymes. On the basis of correlations between Rubisco kinetic parameters, it is widely posited that constraints embedded in the catalytic mechanism enforce trade-offs between CO2 specificity, SC/O, and maximum carboxylation rate, kcat,C. However, the reasoning that established this view was based on data from ≈20 organisms. Here, we re-examine models of trade-offs in Rubisco catalysis using a data set from ≈300 organisms. Correlations between kinetic parameters are substantially attenuated in this larger data set, with the inverse relationship between kcat,C and SC/O being a key example. Nonetheless, measured kinetic parameters display extremely limited variation, consistent with a view of Rubisco as a highly constrained enzyme. More than 95% of kcat,C values are between 1 and 10 s-1, and no measured kcat,C exceeds 15 s-1. Similarly, SC/O varies by only 30% among Form I Rubiscos and

Many bacterial autotrophs rely on CO2concentrating mechanisms (CCMs) to assimilate carbon. Although many CCM proteins have been identified, including a 200+ MDa protein organelle called the carboxysome, a systematic screen of CCM components has not been carried out. Here, we performed a genome-wide barcoded transposon screen to identify essential and CCM-related genes in the ɣ-proteobacteriumH. neapolitanus. Our screen revealed an operon critical for CCM function which encodes a domain of unknown function (PFAM:PF10070) and putative cation transporter subunit (PFAM:PF00361). These two proteins, which we name DabA and DabB for “DABs accumulate bicarbonate,” function as a heterodimeric, energy-coupled inorganic carbon pump inE. coli. Furthermore, DabA binds zinc and has a an active site homologous to a β-carbonic anhydrase. Based on these results, we propose that DABs function as vectorial CAs coupled to cation gradients and serve as inorganic carbon pumps throughout prokaryotic phyla.

Rubisco is the most abundant enzyme in the biosphere and one of the best-characterized enzymes. Based on correlations between Rubisco kinetic parameters, it is widely posited that tradeoffs embedded in the catalytic mechanism constrain its specificity and maximum catalytic rate. However, the reasoning that established this view was based on data from ≈20 organisms. We re-examine these tradeoff models using a dataset from ≈300 organisms. Most correlations are substantially attenuated, with the inverse relationship between carboxylation kcat and specificity SC/O being a key example. Only one tradeoff model survives in our dataset. In this model, increasing catalytic efficiency (kcat/KM) for carboxylation requires increased catalytic efficiency for the competing oxygenation reaction, evidenced by strong power-law correlation between catalytic efficiencies. Our results imply that Rubisco evolution is constrained primarily by the physicochemical limits of O2/CO2 discrimination, which should reframe efforts to engineer this very central enzyme.

Thermodynamics dictates the structure and function of metabolism. Redox reactions drive cellular energy and material flow. Hence, accurately quantifying the thermodynamics of redox reactions should reveal key design principles that shape cellular metabolism. However, only a limited number of redox potentials have been measured experimentally, and mostly with inconsistent, poorly-reported experimental setups. Here, we develop a quantum chemistry approach for the calculation of redox potentials of biochemical reactions. We demonstrate that our method predicts experimentally measured potentials with unparalleled accuracy. We calculate the reduction potentials of all redox pairs that can be generated from biochemically relevant compounds and highlight fundamental thermodynamic trends that define cellular redox biochemistry. We further use the calculated potentials to address the question of why NAD/NADP are used as the primary cellular electron carriers, demonstrating how their physiological redox range specifically fits the reactions of central metabolism and minimizes the concentration of reactive carbonyls. The use of quantum chemistry tools, as demonstrated in this study, can revolutionize our understanding of key biochemical phenomena by enabling fast and accurate calculation of large datasets of thermodynamic values.

Electrosynthesis is a promising approach that enables the biological production of commodities, like fuels and fine chemicals, using renewably produced electricity. Several techniques have been proposed to mediate the transfer of electrons from the cathode to living cells. Of these, the electroproduction of formate as a mediator seems especially promising: formate is readily soluble, of low toxicity and can be produced at relatively high efficiency and at reasonable current density. While organisms that are capable of formatotrophic growth, i.e. growth on formate, exist naturally, they are generally less suitable for bulk cultivation and industrial needs. Hence, it may be helpful to engineer a model organism of industrial relevance, such as E. coli, for growth on formate. There are numerous metabolic pathways that can potentially support formatotrophic growth. Here we analyze these diverse pathways according to various criteria including biomass yield, thermodynamic favorability, chemical motive force, kinetics and the practical challenges posed by their expression. We find that the reductive glycine pathway, composed of the tetrahydrofolate system, the glycine cleavage system, serine hydroxymethyltransferase and serine deaminase, is a promising candidate to support electrosynthesis in E. coli. The approach presented here exemplifies how combining different computational approaches into a systematic analysis methodology provides assistance in redesigning metabolism. This article is part of a Special Issue entitled: Metals in Bioenergetics and Biomimetics Systems.

Many carbon-fixing bacteria rely on a CO2 concentrating mechanism (CCM) to elevate the CO2 concentration around the carboxylating enzyme ribulose bisphosphate carboxylase/oxygenase (RuBisCO). The CCM is postulated to simultaneously enhance the rate of carboxylation and minimize oxygenation, a competitive reaction with O2 also catalyzed by RuBisCO. To achieve this effect, the CCM combines two features: active transport of inorganic carbon into the cell and colocalization of carbonic anhydrase and RuBisCO inside proteinaceous microcompartments called carboxysomes. Understanding the significance of the various CCM components requires reconciling biochemical intuition with a quantitative description of the system. To this end, we have developed a mathematical model of the CCM to analyze its energetic costs and the inherent intertwining of physiology and pH. We find that intracellular pH greatly affects the cost of inorganic carbon accumulation. At low pH the inorganic carbon pool contains more of the highly cell-permeable H2CO3, necessitating a substantial expenditure of energy on transport to maintain internal inorganic carbon levels. An intracellular pH ≈8 reduces leakage, making the CCM significantly more energetically efficient. This pH prediction coincides well with our measurement of intracellular pH in a model cyanobacterium. We also demonstrate that CO2 retention in the carboxysome is necessary, whereas selective uptake of HCO3 (-) into the carboxysome would not appreciably enhance energetic efficiency. Altogether, integration of pH produces a model that is quantitatively consistent with cyanobacterial physiology, emphasizing that pH cannot be neglected when describing biological systems interacting with inorganic carbon pools.

Thermodynamics impose a major constraint on the structure of metabolic pathways. Here, we use carbon fixation pathways to demonstrate how thermodynamics shape the structure of pathways and determine the cellular resources they consume. We analyze the energetic profile of prototypical reactions and show that each reaction type displays a characteristic change in Gibbs energy. Specifically, although carbon fixation pathways display a considerable structural variability, they are all energetically constrained by two types of reactions: carboxylation and carboxyl reduction. In fact, all adenosine triphosphate (ATP) molecules consumed by carbon fixation pathways – with a single exception – are used, directly or indirectly, to power one of these unfavorable reactions. When an indirect coupling is employed, the energy released by ATP hydrolysis is used to establish another chemical bond with high energy of hydrolysis, e.g. a thioester. This bond is cleaved by a downstream enzyme to energize an unfavorable reaction. Notably, many pathways exhibit reduced ATP requirement as they couple unfavorable carboxylation or carboxyl reduction reactions to exergonic reactions other than ATP hydrolysis. In the most extreme example, the reductive acetyl coenzyme A (acetyl-CoA) pathway bypasses almost all ATP-consuming reactions. On the other hand, the reductive pentose phosphate pathway appears to be the least ATP-efficient because it is the only carbon fixation pathway that invests ATP in metabolic aims other than carboxylation and carboxyl reduction. Altogether, our analysis indicates that basic thermodynamic considerations accurately predict the resource investment required to support a metabolic pathway and further identifies biochemical mechanisms that can decrease this requirement.

Thermodynamics dictates the structure and function of metabolism. Redox reactions drive cellular energy and material flow. Hence, accurately quantifying the thermodynamics of redox reactions should reveal design principles that shape cellular metabolism. However, only few redox potentials have been measured, and mostly with inconsistent experimental setups. Here, we develop a quantum chemistry approach to calculate redox potentials of biochemical reactions and demonstrate our method predicts experimentally measured potentials with unparalleled accuracy. We then calculate the potentials of all redox pairs that can be generated from biochemically relevant compounds and highlight fundamental trends in redox biochemistry. We further address the question of why NAD/NADP are used as primary electron carriers, demonstrating how their physiological potential range fits the reactions of central metabolism and minimizes the concentration of reactive carbonyls. The use of quantum chemistry can revolutionize our understanding of biochemical phenomena by enabling fast and accurate calculation of thermodynamic values., PLoS Computational Biology, 14 (10), ISSN:1553-734X, ISSN:1553-7358

Michaelis and Menten’s mechanism for enzymatic catalysis is remarkable both in its simplicity and its wide applicability. The extension for reversible processes, as done by Haldane, makes it even more relevant as most enzymes catalyze reactions that are reversible in nature and carry in vivo flux in both directions. Here, we decompose the reversible Michaelis–Menten equation into three terms, each with a clear physical meaning: catalytic capacity, substrate saturation and thermodynamic driving force. This decomposition facilitates a better understanding of enzyme kinetics and highlights the relationship between thermodynamics and kinetics, a relationship which is often neglected. We further demonstrate how our separable rate law can be understood from different points of view, shedding light on factors shaping enzyme catalysis.

Contrary to the textbook portrayal of glycolysis as a single pathway conserved across all domains of life, not all sugar-consuming organisms use the canonical Embden–Meyerhoff–Parnass (EMP) glycolytic pathway. Prokaryotic glucose metabolism is particularly diverse, including several alternative glycolytic pathways, the most common of which is the Entner–Doudoroff (ED) pathway. The prevalence of the ED pathway is puzzling as it produces only one ATP per glucose—half as much as the EMP pathway. We argue that the diversity of prokaryotic glucose metabolism may reflect a tradeoff between a pathway’s energy (ATP) yield and the amount of enzymatic protein required to catalyze pathway flux. We introduce methods for analyzing pathways in terms of thermodynamics and kinetics and show that the ED pathway is expected to require several-fold less enzymatic protein to achieve the same glucose conversion rate as the EMP pathway. Through genomic analysis, we further show that prokaryotes use different glycolytic pathways depending on their energy supply. Specifically, energy-deprived anaerobes overwhelmingly rely upon the higher ATP yield of the EMP pathway, whereas the ED pathway is common among facultative anaerobes and even more common among aerobes. In addition to demonstrating how protein costs can explain the use of alternative metabolic strategies, this study illustrates a direct connection between an organism’s environment and the thermodynamic and biochemical properties of the metabolic pathways it employs.

What governs the concentrations of metabolites within living cells? Beyond specific metabolic and enzymatic considerations, are there global trends that affect their values? We hypothesize that the physico-chemical properties of metabolites considerably affect their in-vivo concentrations. The recently achieved experimental capability to measure the concentrations of many metabolites simultaneously has made the testing of this hypothesis possible. Here, we analyze such recently available data sets of metabolite concentrations within E. coli, S. cerevisiae, B. subtilis and human. Overall, these data sets encompass more than twenty conditions, each containing dozens (28-108) of simultaneously measured metabolites. We test for correlations with various physico-chemical properties and find that the number of charged atoms, non-polar surface area, lipophilicity and solubility consistently correlate with concentration. In most data sets, a change in one of these properties elicits a ∼100 fold increase in metabolite concentrations. We find that the non-polar surface area and number of charged atoms account for almost half of the variation in concentrations in the most reliable and comprehensive data set. Analyzing specific groups of metabolites, such as amino-acids or phosphorylated nucleotides, reveals even a higher dependence of concentration on hydrophobicity. We suggest that these findings can be explained by evolutionary constraints imposed on metabolite concentrations and discuss possible selective pressures that can account for them. These include the reduction of solute leakage through the lipid membrane, avoidance of deleterious aggregates and reduction of non-specific hydrophobic binding. By highlighting the global constraints imposed on metabolic pathways, future research could shed light onto aspects of biochemical evolution and the chemical constraints that bound metabolic engineering efforts., Author Summary What governs the identity and concentrations of metabolites within living cells? The first part of this question has received much attention. Organisms were found to qualitatively prefer hydrophilic and charged metabolites, a phenomenon that was explained to be a result of constraints imposed by contemporary as well as archaic metabolism. However, among the metabolites that are used, a quantitative preference has never been analyzed systematically. Here we use the most comprehensive data sets of metabolite concentrations available to explore such trends. We find that in various organisms and growth conditions, living cells minimize the concentrations of non-polar, un-charged metabolites. More specifically, metabolites' hydrophobicity alters concentrations by two orders of magnitudes on average and explains up to half of the variation of metabolite concentrations within cells. We suggest that this can be attributed to an evolutionary pressure to avoid an unspecific hydrophobic effect: the preference of hydrophobic surfaces in an aqueous environment to adhere to other hydrophobic surfaces. Our findings shed light on the evolution of the internal makeup of living cells and can assist in establishing metabolic models that support synthetic biology and metabolic engineering efforts.

In metabolism research, thermodynamics is usually used to determine the directionality of a reaction or the feasibility of a pathway. However, the relationship between thermodynamic potentials and fluxes is not limited to questions of directionality: thermodynamics also affects the kinetics of reactions through the flux-force relationship, which states that the logarithm of the ratio between the forward and reverse fluxes is directly proportional to the change in Gibbs energy due to a reaction (ΔrG′). Accordingly, if an enzyme catalyzes a reaction with a ΔrG′ of -5.7 kJ/mol then the forward flux will be roughly ten times the reverse flux. As ΔrG′ approaches equilibrium (ΔrG′ = 0 kJ/mol), exponentially more enzyme counterproductively catalyzes the reverse reaction, reducing the net rate at which the reaction proceeds. Thus, the enzyme level required to achieve a given flux increases dramatically near equilibrium. Here, we develop a framework for quantifying the degree to which pathways suffer these thermodynamic limitations on flux. For each pathway, we calculate a single thermodynamically-derived metric (the Max-min Driving Force, MDF), which enables objective ranking of pathways by the degree to which their flux is constrained by low thermodynamic driving force. Our framework accounts for the effect of pH, ionic strength and metabolite concentration ranges and allows us to quantify how alterations to the pathway structure affect the pathway's thermodynamics. Applying this methodology to pathways of central metabolism sheds light on some of their features, including metabolic bypasses (e.g., fermentation pathways bypassing substrate-level phosphorylation), substrate channeling (e.g., of oxaloacetate from malate dehydrogenase to citrate synthase), and use of alternative cofactors (e.g., quinone as an electron acceptor instead of NAD). The methods presented here place another arrow in metabolic engineers' quiver, providing a simple means of evaluating the thermodynamic and kinetic quality of different pathway chemistries that produce the same molecules., Author Summary Given data about enzyme kinetics and reaction thermodynamics, traditional metabolic control analysis (MCA) can pinpoint the enzymes whose expression will have the largest effect on steady-state flux through the pathway. These analyses can aid experimentalists in tuning enzyme expression levels along a metabolic pathway. In this work, we offer a framework that is complementary to MCA. Rather than focusing on the relationship between enzyme levels and pathway flux, we examine a pathway's stoichiometry and thermodynamics and ask whether it is likely to support high flux in cellular conditions. Our framework calculates a single thermodynamically-derived metric (the MDF) for each pathway, which is convenient for selecting the promising pathways from a large collection. This approach has several advantages. First, enzyme kinetic properties are laborious to measure and differ between organisms and isozymes, but no kinetic data is required to calculate the MDF. Second, as our framework accounts for pH, ionic strength and allowed concentration ranges, it is simple to model the effect of these parameters on the MDF. Finally, as it can be difficult to control the exact expression level of enzymes within cells, the MDF helps identify alternative pathways that are less sensitive to the levels of their constituent enzymes.