Coordination of microbial metabolism

Synthetic biology and regulatory networks: where metabolic systems biology meets control engineering

Metabolic pathways can be engineered to maximize the synthesis of various products of interest. With the advent of computational systems biology, this endeavour is usually carried out through in silico theoretical studies with the aim to guide and complement further in vitro and in vivo experimental efforts. Clearly, what counts is the result in vivo, not only in terms of maximal productivity but also robustness against environmental perturbations. Engineering an organism towards an increased production flux, however, often compromises that robustness. In this contribution, we review and investigate how various analytical approaches used in metabolic engineering and synthetic biology are related to concepts developed by systems and control engineering. While trade-offs between production optimality and cellular robustness have already been studied diagnostically and statically, the dynamics also matter. Integration of the dynamic design aspects of control engineering with the more diagnostic aspects of metabolic, hierarchical control and regulation analysis is leading to the new, conceptual and operational framework required for the design of robust and productive dynamic pathways.

Synthetic and systems biology for microbial production of commodity chemicals

The combination of synthetic and systems biology is a powerful framework to study fundamental questions in biology and produce chemicals of immediate practical application such as biofuels, polymers, or therapeutics. However, we cannot yet engineer biological systems as easily and precisely as we engineer physical systems. In this review, we describe the path from the choice of target molecule to scaling production up to commercial volumes. We present and explain some of the current challenges and gaps in our knowledge that must be overcome in order to bring our bioengineering capabilities to the level of other engineering disciplines. Challenges start at molecule selection, where a difficult balance between economic potential and biological feasibility must be struck. Pathway design and construction have recently been revolutionized by next-generation sequencing and exponentially improving DNA synthesis capabilities. Although pathway optimization can be significantly aided by enzyme expression characterization through proteomics, choosing optimal relative protein expression levels for maximum production is still the subject of heuristic, non-systematic approaches. Toxic metabolic intermediates and proteins can significantly affect production, and dynamic pathway regulation emerges as a powerful but yet immature tool to prevent it. Host engineering arises as a much needed complement to pathway engineering for high bioproduct yields; and systems biology approaches such as stoichiometric modeling or growth coupling strategies are required. A final, and often underestimated, challenge is the successful scale up of processes to commercial volumes. Sustained efforts in improving reproducibility and predictability are needed for further development of bioengineering.

The Emergence of 2-Oxoglutarate as a Master Regulator Metabolite

The metabolite 2-oxoglutarate (also known as α-ketoglutarate, 2-ketoglutaric acid, or oxoglutaric acid) lies at the intersection between the carbon and nitrogen metabolic pathways. This compound is a key intermediate of one of the most fundamental biochemical pathways in carbon metabolism, the tricarboxylic acid (TCA) cycle. In addition, 2-oxoglutarate also acts as the major carbon skeleton for nitrogen-assimilatory reactions. Experimental data support the conclusion that intracellular levels of 2-oxoglutarate fluctuate according to nitrogen and carbon availability. This review summarizes how nature has capitalized on the ability of 2-oxoglutarate to reflect cellular nutritional status through evolution of a variety of 2-oxoglutarate-sensing regulatory proteins. The number of metabolic pathways known to be regulated by 2-oxoglutarate levels has increased significantly in recent years. The signaling properties of 2-oxoglutarate are highlighted by the fact that this metabolite regulates the synthesis of the well-established master signaling molecule, cyclic AMP (cAMP), in Escherichia coli.

Rapid bacterial antibiotic susceptibility test based on simple surface-enhanced Raman spectroscopic biomarkers

Rapid bacterial antibiotic susceptibility test (AST) and minimum inhibitory concentration (MIC) measurement are important to help reduce the widespread misuse of antibiotics and alleviate the growing drug-resistance problem. We discovered that, when a susceptible strain of Staphylococcus aureus or Escherichia coli is exposed to an antibiotic, the intensity of specific biomarkers in its surface-enhanced Raman scattering (SERS) spectra drops evidently in two hours. The discovery has been exploited for rapid AST and MIC determination of methicillin-susceptible S. aureus and wild-type E. coli as well as clinical isolates. The results obtained by this SERS-AST method were consistent with that by the standard incubation-based method, indicating its high potential to supplement or replace existing time-consuming methods and help mitigate the challenge of drug resistance in clinical microbiology.

Dynamical Allocation of Cellular Resources as an Optimal Control Problem: Novel Insights into Microbial Growth Strategies

Microbial physiology exhibits growth laws that relate the macromolecular composition of the cell to the growth rate. Recent work has shown that these empirical regularities can be derived from coarse-grained models of resource allocation. While these studies focus on steady-state growth, such conditions are rarely found in natural habitats, where microorganisms are continually challenged by environmental fluctuations. The aim of this paper is to extend the study of microbial growth strategies to dynamical environments, using a self-replicator model. We formulate dynamical growth maximization as an optimal control problem that can be solved using Pontryagin’s Maximum Principle. We compare this theoretical gold standard with different possible implementations of growth control in bacterial cells. We find that simple control strategies enabling growth-rate maximization at steady state are suboptimal for transitions from one growth regime to another, for example when shifting bacterial cells to a medium supporting a higher growth rate. A near-optimal control strategy in dynamical conditions is shown to require information on several, rather than a single physiological variable. Interestingly, this strategy has structural analogies with the regulation of ribosomal protein synthesis by ppGpp in the enterobacterium Escherichia coli. It involves sensing a mismatch between precursor and ribosome concentrations, as well as the adjustment of ribosome synthesis in a switch-like manner. Our results show how the capability of regulatory systems to integrate information about several physiological variables is critical for optimizing growth in a changing environment.

Microbial growth is the process by which cells sustain and reproduce themselves from available matter and energy. Strategies enabling microorganisms to optimize their growth rate have been extensively studied, but mostly in stable environments. Here, we build a coarse-grained model of microbial growth and use methods from optimal control theory to determine a resource allocation scheme that would lead to maximal biomass accumulation when the cells are dynamically shifted from one growth medium to another. We compare this optimal solution with several cellular implementations of growth control, based on the capacity of the cell to sense different physiological variables. We find that strategies maximizing growth in steady-state conditions perform quite differently in dynamical conditions. Moreover, the control strategy with performance close to the theoretical maximum exploits information of more than one physiological variable, suggesting that optimization of microbial growth in dynamical rather than steady environments requires broader sensory capacities. Interestingly, the ppGpp alarmone system in the enterobacterium Escherichia coli, known to play an important role in growth control, has structural similarities with the control strategy approaching the theoretical maximum. It senses a discrepancy between the concentrations of precursors and ribosomes, and adjusts ribosome synthesis in an on-off fashion. This suggests that E. coli is adapted for environments with intermittent, rapid changes in nutrient availability.

Global characterization of in vivo enzyme catalytic rates and their correspondence to in vitro kcat measurements

Turnover numbers, also known as kcat values, are fundamental properties of enzymes. However, kcat data are scarce and measured in vitro, thus may not faithfully represent the in vivo situation. A basic question that awaits elucidation is: how representative are kcat values for the maximal catalytic rates of enzymes in vivo? Here, we harness omics data to calculate kmax(vivo), the observed maximal catalytic rate of an enzyme inside cells. Comparison with kcat values from Escherichia coli, yields a correlation ofr(2)= 0.62 in log scale (p < 10(-10)), with a root mean square difference of 0.54 (3.5-fold in linear scale), indicating that in vivo and in vitro maximal rates generally concur. By accounting for the degree of saturation of enzymes and the backward flux dictated by thermodynamics, we further refine the correspondence between kmax(vivo) and kcat values. The approach we present here characterizes the quantitative relationship between enzymatic catalysis in vitro and in vivo and offers a high-throughput method for extracting enzyme kinetic constants from omics data.

Evidence for quorum sensing and differential metabolite production by a marine bacterium in response to DMSP

Microbes, the foundation of the marine foodweb, do not function in isolation, but rather rely on molecular level interactions among species to thrive. Although certain types of interactions between autotrophic and heterotrophic microorganisms have been well documented, the role of specific organic molecules in regulating inter-species relationships and supporting growth are only beginning to be understood. Here, we examine one such interaction by characterizing the metabolic response of a heterotrophic marine bacterium, Ruegeria pomeroyi DSS-3, to growth on dimethylsulfoniopropionate (DMSP), an abundant organosulfur metabolite produced by phytoplankton. When cultivated on DMSP, R. pomeroyi synthesized a quorum-sensing molecule, N-(3-oxotetradecanoyl)-l-homoserine lactone, at significantly higher levels than during growth on propionate. Concomitant with the production of a quorum-sensing molecule, we observed differential production of intra- and extracellular metabolites including glutamine, vitamin B2 and biosynthetic intermediates of cyclic amino acids. Our metabolomics data indicate that R. pomeroyi changes regulation of its biochemical pathways in a manner that is adaptive for a cooperative lifestyle in the presence of DMSP, in anticipation of phytoplankton-derived nutrients and higher microbial density. This behavior is likely to occur on sinking marine particles, indicating that this response may impact the fate of organic matter.

Global Metabolic Responses to Salt Stress in Fifteen Species

Cells constantly adapt to unpredictably changing extracellular solute concentrations. A cornerstone of the cellular osmotic stress response is the metabolic supply of energy and building blocks to mount appropriate defenses. Yet, the extent to which osmotic stress impinges on the metabolic network remains largely unknown. Moreover, it is mostly unclear which, if any, of the metabolic responses to osmotic stress are conserved among diverse organisms or confined to particular groups of species. Here we investigate the global metabolic responses of twelve bacteria, two yeasts and two human cell lines exposed to sustained hyperosmotic salt stress by measuring semiquantitative levels of hundreds of cellular metabolites using nontargeted metabolomics. Beyond the accumulation of osmoprotectants, we observed significant changes of numerous metabolites in all species. Global metabolic responses were predominantly species-specific, yet individual metabolites were characteristically affected depending on species’ taxonomy, natural habitat, envelope structure or salt tolerance. Exploiting the breadth of our dataset, the correlation of individual metabolite response magnitudes across all species implicated lower glycolysis, tricarboxylic acid cycle, branched-chain amino acid metabolism and heme biosynthesis to be generally important for salt tolerance. Thus, our findings place the global metabolic salt stress response into a phylogenetic context and provide insights into the cellular phenotype associated with salt tolerance.

Overflow metabolism in Escherichia coli results from efficient proteome allocation

Overflow metabolism refers to the seemingly wasteful strategy in which cells use fermentation instead of the more efficient respiration to generate energy, despite the availability of oxygen. Known as Warburg effect in the context of cancer growth, this phenomenon occurs ubiquitously for fast growing cells, including bacteria, fungi, and mammalian cells, but its origin has remained mysterious despite decades of research. Here we study metabolic overflow in E. coli and show that it is a global physiological response used to cope with changing proteomic demands of energy biogenesis and biomass synthesis under different growth conditions. A simple model of proteomic resource allocation can quantitatively account for all of the observed behaviors and accurately predict responses to novel perturbations. The key hypothesis of the model, that the proteome cost of energy biogenesis by respiration exceeds that by fermentation, is quantitatively confirmed by direct measurement of protein abundances via quantitative mass spectrometry.

Facile synthesis of highly uniform selenium nanoparticles using glucose as the reductant and surface decorator to induce cancer cell apoptosis

Herein, we demonstrated a new and facial synthesis of highly uniformed SeNPs using glucose as the reductant and surface decorator. Glu–SeNPs induced cancer cell apoptosisviainduction of apoptosis by triggering intracellular ROS overproduction and mitochondrial dysfunction.

HexR Controls Glucose-Responsive Genes and Central Carbon Metabolism in Neisseria meningitidis

Neisseria meningitidis, an exclusively human pathogen and the leading cause of bacterial meningitis, must adapt to different host niches during human infection. N. meningitidis can utilize a restricted range of carbon sources, including lactate, glucose, and pyruvate, whose concentrations vary in host niches. Microarray analysis of N. meningitidis grown in a chemically defined medium in the presence or absence of glucose allowed us to identify genes regulated by carbon source availability. Most such genes are implicated in energy metabolism and transport, and some are implicated in virulence. In particular, genes involved in glucose catabolism were upregulated, whereas genes involved in the tricarboxylic acid cycle were downregulated. Several genes encoding surface-exposed proteins, including the MafA adhesins and Neisseria surface protein A, were upregulated in the presence of glucose. Our microarray analysis led to the identification of a glucose-responsive hexR-like transcriptional regulator that controls genes of the central carbon metabolism of N. meningitidis in response to glucose. We characterized the HexR regulon and showed that the hexR gene is accountable for some of the glucose-responsive regulation; in vitro assays with the purified protein showed that HexR binds to the promoters of the central metabolic operons of the bacterium. Based on DNA sequence alignment of the target sites, we propose a 17-bp pseudopalindromic consensus HexR binding motif. Furthermore, N. meningitidis strains lacking hexR expression were deficient in establishing successful bacteremia in an infant rat model of infection, indicating the importance of this regulator for the survival of this pathogen in vivo.

IMPORTANCE

Neisseria meningitidis grows on a limited range of nutrients during infection. We analyzed the gene expression of N. meningitidis in response to glucose, the main energy source available in human blood, and we found that glucose regulates many genes implicated in energy metabolism and nutrient transport, as well as some implicated in virulence. We identified and characterized a transcriptional regulator (HexR) that controls metabolic genes of N. meningitidis in response to glucose. We generated a mutant lacking HexR and found that the mutant was impaired in causing systemic infection in animal models. Since N. meningitidis lacks known bacterial regulators of energy metabolism, our findings suggest that HexR plays a major role in its biology by regulating metabolism in response to environmental signals.

Synthetic biology for microbial production of lipid-based biofuels

The risks of maintaining current CO2 emission trends have led to interest in producing biofuels using engineered microbes. Microbial biofuels reduce emissions because CO2 produced by fuel combustion is offset by CO2 captured by growing biomass, which is later used as feedstock for biofuel fermentation. Hydrocarbons found in petroleum fuels share striking similarity with biological lipids. Here we review synthetic metabolic pathways based on fatty acid and isoprenoid metabolism to produce alkanes and other molecules suitable as biofuels. We further discuss engineering strategies to optimize engineered biosynthetic routes, as well as the potential of synthetic biology for sustainable manufacturing.

Real-time metabolome profiling of the metabolic switch between starvation and growth

Metabolic systems are often the first networks to respond to environmental changes, and the ability to monitor metabolite dynamics is key for understanding these cellular responses. Because monitoring metabolome changes is experimentally tedious and demanding, dynamic data on time scales from seconds to hours are scarce. Here we describe real-time metabolome profiling by direct injection of living bacteria, yeast or mammalian cells into a high-resolution mass spectrometer, which enables automated monitoring of about 300 compounds in 15-30-s cycles over several hours. We observed accumulation of energetically costly biomass metabolites in Escherichia coli in carbon starvation-induced stationary phase, as well as the rapid use of these metabolites upon growth resumption. By combining real-time metabolome profiling with modeling and inhibitor experiments, we obtained evidence for switch-like feedback inhibition in amino acid biosynthesis and for control of substrate availability through the preferential use of the metabolically cheaper one-step salvaging pathway over costly ten-step de novo purine biosynthesis during growth resumption.

Pseudomonas putida KT2440 Strain Metabolizes Glucose through a Cycle Formed by Enzymes of the Entner-Doudoroff, Embden-Meyerhof-Parnas, and Pentose Phosphate Pathways

The soil bacterium Pseudomonas putida KT2440 lacks a functional Embden-Meyerhof-Parnas (EMP) pathway, and glycolysis is known to proceed almost exclusively through the Entner-Doudoroff (ED) route. To investigate the raison d'être of this metabolic arrangement, the distribution of periplasmic and cytoplasmic carbon fluxes was studied in glucose cultures of this bacterium by using (13)C-labeled substrates, combined with quantitative physiology experiments, metabolite quantification, and in vitro enzymatic assays under both saturating and non-saturating, quasi in vivo conditions. Metabolic flux analysis demonstrated that 90% of the consumed sugar was converted into gluconate, entering central carbon metabolism as 6-phosphogluconate and further channeled into the ED pathway. Remarkably, about 10% of the triose phosphates were found to be recycled back to form hexose phosphates. This set of reactions merges activities belonging to the ED, the EMP (operating in a gluconeogenic fashion), and the pentose phosphate pathways to form an unforeseen metabolic architecture (EDEMP cycle). Determination of the NADPH balance revealed that the default metabolic state of P. putida KT2440 is characterized by a slight catabolic overproduction of reducing power. Cells growing on glucose thus run a biochemical cycle that favors NADPH formation. Because NADPH is required not only for anabolic functions but also for counteracting different types of environmental stress, such a cyclic operation may contribute to the physiological heftiness of this bacterium in its natural habitats.

Mapping high-growth phenotypes in the flux space of microbial metabolism

Experimental and empirical observations on cell metabolism cannot be understood as a whole without their integration into a consistent systematic framework. However, the characterization of metabolic flux phenotypes is typically reduced to the study of a single optimal state, such as maximum biomass yield that is by far the most common assumption. Here, we confront optimal growth solutions to the whole set of feasible flux phenotypes (FFPs), which provides a benchmark to assess the likelihood of optimal and high-growth states and their agreement with experimental results. In addition, FFP maps are able to uncover metabolic behaviours, such as aerobic fermentation accompanying exponential growth on sugars at nutrient excess conditions, that are unreachable using standard models based on optimality principles. The information content of the full FFP space provides us with a map to explore and evaluate metabolic behaviour and capabilities, and so it opens new avenues for biotechnological and biomedical applications.

Regulation of indole-3-acetic acid biosynthesis by branched-chain amino acids in Enterobacter cloacae UW5

The soil bacterium Enterobacter cloacae UW5 produces the rhizosphere signaling molecule indole-3-acetic acid (IAA) via the indolepyruvate pathway. Expression of indolepyruvate decarboxylase, a key pathway enzyme encoded by ipdC, is upregulated by the transcription factor TyrR in response to aromatic amino acids. Some members of the TyrR regulon may also be controlled by branched-chain amino acids and here we show that expression from the ipdC promoter and production of IAA are downregulated by valine, leucine and isoleucine. Regulation of the IAA synthesis pathway by both aromatic and branched-chain amino acids suggests a broader role for this pathway in bacterial physiology, beyond plant interactions.

An overview on transcriptional regulators in Streptomyces

Streptomyces are Gram-positive microorganisms able to adapt and respond to different environmental conditions. It is the largest genus of Actinobacteria comprising over 900 species. During their lifetime, these microorganisms are able to differentiate, produce aerial mycelia and secondary metabolites. All of these processes are controlled by subtle and precise regulatory systems. Regulation at the transcriptional initiation level is probably the most common for metabolic adaptation in bacteria. In this mechanism, the major players are proteins named transcription factors (TFs), capable of binding DNA in order to repress or activate the transcription of specific genes. Some of the TFs exert their action just like activators or repressors, whereas others can function in both manners, depending on the target promoter. Generally, TFs achieve their effects by using one- or two-component systems, linking a specific type of environmental stimulus to a transcriptional response. After DNA sequencing, many streptomycetes have been found to have chromosomes ranging between 6 and 12Mb in size, with high GC content (around 70%). They encode for approximately 7000 to 10,000 genes, 50 to 100 pseudogenes and a large set (around 12% of the total chromosome) of regulatory genes, organized in networks, controlling gene expression in these bacteria. Among the sequenced streptomycetes reported up to now, the number of transcription factors ranges from 471 to 1101. Among these, 315 to 691 correspond to transcriptional regulators and 31 to 76 are sigma factors. The aim of this work is to give a state of the art overview on transcription factors in the genus Streptomyces.

Posttranslational regulation of microbial metabolism

Fluxes in microbial metabolism are controlled by various regulatory layers that alter abundance or activity of metabolic enzymes. Recent studies suggest a division of labor between these layers: transcriptional regulation mostly controls the allocation of protein resources, passive flux regulation by enzyme saturation and thermodynamics allows rapid responses at the expense of higher protein cost, and posttranslational regulation is utilized by cells to directly take control of metabolic decisions. We present recent advances in elucidating the role of these regulatory layers, focusing on posttranslational modifications and allosteric interactions. As the systematic mapping of posttranslational regulatory events has now become possible, the next challenge is to identify those regulatory events that are functionally relevant under a given condition.

Data-driven integration of genome-scale regulatory and metabolic network models

Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription, and signaling) have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert-a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or more network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. In this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system.

A growth-rate composition formula for the growth of E.coli on co-utilized carbon substrates

When bacteria are cultured in medium with multiple carbon substrates, they frequently consume these substrates simultaneously. Building on recent advances in the understanding of metabolic coordination exhibited by Escherichia coli cells through cAMP-Crp signaling, we show that this signaling system responds to the total carbon-uptake flux when substrates are co-utilized and derive a mathematical formula that accurately predicts the resulting growth rate, based only on the growth rates on individual substrates.

A Sense of Balance: Experimental Investigation and Modeling of a Malonyl-CoA Sensor in Escherichia coli

Production of value-added chemicals in microorganisms is regarded as a viable alternative to chemical synthesis. In the past decade, several engineered pathways producing such chemicals, including plant secondary metabolites in microorganisms have been reported; upscaling their production yields, however, was often challenging. Here, we analyze a modular device designed for sensing malonyl-CoA, a common precursor for both fatty acid and flavonoid biosynthesis. The sensor can be used either for high-throughput pathway screening in synthetic biology applications or for introducing a feedback circuit to regulate production of the desired chemical. Here, we used the sensor to compare the performance of several predicted malonyl-CoA-producing pathways, and validated the utility of malonyl-CoA reductase and malonate-CoA transferase for malonyl-CoA biosynthesis. We generated a second-order dynamic linear model describing the relation of the fluorescence generated by the sensor to the biomass of the host cell representing a filter/amplifier with a gain that correlates with the level of induction. We found the time constants describing filter dynamics to be independent of the level of induction but distinctively clustered for each of the production pathways, indicating the robustness of the sensor. Moreover, by monitoring the effect of the copy-number of the production plasmid on the dose–response curve of the sensor, we managed to coarse-tune the level of pathway expression to maximize malonyl-CoA synthesis. In addition, we provide an example of the sensor’s use in analyzing the effect of inducer or substrate concentrations on production levels. The rational development of models describing sensors, supplemented with the power of high-throughput optimization provide a promising potential for engineering feedback loops regulating enzyme levels to maximize productivity yields of synthetic metabolic pathways.

A general framework for thermodynamically consistent parameterization and efficient sampling of enzymatic reactions

Kinetic models provide the means to understand and predict the dynamic behaviour of enzymes upon different perturbations. Despite their obvious advantages, classical parameterizations require large amounts of data to fit their parameters. Particularly, enzymes displaying complex reaction and regulatory (allosteric) mechanisms require a great number of parameters and are therefore often represented by approximate formulae, thereby facilitating the fitting but ignoring many real kinetic behaviours. Here, we show that full exploration of the plausible kinetic space for any enzyme can be achieved using sampling strategies provided a thermodynamically feasible parameterization is used. To this end, we developed a General Reaction Assembly and Sampling Platform (GRASP) capable of consistently parameterizing and sampling accurate kinetic models using minimal reference data. The former integrates the generalized MWC model and the elementary reaction formalism. By formulating the appropriate thermodynamic constraints, our framework enables parameterization of any oligomeric enzyme kinetics without sacrificing complexity or using simplifying assumptions. This thermodynamically safe parameterization relies on the definition of a reference state upon which feasible parameter sets can be efficiently sampled. Uniform sampling of the kinetics space enabled dissecting enzyme catalysis and revealing the impact of thermodynamics on reaction kinetics. Our analysis distinguished three reaction elasticity regions for common biochemical reactions: a steep linear region (0> ΔGr >-2 kJ/mol), a transition region (-2> ΔGr >-20 kJ/mol) and a constant elasticity region (ΔGr <-20 kJ/mol). We also applied this framework to model more complex kinetic behaviours such as the monomeric cooperativity of the mammalian glucokinase and the ultrasensitive response of the phosphoenolpyruvate carboxylase of Escherichia coli. In both cases, our approach described appropriately not only the kinetic behaviour of these enzymes, but it also provided insights about the particular features underpinning the observed kinetics. Overall, this framework will enable systematic parameterization and sampling of enzymatic reactions.

The Crc/CrcZ-CrcY global regulatory system helps the integration of gluconeogenic and glycolytic metabolism in Pseudomonas putida

In metabolically versatile bacteria, carbon catabolite repression (CCR) facilitates the preferential assimilation of the most efficient carbon sources, improving growth rates and fitness. In Pseudomonas putida, the Crc and Hfq proteins and the CrcZ and CrcY small RNAs, which are believed to antagonize Crc/Hfq, are key players in CCR. Unlike that seen in other bacterial species, succinate and glucose elicit weak CCR in this bacterium. In the present work, metabolic, transcriptomic and constraint-based metabolic flux analyses were combined to clarify whether P. putida prefers succinate or glucose, and to identify the role of the Crc protein in the metabolism of these compounds. When provided simultaneously, succinate was consumed faster than glucose, although both compounds were metabolized. CrcZ and CrcY levels were lower when both substrates were present than when only one was provided, suggesting a role for Crc in coordinating metabolism of these compounds. Flux distribution analysis suggested that, when both substrates are present, Crc works to organize a metabolism in which carbon compounds flow in opposite directions: from glucose to pyruvate, and from succinate to pyruvate. Thus, our results support that Crc not only favours the assimilation of preferred compounds, but balances carbon fluxes, optimizing metabolism and growth.

Reassessment of the Genetic Regulation of Fatty Acid Synthesis in Escherichia coli: Global Positive Control by the Dual Functional Regulator FadR

In Escherichia coli, the FadR transcriptional regulator represses the expression of fatty acid degradation (fad) genes. However, FadR is also an activator of the expression of fabA and fabB, two genes involved in unsaturated fatty acid synthesis. Therefore, FadR plays an important role in maintaining the balance between saturated and unsaturated fatty acids in the membrane. We recently showed that FadR also activates the promoter upstream of the fabH gene (L. My, B. Rekoske, J. J. Lemke, J. P. Viala, R. L. Gourse, and E. Bouveret, J Bacteriol 195:3784-3795, 2013, doi:10.1128/JB.00384-13). Furthermore, recent transcriptomic and proteomic data suggested that FadR activates the majority of fatty acid (FA) synthesis genes. In the present study, we tested the role of FadR in the expression of all genes involved in FA synthesis. We found that FadR activates the transcription of all tested FA synthesis genes, and we identified the FadR binding site for each of these genes. This necessitated the reassessment of the transcription start sites for accA and accB genes described previously, and we provide evidence for the presence of multiple promoters driving the expression of these genes. We showed further that regulation by FadR impacts the amount of FA synthesis enzymes in the cell. Our results show that FadR is a global regulator of FA metabolism in E. coli, acting both as a repressor of catabolism and an activator of anabolism, two directly opposing pathways.

IMPORTANCE

In most bacteria, a transcriptional regulator tunes the level of FA synthesis enzymes. Oddly, such a global regulator still was missing for E. coli, which nonetheless is one of the prominent model bacteria used for engineering biofuel production using the FA synthesis pathway. Our work identifies the FadR functional dual regulator as a global activator of almost all FA synthesis genes in E. coli. Because FadR also is the repressor of FA degradation, FadR acts both as a repressor and an activator of the two opposite pathways of FA degradation and synthesis. Our results show that there are still discoveries waiting to be made in the understanding of the genetic regulation of FA synthesis, even in the very well-known bacterium E. coli.

Multiple ways to regulate translation initiation in bacteria: Mechanisms, regulatory circuits, dynamics

To adapt their metabolism rapidly and constantly in response to environmental variations, bacteria often target the translation initiation process, during which the ribosome assembles on the mRNA. Here, we review different mechanisms of regulation mediated by cis-acting elements, sRNAs and proteins, showing, when possible, their intimate connection with the translational apparatus. Indeed the ribosome itself could play a direct role in several regulatory mechanisms. Different features of the regulatory signals (sequences, structures and their positions on the mRNA) are contributing to the large variety of regulatory mechanisms. Ribosome heterogeneity, variation of individual cells responses and the spatial and temporal organization of the translation process add more layers of complexity. This hampers to define manageable set of rules for bacterial translation initiation control.

Transhydrogenase promotes the robustness and evolvability of E. coli deficient in NADPH production

Metabolic networks revolve around few metabolites recognized by diverse enzymes and involved in myriad reactions. Though hub metabolites are considered as stepping stones to facilitate the evolutionary expansion of biochemical pathways, changes in their production or consumption often impair cellular physiology through their system-wide connections. How does metabolism endure perturbations brought immediately by pathway modification and restore hub homeostasis in the long run? To address this question we studied laboratory evolution of pathway-engineered Escherichia coli that underproduces the redox cofactor NADPH on glucose. Literature suggests multiple possibilities to restore NADPH homeostasis. Surprisingly, genetic dissection of isolates from our twelve evolved populations revealed merely two solutions: (1) modulating the expression of membrane-bound transhydrogenase (mTH) in every population; (2) simultaneously consuming glucose with acetate, an unfavored byproduct normally excreted during glucose catabolism, in two subpopulations. Notably, mTH displays broad phylogenetic distribution and has also played a predominant role in laboratory evolution of Methylobacterium extorquens deficient in NADPH production. Convergent evolution of two phylogenetically and metabolically distinct species suggests mTH as a conserved buffering mechanism that promotes the robustness and evolvability of metabolism. Moreover, adaptive diversification via evolving dual substrate consumption highlights the flexibility of physiological systems to exploit ecological opportunities.

CceR and AkgR regulate central carbon and energy metabolism in alphaproteobacteria

Many pathways of carbon and energy metabolism are conserved across the phylogeny, but the networks that regulate their expression or activity often vary considerably among organisms. In this work, we show that two previously uncharacterized transcription factors (TFs) are direct regulators of genes encoding enzymes of central carbon and energy metabolism in the alphaproteobacterium Rhodobacter sphaeroides. The LacI family member CceR (RSP_1663) directly represses genes encoding enzymes in the Entner-Doudoroff pathway, while activating those encoding the F1F0 ATPase and enzymes of the tricarboxylic acid (TCA) cycle and gluconeogenesis, providing a direct transcriptional network connection between carbon and energy metabolism. We identified bases that are important for CceR DNA binding and showed that DNA binding by this TF is inhibited by 6-phosphogluconate. We also showed that the GntR family TF AkgR (RSP_0981) directly activates genes encoding several TCA cycle enzymes, and we identified conditions where its activity is increased. The properties of single and double ΔCceR and ΔAkgR mutants illustrate that these 2 TFs cooperatively regulate carbon and energy metabolism. Comparative genomic analysis indicates that CceR and AkgR orthologs are found in other alphaproteobacteria, where they are predicted to have a conserved function in regulating central carbon metabolism. Our characterization of CceR and AkgR has provided important new insight into the networks that control central carbon and energy metabolism in alphaproteobacteria that can be exploited to modify or engineer new traits in these widespread and versatile bacteria.

IMPORTANCE

To extract and conserve energy from nutrients, cells coordinate a set of metabolic pathways into integrated networks. Many pathways that conserve energy or interconvert metabolites are conserved across cells, but the networks regulating these processes are often highly variable. In this study, we characterize two previously unknown transcriptional regulators of carbon and energy metabolism that are conserved in alphaproteobacteria, a group of abundant, environmentally and biotechnologically important organisms. We identify the genes they regulate, the DNA sequences they recognize, the metabolite that controls the activity of one of the regulators, and conditions where they are required for growth. We provide important new insight into conserved cellular networks that can also be used to improve a variety of hosts for converting feedstock into valuable products.

Galactose metabolic genes in yeast respond to a ratio of galactose and glucose

Natural environments are filled with multiple, often competing, signals. In contrast, biological systems are often studied in "well-controlled" environments where only a single input is varied, potentially missing important interactions between signals. Catabolite repression of galactose by glucose is one of the best-studied eukaryotic signal integration systems. In this system, it is believed that galactose metabolic (GAL) genes are induced only when glucose levels drop below a threshold. In contrast, we show that GAL gene induction occurs at a constant external galactose:glucose ratio across a wide range of sugar concentrations. We systematically perturbed the components of the canonical galactose/glucose signaling pathways and found that these components do not account for ratio sensing. Instead we provide evidence that ratio sensing occurs upstream of the canonical signaling pathway and results from the competitive binding of the two sugars to hexose transporters. We show that a mutant that behaves as the classical model expects (i.e., cannot use galactose above a glucose threshold) has a fitness disadvantage compared with wild type. A number of common biological signaling motifs can give rise to ratio sensing, typically through negative interactions between opposing signaling molecules. We therefore suspect that this previously unidentified nutrient sensing paradigm may be common and overlooked in biology.

Post-translational modifications as key regulators of bacterial metabolic fluxes

In order to survive and compete in natural settings, bacteria must excel at quickly adapting their metabolism to fluctuations in nutrient availability and other environmental variables. This necessitates fast-acting post-translational regulatory mechanisms, that is, allostery or covalent modification, to control metabolic flux. While allosteric regulation has long been a well-established strategy for regulating metabolic enzyme activity in bacteria, covalent post-translational modes of regulation, such as phosphorylation or acetylation, have previously been regarded as regulatory mechanisms employed primarily by eukaryotic organisms. Recent findings, however, have shifted this perception and point to a widespread role for covalent posttranslational modification in the regulation of metabolic enzymes and fluxes in bacteria. This review provides an outline of the exciting recent advances in this area.

Characterization of the pivotal carbon metabolism of Streptococcus suis serotype 2 under ex vivo and chemically defined in vitro conditions by isotopologue profiling

Streptococcus suis is a neglected zoonotic pathogen that has to adapt to the nutritional requirements in the different host niches encountered during infection and establishment of invasive diseases. To dissect the central metabolic activity of S. suis under different conditions of nutrient availability, we performed labeling experiments starting from [(13)C]glucose specimens and analyzed the resulting isotopologue patterns in amino acids of S. suis grown under in vitro and ex vivo conditions. In combination with classical growth experiments, we found that S. suis is auxotrophic for Arg, Gln/Glu, His, Leu, and Trp in chemically defined medium. De novo biosynthesis was shown for Ala, Asp, Ser, and Thr at high rates and for Gly, Lys, Phe, Tyr, and Val at moderate or low rates, respectively. Glucose degradation occurred mainly by glycolysis and to a minor extent by the pentose phosphate pathway. Furthermore, the exclusive formation of oxaloacetate by phosphoenolpyruvate (PEP) carboxylation became evident from the patterns in de novo synthesized amino acids. Labeling experiments with S. suis grown ex vivo in blood or cerebrospinal fluid reflected the metabolic adaptation to these host niches with different nutrient availability; however, similar key metabolic activities were identified under these conditions. This points at the robustness of the core metabolic pathways in S. suis during the infection process. The crucial role of PEP carboxylation for growth of S. suis in the host was supported by experiments with a PEP carboxylase-deficient mutant strain in blood and cerebrospinal fluid.

Computing the functional proteome: recent progress and future prospects for genome-scale models

Constraint-based models enable the computation of feasible, optimal, and realized biological phenotypes from reaction network reconstructions and constraints on their operation. To date, stoichiometric reconstructions have largely focused on metabolism, resulting in genome-scale metabolic models (M-Models). Recent expansions in network content to encompass proteome synthesis have resulted in models of metabolism and protein expression (ME-Models). ME-Models advance the predictions possible with constraint-based models from network flux states to the spatially resolved molecular composition of a cell. Specifically, ME-Models enable the prediction of transcriptome and proteome allocation and limitations, and basal expression states and regulatory needs. Continued expansion in reconstruction content and constraints will result in an increasingly refined representation of cellular composition and behavior.

Perturbation Experiments: Approaches for Metabolic Pathway Analysis in Bioreactors

In the last decades, targeted metabolic engineering of microbial cells has become one of the major tools in bioprocess design and optimization. For successful application, a detailed knowledge is necessary about the relevant metabolic pathways and their regulation inside the cells. Since in vitro experiments cannot display process conditions and behavior properly, process data about the cells' metabolic state have to be collected in vivo. For this purpose, special techniques and methods are necessary. Therefore, most techniques enabling in vivo characterization of metabolic pathways rely on perturbation experiments, which can be divided into dynamic and steady-state approaches. To avoid any process disturbance, approaches which enable perturbation of cell metabolism in parallel to the continuing production process are reasonable. Furthermore, the fast dynamics of microbial production processes amplifies the need of parallelized data generation. These points motivate the development of a parallelized approach for multiple metabolic perturbation experiments outside the operating production reactor. An appropriate approach for in vivo characterization of metabolic pathways is presented and applied exemplarily to a microbial L-phenylalanine production process on a 15 L-scale.

Hierarchy of non-glucose sugars in Escherichia coli

BACKGROUND

Understanding how cells make decisions, and why they make the decisions they make, is of fundamental interest in systems biology. To address this, we study the decisions made by E. coli on which genes to express when presented with two different sugars. It is well-known that glucose, E. coli's preferred carbon source, represses the uptake of other sugars by means of global and gene-specific mechanisms. However, less is known about the utilization of glucose-free sugar mixtures which are found in the natural environment of E. coli and in biotechnology.

RESULTS

Here, we combine experiment and theory to map the choices of E. coli among 6 different non-glucose carbon sources. We used robotic assays and fluorescence reporter strains to make precise measurements of promoter activity and growth rate in all pairs of these sugars. We find that the sugars can be ranked in a hierarchy: in a mixture of a higher and a lower sugar, the lower sugar system shows reduced promoter activity. The hierarchy corresponds to the growth rate supported by each sugar- the faster the growth rate, the higher the sugar on the hierarchy. The hierarchy is 'soft' in the sense that the lower sugar promoters are not completely repressed. Measurement of the activity of the master regulator CRP-cAMP shows that the hierarchy can be quantitatively explained based on differential activation of the promoters by CRP-cAMP. Comparing sugar system activation as a function of time in sugar pair mixtures at sub-saturating concentrations, we find cases of sequential activation, and also cases of simultaneous expression of both systems. Such simultaneous expression is not predicted by simple models of growth rate optimization, which predict only sequential activation. We extend these models by suggesting multi-objective optimization for both growing rapidly now and preparing the cell for future growth on the poorer sugar.

CONCLUSION

We find a defined hierarchy of sugar utilization, which can be quantitatively explained by differential activation by the master regulator cAMP-CRP. The present approach can be used to understand cell decisions when presented with mixtures of conditions.

Global analysis of photosynthesis transcriptional regulatory networks

Photosynthesis is a crucial biological process that depends on the interplay of many components. This work analyzed the gene targets for 4 transcription factors: FnrL, PrrA, CrpK and MppG (RSP_2888), which are known or predicted to control photosynthesis in Rhodobacter sphaeroides. Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) identified 52 operons under direct control of FnrL, illustrating its regulatory role in photosynthesis, iron homeostasis, nitrogen metabolism and regulation of sRNA synthesis. Using global gene expression analysis combined with ChIP-seq, we mapped the regulons of PrrA, CrpK and MppG. PrrA regulates ∼34 operons encoding mainly photosynthesis and electron transport functions, while CrpK, a previously uncharacterized Crp-family protein, regulates genes involved in photosynthesis and maintenance of iron homeostasis. Furthermore, CrpK and FnrL share similar DNA binding determinants, possibly explaining our observation of the ability of CrpK to partially compensate for the growth defects of a ΔFnrL mutant. We show that the Rrf2 family protein, MppG, plays an important role in photopigment biosynthesis, as part of an incoherent feed-forward loop with PrrA. Our results reveal a previously unrealized, high degree of combinatorial regulation of photosynthetic genes and significant cross-talk between their transcriptional regulators, while illustrating previously unidentified links between photosynthesis and the maintenance of iron homeostasis.

Photosynthetic organisms are among the most abundant life forms on earth. Their unique ability to harvest solar energy and use it to fix atmospheric carbon dioxide is at the foundation of the global food chain. This paper reports the first comprehensive analysis of networks that control expression of photosynthesis genes using Rhodobacter sphaeroides, a microbe that has been studied for decades as a model of solar energy capture and other aspects of the photosynthetic lifestyle. We find a previously unappreciated complexity in the level of control of photosynthetic genes, while identifying new links between photosynthesis and central processes like iron availability. This organism is an ancestor of modern day plants, so our data can inform studies in other photosynthetic organisms and improve our ability to harness solar energy for food and industrial processes.

Understanding carbon catabolite repression in Escherichia coli using quantitative models

Carbon catabolite repression (CCR) controls the order in which different carbon sources are metabolized. Although this system is one of the paradigms of the regulation of gene expression in bacteria, the underlying mechanisms remain controversial. CCR involves the coordination of different subsystems of the cell that are responsible for the uptake of carbon sources, their breakdown for the production of energy and precursors, and the conversion of the latter to biomass. The complexity of this integrated system, with regulatory mechanisms cutting across metabolism, gene expression, and signaling, and that are subject to global physical and physiological constraints, has motivated important modeling efforts over the past four decades, especially in the enterobacterium Escherichia coli. Different hypotheses concerning the dynamic functioning of the system have been explored by a variety of modeling approaches. We review these studies and summarize their contributions to the quantitative understanding of CCR, focusing on diauxic growth in E. coli. Moreover, we propose a highly simplified representation of diauxic growth that makes it possible to bring out the salient features of the models proposed in the literature and confront and compare the explanations they provide.

Computationally Modeling Lipid Metabolism and Aging: A Mini-review

One of the greatest challenges in biology is to improve the understanding of the mechanisms which underpin aging and how these affect health. The need to better understand aging is amplified by demographic changes, which have caused a gradual increase in the global population of older people. Aging western populations have resulted in a rise in the prevalence of age-related pathologies. Of these diseases, cardiovascular disease is the most common underlying condition in older people. The dysregulation of lipid metabolism due to aging impinges significantly on cardiovascular health. However, the multifaceted nature of lipid metabolism and the complexities of its interaction with aging make it challenging to understand by conventional means. To address this challenge computational modeling, a key component of the systems biology paradigm is being used to study the dynamics of lipid metabolism. This mini-review briefly outlines the key regulators of lipid metabolism, their dysregulation, and how computational modeling is being used to gain an increased insight into this system.

Metabolic sensor governing bacterial virulence in Staphylococcus aureus

An effective metabolism is essential to all living organisms, including the important human pathogen Staphylococcus aureus. To establish successful infection, S. aureus must scavenge nutrients and coordinate its metabolism for proliferation. Meanwhile, it also must produce an array of virulence factors to interfere with host defenses. However, the ways in which S. aureus ties its metabolic state to its virulence regulation remain largely unknown. Here we show that citrate, the first intermediate of the tricarboxylic acid (TCA) cycle, binds to and activates the catabolite control protein E (CcpE) of S. aureus. Using structural and site-directed mutagenesis studies, we demonstrate that two arginine residues (Arg145 and Arg256) within the putative inducer-binding cavity of CcpE are important for its allosteric activation by citrate. Microarray analysis reveals that CcpE tunes the expression of 126 genes that comprise about 4.7% of the S. aureus genome. Intriguingly, although CcpE is a major positive regulator of the TCA-cycle activity, its regulon consists predominantly of genes involved in the pathogenesis of S. aureus. Moreover, inactivation of CcpE results in increased staphyloxanthin production, improved ability to acquire iron, increased resistance to whole-blood-mediated killing, and enhanced bacterial virulence in a mouse model of systemic infection. This study reveals CcpE as an important metabolic sensor that allows S. aureus to sense and adjust its metabolic state and subsequently to coordinate the expression of virulence factors and bacterial virulence.

Multi-tasking of biosynthetic and energetic functions of glycolysis explained by supply and demand logic

After more than a century of research on glycolysis, we have detailed descriptions of its molecular organization, but despite this wealth of knowledge, linking the enzyme properties to metabolic pathway behavior remains challenging. These challenges arise from multi-layered regulation and the context and time dependence of component functions. However, when viewed as a system that functions according to the principles of supply and demand, a simplifying theoretical framework can be applied to study its regulation logic and to assess the coherence of experimental interpretations. These principles are universally applicable, as they emphasize the common metabolic tasks of glycolysis: the provision of free-energy carriers, and precursors for biosynthesis and stress-related compounds. Here we will review the regulation of multi-tasking by glycolysis and consider how an understanding of this central metabolic pathway can be pursued using general principles, rather than focusing on the biochemical details of constituent components.

Biological insights through nontargeted metabolomics

Metabolomics is increasingly employed to investigate metabolism and its reciprocal crosstalk with cellular signaling and regulation. In recent years, several nontargeted metabolomics methods providing substantial metabolome coverage have been developed. Here, we review and compare the contributions of traditional targeted and nontargeted metabolomics in advancing different research areas ranging from biotechnology to human health. Although some studies demonstrated the power of nontargeted profiling in generating unexpected and yet highly important insights, we found that most mechanistic links were still revealed by hypothesis-driven targeted methods. Novel computational approaches for formal interpretation of complex metabolic patterns and integration of complementary molecular layers are required to tap the full potential of nontargeted metabolomics for data-driven, discovery-oriented research and rapidly nucleating novel biological insights.

High-throughput discovery metabolomics

Non-targeted metabolomics by mass spectrometry has established as the method of choice for investigating metabolic phenotypes in basic and applied research. Compared to other omics, metabolomics provides broad scope and yet direct information on the integrated cellular response with low demand in material and sample preparation. These features render non-targeted metabolomics ideally suited for large scale screens and discovery. Here we review the achievements and potential in high-throughput, non-targeted metabolomics. We found that routine and precise analysis of thousands of small molecular features in thousands of complex samples per day and instrument is already reality, and ongoing developments in microfluidics and integrated interfaces will likely further boost throughput in the next few years.

Dependency of cellular decision making in physiology and influence of preceding growth conditions

Events from the past growth conditions influence the course of physiology, and it gets reflected in the present cell behaviour. During this process, cells acquire a metabolic option which carries signature of the past, and it dictates the performance in the present situation. Study uses Escherichia coli as a sample organism wherein three scenarios of preceding growth conditions were created with varying nutritional status and pre-treatment strategies. This exercise leads to different seed cultures, which were subjected to growth using the four different substrates. The different seed culture behaviours were analysed by observing the respirometric rate of the seed culture and were followed by growth dynamics with different substrates. These two data sets were independently analysed by three-way ANOVA to arrive at strategic coupling of programming conditions to relate the available (respirometric rates) and executable physiology (growth kinetics).

Metabolomics: a window into the adaptive physiology of Mycobacterium tuberculosis

Mycobacterium tuberculosis is the causative agent of tuberculosis (TB) and second leading cause of human mortality due to a single infectious agent. This is mostly because of M. tuberculosis' ability to adapt its metabolism to the host environment and regulate entry into and exit from cell cycle. Knowledge of the specific metabolic changes accompanying these transitions however is incomplete. Metabolomics has emerged as a new biochemical window into M. tuberculosis physiology. This review highlights recent insights from the application of such technologies to studies of the M. tuberculosis lifecycle.

Tuning transcription of nutrient utilization genes to catabolic rate promotes growth in a gut bacterium

Cells respond to nutrient availability by expressing nutrient catabolic genes. We report that the regulator controlling utilization of chondroitin sulphate (CS) in the mammalian gut symbiont Bacteroides thetaiotaomicron is activated by an intermediate in CS breakdown rather than CS itself. We determine that the rate-determining enzyme in CS breakdown is responsible for degrading this intermediate and establish that the levels of the enzyme increase 100-fold, whereas those of the regulator remain constant upon exposure to CS. Because enzyme and regulator compete for the intermediate, B. thetaiotaomicron tunes transcription of CS utilization genes to CS catabolic rate. This tuning results in a transient increase in CS utilization transcripts upon exposure to excess CS. Constitutive expression of the rate-determining enzyme hindered activation of CS utilization genes and growth on CS. An analogous mechanism regulates heparin utilization genes, suggesting that the identified strategy aids B. thetaiotaomicron in the competitive gut environment.