Understanding glucose transport by the bacterial phosphoenolpyruvate:glycose phosphotransferase system on the basis of kinetic measurements in vitro

Functional expansion of the natural inorganic phosphorus starvation response system in Escherichia coli

Phosphorus, an indispensable nutrient, plays an essential role in cell composition, metabolism, and signal transduction. When inorganic phosphorus (Pi) is scarce, the Pi starvation response in E. coli is activated to increase phosphorus acquisition and drive the cells into a non-growing state to reduce phosphorus consumption. In the six decades of research history, the initiation, output, and shutdown processes of the Pi starvation response have been extensively studied. Simultaneously, Pi starvation has been used in biosensor development, recombinant protein production, and natural product biosynthesis. In this review, we focus on the output process and the applications of the Pi starvation response that have not been summarized before. Meanwhile, based on the current status of mechanistic studies and applications, we propose practical strategies to develop the natural Pi starvation response into a multifunctional and standardized regulatory system in four aspects, including response threshold, temporal expression, intensity range, and bifunctional regulation, which will contribute to its broader application in more fields such as industrial production, medical analysis, and environmental protection.

Learning in Transcriptional Network Models: Computational Discovery of Pathway-Level Memory and Effective Interventions

Trainability, in any substrate, refers to the ability to change future behavior based on past experiences. An understanding of such capacity within biological cells and tissues would enable a particularly powerful set of methods for prediction and control of their behavior through specific patterns of stimuli. This top-down mode of control (as an alternative to bottom-up modification of hardware) has been extensively exploited by computer science and the behavioral sciences; in biology however, it is usually reserved for organism-level behavior in animals with brains, such as training animals towards a desired response. Exciting work in the field of basal cognition has begun to reveal degrees and forms of unconventional memory in non-neural tissues and even in subcellular biochemical dynamics. Here, we characterize biological gene regulatory circuit models and protein pathways and find them capable of several different kinds of memory. We extend prior results on learning in binary transcriptional networks to continuous models and identify specific interventions (regimes of stimulation, as opposed to network rewiring) that abolish undesirable network behavior such as drug pharmacoresistance and drug sensitization. We also explore the stability of created memories by assessing their long-term behavior and find that most memories do not decay over long time periods. Additionally, we find that the memory properties are quite robust to noise; surprisingly, in many cases noise actually increases memory potential. We examine various network properties associated with these behaviors and find that no one network property is indicative of memory. Random networks do not show similar memory behavior as models of biological processes, indicating that generic network dynamics are not solely responsible for trainability. Rational control of dynamic pathway function using stimuli derived from computational models opens the door to empirical studies of proto-cognitive capacities in unconventional embodiments and suggests numerous possible applications in biomedicine, where behavior shaping of pathway responses stand as a potential alternative to gene therapy.

Fundamental behaviors emerge from simulations of a living minimal cell

We present a whole-cell fully dynamical kinetic model (WCM) of JCVI-syn3A, a minimal cell with a reduced genome of 493 genes that has retained few regulatory proteins or small RNAs. Cryo-electron tomograms provide the cell geometry and ribosome distributions. Time-dependent behaviors of concentrations and reaction fluxes from stochastic-deterministic simulations over a cell cycle reveal how the cell balances demands of its metabolism, genetic information processes, and growth, and offer insight into the principles of life for this minimal cell. The energy economy of each process including active transport of amino acids, nucleosides, and ions is analyzed. WCM reveals how emergent imbalances lead to slowdowns in the rates of transcription and translation. Integration of experimental data is critical in building a kinetic model from which emerges a genome-wide distribution of mRNA half-lives, multiple DNA replication events that can be compared to qPCR results, and the experimentally observed doubling behavior.

Evolution of diversity in metabolic strategies

Understanding the origin and maintenance of biodiversity is a fundamental problem. Many theoretical approaches have been investigating ecological interactions, such as competition, as potential drivers of diversification. Classical consumer-resource models predict that the number of coexisting species should not exceed the number of distinct resources, a phenomenon known as the competitive exclusion principle. It has recently been argued that including physiological tradeoffs in consumer-resource models can lead to violations of this principle and to ecological coexistence of very high numbers of species. Here, we show that these results crucially depend on the functional form of the tradeoff. We investigate the evolutionary dynamics of resource use constrained by tradeoffs and show that if the tradeoffs are non-linear, the system either does not diversify or diversifies into a number of coexisting species that do not exceed the number of resources. In particular, very high diversity can only be observed for linear tradeoffs.

The mannose phosphotransferase system (Man-PTS) - Mannose transporter and receptor for bacteriocins and bacteriophages

Mannose transporters constitute a superfamily (Man-PTS) of the Phosphoenolpyruvate Carbohydrate Phosphotransferase System (PTS). The membrane complexes are homotrimers of protomers consisting of two subunits, IIC and IID. The two subunits without recognizable sequence similarity assume the same fold, and in the protomer are structurally related by a two fold pseudosymmetry axis parallel to membrane-plane (Liu et al. (2019) Cell Research 29 680). Two reentrant loops and two transmembrane helices of each subunit together form the N-terminal transport domain. Two three-helix bundles, one of each subunit, form the scaffold domain. The protomer is stabilized by a helix swap between these bundles. The two C-terminal helices of IIC mediate the interprotomer contacts. PTS occur in bacteria and archaea but not in eukaryotes. Man-PTS are abundant in Gram-positive bacteria living on carbohydrate rich mucosal surfaces. A subgroup of IICIID complexes serve as receptors for class IIa bacteriocins and as channel for the penetration of bacteriophage lambda DNA across the inner membrane. Some Man-PTS are associated with host-pathogen and -symbiont processes.

Self-replenishment cycles generate a threshold response

Many metabolic cycles, including the tricarboxylic acid cycle, glyoxylate cycle, Calvin cycle, urea cycle, coenzyme recycling, and substrate cycles, are well known to catabolize and anabolize different metabolites for efficient energy and mass conversion. In terms of stoichiometric structure, this study explicitly identifies two types of metabolic cycles. One is the well-known, elementary cycle that converts multiple substrates into different products and recycles one of the products as a substrate, where the recycled substrate is supplied from the outside to run the cycle. The other is the self-replenishment cycle that merges multiple substrates into two or multiple identical products and reuses one of the products as a substrate. The substrates are autonomously supplied within the cycle. This study first defines the self-replenishment cycles that many scientists have overlooked despite its functional importance. Theoretical analysis has revealed the design principle of the self-replenishment cycle that presents a threshold response without any bistability nor cooperativity. To verify the principle, three detailed kinetic models of self-replenishment cycles embedded in an E. coli metabolic system were simulated. They presented the threshold response or digital switch-like function that steeply shift metabolic status.

Carbohydrate Transport by Group Translocation: The Bacterial Phosphoenolpyruvate: Sugar Phosphotransferase System

The Bacterial Phosphoenolpyruvate (PEP) : Sugar Phosphotransferase System (PTS) mediates the uptake and phosphorylation of carbohydrates, and controls the carbon- and nitrogen metabolism in response to the availability of sugars. PTS occur in eubacteria and in a few archaebacteria but not in animals and plants. All PTS comprise two cytoplasmic phosphotransferase proteins (EI and HPr) and a species-dependent, variable number of sugar-specific enzyme II complexes (IIA, IIB, IIC, IID). EI and HPr transfer phosphorylgroups from PEP to the IIA units. Cytoplasmic IIA and IIB units sequentially transfer phosphates to the sugar, which is transported by the IIC and IICIID integral membrane protein complexes. Phosphorylation by IIB and translocation by IIC(IID) are tightly coupled. The IIC(IID) sugar transporters of the PTS are in the focus of this review. There are four structurally different PTS transporter superfamilies (glucose, glucitol, ascorbate, mannose) . Crystal structures are available for transporters of two superfamilies: bcIIC^mal (MalT, 5IWS, 6BVG) and bcIIC^chb (ChbC, 3QNQ) of B. subtilis from the glucose family, and IIC^asc (UlaA, 4RP9, 5ZOV) of E. coli from the ascorbate superfamily . They are homodimers and each protomer has an independent transport pathway which functions by an elevator-type alternating-access mechanism. bcIIC^mal and bcIIC^chb have the same fold, IIC^asc has a completely different fold. Biochemical and biophysical data accumulated in the past with the transporters for mannitol (IICBA^mtl) and glucose (IICB^glc) are reviewed and discussed in the context of the bcIIC^mal crystal structures. The transporters of the mannose superfamily are dimers of protomers consisting of a IIC and a IID protein chain. The crystal structure is not known and the topology difficult to predict. Biochemical data indicate that the IICIID complex employs a different transport mechanism . Species specific IICIID serve as a gateway for the penetration of bacteriophage lambda DNA across, and insertion of class IIa bacteriocins into the inner membrane. PTS transporters are inserted into the membrane by SecYEG translocon and have specific lipid requirements. Immunoelectron- and fluorescence microscopy indicate a non-random distribution and supramolecular complexes of PTS proteins.

Evidence of link between quorum sensing and sugar metabolism in Escherichia coli revealed via cocrystal structures of LsrK and HPr

Quorum sensing (QS), a bacterial process that regulates population-scale behavior, is mediated by small signaling molecules, called autoinducers (AIs), that are secreted and perceived, modulating a "collective" phenotype. Because the autoinducer AI-2 is secreted by a wide variety of bacterial species, its "perception" cues bacterial behavior. This response is mediated by the lsr (LuxS-regulated) operon that includes the AI-2 transporter LsrACDB and the kinase LsrK. We report that HPr, a phosphocarrier protein central to the sugar phosphotransferase system of Escherichia coli, copurifies with LsrK. Cocrystal structures of an LsrK/HPr complex were determined, and the effects of HPr and phosphorylated HPr on LsrK activity were assessed. LsrK activity is inhibited when bound to HPr, revealing new linkages between QS activity and sugar metabolism. These findings help shed new light on the abilities of bacteria to rapidly respond to changing nutrient levels at the population scale. They also suggest new means of manipulating QS activity among bacteria and within various niches.

Metabolic regulation is sufficient for global and robust coordination of glucose uptake, catabolism, energy production and growth in Escherichia coli

The metabolism of microorganisms is regulated through two main mechanisms: changes of enzyme capacities as a consequence of gene expression modulation (“hierarchical control”) and changes of enzyme activities through metabolite-enzyme interactions. An increasing body of evidence indicates that hierarchical control is insufficient to explain metabolic behaviors, but the system-wide impact of metabolic regulation remains largely uncharacterized. To clarify its role, we developed and validated a detailed kinetic model of Escherichia coli central metabolism that links growth to environment. Metabolic control analyses confirm that the control is widely distributed across the network and highlight strong interconnections between all the pathways. Exploration of the model solution space reveals that several robust properties emerge from metabolic regulation, from the molecular level (e.g. homeostasis of total metabolite pool) to the overall cellular physiology (e.g. coordination of carbon uptake, catabolism, energy and redox production, and growth), while allowing a large degree of flexibility at most individual metabolic steps. These properties have important physiological implications for E. coli and significantly expand the self-regulating capacities of its metabolism.

Metabolism is a fundamental biochemical process that enables cells to operate and grow by converting nutrients into ‘building blocks’ and energy. Metabolism happens through the work of enzymes, which are encoded by genes. Thus, genes and their regulation are often thought of controlling metabolism, somewhat at the top of a hierarchical control system. However, an increasing body of evidence indicates that metabolism plays an active role in the control of its own operation via a dense network of metabolite-enzyme interactions. The system-wide role of metabolic regulation is hard to dissect and so far remains largely uncharacterized. To better understand its role, we constructed a detailed kinetic model of the carbon and energy metabolism of the bacterium Escherichia coli, a model organism in Systems and Synthetic biology. Model simulations indicate that kinetic considerations of metabolism alone can explain data from hundreds of experiments, without needing to invoke regulation of gene expression. In particular, metabolic regulation is sufficient to coordinate carbon utilization, redox and energy production, and growth, while maintaining local flexibility at individual metabolic steps. These findings indicate that the self-regulating capacities of E. coli metabolism are far more significant than previously expected, and improve our understanding on how cells work.

Biophysical characterization of the domain association between cytosolic A and B domains of the mannitol transporter enzymes II(Mtl) in the presence and absence of a connecting linker

The mannitol transporter enzyme II(Mtl) of the bacterial phosphotransferase system is a multi-domain protein that catalyzes mannitol uptake and phosphorylation. Here we investigated the domain association between cytosolic A and B domains of enzyme II(Mtl) , which are natively connected in Escherichia coli, but separated in Thermoanaerobacter tengcongensis. NMR backbone assignment and residual dipolar couplings indicated that backbone folds were well conserved between the homologous domains. The equilibrium binding of separately expressed domains, however, exhibited ∼28-fold higher affinity compared to the natively linked ones. Phosphorylation of the active site loop significantly contributed to the binding by reducing conformational dynamics at the binding interface, and a few key mutations at the interface were critical to further stabilize the complex by hydrogen bonding and hydrophobic interactions. The affinity increase implicated that domain associations in cell could be maintained at an optimal level regardless of the linker.

Sugar Influx Sensing by the Phosphotransferase System of Escherichia coli

The phosphotransferase system (PTS) plays a pivotal role in the uptake of multiple sugars in Escherichia coli and many other bacteria. In the cell, individual sugar-specific PTS branches are interconnected through a series of phosphotransfer reactions, thus creating a global network that not only phosphorylates incoming sugars but also regulates a number of cellular processes. Despite the apparent importance of the PTS network in bacterial physiology, the holistic function of the network in the cell remains unclear. Here we used Förster resonance energy transfer (FRET) to investigate the PTS network in E. coli, including the dynamics of protein interactions and the processing of different stimuli and their transmission to the chemotaxis pathway. Our results demonstrate that despite the seeming complexity of the cellular PTS network, its core part operates in a strikingly simple way, sensing the overall influx of PTS sugars irrespective of the sugar identity and distributing this information equally through all studied branches of the network. Moreover, it also integrates several other specific metabolic inputs. The integrated output of the PTS network is then transmitted linearly to the chemotaxis pathway, in stark contrast to the amplification of conventional chemotactic stimuli. Finally, we observe that default uptake through the uninduced PTS network correlates well with the quality of the carbon source, apparently representing an optimal regulatory strategy.

The bacterial phosphotransferase system (PTS) mediates uptake of multiple sugars from the environment and also controls cell physiology and swimming behavior in sugar gradients. In Escherichia coli and other bacteria, the PTS consists of a number of sugar-specific branches, interconnected via shared components through a series of phosphotransfer reactions. Whereas most previous studies have focused on understanding individual PTS branches, the holistic function of the entire PTS network in the cell remained elusive. In this study we address this question by investigating the dynamics of multiple protein interactions within the cellular PTS network upon stimulation with sugars and other metabolites. We demonstrate that despite its seeming complexity, the core part of the PTS network operates in a strikingly simple way, sensing the overall influx of PTS sugars and key metabolites into the cell and utilizing this information to control bacterial behavior. We further show that the default influx of the carbon source correlates with its quality, and we use computer simulations to demonstrate that this correlation apparently represents an optimal regulatory strategy.

Single-cell characterization of metabolic switching in the sugar phosphotransferase system of Escherichia coli

The utilization of several sugars in Escherichia coli is regulated by the Phosphotransferase System (PTS), in which diverse sugar utilization modules compete for phosphoryl flux from the general PTS proteins. Existing theoretical work predicts a winner-take-all outcome when this flux limits carbon uptake. To date, no experimental work has interrogated competing PTS uptake modules with single-cell resolution. Using time-lapse microscopy in perfused microchannels, we analyzed the competition between N-acetyl-glucosamine and sorbitol, as representative PTS sugars, by measuring both the expression of their utilization systems and the concomitant impact of sugar utilization on growth rates. We find two distinct regimes: hierarchical usage of the carbohydrates, and co-expression of the genes for both systems. Simulations of a mathematical model incorporating asymmetric sugar quality reproduce our metabolic phase diagram, indicating that under conditions of nonlimiting phosphate flux, co-expression is due to uncoupling of both sugar utilization systems. Our model reproduces hierarchical winner-take-all behaviour and stochastic co-expression, and predicts the switching between both strategies as a function of available phosphate flux. Hence, experiments and theory both suggest that PTS sugar utilization involves not only switching between the sugars utilized but also switching of utilization strategies to accommodate prevailing environmental conditions.

Histidine phosphocarrier protein regulates pyruvate kinase A activity in response to glucose in Vibrio vulnificus

The bacterial phosphoenolpyruvate:sugar phosphotransferase system (PTS) consists of two general energy-coupling proteins [enzyme I and histidine phosphocarrier protein (HPr)] and several sugar-specific enzyme IIs. Although, in addition to the phosphorylation-coupled transport of sugars, various regulatory roles of PTS components have been identified in Escherichia coli, much less is known about the PTS in the opportunistic human pathogen Vibrio vulnificus. In this study, we have identified pyruvate kinase A (PykA) as a binding partner of HPr in V. vulnificus. The interaction between HPr and PykA was strictly dependent on the presence of inorganic phosphate, and only dephosphorylated HPr interacted with PykA. Experiments involving domain swapping between the PykAs of V. vulnificus and E. coli revealed the requirement for the C-terminal domain of V. vulnificus PykA for a specific interaction with V. vulnificus HPr. Dephosphorylated HPr decreased the Km of PykA for phosphoenolpyruvate by approximately fourfold without affecting Vmax . Taken together, these findings indicate that the V. vulnificus PTS catalyzing the first step of glycolysis stimulates the final step of glycolysis in the presence of glucose through the direct interaction of dephospho-HPr with the C-terminal domain of PykA.

Spatial localization of the first and last enzymes effectively connects active metabolic pathways in bacteria

Background

Although much is understood about the enzymatic cascades that underlie cellular biosynthesis, comparatively little is known about the rules that determine their cellular organization. We performed a detailed analysis of the localization of E.coli GFP-tagged enzymes for cells growing exponentially.

Results

We found that out of 857 globular enzymes, at least 219 have a discrete punctuate localization in the cytoplasm and catalyze the first or the last reaction in 60% of biosynthetic pathways. A graph-theoretic analysis of E.coli’s metabolic network shows that localized enzymes, in contrast to non-localized ones, form a tree-like hierarchical structure, have a higher within-group connectivity, and are traversed by a higher number of feed-forward and feedback loops than their non-localized counterparts. A Gene Ontology analysis of these enzymes reveals an enrichment of terms related to essential metabolic functions in growing cells. Given that these findings suggest a distinct metabolic role for localization, we studied the dynamics of cellular localization of the cell wall synthesizing enzymes in B. subtilis and found that enzymes localize during exponential growth but not during stationary growth.

Conclusions

We conclude that active biochemical pathways inside the cytoplasm are organized spatially following a rule where their first or their last enzymes localize to effectively connect the different active pathways and thus could reflect the activity state of the cell’s metabolic network.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-014-0131-1) contains supplementary material, which is available to authorized users.

Identification of key regulators in glycogen utilization in E. coli based on the simulations from a hybrid functional Petri net model

BACKGROUND

Glycogen and glucose are two sugar sources available during the lag phase of E. coli, but the mechanism that regulates their utilization is still unclear.

METHODS

Attempting to unveil the relationship between glucose and glycogen, we propose an integrated hybrid functional Petri net (HFPN) model including glycolysis, PTS, glycogen metabolic pathway, and their internal regulatory systems.

RESULTS AND CONCLUSIONS

By comparing known biological results to this model, basic necessary regulatory mechanism for utilizing glucose and glycogen were identified as a feedback circuit in which HPr and EIIAGlc play key roles. Based on this regulatory HFPN model, we discuss the process of glycogen utilization in E. coli in the context of a systematic understanding of carbohydrate metabolism.

HPr antagonizes the anti-σ70 activity of Rsd in Escherichia coli

The bacterial phosphoenolpyruvate:sugar phosphotransferase system (PTS) is a multicomponent system that participates in a variety of physiological processes in addition to the phosphorylation-coupled transport of numerous sugars. In Escherichia coli and other enteric bacteria, enzyme IIA(Glc) (EIIA(Glc)) is known as the central processing unit of carbon metabolism and plays multiple roles, including regulation of adenylyl cyclase, the fermentation/respiration switch protein FrsA, glycerol kinase, and several non-PTS transporters, whereas the only known regulatory role of the E. coli histidine-containing phosphocarrier protein HPr is in the activation of glycogen phosphorylase. Because HPr is known to be more abundant than EIIA(Glc) in enteric bacteria, we assumed that there might be more regulatory mechanisms connected with HPr. The ligand fishing experiment in this study identified Rsd, an anti-sigma factor known to complex with σ(70) in stationary-phase cells, as an HPr-binding protein in E. coli. Only the dephosphorylated form of HPr formed a tight complex with Rsd and thereby inhibited complex formation between Rsd and σ(70). Dephosphorylated HPr, but not phosphorylated HPr, antagonized the inhibitory effect of Rsd on σ(70)-dependent transcriptions both in vivo and in vitro, and also influenced the competition between σ(70) and σ(S) for core RNA polymerase in the presence of Rsd. Based on these data, we propose that the anti-σ(70) activity of Rsd is regulated by the phosphorylation state-dependent interaction of HPr with Rsd.

Clusters of reaction rates and concentrations in protein networks such as the phosphotransferase system

To understand the functioning of living cells, it is often helpful or even necessary to exploit inherent timescale disparities and focus on long-term dynamic behaviour. In the present study, we explore this type of behaviour for the biochemical network of the phosphotransferase system. We show that, during the slow phase that follows a fast initial transient, the network reaction rates are partitioned into clusters corresponding to connected parts of the reaction network. Rates within any of these clusters assume essentially the same value: differences within each cluster are vastly smaller than that from one cluster to another. This rate clustering induces an analogous clustering of the reactive compounds: only the molecular concentrations on the interface between these clusters are produced and consumed at substantially different rates and hence change considerably during the slow phase. The remaining concentrations essentially assume their steady-state values already by the end of the transient phase. Further, we find that this clustering phenomenon occurs for a large number of parameter values and also for models with different topologies; to each of these models, there corresponds a particular network partitioning. Our results show that, in spite of its complexity, the phosphotransferase system tends to behave in a rather simple (yet versatile) way. The persistence of clustering for the perturbed models we examined suggests that it is likely to be encountered in various environmental conditions, as well as in other signal transduction pathways with network structures similar to that of the phosphotransferase system.

Structure, dynamics and biophysics of the cytoplasmic protein-protein complexes of the bacterial phosphoenolpyruvate: sugar phosphotransferase system

The bacterial phosphotransferase system (PTS) couples phosphoryl transfer, via a series of bimolecular protein-protein interactions, to sugar transport across the membrane. The multitude of complexes in the PTS provides a paradigm for studying protein interactions, and for understanding how the same binding surface can specifically recognize a diverse array of targets. Fifteen years of work aimed at solving the solution structures of all soluble protein-protein complexes of the PTS has served as a test bed for developing NMR and integrated hybrid approaches to study larger complexes in solution and to probe transient, spectroscopically invisible states, including encounter complexes. We review these approaches, highlighting the problems that can be tackled with these methods, and summarize the current findings on protein interactions.

Structural basis for enzyme I inhibition by α-ketoglutarate

Creating new bacterial strains in which carbon and nitrogen metabolism are uncoupled is potentially very useful for optimizing yields of microbial produced chemicals from renewable carbon sources. However, the mechanisms that balance carbon and nitrogen consumption in bacteria are poorly understood. Recently, α-ketoglutarate (αKG), the carbon substrate for ammonia assimilation, has been observed to inhibit Escherichia coli enzyme I (EI), the first component of the bacterial phosphotransferase system (PTS), thereby providing a direct biochemical link between central carbon and nitrogen metabolism. Here we investigate the EI-αKG interaction by NMR and enzymatic assays. We show that αKG binds with a KD of ∼2.2 mM at the active site of EI, acting as a competitive inhibitor. In addition, we use molecular docking simulations to derive a structural model of the enzyme-inhibitor complex that is fully consistent with NMR and analytical ultracentrifugation data. We expect that the EI-αKG structure presented here will provide a starting point for structure-based design of EI mutants resistant to αKG.

Analysis and Design of Stimulus Response Curves of E. coli

Metabolism and signalling are tightly coupled in bacteria. Combining several theoretical approaches, a core model is presented that describes transcriptional and allosteric control of glycolysis in Escherichia coli. Experimental data based on microarrays, signaling components and extracellular metabolites are used to estimate kinetic parameters. A newly designed strain was used that adjusts the incoming glucose flux into the system and allows a kinetic analysis. Based on the results, prediction for intracelluar metabolite concentrations over a broad range of the growth rate could be performed and compared with data from literature.

Understanding complexity in neurodegenerative diseases: in silico reconstruction of emergence

Healthy functioning is an emergent property of the network of interacting biomolecules that comprise an organism. It follows that disease (a network shift that causes malfunction) is also an emergent property, emerging from a perturbation of the network. On the one hand, the biomolecular network of every individual is unique and this is evident when similar disease-producing agents cause different individual pathologies. Consequently, a personalized model and approach for every patient may be required for therapies to become effective across mankind. On the other hand, diverse combinations of internal and external perturbation factors may cause a similar shift in network functioning. We offer this as an explanation for the multi-factorial nature of most diseases: they are "systems biology diseases," or "network diseases." Here we use neurodegenerative diseases, like Parkinson's disease (PD), as an example to show that due to the inherent complexity of these networks, it is difficult to understand multi-factorial diseases with simply our "naked brain." When describing interactions between biomolecules through mathematical equations and integrating those equations into a mathematical model, we try to reconstruct the emergent properties of the system in silico. The reconstruction of emergence from interactions between huge numbers of macromolecules is one of the aims of systems biology. Systems biology approaches enable us to break through the limitation of the human brain to perceive the extraordinarily large number of interactions, but this also means that we delegate the understanding of reality to the computer. We no longer recognize all those essences in the system's design crucial for important physiological behavior (the so-called "design principles" of the system). In this paper we review evidence that by using more abstract approaches and by experimenting in silico, one may still be able to discover and understand the design principles that govern behavioral emergence.

Conformational selection and substrate binding regulate the monomer/dimer equilibrium of the C-terminal domain of Escherichia coli enzyme I

The bacterial phosphotransferase system (PTS) is a signal transduction pathway that couples phosphoryl transfer to active sugar transport across the cell membrane. The PTS is initiated by the binding of phosphoenolpyruvate (PEP) to the C-terminal domain (EIC) of enzyme I (EI), a highly conserved protein that is common to all sugar branches of the PTS. EIC exists in a dynamic monomer/dimer equilibrium that is modulated by ligand binding and is thought to regulate the overall PTS. Isolation of EIC has proven challenging, and conformational dynamics within the EIC domain during the catalytic cycle are still largely unknown. Here, we present a robust protocol for expression and purification of recombinant EIC from Escherichia coli and show that isolated EIC is capable of hydrolyzing PEP. NMR analysis and residual dipolar coupling measurements indicate that the isolated EIC domain in solution adopts a stable tertiary fold and quaternary structure that is consistent with previously reported crystallographic data. NMR relaxation dispersion measurements indicate that residues around the PEP binding site and in the β3α3 turn (residues 333-366), which is located at the dimer interface, undergo a rapid transition on the sub-millisecond time scale (with an exchange rate constant of ∼1500 s(-1)) between major open (∼97%) and minor closed (∼3%) conformations. Upon PEP binding, the β3α3 turn is effectively locked in the closed state by the formation of salt bridges between the phosphate group of PEP and the side chains of Lys(340) and Arg(358), thereby stabilizing the dimer.

α-Ketoglutarate coordinates carbon and nitrogen utilization via enzyme I inhibition

Microbes survive in a variety of nutrient environments by modulating their intracellular metabolism. Balanced growth requires coordinated uptake of carbon and nitrogen, the primary substrates for biomass production. The mechanisms that balance carbon and nitrogen uptake are, however, poorly understood. We find in Escherichia coli that a sudden increase in nitrogen availability results in an almost immediate increase in glucose uptake. The concentrations of known glycolytic intermediates and regulators, however, remain homeostatic. Instead, we find that α-ketoglutarate, which accumulates in nitrogen limitation, directly blocks glucose uptake by inhibiting Enzyme I, the first step of the phosphotransferase system (PTS). This enables rapid modulation of glycolytic flux without marked concentration changes in glycolytic intermediates by simultaneously accelerating glucose import and consumption of the terminal glycolytic intermediate phosphoenolpyruvate. Quantitative modeling shows that this previously unidentified regulatory connection is in principle sufficient to coordinate carbon and nitrogen utilization.

EI of the Phosphotransferase System of Escherichia coli: Mathematical Modeling Approach to Analysis of Its Kinetic Properties

The mathematical model of the operation of the first enzyme of the Escherichia coli phosphotransferase system, EI, is proposed. Parameters of the kinetic model describing the operation of EI under different conditions are identified on the basis of a large amount of known experimental data. The verified model is employed to predict modes of operation of EI under both in vivo physiological conditions and in vitro nonphysiological conditions. The model predicts that under in vivo physiological conditions, the rate of phosphotransfer from EI to the second protein of the phosphotransferase system HPr by the dimer is much higher than by the monomer. A hypothesis is proposed on the basis of calculations that the transfer by a monomer plays a role in the regulation of chemotaxis. At submicromolar pyruvate concentration, the model predicts nonmonotonic dependence of the phosphotransfer rate on the substrate (PEP) concentration.

Model reduction using piecewise-linear approximations preserves dynamic properties of the carbon starvation response in Escherichia coli

The adaptation of the bacterium Escherichia coli to carbon starvation is controlled by a large network of biochemical reactions involving genes, mRNAs, proteins, and signalling molecules. The dynamics of these networks is difficult to analyze, notably due to a lack of quantitative information on parameter values. To overcome these limitations, model reduction approaches based on quasi-steady-state (QSS) and piecewise-linear (PL) approximations have been proposed, resulting in models that are easier to handle mathematically and computationally. These approximations are not supposed to affect the capability of the model to account for essential dynamical properties of the system, but the validity of this assumption has not been systematically tested. In this paper, we carry out such a study by evaluating a large and complex PL model of the carbon starvation response in E. coli using an ensemble approach. The results show that, in comparison with conventional nonlinear models, the PL approximations generally preserve the dynamics of the carbon starvation response network, although with some deviations concerning notably the quantitative precision of the model predictions. This encourages the application of PL models to the qualitative analysis of bacterial regulatory networks, in situations where the reference time scale is that of protein synthesis and degradation.

Solution structure of the 128 kDa enzyme I dimer from Escherichia coli and its 146 kDa complex with HPr using residual dipolar couplings and small- and wide-angle X-ray scattering

The solution structures of free Enzyme I (EI, ∼128 kDa, 575 × 2 residues), the first enzyme in the bacterial phosphotransferase system, and its complex with HPr (∼146 kDa) have been solved using novel methodology that makes use of prior structural knowledge (namely, the structures of the dimeric EIC domain and the isolated EIN domain both free and complexed to HPr), combined with residual dipolar coupling (RDC), small- (SAXS) and wide- (WAXS) angle X-ray scattering and small-angle neutron scattering (SANS) data. The calculational strategy employs conjoined rigid body/torsion/Cartesian simulated annealing, and incorporates improvements in calculating and refining against SAXS/WAXS data that take into account complex molecular shapes in the description of the solvent layer resulting in a better representation of the SAXS/WAXS data. The RDC data orient the symmetrically related EIN domains relative to the C(2) symmetry axis of the EIC dimer, while translational, shape, and size information is provided by SAXS/WAXS. The resulting structures are independently validated by SANS. Comparison of the structures of the free EI and the EI-HPr complex with that of the crystal structure of a trapped phosphorylated EI intermediate reveals large (∼70-90°) hinge body rotations of the two subdomains comprising the EIN domain, as well as of the EIN domain relative to the dimeric EIC domain. These large-scale interdomain motions shed light on the structural transitions that accompany the catalytic cycle of EI.

Mechanistic details of a protein-protein association pathway revealed by paramagnetic relaxation enhancement titration measurements

Protein-protein association generally proceeds via the intermediary of a transient, lowly populated, encounter complex ensemble. The mechanism whereby the interacting molecules in this ensemble locate their final stereospecific structure is poorly understood. Further, a fundamental question is whether the encounter complex ensemble is an effectively homogeneous population of nonspecific complexes or whether it comprises a set of distinct structural and thermodynamic states. Here we use intermolecular paramagnetic relaxation enhancement (PRE), a technique that is exquisitely sensitive to lowly populated states in the fast exchange regime, to characterize the mechanistic details of the transient encounter complex interactions between the N-terminal domain of Enzyme I (EIN) and the histidine-containing phosphocarrier protein (HPr), two major bacterial signaling proteins. Experiments were conducted at an ionic strength of 150 mM NaCl to eliminate any spurious nonspecific associations not relevant under physiological conditions. By monitoring the dependence of the intermolecular transverse PRE (Gamma(2)) rates measured on (15)N-labeled EIN on the concentration of paramagnetically labeled HPr, two distinct types of encounter complex configurations along the association pathway are identified and dissected. The first class, which is in equilibrium with and sterically occluded by the specific complex, probably involves rigid body rotations and small translations near or at the active site. In contrast, the second class of encounter complex configurations can coexist with the specific complex to form a ternary complex ensemble, which may help EIN compete with other HPr binding partners in vivo by increasing the effective local concentration of HPr even when the active site of EIN is occupied.

Elementary network reconstruction: a framework for the analysis of regulatory networks in biological systems

Complexity of regulatory networks arises from the high degree of interaction between network components such as DNA, RNA, proteins, and metabolites. We have developed a modeling tool, elementary network reconstruction (ENR), to characterize these networks. ENR is a knowledge-driven, steady state, deterministic, quantitative modeling approach based on linear perturbation theory. In ENR we demonstrate a novel means of expressing control mechanisms by way of dimensionless steady state gains relating input and output variables, which are purely in terms of species abundances (extensive variables). As a result of systematic enumeration of network species in nxn matrix, the two properties of linear perturbation are manifested in graphical representations: transitive property is evident in a special L-shape structure, and additive property is evident in multiple L-shape structures arriving at the same matrix cell. Upon imposing mechanistic (lowest-level) gains, network self-assembly through transitive and additive properties results in elucidation of inherent topology and explicit cataloging of higher level gains, which in turn can be used to predict perturbation results. Application of ENR to the regulatory network behind carbon catabolite repression in Escherichia coli is presented. Through incorporation of known molecular mechanisms governing transient and permanent repressions, the ENR model correctly predicts several key features of this regulatory network, including a 50% downshift in intracellular cAMP level upon exposure to glucose. Since functional genomics studies are mainly concerned with redistribution of species abundances in perturbed systems, ENR could be exploited in the system-level analysis of biological systems.

In silico strategy to rationally engineer metabolite production: A case study for threonine in Escherichia coli

Genetic engineering of metabolic pathways is a standard strategy to increase the production of metabolites of economic interest. However, such flux increases could very likely lead to undesirable changes in metabolite concentrations, producing deleterious perturbations on other cellular processes. These negative effects could be avoided by implementing a balanced increase of enzyme concentrations according to the Universal Method [Kacser and Acerenza (1993) Eur J Biochem 216:361-367]. Exact application of the method usually requires modification of many reactions, which is difficult to achieve in practice. Here, improvement of threonine production via pyruvate kinase deletion in Escherichia coli is used as a case study to demonstrate a partial application of the Universal Method, which includes performing sensitivity analysis. Our analysis predicts that manipulating a few reactions is sufficient to obtain an important increase in threonine production without major perturbations of metabolite concentrations.

Control of specific growth rate in Saccharomyces cerevisiae

In this contribution we resolve the long-standing dispute whether or not the Monod constant (K(S)), describing the overall affinity of an organism for its growth-limiting substrate, can be related to the affinity of the transporter for that substrate (K(M)). We show how this can be done via the control of the transporter on the specific growth rate; they are identical if the transport step has full control. The analysis leads to the counter-intuitive result that the affinity of an organism for its substrate is expected to be higher than the affinity of the enzyme that facilitates its transport. Experimentally, we show this indeed to be the case for the yeast Saccharomyces cerevisiae, for which we determined a K(M) value for glucose more than two times higher than the K(S) value in glucose-limited chemostat cultures. Moreover, we calculated that at glucose concentrations of 0.03 and 0.29 mM, the transport step controls the specific growth rate at 78 and 49 %, respectively.

Impact of phosphorylation on structure and thermodynamics of the interaction between the N-terminal domain of enzyme I and the histidine phosphocarrier protein of the bacterial phosphotransferase system

The structural and thermodynamic impact of phosphorylation on the interaction of the N-terminal domain of enzyme I (EIN) and the histidine phosphocarrier protein (HPr), the two common components of all branches of the bacterial phosphotransferase system, have been examined using NMR spectroscopy and isothermal titration calorimetry. His-189 is located at the interface of the alpha and alphabeta domains of EIN, resulting in rather widespread chemical shift perturbation upon phosphorylation, in contrast to the highly localized perturbations seen for HPr, where His-15 is fully exposed to solvent. Residual dipolar coupling measurements, however, demonstrate unambiguously that no significant changes in backbone conformation of either protein occur upon phosphorylation: for EIN, the relative orientation of the alpha and alphabeta domains remains unchanged; for HPr, the backbone /Psi torsion angles of the active site residues are unperturbed within experimental error. His --> Glu/Asp mutations of the active site histidines designed to mimic the phosphorylated states reveal binding equilibria that favor phosphoryl transfer from EIN to HPr. Although binding of phospho-EIN to phospho-HPr is reduced by a factor of approximately 21 relative to the unphosphorylated complex, residual dipolar coupling measurements reveal that the structures of the unphosphorylated and biphosphorylated complexes are the same. Hence, the phosphorylation states of EIN and HPr shift the binding equilibria predominantly by modulating intermolecular electrostatic interactions without altering either the backbone scaffold or binding interface. This facilitates highly efficient phosphoryl transfer between EIN and HPr, which is estimated to occur at a rate of approximately 850 s(-1) from exchange spectroscopy.

Extraction of elementary rate constants from global network analysis of E. coli central metabolism

Background

As computational performance steadily increases, so does interest in extending one-particle-per-molecule models to larger physiological problems. Such models however require elementary rate constants to calculate time-dependent rate coefficients under physiological conditions. Unfortunately, even when in vivo kinetic data is available, it is often in the form of aggregated rate laws (ARL) that do not specify the required elementary rate constants corresponding to mass-action rate laws (MRL). There is therefore a need to develop a method which is capable of automatically transforming ARL kinetic information into more detailed MRL rate constants.

Results

By incorporating proteomic data related to enzyme abundance into an MRL modelling framework, here we present an efficient method operating at a global network level for extracting elementary rate constants from experiment-based aggregated rate law (ARL) models. The method combines two techniques that can be used to overcome the difficult properties in parameterization. The first, a hybrid MRL/ARL modelling technique, is used to divide the parameter estimation problem into sub-problems, so that the parameters of the mass action rate laws for each enzyme are estimated in separate steps. This reduces the number of parameters that have to be optimized simultaneously. The second, a hybrid algebraic-numerical simulation and optimization approach, is used to render some rate constants identifiable, as well as to greatly narrow the bounds of the other rate constants that remain unidentifiable. This is done by incorporating equality constraints derived from the King-Altman and Cleland method into the simulated annealing algorithm. We apply these two techniques to estimate the rate constants of a model of E. coli glycolytic pathways. The simulation and statistical results show that our innovative method performs well in dealing with the issues of high computation cost, stiffness, local minima and uncertainty inherent with large-scale non-convex nonlinear MRL models.

Conclusion

In short, this new hybrid method can ensure the proper solution of a challenging parameter estimation problem of nonlinear dynamic MRL systems, while keeping the computational effort reasonable. Moreover, the work provides us with some optimism that physiological models at the particle scale can be rooted on a firm foundation of parameters generated in the macroscopic regime on an experimental basis. Thus, the proposed method should have applications to multi-scale modelling of the real biological systems allowing for enzyme intermediates, stochastic and spatial effects inside a cell.

A stochastic automaton shows how enzyme assemblies may contribute to metabolic efficiency

BACKGROUND

The advantages of grouping enzymes into metabolons and into higher order structures have long been debated. To quantify these advantages, we have developed a stochastic automaton that allows experiments to be performed in a virtual bacterium with both a membrane and a cytoplasm. We have investigated the general case of transport and metabolism as inspired by the phosphoenolpyruvate:sugar phosphotransferase system (PTS) for glucose importation and by glycolysis.

RESULTS

We show that PTS and glycolytic metabolons can increase production of pyruvate eightfold at low concentrations of phosphoenolpyruvate. A fourfold increase in the numbers of enzyme EI led to a 40% increase in pyruvate production, similar to that observed in vivo in the presence of glucose. Although little improvement resulted from the assembly of metabolons into a hyperstructure, such assembly can generate gradients of metabolites and signaling molecules.

CONCLUSION

in silico experiments may be performed successfully using stochastic automata such as HSIM (Hyperstructure Simulator) to help answer fundamental questions in metabolism about the properties of molecular assemblies and to devise strategies to modify such assemblies for biotechnological ends.

Computer-aided rational design of the phosphotransferase system for enhanced glucose uptake in Escherichia coli

The phosphotransferase system (PTS) is the sugar transportation machinery that is widely distributed in prokaryotes and is critical for enhanced production of useful metabolites. To increase the glucose uptake rate, we propose a rational strategy for designing the molecular architecture of the Escherichia coli glucose PTS by using a computer-aided design (CAD) system and verified the simulated results with biological experiments. CAD supports construction of a biochemical map, mathematical modeling, simulation, and system analysis. Assuming that the PTS aims at controlling the glucose uptake rate, the PTS was decomposed into hierarchical modules, functional and flux modules, and the effect of changes in gene expression on the glucose uptake rate was simulated to make a rational strategy of how the gene regulatory network is engineered. Such design and analysis predicted that the mlc knockout mutant with ptsI gene overexpression would greatly increase the specific glucose uptake rate. By using biological experiments, we validated the prediction and the presented strategy, thereby enhancing the specific glucose uptake rate.

Analysis of global control of Escherichia coli carbohydrate uptake

Background

Global control influences the regulation of many individual subsystems by superimposed regulator proteins. A prominent example is the control of carbohydrate uptake systems by the transcription factor Crp in Escherichia coli. A detailed understanding of the coordination of the control of individual transporters offers possibilities to explore the potential of microorganisms e.g. in biotechnology.

Results

An o.d.e. based mathematical model is presented that maps a physiological parameter – the specific growth rate – to the sensor of the signal transduction unit, here a component of the bacterial phosphotransferase system (PTS), namely EIIA^Crr. The model describes the relation between the growth rate and the degree of phosphorylation of EIIA ^crr for a number of carbohydrates by a distinctive response curve, that differentiates between PTS transported carbohydrates and non-PTS carbohydrates. With only a small number of kinetic parameters, the model is able to describe a broad range of experimental steady-state and dynamical conditions.

Conclusion

The steady-state characteristic presented shows a relationship between the growth rate and the output of the sensor system PTS. The glycolytic flux that is measured by this sensor is a good indicator to represent the nutritional status of the cell.

Modelling gene expression control using P systems: The Lac Operon, a case study

In this paper P systems are used as a formal framework for the specification and simulation of biological systems. In particular, we will deal with gene regulation systems consisting of protein-protein and protein-DNA interactions that take place in different compartments of the hierarchical structure of the living cell or in different individual cells from a colony. We will explicitly model transcription and translation as concurrent and discrete processes using rewriting rules on multisets of objects and strings. Our approach takes into account the discrete character of the components of the system, its random behaviour and the key role played by membranes in processes involving signalling at the cell surface and selective uptake of substances from the environment. Our systems will evolve according to an extension of Gillespie's algorithm, called Multicompartmental Gillespie's Algorithm. The well known gene regulation system in the Lac Operon in Escherichia coli will be modelled as a case study to benchmark our approach.

Introduction to systems biology

The developments in the molecular biosciences have made possible a shift to combined molecular and system-level approaches to biological research under the name of Systems Biology. It integrates many types of molecular knowledge, which can best be achieved by the synergistic use of models and experimental data. Many different types of modeling approaches are useful depending on the amount and quality of the molecular data available and the purpose of the model. Analysis of such models and the structure of molecular networks have led to the discovery of principles of cell functioning overarching single species. Two main approaches of systems biology can be distinguished. Top-down systems biology is a method to characterize cells using system-wide data originating from the Omics in combination with modeling. Those models are often phenomenological but serve to discover new insights into the molecular network under study. Bottom-up systems biology does not start with data but with a detailed model of a molecular network on the basis of its molecular properties. In this approach, molecular networks can be quantitatively studied leading to predictive models that can be applied in drug design and optimization of product formation in bioengineering. In this chapter we introduce analysis of molecular network by use of models, the two approaches to systems biology, and we shall discuss a number of examples of recent successes in systems biology.

Intramolecular domain-domain association/dissociation and phosphoryl transfer in the mannitol transporter of Escherichia coli are not coupled

The Escherichia coli mannitol transporter (II(Mtl)) comprises three domains connected by flexible linkers: a transmembrane domain (C) and two cytoplasmic domains (A and B). II(Mtl) catalyzes three successive phosphoryl-transfer reactions: one intermolecular (from histidine phosphocarrier protein to the A domain) and two intramolecular (from the A to the B domain and from the B domain to the incoming sugar bound to the C domain). A key functional requirement of II(Mtl) is that the A and B cytoplasmic domains be able to rapidly associate and dissociate while maintaining reasonably high occupancy of an active stereospecific AB complex to ensure effective phosphoryl transfer along the pathway. We have investigated the rate of intramolecular domain-domain association and dissociation in IIBA(Mtl) by using (1)H relaxation dispersion spectroscopy in the rotating frame. The open, dissociated state (comprising an ensemble of states) and the closed, associated state (comprising the stereospecific complex) are approximately equally populated. The first-order rate constants for intramolecular association and dissociation are 1.7 (+/-0.3) x 10(4) and 1.8 (+/-0.4) x 10(4) s(-1), respectively. These values compare to rate constants of approximately 500 s(-1) for A --> B and B --> A phosphoryl transfer, derived from qualitative line-shape analysis of (1)H-(15)N correlation spectra taken during the course of active catalysis. Thus, on average, approximately 80 association/dissociation events are required to effect a single phosphoryl-transfer reaction. We conclude that intramolecular phosphoryl transfer between the A and B domains of II(Mtl) is rate-limited by chemistry and not by the rate of formation or dissociation of a stereospecific complex in which the active sites are optimally apposed.

How phosphotransferase system-related protein phosphorylation regulates carbohydrate metabolism in bacteria

The phosphoenolpyruvate(PEP):carbohydrate phosphotransferase system (PTS) is found only in bacteria, where it catalyzes the transport and phosphorylation of numerous monosaccharides, disaccharides, amino sugars, polyols, and other sugar derivatives. To carry out its catalytic function in sugar transport and phosphorylation, the PTS uses PEP as an energy source and phosphoryl donor. The phosphoryl group of PEP is usually transferred via four distinct proteins (domains) to the transported sugar bound to the respective membrane component(s) (EIIC and EIID) of the PTS. The organization of the PTS as a four-step phosphoryl transfer system, in which all P derivatives exhibit similar energy (phosphorylation occurs at histidyl or cysteyl residues), is surprising, as a single protein (or domain) coupling energy transfer and sugar phosphorylation would be sufficient for PTS function. A possible explanation for the complexity of the PTS was provided by the discovery that the PTS also carries out numerous regulatory functions. Depending on their phosphorylation state, the four proteins (domains) forming the PTS phosphorylation cascade (EI, HPr, EIIA, and EIIB) can phosphorylate or interact with numerous non-PTS proteins and thereby regulate their activity. In addition, in certain bacteria, one of the PTS components (HPr) is phosphorylated by ATP at a seryl residue, which increases the complexity of PTS-mediated regulation. In this review, we try to summarize the known protein phosphorylation-related regulatory functions of the PTS. As we shall see, the PTS regulation network not only controls carbohydrate uptake and metabolism but also interferes with the utilization of nitrogen and phosphorus and the virulence of certain pathogens.