Time-dependent regulation of yeast glycolysis upon nitrogen starvation depends on cell history.

In this study, the authors investigated how the glycolytic flux was regulated in time upon nitrogen starvation of cells with different growth histories. We have compared cells grown in glucose-limited chemostat cultures under respiratory conditions (low dilution rate of 0.1/h) to cells grown under respirofermentative conditions (high dilution rate of 0.35/h). The fermentative capacity was lower in cells grown under respiratory conditions than in cells grown under respirofermentative conditions, yet more resilient to prolonged nitrogen starvation. The time profiles revealed that the fermentative capacity even increased in cells grown under respiratory conditions during the first hours of nitrogen starvation. In cells grown under respirofermentative conditions the fermentative capacity decreased from the onset of nitrogen starvation. We have applied time-dependent Regulation Analysis to follow the fermentative capacity during nitrogen starvation. In both experiments, diverse categories of regulation were found. However, in the cells grown under respiratory conditions regulation was predominantly metabolic, whereas in the cells grown under respirofermentative conditions hierarchical regulation was dominant. To study the metabolic regulation, concentrations of intracellular metabolites, including allosteric regulators, were measured. The obtained results can explain some aspects of the metabolic regulation, but not all.

Control, responses and modularity of cellular regulatory networks: a control analysis perspective.

Cells adapt to changes in environmental conditions through the concerted action of signalling, gene expression and metabolic subsystems. The authors will discuss a theoretical framework addressing such integrated systems. This 'hierarchical analysis' was first developed as an extension to a metabolic control analysis. It builds on the phenomenon that often the communication between signalling, gene expression and metabolic subsystems is almost exclusively via regulatory interactions and not via mass flow interactions. This allows for the treatment of the said subsystems as 'levels' in a hierarchical view of the organisation of the molecular reaction network of cells. Such a hierarchical approach has as a major advantage that levels can be analysed conceptually in isolation of each other (from a local intra-level perspective) and at a later stage integrated via their interactions (from a global inter-level perspective). Hereby, it allows for a modular approach with variable scope. A number of different approaches have been developed for the analysis of hierarchical systems, for example hierarchical control analysis and modular response analysis. The authors, here, review these methods and illustrate the strength of these types of analyses using a core model of a system with gene expression, metabolic and signal transduction levels.

BDI-modelling of complex intracellular dynamics.

A BDI-based continuous-time modelling approach for intracellular dynamics is presented. It is shown how temporalized BDI-models make it possible to model intracellular biochemical processes as decision processes. By abstracting from some of the details of the biochemical pathways, the model achieves understanding in nearly intuitive terms, without losing veracity: classical intentional state properties such as beliefs, desires and intentions are founded in reality through precise biochemical relations. In an extensive example, the complex regulation of Escherichia coli vis-à-vis lactose, glucose and oxygen is simulated as a discrete-state, continuous-time temporal decision manager. Thus a bridge is introduced between two different scientific areas: the area of BDI-modelling and the area of intracellular dynamics.

Systems biology: new paradigms for cell biology and drug design.

In this chapter various facets of and approaches to systems biology will be discussed. This then leads to an illustration of how systems biology may be used in drug target design. We present five new paradigms for drug target research and show how these are based in systems biology.

Time-dependent hierarchical regulation analysis: deciphering cellular adaptation.

Cells adapt to changes in their environment by the concerted action of many different regulatory mechanisms. Examples of such mechanisms are feedback inhibition by intermediates of metabolism, covalent modification of enzymes and changes in the abundance of mRNAs and proteins. These mechanisms act in parallel at different levels in the cellular hierarchy while regulating a single process. Existing hierarchical regulation analysis determines the relative importance of these mechanisms when the cell regulates a transition from one steady-state to another. Here, the analysis is extended to the regulation of time-dependent phenomena, for which two methods are introduced and illustrated with a kinetic model incorporating transcription and translation of metabolic enzymes.

Summation theorems for flux and concentration control coefficients of dynamic systems.

Metabolic control analysis (MCA) was developed to quantify how system variables are affected by parameter variations in a system. In addition, MCA can express the global properties of a system in terms of the individual catalytic steps, using connectivity and summation theorems to link the control coefficients to the elasticity coefficients. MCA was originally developed for steady-state analysis and not all summation theorems have been derived for dynamic systems. A method to determine time-dependent flux and concentration control coefficients for dynamic systems by expressing the time domain as a function of percentage progression through any arbitrary fixed interval of time is reported. Time-dependent flux and concentration control coefficients of dynamic systems, provided that they are evaluated in this novel way, obey the same summation theorems as steady-state flux and concentration control coefficients, respectively.

Is there an optimal ribosome concentration for maximal protein production?

A core model is presented for protein production in Escherichia coli to address the question whether there is an optimal ribosomal concentration for non-ribosome protein production. Analysing the steady-state solution of the model over a range of mRNA concentrations, indicates that such an optimum ribosomal content exists, and that the optimum shifts to higher ribosomal contents at higher specific growth rates.

Approaches to biosimulation of cellular processes.

Modelling and simulation are at the heart of the rapidly developing field of systems biology. This paper reviews various types of models, simulation methods, and theoretical approaches that are presently being used in the quantitative description of cellular processes. We first describe how molecular interaction networks can be represented by means of stoichiometric, topological and kinetic models. We briefly discuss the formulation of kinetic models using mesoscopic (stochastic) or macroscopic (continuous) approaches, and we go on to describe how detailed models of molecular interaction networks (silicon cells) can be constructed on the basis of experimentally determined kinetic parameters for cellular processes. We show how theory can help in analyzing models by applying control analysis to a recently published silicon cell model. Finally, we review some of the theoretical approaches available to analyse kinetic models and experimental data, respectively.

How to distinguish between the vacuum cleaner and flippase mechanisms of the lmrA multi-drug transporter in Lactococcus lactis.

A numerical model of the LmrA multi-drug transport system of Lactococcus lactis is used to explore the possibility of distinguishing experimentally between two putative transport mechanisms, i.e., the vacuum-cleaner and the flippase mechanisms. This comparative model also serves as an example of numerical simulation with the scripting language Python and its scientific add-on Scipy.

Cytochromes c(550), c(552), and c(1) in the electron transport network of Paracoccus denitrificans: redundant or subtly different in function?

Paracoccus denitrificans strains with mutations in the genes encoding the cytochrome c(550), c(552), or c(1) and in combinations of these genes were constructed, and their growth characteristics were determined. Each mutant was able to grow heterotrophically with succinate as the carbon and free-energy source, although their specific growth rates and maximum cell numbers fell variably behind those of the wild type. Maximum cell numbers and rates of growth were also reduced when these strains were grown with methylamine as the sole free-energy source, with the triple cytochrome c mutant failing to grow on this substrate. Under anaerobic conditions in the presence of nitrate, none of the mutant strains lacking the cytochrome bc(1) complex reduced nitrite, which is cytotoxic and accumulated in the medium. The cytochrome c(550)-deficient mutant did denitrify provided copper was present. The cytochrome c(552) mutation had no apparent effect on the denitrifying potential of the mutant cells. The studies show that the cytochromes c have multiple tasks in electron transfer. The cytochrome bc(1) complex is the electron acceptor of the Q-pool and of amicyanin. It is also the electron donor to cytochromes c(550) and c(552) and to the cbb(3)-type oxidase. Cytochrome c(552) is an electron acceptor both of the cytochrome bc(1) complex and of amicyanin, as well as a dedicated electron donor to the aa(3)-type oxidase. Cytochrome c(550) can accept electrons from the cytochrome bc(1) complex and from amicyanin, whereas it is also the electron donor to both cytochrome c oxidases and to at least the nitrite reductase during denitrification. Deletion of the c-type cytochromes also affected the concentrations of remaining cytochromes c, suggesting that the organism is plastic in that it adjusts its infrastructure in response to signals derived from changed electron transfer routes.

Autoamplification of a two-component regulatory system results in "learning" behavior.

We have tested the hypothesis that the autoamplification of two-component regulatory systems results in "learning" behavior, i.e., that bacteria respond faster or more extensively to a signal when a similar signal has been perceived in the past. Indeed, the induction of alkaline phosphatase activity upon phosphate limitation was faster if the cultures had been limited for phosphate previously, and this faster response correlated with the autoamplification of the cognate two-component system.

Transcriptome meets metabolome: hierarchical and metabolic regulation of the glycolytic pathway.

The fact that information flows from DNA to RNA to protein to function suggests that regulation is 'hierarchical', i.e. dominated by regulation of gene expression. In the case of dominant regulation at the metabolic level, however, there is no quantitative relationship between mRNA levels and function. We here develop a method to quantitate the relative contributions of metabolic and hierarchical regulation. Applying this method to the glycolytic flux in three species of parasitic protists, we conclude that it is rarely regulated by gene expression alone. This casts strong doubts on whether transcriptome and proteome analysis suffices to assess biological function.

Regulation of expression of terminal oxidases in Paracoccus denitrificans.

In order to study the induction of terminal oxidases in Paracoccus denitrificans, their promoters were fused to the lacZ reporter gene and analysed in the wild-type strain, in an FnrP-negative mutant, in a cytochrome bc1-negative mutant, and in six single or double oxidase-negative mutant strains. The strains were grown under aerobic, semi-aerobic, and denitrifying conditions. The oxygen-sensing transcriptional-regulatory protein FnrP negatively regulated the activity of the qox promoter, which controls expression of the ba3-type quinol oxidase, while it positively regulated the activity of the cco promoter, which controls expression of the cbb3-type cytochrome c oxidase. The ctaDII and ctaC promoters, which control the expression of the aa3-type cytochrome c oxidase subunits I and II, respectively, were not regulated by FnrP. The activities of the latter two promoters, however, did decrease with decreasing oxygen concentrations in the growth medium, suggesting that an additional oxygen-sensing mechanism exists that regulates transcription of ctaDII and ctaC. Apparently, the intracellular oxygen concentration (as sensed by FnrP) was not the only signal to which the oxidase promoters responded. At given extracellular oxygen status, both the qox and the cco promoters responded to mutations in terminal oxidase genes, whereas the ctaDII and ctaC promoters did not. The change of electron distribution through the respiratory network, resulting from elimination of one or more oxidase genes, may have changed intracellular signals that affect the activities of the qox and cco promoters. On the other hand, the re-routing of electron distribution in the respiratory mutants hardly affected the oxygen consumption rate as compared to that of the wild-type. This suggests that the mutants adapted their respiratory network in such a way that they were able to consume oxygen at a rate similar to that of the wild-type strain.

The potential role of adenosine in the pathophysiology of the insulin resistance syndrome.

An increased intracellular availability of the co-enzyme A esters of long-chain fatty acids is thought to underlie many aspects of the insulin resistance syndrome. However, the cause of clustering of a hyperdynamic circulation, sympathetic activation, hypertension, hyperuricaemia, and a raised haematocrit in the insulin resistance syndrome remains to be elucidated. We propose a mechanism that expands the etiological role of long-chain fatty acids. By inhibiting adenine nucleotide translocators, elevated intracellular concentrations of the co-enzyme A esters of long-chain fatty acids impair mitochondrial oxidative phosphorylation. This is expected to result in a chronic systemic increase in extracellular adenosine concentrations. As adenosine stimulates the sympathetic nervous system, induces systemic vasodilatation, stimulates erythropoiesis, and induces renal vasoconstriction with renal sodium retention, increased extracellular ADO concentrations may be the common denominator explaining the above-mentioned and still unexplained phenomena associated with the insulin resistance syndrome. Along the same lines, hyperuricaemia can be explained by the fact that adenosine is broken down to urate and because of increased renal urate retention.

Pumping capacity of bacterial reaction centers and backpressure regulation of energy transduction.

Transduction of free-energy by Rhodobacter sphaeroides reaction-center-light-harvesting-complex-1 (RCLH1) was quantified. RCLH1 complexes were reconstituted into liposomal membranes. The capacity of the RCLH1 complex to build up a proton motive force was examined at a range of incident light intensities, and induced proton permeabilities, in the presence of artificial electron donors and acceptors. Experiments were also performed with RCLH1 complexes in which the midpoint potential of the reaction center primary donor was modified over an 85-mV range by replacement of the tyrosine residue at the M210 position of the reaction center protein by histidine, phenylalanine, leucine or tryptophan. The intrinsic driving force with which the reaction center pumped protons tended to decrease as the midpoint potential of the primary donor was increased. This observation is discussed in terms of the control of the energetics of the first steps in light-driven electron transfer on the thermodynamic efficiency of the bacterial photosynthetic process. The light intensity at which half of the maximal proton motive force was generated, increased with increasing proton permeability of the membrane. This presents the first direct evidence for so-called backpressure control exerted by the proton motive force on steady-state cyclic electron transfer through and coupled proton pumping by the bacterial reaction center.

Building the cellular puzzle: control in multi-level reaction networks.

Quantitative conceptual tools dealing with control and regulation of cellular processes have been mostly developed for and applied to the pathways of intermediary metabolism. Yet, cellular processes are organized in different levels, metabolism forming the lowest level in a cascade of processes. Well-known examples are the DNA-mRNA-enzyme-metabolism cascade and the signal transduction cascades consisting of covalent modification cycles. The reaction network that constitutes each level can be viewed as a "module" in which reactions are linked by mass transfer. Although in principle all of these cellular modules are ultimately linked by mass transfer, in practice they can often be regarded as "isolated" from each other in terms of mass transfer. Here modules can interact with each other only by means of regulatory or catalytic effects-a chemical species in one module may affect the rate of a reaction in another module by binding to an enzyme or transport system or by acting as a catalyst. This paper seeks to answer two questions about the control and regulation of such multi-level reaction networks: (i) How can the control properties of the system as a whole be expressed in terms of the control properties of individual modules and the effects between modules? (ii) How do the control properties of a module in its isolated state change when it is embedded in the whole system through its connections with the other modules? In order to answer these questions a quantitative theoretical framework is developed and applied to systems containing two, three or four fully interacting modules; it is shown how it can be extended in principle to n modules. This newly developed theory therefore makes it possible to quantitatively dissect intermodular, internal and external regulation in multi-level systems.

Control of glycolytic dynamics by hexose transport in Saccharomyces cerevisiae.

It is becoming accepted that steady-state fluxes are not necessarily controlled by single rate-limiting steps. This leaves open the issue whether cellular dynamics are controlled by single pacemaker enzymes, as has often been proposed. This paper shows that yeast sugar transport has substantial but not complete control of the frequency of glycolytic oscillations. Addition of maltose, a competitive inhibitor of glucose transport, reduced both average glucose consumption flux and frequency of glycolytic oscillations. Assuming a single kinetic component and a symmetrical carrier, a frequency control coefficient of between 0.4 and 0.6 and an average-flux control coefficient of between 0.6 and 0.9 were calculated for hexose transport activity. In a second approach, mannose was used as the carbon and free-energy source, and the dependencies on the extracellular mannose concentration of the transport activity, of the frequency of oscillations, and of the average flux were compared. In this case the frequency control coefficient and the average-flux control coefficient of hexose transport activity amounted to 0.7 and 0.9, respectively. From these results, we conclude that 1) transport is highly important for the dynamics of glycolysis, 2) most but not all control resides in glucose transport, and 3) there should at least be one step other than transport with substantial control.

A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations.

A large proportion of the 6,000 genes present in the genome of Saccharomyces cerevisiae, and of those sequenced in other organisms, encode proteins of unknown function. Many of these genes are "silent, " that is, they show no overt phenotype, in terms of growth rate or other fluxes, when they are deleted from the genome. We demonstrate how the intracellular concentrations of metabolites can reveal phenotypes for proteins active in metabolic regulation. Quantification of the change of several metabolite concentrations relative to the concentration change of one selected metabolite can reveal the site of action, in the metabolic network, of a silent gene. In the same way, comprehensive analyses of metabolite concentrations in mutants, providing "metabolic snapshots," can reveal functions when snapshots from strains deleted for unstudied genes are compared to those deleted for known genes. This approach to functional analysis, using comparative metabolomics, we call FANCY-an abbreviation for functional analysis by co-responses in yeast.