Critical switch of the metabolic fluxes by phosphofructo-2-kinase:fructose-2,6-bisphosphatase. A kinetic model

A fundamental trade-off in covalent switching and its circumvention by enzyme bifunctionality in glucose homeostasis

Covalent modification provides a mechanism for modulating molecular state and regulating physiology. A cycle of competing enzymes that add and remove a single modification can act as a molecular switch between "on" and "off" and has been widely studied as a core motif in systems biology. Here, we exploit the recently developed "linear framework" for time scale separation to determine the general principles of such switches. These methods are not limited to Michaelis-Menten assumptions, and our conclusions hold for enzymes whose mechanisms may be arbitrarily complicated. We show that switching efficiency improves with increasing irreversibility of the enzymes and that the on/off transition occurs when the ratio of enzyme levels reaches a value that depends only on the rate constants. Fluctuations in enzyme levels, which habitually occur due to cellular heterogeneity, can cause flipping back and forth between on and off, leading to incoherent mosaic behavior in tissues, that worsens as switching becomes sharper. This trade-off can be circumvented if enzyme levels are correlated. In particular, if the competing catalytic domains are on the same protein but do not influence each other, the resulting bifunctional enzyme can switch sharply while remaining coherent. In the mammalian liver, the switch between glycolysis and gluconeogenesis is regulated by the bifunctional 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase (PFK-2/FBPase-2). We suggest that bifunctionality of PFK-2/FBPase-2 complements the metabolic zonation of the liver by ensuring coherent switching in response to insulin and glucagon.

GraTeLPy: graph-theoretic linear stability analysis

BACKGROUND

A biochemical mechanism with mass action kinetics can be represented as a directed bipartite graph (bipartite digraph), and modeled by a system of differential equations. If the differential equations (DE) model can give rise to some instability such as multistability or Turing instability, then the bipartite digraph contains a structure referred to as a critical fragment. In some cases the existence of a critical fragment indicates that the DE model can display oscillations for some parameter values. We have implemented a graph-theoretic method that identifies the critical fragments of the bipartite digraph of a biochemical mechanism.

RESULTS

GraTeLPy lists all critical fragments of the bipartite digraph of a given biochemical mechanism, thus enabling a preliminary analysis on the potential of a biochemical mechanism for some instability based on its topological structure. The correctness of the implementation is supported by multiple examples. The code is implemented in Python, relies on open software, and is available under the GNU General Public License.

CONCLUSIONS

GraTeLPy can be used by researchers to test large biochemical mechanisms with mass action kinetics for their capacity for multistability, oscillations and Turing instability.

Design of fructose-2,6-bisphosphatase inhibitors: A novel virtual screening approach

Fructose-2,6-bisphosphatase (FBPase-2) is a switch between gluconeogenesis and glycolysis in the hepatic cells. The structural features required for inhibitory activity of FBPase-2 were unidentified; no leads are available for inhibiting this important enzyme. In this paper pharmacophore mapping, molecular docking methods were employed in a virtual screening strategy to identify leads for FBPase-2. A receptor based pharmacophore map was modeled which comprised of important interactions as observed in co-crystal of rat liver isozyme with the product inhibitor fructose-6-phosphate. The pharmacophore model was validated against two databases of best docked structural analogues of fructose-2,6-bisphosphate and fructose-6-phosphate. The query generated was submitted for flexible search of ligands in chemical databases, namely LeadQuest, Maybridge and NCI. The hits obtained were further screened by molecular docking using FlexX.

Graph-theoretic methods for the analysis of chemical and biochemical networks. I. Multistability and oscillations in ordinary differential equation models

A chemical mechanism is a model of a chemical reaction network consisting of a set of elementary reactions that express how molecules react with each other. In classical mass-action kinetics, a mechanism implies a set of ordinary differential equations (ODEs) which govern the time evolution of the concentrations. In this article, ODE models of chemical kinetics that have the potential for multiple positive equilibria or oscillations are studied. We begin by considering some methods of stability analysis based on the digraph of the Jacobian matrix. We then prove two theorems originally given by A. N. Ivanova which correlate the bifurcation structure of a mass-action model to the properties of a bipartite graph with nodes representing chemical species and reactions. We provide several examples of the application of these theorems.

Switching mechanism for branched biochemical fluxes: Graph-theoretical analysis

A graph-theoretical method is applied to characterize the structure of a simplest switching mechanism of common biochemical importance. This mechanism is based on competition of two coupled substrate-binding pathways for a single substrate. No other regulatory interactions are shown to be needed for the switching phenomenon to be observed. It is shown that switch in branch effluxes is observed as bistability or reciprocal oscillations, depending on the value of steady influx. Frequency of reciprocal efflux oscillations in branches is regulated by steady influx. Therefore, the switching mechanism can function as the coding mechanism in the manner of "influx steady level-efflux frequency". The calculated kinetic equations for the switching mechanism demonstrate very steep transitions in the branch fluxes without using high non-linearity of these equations.

A graph-theoretic method for detecting potential Turing bifurcations

The conditions for diffusion-driven (Turing) instabilities in systems with two reactive species are well known. General methods for detecting potential Turing bifurcations in larger reaction schemes are, on the other hand, not well developed. We prove a theorem for a graph-theoretic condition originally given by Volpert and Ivanova [Mathematical Modeling (Nauka, Moscow, 1987) (in Russian), p. 57] for Turing instabilities in a mass-action reaction-diffusion system involving n substances. The method is based on the representation of a reaction mechanism as a bipartite graph with two types of nodes representing chemical species and reactions, respectively. The condition for diffusion-driven instability is related to the existence of a structure in the graph known as a critical fragment. The technique is illustrated using a substrate-inhibited bifunctional enzyme mechanism which involves seven chemical species.

Computational multiple steady states for enzymatic esterification of ethanol and oleic acid in an isothermal CSTR

The capacity of complex biochemical reaction networks (consisting of 11 coupled non-linear ordinary differential equations) to show multiple steady states, was investigated. The system involved esterification of ethanol and oleic acid by lipase in an isothermal continuous stirred tank reactor (CSTR). The Deficiency One Algorithm and the Subnetwork Analysis were applied to determine the steady state multiplicity. A set of rate constants and two corresponding steady states are computed. The phenomena of bistability, hysteresis and bifurcation are discussed. Moreover, the capacity of steady state multiplicity is extended to the family of the studied reaction networks.

What makes biochemical networks tick?

In view of the increasing number of reported concentration oscillations in living cells, methods are needed that can identify the causes of these oscillations. These causes always derive from the influences that concentrations have on reaction rates. The influences reach over many molecular reaction steps and are defined by the detailed molecular topology of the network. So-called 'autoinfluence paths', which quantify the influence of one molecular species upon itself through a particular path through the network, can have positive or negative values. The former bring a tendency towards instability. In this molecular context a new graphical approach is presented that enables the classification of network topologies into oscillophoretic and nonoscillophoretic, i.e. into ones that can and ones that cannot induce concentration oscillations. The network topologies are formulated in terms of a set of uni-molecular and bi-molecular reactions, organized into branched cycles of directed reactions, and presented as graphs. Subgraphs of the network topologies are then classified as negative ones (which can) and positive ones (which cannot) give rise to oscillations. A subgraph is oscillophoretic (negative) when it contains more positive than negative autoinfluence paths. Whether the former generates oscillations depends on the values of the other subgraphs, which again depend on the kinetic parameters. An example shows how this can be established. By following the rules of our new approach, various oscillatory kinetic models can be constructed and analyzed, starting from the classified simplest topologies and then working towards desirable complications. Realistic biochemical examples are analyzed with the new method, illustrating two new main classes of oscillophore topologies.

Nutrient-gene interactions: a single nutrient and hundreds of target genes

Based on the effects of a selective experimental zinc deficiency in a rodent model we explore the use of transcriptome profiling for assessing nutrient-gene interactions in the liver at the molecular and cellular levels. Zinc deficiency caused pleiotropic alterations in mRNA/protein levels of hundreds of genes. In the context of observed metabolic alterations in hepatic metabolism, possible mechanisms are discussed for how a low zinc status may be sensed and transmitted into changes in various metabolic pathways. However, it also becomes obvious that analysis of such complex nutrient-gene interactions beyond the descriptional level is a real challenge for systems biology.