Analysis of gene network robustness based on saturated fixed point attractors

The analysis of gene network robustness to noise and mutation is important for fundamental and practical reasons. Robustness refers to the stability of the equilibrium expression state of a gene network to variations of the initial expression state and network topology. Numerical simulation of these variations is commonly used for the assessment of robustness. Since there exists a great number of possible gene network topologies and initial states, even millions of simulations may be still too small to give reliable results. When the initial and equilibrium expression states are restricted to being saturated (i.e., their elements can only take values 1 or −1 corresponding to maximum activation and maximum repression of genes), an analytical gene network robustness assessment is possible. We present this analytical treatment based on determination of the saturated fixed point attractors for sigmoidal function models. The analysis can determine (a) for a given network, which and how many saturated equilibrium states exist and which and how many saturated initial states converge to each of these saturated equilibrium states and (b) for a given saturated equilibrium state or a given pair of saturated equilibrium and initial states, which and how many gene networks, referred to as viable, share this saturated equilibrium state or the pair of saturated equilibrium and initial states. We also show that the viable networks sharing a given saturated equilibrium state must follow certain patterns. These capabilities of the analytical treatment make it possible to properly define and accurately determine robustness to noise and mutation for gene networks. Previous network research conclusions drawn from performing millions of simulations follow directly from the results of our analytical treatment. Furthermore, the analytical results provide criteria for the identification of model validity and suggest modified models of gene network dynamics. The yeast cell-cycle network is used as an illustration of the practical application of this analytical treatment.     

Hutchinson revisited: Patterns of density regulation and the coexistence of strong competitors

Ecologists have long been searching for mechanisms of species coexistence, particularly since G.E. Hutchinson raised the ‘paradox of the plankton’. A promising approach to solve this paradox and to explain the coexistence of many species with strong niche overlap is to consider over-compensatory density regulation with its ability to generate endogenous population fluctuations.Previous work has analysed the role of over-compensation in coexistence based on analytical approaches. Using a spatially explicit time-discrete simulation model, we systematically explore the dynamics and conditions for coexistence of two species. We go beyond the analytically accessible range of models by studying the whole range of density regulation from under- to very strong over-compensation and consider the impact of spatial structure and temporal disturbances. In particular, we investigate how coexistence can emerge in different types of population growth models.We show that two strong competitors are able to coexist if at least one species exhibits over-compensation. Analysing the time series of population dynamics reveals how the differential responses to density fluctuations of the two competitors lead to coexistence: The over-compensator generates density fluctuations but is the inferior competitor at strong amplitudes of those fluctuations; the competitor, therefore, becomes frequent and dampens the over-compensator's amplitudes, but it becomes inferior under dampened fluctuations.These species interactions cause a dynamic alternation of community states with long-term persistence of both species. We show that a variety of population growth models is able to reproduce this coexistence although the particular parameter ranges differ among the models. Spatial structure influences the probability of coexistence but coexistence is maintained for a broad range of dispersal parameters.The flexibility and robustness of coexistence through over-compensation emphasize the importance of nonlinear density dependence for species interactions, and they also highlight the potential of applying more flexible models than the classical Lotka-Volterra equations in community ecology.     

Population models in a periodically fluctuating environment

Summary We investigate the behavior of population models in the presence of a periodically fluctuating environment. We consider in particular single-species models and models of interspecific competition. It is shown that the fluctuations cause constant equilibrium states to be replaced by periodic equilibrium states, with a shift in the mean value relative to the constant-environment state. It is shown also that the locations of points of exchange of stability may be changed as a result of the fluctuations.     

Forest dynamics,differential mortality and variable recruitment probabilities

Abstract. Both spatial and temporal variability in recruitment probabilities can lead to coexistence in gap-phase regenerating forests which would otherwise tend to be dominated by fewer species. Using modified Markov models, the potential roles were examined of temporal variability and differential mortality rates among species in the dynamics of a forest for which spatial variability has been rejected as a strong factor leading to coexistence. Differential longevity modifies results obtained from a simple Markov model: it exerts a strong influence on the equilibrium species composition, on the rate of community change and on the time a community requires to reach equilibrium. Simulations with varying transition probabilities mimicked a changing climate, producing four main results: 1. Unless the duration of climate states is very long or very short, forest composition is in a continual state of disequilibrium. 2. Species vary in their response times to changing climate. 3. The mean abundance of each species under a varying climate scenario is different from that expected from the mean climate state. 4. The rare, long-lived species was favored by climatic fluctuations at the expense of more common shorter lived species. Differential mortality rates provide an equilibrium-based mechanism for coexistence, and temporally fluctuating recruitment probabilities a non-equilibrium mechanism. Composition could be maintained by differential longevity among species and climatic fluctuations allowing periodic recruitment of the less common species.     

Analysis of continuous cultures of recombinant methylotrophs

Static and dynamic characteristics of continuous cultures of recombinant methylotrophs, which are designed to improve the selectivity of plasmid-bearing cells and the plasmid stability, are investigated in detail. Operational regions in which coexistence (survival of plasmid-bearing and plasmid-free cells) operation is feasible have been identified in the entire space of kinetic parameters and operating variables. The stability characteristics of each steady state are examined. The existence of oscillatory states around the coexistence steady state is investigated using the dynamic (Hopf) bifurcation analysis. For proper startup of the continuous culture operation, it is critical to identify the sets of initial conditions, if any, which lead to transients that ultimately result in washout of plasmid-bearing cells and avoid such conditions. For the numerical illustrations presented, the coexistence steady state happens to be locally stable over much of its region of existence, particular for the operating conditions corresponding to maximum productivity.     

Global positive coexistence of a nonlinear elliptic biological interacting model

The purpose of this note is to give a necessary and sufficient condition for the coexistence of positive solutions to a rather general type of elliptic predator-prey system of the Dirichlet problem on the bounded domain omega when omega is a subset of Rn is large. The result is that the partial differential equation system possesses positive coexistence if and only if the corresponding ordinary differential equation system has positive equilibrium, the positive constant states. This result thus yields an algebraically computable criterion for the positive coexistence of predator and prey in many biological models.     

Coexistence in MacArthur-style consumer-resource models

The nature of and conditions for permanent coexistence of consumers and resources are characterized in a family of models that generalize MacArthur's consumer-resource model. The generalization is of the resource dynamics, which need not be of Lotka-Volterra form but are subject only to certain restrictions loose enough to admit many resource dynamics of biological interest. For any such model, (1) if there is an interior equilibrium, then it is globally attracting, else some boundary equilibrium is globally attracting-thus permanent coexistence is coexistence at a globally attracting equilibrium; (2) there is an interior equilibrium if and only if for any species, the equilibrium approached in the absence of that species and the presence of the others is invasible by that species--thus permanent coexistence is equivalent to mutual invasibility; (3) for resources without direct interactions, the conditions for permanent coexistence of the consumers admit an instructive formulation in terms of regression statistics. The significance and limitations of the models and results are discussed.     

Impact of Allee effect on an eco-epidemiological system

In this paper, we propose a general ratio-dependent prey-predator model with disease in predator subject to the strong Allee effect in prey. We obtain the complete dynamics of both models: (a) full model with Allee effect; (b) full model without Allee effect. Model (a) may have more than one interior equilibrium point, but model (b) has only one interior equilibrium point. Numerical results reveal that the coexistence of all the populations at the endemic state is possible for both the models. But for the model with Allee effect, the coexistence can be destroyed by an increased supply of alternative food for the predators. It can also be proved that for the full model with Allee effect, the disease can be suppressed under certain parametric conditions. Also by comparing models (a) and (b), we conclude that Allee effect can create or destroy the interior attractor. Finally, we have studied the disease free-submodel (prey and susceptible predator model) with and without Allee effect. The comparative study between these two submodels leads to the following conclusions: 1) In the presence of Allee effect, the number of interior equilibrium points can change from zero to two whereas the submodel without Allee effect has unique interior equilibrium point; 2) Both with and without Allee effect, initial conditions play an important role on the survival and extinction of prey as well as its corresponding predator; 3) In the presence of Allee effect, bi-stability occurs with stable or periodic coexistence of prey and susceptible predator and the extinction of prey and susceptible predator; 4) Allee effect can generate or destroy the interior equilibrium points.     

Mechanism of chaperone function in small heat shock proteins: dissociation of the HSP27 oligomer is required for recognition and binding of destabilized T4 lysozyme

Mammalian small heat shock proteins (sHSP) form polydisperse and dynamic oligomers that undergo equilibrium subunit exchange. Current models of their chaperone activity hypothesize that recognition and binding of protein non-native states involve changes in the oligomeric state. The equivalent thermodynamic representation is a set of three coupled equilibria that includes the sHSP oligomeric equilibrium, the substrate folding equilibrium, and the equilibrium binding between the sHSP and the substrate non-native states. To test this hypothesis and define the binding-competent oligomeric state of human Hsp27, we have perturbed the two former equilibria and quantitatively determined the consequences on binding. The substrate is a set of T4 lysozyme (T4L) mutants that bind under conditions that favor the folded state over the unfolded state by 10(2)-10(4)-fold. The concentration-dependent oligomer equilibrium of Hsp27 was perturbed by mutations that alter the relative stability of two major oligomeric states including phosphorylation-mimicking mutations that result in the dissociation to a small multimer over a wide range of concentrations. Correlation of binding isotherms with size exclusion chromatography analysis of the Hsp27 oligomer equilibrium demonstrates that the multimer is the binding-competent state. Binding occurs through two modes, each characterized by different affinity and number of binding sites, and results in T4L.Hsp27 complexes of different hydrodynamic properties. Mutants of the Hsp27 phosphorylation mimic that reverse the reduction in oligomer size also reduce the extent of T4L binding. Taken together, these results suggest a central role for the oligomeric equilibrium in regulating the chaperone activity of sHSP. The mutants identify sequence features important for modulating this equilibrium.     

Large amplification in stage-structured models: Arnol’d tongues revisited

The coexistence of periodic and point attractors has been confirmed for a range of stage-structured discrete time models. The periodic attractor cycles have large amplitude, with the populations cycling between extremely low and surprisingly high values when compared to the equilibrium level. In this situation a stable state can be shocked by noise of sufficient strength into a state of high volatility. We found that the source of these large amplitude cycles are Arnold tongues, special regions of parameter space where the system exhibits periodic behaviour. Most of these tongues lie entirely in that part of parameter space where the system is unstable, but there are exceptions and these exceptions are the tongues that lead to attractor coexistence. Similarity in the geometry of Arnold tongues over the range of models considered might suggest that this is a common feature of stage-structured models but in the absence of proof this can only be a useful working hypothesis. The analysis shows that although large amplitude cycles might exist mathematically they might not be accessible biologically if biological constraints, such as non-negativity of population densities and vital rates, are imposed. Accessibility is found to be highly sensitive to model structure even though the mathematical structure is not. This highlights the danger of drawing biological conclusions from particular models. Having a comprehensive view of the different mechanisms by which periodic states can arise in families of discrete time models is important in the debate on whether the causes of periodicity in particular ecological systems are intrinsic, environmental or trophic. This paper is a contribution to that continuing debate.     

Parametric analysis of the ratio-dependent predator–prey model

We present a complete parametric analysis of stability properties and dynamic regimes of an ODE model in which the functional response is a function of the ratio of prey and predator abundances. We show the existence of eight qualitatively different types of system behaviors realized for various parameter values. In particular, there exist areas of coexistence (which may be steady or oscillating), areas in which both populations become extinct, and areas of "conditional coexistence" depending on the initial values. One of the main mathematical features of ratio-dependent models, distinguishing this class from other predator-prey models, is that the Origin is a complicated equilibrium point, whose characteristics crucially determine the main properties of the model. This is the first demonstration of this phenomenon in an ecological model. The model is investigated with methods of the qualitative theory of ODEs and the theory of bifurcations. The biological relevance of the mathematical results is discussed both regarding conservation issues (for which coexistence is desired) and biological control (for which extinction is desired).     

Self-organized dynamics in plastic neural networks: bistability and coherence

 In this paper, we study the combined dynamics of the neural activity and the synaptic efficiency changes in a fully connected network of biologically realistic neurons with simple synaptic plasticity dynamics including both potentiation and depression. Using a mean-field of technique, we analyzed the equilibrium states of neural networks with dynamic synaptic connections and found a class of bistable networks. For this class of networks, one of the stable equilibrium states shows strong connectivity and coherent responses to external input. In the other stable equilibrium, the network is loosely connected and responds non coherently to external input. Transitions between the two states can be achieved by positively or negatively correlated external inputs. Such networks can therefore switch between their phases according to the statistical properties of the external input. Non-coherent input can only “rcad” the state of the network, while a correlated one can change its state. We speculate that this property, specific for plastic neural networks, can give a clue to understand fully unsupervised learning models. Received: 8 August 1999 / Accepted in revised form: 16 March 2000     

Modelling of predator–prey trophic interactions. Part II: Three trophic levels

A general class of lumped parameter models describing the local dynamics of a tri-trophic chain in a controlled environment is analyzed in detail. The trophic functions characterizing the interactions are defined only by some properties and allow us to treat both prey-dependent and ratio-dependent models in a unified manner. Conditions for existence and stability of extinction and coexistence equilibrium states are determined. Some peculiar aspects of the dynamics of the system depending on the bioecological parameters are presented, with particular attention to bistability situations, limit cycles and chaotic behaviours.     

Large-Scale Genomic Analysis Suggests a Neutral Punctuated Dynamics of Transposable Elements in Bacterial Genomes

Insertion sequences (IS) are the simplest and most abundant form of transposable DNA found in bacterial genomes. When present in multiple copies, it is thought that they can promote genomic plasticity and genetic exchange, thus being a major force of evolutionary change. The main processes that determine IS content in genomes are, though, a matter of debate. In this work, we take advantage of the large amount of genomic data currently available and study the abundance distributions of 33 IS families in 1811 bacterial chromosomes. This allows us to test simple models of IS dynamics and estimate their key parameters by means of a maximum likelihood approach. We evaluate the roles played by duplication, lateral gene transfer, deletion and purifying selection. We find that the observed IS abundances are compatible with a neutral scenario where IS proliferation is controlled by deletions instead of purifying selection. Even if there may be some cases driven by selection, neutral behavior dominates over large evolutionary scales. According to this view, IS and hosts tend to coexist in a dynamic equilibrium state for most of the time. Our approach also allows for a detection of recent IS expansions, and supports the hypothesis that rapid expansions constitute transient events—punctuations—during which the state of coexistence of IS and host becomes perturbated.     

Single ion channel models incorporating aggregation and time interval omission.

We present a general theoretical framework, incorporating both aggregation of states into classes and time interval omission, for stochastic modeling of the dynamic aspects of single channel behavior. Our semi-Markov models subsume the standard continuous-time Markov models, diffusion models and fractal models. In particular our models allow for quite general distributions of state sojourn times and arbitrary correlations between successive sojourn times. Another key feature is the invariance of our framework with respect to time interval omission: that is, properties of the aggregated process incorporating time interval omission can be derived directly from corresponding properties of the process without it. Even in the special case when the underlying process is Markov, this leads to considerable clarification of the effects of time interval omission. Among the properties considered are equilibrium behavior, sojourn time distributions and their moments, and auto-correlation and cross-correlation functions. The theory is motivated by ion channel mechanisms drawn from the literature, and illustrated by numerical examples based on these.     

Coexistence of multiple propagating wave-fronts in a regulated enzyme reaction model: link with birhythmicity and multi-threshold excitability

We analyze the spatial propagation of wave-fronts in a biochemical model for a product-activated enzyme reaction with non-linear recycling of product into substrate. This model was previously studied as a prototype for the coexistence of two distinct types of periodic oscillations (birhythmicity). The system is initially in a stable steady state characterized by the property of multi-threshold excitability, by which it is capable of amplifying in a pulsatory manner perturbations exceeding two distinct thresholds. In such conditions, when the effect of diffusion is taken into account, two distinct wave-fronts are shown to propagate in space, with distinct amplitudes and velocities, for the same set of parameter values, depending on the magnitude of the initial perturbation. Such a multiplicity of propagating wave-fronts represents a new type of coexistence of multiple modes of dynamic behavior, besides the coexistence involving, under spatially homogeneous conditions, multiple steady states, multiple periodic regimes, or a combination of steady and periodic regimes.     

Coexistence of memory patterns and mixed states in a sparsely encoded associative memory model storing ultrametric patterns

Analyzing the coexistence of memory patterns and mixed states gives important information for constructing a model for the face responsive neurons of the monkey inferior-temporal cortex. We analyzed whether the memory patterns coexist with mixed states when the sparse coding scheme is used for the associative memory model storing ultrametric patterns. For memory patterns and mixed states to coexist, there must be sufficient capacity for storing them and their threshold values must be the same. We determined that the storage capacities for all mixed states composed of correlated memory patterns diverge as 1/|flogf| (where f is the firing rate) even when the correlation of the memory patterns is infinitesimally small. We also determined that the memory patterns and the mixed states can become the equilibrium state of the model in the same threshold value. These results mean that they can coexist in this model. These findings should contribute to research on face responsive neurons in the monkey inferior-temporal cortex.