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Kunihiko Kaneko

Publications and source records attributed to Kunihiko Kaneko.

At least 127 records · Page 7Linked to original sources

Evolution of Robustness to Noise and Mutation in Gene Expression Dynamics

Phenotype of biological systems needs to be robust against mutation in order to sustain themselves between generations. On the other hand, phenotype of an individual also needs to be robust against fluctuations of both internal and external origins that are encountered during growth and development. Is there a relationship between these two types of robustness, one during a single generation and the other during evolution? Could stochasticity in gene expression have any relevance to the evolution of these robustness? Robustness can be defined by the sharpness of the distribution of phenotype; the variance of phenotype distribution due to genetic variation gives a measure of `genetic robustness' while that of isogenic individuals gives a measure of `developmental robustness'. Through simulations of a simple stochastic gene expression network that undergoes mutation and selection, we show that in order for the network to acquire both types of robustness, the phenotypic variance induced by mutations must be smaller than that observed in an isogenic population. As the latter originates from noise in gene expression, this signifies that the genetic robustness evolves only when the noise strength in gene expression is larger than some threshold. In such a case, the two variances decrease throughout the evolutionary time course, indicating increase in robustness. The results reveal how noise that cells encounter during growth and development shapes networks' robustness to stochasticity in gene expression, which in turn shapes networks' robustness to mutation. The condition for evolution of robustness as well as relationship between genetic and developmental robustness is derived through the variance of phenotypic fluctuations, which are measurable experimentally.

q-bio.PE↗

Switching Dynamics in Reaction Networks Induced by Molecular Discreteness

To study the fluctuations and dynamics in chemical reaction processes, stochastic differential equations based on the rate equation involving chemical concentrations are often adopted. When the number of molecules is very small, however, the discreteness in the number of molecules cannot be neglected since the number of molecules must be an integer. This discreteness can be important in biochemical reactions, where the total number of molecules is not significantly larger than the number of chemical species. To elucidate the effects of such discreteness, we study autocatalytic reaction systems comprising several chemical species through stochastic particle simulations. The generation of novel states is observed; it is caused by the extinction of some molecular species due to the discreteness in their number. We demonstrate that the reaction dynamics are switched by a single molecule, which leads to the reconstruction of the acting network structure. We also show the strong dependence of the chemical concentrations on the system size, which is caused by transitions to discreteness-induced novel states.

physics.chem-ph↗

Evolution Equation of Phenotype Distribution: General Formulation and Application to Error Catastrophe

An equation describing the evolution of phenotypic distribution is derived using methods developed in statistical physics. The equation is solved by using the singular perturbation method, and assuming that the number of bases in the genetic sequence is large. Applying the equation to the mutation-selection model by Eigen provides the critical mutation rate for the error catastrophe. Phenotypic fluctuation of clones (individuals sharing the same gene) is introduced into this evolution equation. With this formalism, it is found that the critical mutation rate is sometimes increased by the phenotypic fluctuations, i.e., noise can enhance robustness of a fitted state to mutation. Our formalism is systematic and general, while approximations to derive more tractable evolution equations are also discussed.

q-bio.PE↗

On a Condition for Intracellular Adaptive Dynamics for Chemotaxis

Microorganisms often perform chemotaxis, (i.e., sensing and moving toward a region with a higher concentration of an attractive chemical) by changing the rate of tumbling for random walk. We studied several models with internal adaptive dynamics numerically to examine the validity of the condition for chemotaxis proposed by Oosawa and Nakaoka, which states that the time scale of tumbling frequency is smaller than that of adaptation and greater than that of sensing. Suitably renormalizing the timescales showed that the condition holds for a variety of environments and for both short- and long-term behavior.

cond-mat.stat-mech↗

On the Distribution of State Values of Reproducing Cells: the General Evolution Equation and its Applications

Fluctuations of cell state, e.g., abundances of some proteins, have attracted much attention both theoretically and experimentally. The distribution of such state over cells, however, is not only a result of intracellular stochastic process, but is also influenced by the growth in cell numbers that depends on the state. By incorporating the growth-death process into the standard Fokker--Planck equation for the probability distribution, a nonlinear temporal evolution equation of distribution is obtained that includes a self-consistent growth term. The derived equation is generally solved analytically by means of eigenfunction expansions. By focusing on the case with linear relaxation, two examples are considered as applications of the proposed general formalism. First, by assuming that the growth rate of a cell increases linearly with the state value $x$, the shift of the average state value $x$ due to the growth effect is shown to be proportional to the variance of the state $x$ and the relaxation time, similarly with the biological fluctuation- response relationship. Second, when there is a gap in the growth rate at some threshold value for the state $x$, existence of a critical gap value is demonstrated, beyond which the average growth rate starts to increase. This critical value is again obtained in terms of the relaxation time and the variance of $x$, all of which are experimentally measurable quantities. The relevance of the results to the analysis of biological data on the distribution of cell states, as obtained for example by flow cytometry, is discussed.

physics.bio-ph↗

Turing Pattern with Proportion Preservation

Although Turing pattern is one of the most universal mechanisms for pattern formation, in its standard model the number of stripes changes with the system size, since the wavelength of the pattern is invariant: It fails to preserve the proportionality of the pattern, i.e., the ratio of the wavelength to the size, that is often required in biological morphogeneis. To get over this problem, we show that the Turing pattern can preserve proportionality by introducing a catalytic chemical whose concentration depends on the system size. Several plausible mechanisms for such size dependence of the concentration are discussed. Following this general discussion, two models are studied in which arising Turing patterns indeed preserve the proportionality. Relevance of the present mechanism to biological morphogenesis is discussed from the viewpoint of its generality, robustness, and evolutionary accessibility.

q-bio.CB↗

Collective motion in a Hamiltonian dynamical system

Oscillation of macroscopic variables is discovered in a metastable state in the Hamiltonian dynamical system of mean field XY model, the duration of which is divergent with the system size. This long-lasting periodic or quasiperiodic collective motion appears through Hopf bifurcation, which is a typical route in low-dimensional dissipative dynamical systems. The origin of the oscillation is explained, with self-consistent analysis of the distribution function, as the emergence of self-excited ``swings'' through the mean-field. The universality of the phenomena is also discussed.

cond-mat.stat-mech↗

Diversity as a product of interspecial interactions

We demonstrate diversification rather than optimisation for highly interacting organisms in a well mixed biological system by means of a simple model and reference to experiment, and find the cause to be the complex network of interactions formed, allowing species less well adapted to an environment to flourish by co-interaction over the `best' species. This diversification can be considered as the construction of many co-evolutionary niches by the network of interactions between species. Evidence for this comes from work with the bacteria Escherichia coli, which may coexist with their own mutants under certain conditions. Diversification only occurs above a certain threshold interaction strength, below which competitive exclusion occurs.

q-bio.PE↗

Evolutionary origin of power-laws in Biochemical Reaction Network; embedding abundance distribution into topology

The evolutionary origin of universal statistics in biochemical reaction network is studied, to explain the power-law distribution of reaction links and the power-law distributions of chemical abundances. Using cell models with catalytic reaction network, we find evidence that the power-law distribution in abundances of chemicals emerges by the selection of cells with higher growth speeds. Through the further evolution, this inhomogeneity in chemical abundances is shown to be embedded in the distribution of links, leading to the power-law distribution. These findings provide novel insights into the nature of network evolution in living cells.

q-bio.PE↗

On Recursive Production and Evolvabilty of Cells: Catalytic Reaction Network Approach

To unveil the logic of cell from a level of chemical reaction dynamics, we need to clarify how ensemble of chemicals can autonomously produce the set of chemical, without assuming a specific external control echanism. A cell consists of a huge number of chemical species that catalyze each other. Often the number of each molecule species is not so large, and accordingly the number fluctuations in each molecule speciescan be large. In the amidst of such diversity and large fluctuations, how can a cell make recursive production? On the other hand, a cell can change its state to evolve to a different type over a longer time span. How are reproduction and evolution compatible? We address these questions, based on several model studies with catalytic reaction network. In the present survey paper, we first formulate basic questions on the recursiveness and evolvability of a cell, and then state the standpoint of our research to answer the questions, that is termed as 'constructive biology'. Based on this standpoint, we present general strategy of modeling a cell as a chemical reaction network.

q-bio.MN↗

Inter-Intra Molecular Dynamics as an Iterated Function System

The dynamics of units (molecules) with slowly relaxing internal states is studied as an iterated function system (IFS) for the situation common in e.g. biological systems where these units are subjected to frequent collisional interactions. It is found that an increase in the collision frequency leads to successive discrete states that can be analyzed as partial steps to form a Cantor set. By considering the interactions among the units, a self-consistent IFS is derived, which leads to the formation and stabilization of multiple such discrete states. The relevance of the results to dynamical multiple states in biomolecules in crowded conditions is discussed.

cond-mat.soft↗

Ubiquity of Log-normal Distributions in Intra-cellular Reaction Dynamic

The discovery of two fundamental laws concerning cellular dynamics with recursive growth is reported. First, the chemical abundances measured over many cells are found to obey a log-normal distribution and second, the relationship between the average and standard deviation of the abundances is found to be linear. The ubiquity of the laws is explored both theoretically and experimentally. First by means of a model with a catalytic reaction network, the laws are shown to appear near the critical state with efficient self-reproduction. Second by measuring distributions of fluorescent proteins in bacteria cells the ubiquity of log-normal distribution of protein abundances is confirmed. Relevance of these findings to cellular function and biological plasticity is briefly discussed.

q-bio.MN↗

Discreteness-Induced Transitions in Autocatalytic Systems

To study the dynamics of chemical processes, we often adopt rate equations to observe the change in chemical concentrations. However, when the number of the molecules is small, the fluctuations cannot be neglected. We often study the effects of fluctuations with the help of stochastic differential equations. Chemicals are composed of molecules on a microscopic level. In principle, the number of molecules must be an integer, which must only change discretely. However, in analysis using stochastic differential equations, the fluctuations are regarded as continuous changes. This approximation can only be valid if applied to fluctuations that involve a sufficiently large number of molecules. In the case of extremely rare chemical species, the actual discreteness of the molecules may critically affect the dynamics of the system. To elucidate the effects of the discreteness, we study an autocatalytic system consisting of several interacting chemical species with a small number of molecules through stochastic particle simulations. We found novel states, which were characterized as an extinction of molecule species, due to the discrete nature of the molecules. We also observed a strong dependence of the chemical concentrations on the size of the system, which was caused by transitions to the novel states.

physics.chem-ph↗

Discreteness-induced Stochastic Steady State in Reaction Diffusion Systems: Self-consistent Analysis and Stochastic Simulations

A self-consistent equation to derive a discreteness-induced stochastic steady state is presented for reaction-diffusion systems. For this formalism, we use the so-called Kuramoto length, a typical distance over which a molecule diffuses in its lifetime, as was originally introduced to determine if local fluctuations influence globally the whole system. We show that this Kuramoto length is also relevant to determine whether the discreteness of molecules is significant or not. If the number of molecules of a certain species within the Kuramoto length is small and discrete, localization of some other chemicals is brought about, which can accelerate certain reactions. When this acceleration influences the concentration of the original molecule species, it is shown that a novel, stochastic steady state is induced that does not appear in the continuum limit. A theory to obtain and characterize this state is introduced, based on the self-consistent equation for chemical concentrations. This stochastic steady state is confirmed by numerical simulations on a certain reaction model, which agrees well with the theoretical estimation. Formation and coexistence of domains with different stochastic states are also reported, which is maintained by the discreteness. Relevance of our result to intracellular reactions is briefly discussed.

physics.chem-ph↗

Molecular Discreteness in Reaction-Diffusion Systems Yields Steady States Not Seen in the Continuum Limit

We investigate the effects of spatial discreteness of molecules in reaction-diffusion systems. It is found that discreteness within the so called Kuramoto length can lead to a localization of molecules, resulting in novel steady states that do not exist in the continuous case. These novel states are analyzed theoretically as the fixed points of accelerated localized reactions, an approach that was verified to be in good agreement with stochastic particle simulations. The relevance of this discreteness-induced state to biological intracellular processes is discussed.

physics.chem-ph↗

Roundabout relaxation: collective excitation requires a detour to equilibrium

Relaxation to equilibrium after strong and collective excitation is studied, by using a Hamiltonian dynamical system of one dimensional XY model. After an excitation of a domain of $K$ elements, the excitation is concentrated to fewer elements, which are made farther away from equilibrium, and the excitation intensity increases logarithmically with $K$. Equilibrium is reached only after taking this ``roundabout'' route, with the time for relaxation diverging asymptotically as $K^γ$ with $γ\approx 4.2$.

cond-mat.stat-mech↗

Dynamical Systems Basis of Metamorphosis: Diversity and Plasticity of Cellular States in Reaction Diffusion Network

Dynamics maintaining diversity of cell types in a multi-cellular system are studied in relationship with the plasticity of cellular states. By adopting a simple theoretical framework for intra-cellular chemical reaction dynamics with considering the division and death of cells, developmental process from a single cell is studied. Cell differentiation process is found to occur through instability in transient dynamics and cell-cell interaction. In a long time behavior, extinction of multiple cells is repeated, which leads to itinerancy over successive quasi-stable multi-cellular states consisting of different types of cells. By defining the plasticity of a cellular state, it is shown that the plasticity of cells decreases before the large extinction, from which diversity and plasticity are recovered. After this switching, decrease of plasticity again occurs, leading to the next extinction of multiple cells. This cycle of diversification and extinction is repeated. Relevance of our results to the development and evolution is briefly discussed.

q-bio.CB↗

Is relaxation to equilibrium hindered by transient dissipative structures in closed systems?

Dissipative structures are generally observed when a system relaxes from a far from equilibrium state. To address the reverse question given by the title, we investigate the relaxation process in a closed chemical reaction-diffusion system which can potentially form Turing-like patterns during the transient. We find that when certain conditions are fulfilled the relaxation process is indeed drastically hindered, once the pattern is formed. This slowing-down is shown to be due to stepwise relaxation, where each plateau in the relaxation process corresponds to residence at a certain spatial pattern. Universality of the phenomena as well as their biological relevance is briefly discussed.

nlin.PS↗