Constructive role of noise in signal transmissions by biomembrane proteins (original) (raw)
Related papers
2009
Noise biology focuses on the sources, processing, and biological consequences of the inherent stochastic fluctuations in molecular transitions or interactions that control cellular behavior. These fluctuations are especially pronounced in small systems where the magnitudes of the fluctuations approach or exceed the mean value of the molecular population. Noise biology is an essential component of nanomedicine where the communication of information is across a boundary that separates small synthetic and biological systems that are bound by their size to reside in environments of large fluctuations. Here we review the fundamentals of the computational, analytical, and experimental approaches to noise biology. We review results that show that the competition between the benefits of low noise and those of low population has resulted in the evolution of genetic system architectures that produce an uneven distribution of stochasticity across the molecular components of cells and, in some cases, use noise to drive biological function. We review the exact and approximate approaches to gene circuit noise analysis and simulation, and review many of the key experimental results obtained using flow cytometry and time-lapse fluorescent microscopy. In addition, we consider the probative value of noise with a discussion of using measured noise properties to elucidate the structure and function of the underlying gene circuit. We conclude with a discussion of the frontiers of and significant future challenges for noise biology.
Noise effects in nonlinear biochemical signaling
Physical Review E, 2012
It has been generally recognized that stochasticity can play an important role in the information processing accomplished by reaction networks in biological cells. Most treatments of that stochasticity employ Gaussian noise even though it is a priori obvious that this approximation can violate physical constraints, such as the positivity of chemical concentrations. Here, we show that even when such nonphysical fluctuations are rare, an exact solution of the Gaussian model shows that the model can yield unphysical results. This is done in the context of a simple incoherent-feedforward model which exhibits perfect adaptation in the deterministic limit. We show how one can use the natural separation of time scales in this model to yield an approximate model, that is analytically solvable, including its dynamical response to an environmental change. Alternatively, one can employ a cutoff procedure to regularize the Gaussian result. PACS numbers: 02.50.Le, 05.65.+b, 87.23.Ge, 87.23.Kg I. INTRODUCTION The role of stochasticity in the functioning of cellular signal transduction networks is a question of great topical interest [1]. Unlike typical condensed-matter systems, biological cells must carry out chemical manipulations with small numbers of molecules, an inherently noisy situation. Noise comes in a variety of forms, including fluctuations in chemicals to be sensed [2], fluctuations in the binding-unbinding of receptor arrays [3], fluctuations during the processing of information [4], and fluctuations in the implementation of downstream actions [5].
The role of noise in some physical and biological systems
2003
A short review of our recent research involving the role of noise in a variety of systems is given. Two classes of problems are discussed. The first is the effect of fluctuations on cellular and intercellular calcium oscillations. Oscillations in intracellular calcium ion concetrations are responsible for the regulation of a remarkable number of different cellular processes in the human body. Fluctuation effects taht are ignored in deterministic models of these oscillations are discussed.
Intrinsic biochemical noise in crowded intracellular conditions
The Journal of Chemical Physics, 2010
Biochemical reactions inside cells occur in conditions which are very different than those found in vitro. Two of the main characteristic features are the inherently stochastic nature of the reactions and the complex nondilute spatial environment in which they occur. In particular, it is known that the cell interior is crowded by a diverse range of macromolecules which though not participating in a given reaction they will necessarily influence the kinetics through the excluded volume effect and reduction of diffusion coefficients. Current approaches either totally ignore both characteristics of intracellular reactions or else they solely take into account the noisiness via the use of chemical master equations. The latter are valid for a well-stirred gas-phase chemical system and hence are not generally suited to probe kinetics in crowded conditions. We postulate a novel modification of the chemical master equation which enables us to calculate the effects of low to intermediate crowding on the magnitude of the intrinsic noise of intracellular biochemical reactions. The approach is validated for a reversible dimerization reaction in a simple model of a crowded membrane by means of Brownian dynamics. For the typical parameter values characteristic of crowding inside cells, we find that the lack of available volume induces a reduction in the noise intensity of the end products of the reaction and a simultaneous increase in the temporal correlations. This suggests that cells may exert some degree of control on the level of noise in biochemical networks via a purely physical nonspecific effect and that crowding is a source of intracellular colored noise.
Noise effects in two different biological systems
The European Physical Journal B, 2009
We investigate the role of the colored noise in two biological systems: (i) adults of Nezara viridula (L.) (Heteroptera: Pentatomidae), and (ii) polymer translocation. In the first system we analyze, by directionality tests, the response of N. viridula individuals to subthreshold signals plus noise in their mating behaviour. The percentage of insects that react to the subthreshold signal shows a nonmonotonic behaviour, characterized by the presence of a maximum, as a function of the noise intensity. This is the signature of the non-dynamical stochastic resonance phenomenon. By using a "soft" threshold model we find that the maximum of the input-output cross correlation occurs in the same range of noise intensity values for which the behavioural activation of the insects has a maximum. Moreover this maximum value is lowered and shifted towards higher noise intensities, compared to the case of white noise. In the second biological system the noise driven translocation of short polymers in crowded solutions is analyzed. An improved version of the Rouse model for a flexible polymer is adopted to mimic the molecular dynamics by taking into account both the interactions between adjacent monomers and the effects of a Lennard-Jones potential between all beads. The polymer dynamics is simulated in a two-dimensional domain by numerically solving the Langevin equations of motion in the presence of thermal fluctuations and a colored noise source. At low temperatures or for strong colored noise intensities the translocation process of the polymer chain is delayed. At low noise intensity, as the polymer length increases, we find a nonmonotonic behaviour for the mean first translocation time of the polymer centre of inertia. We show how colored noise influences the motion of short polymers, by inducing two different regimes of translocation in the dynamics of molecule transport.
Noise generation, amplification and propagation in chemotactic signaling systems of living cells
Biosystems, 2008
Theoretical considerations of stochastic signal transduction in living cells have revealed the gain-fluctuation relation, which provides a theoretical framework to describe quantitatively how noise is generated, amplified and propagated along a signaling cascade in living cells. We chose the chemotactic signaling of bacteria and eukaryotic cells as a typical example of noisy signal transduction and applied the gain-fluctuation relation to these signaling systems in order to analyze the effects of noise on signal transduction. Comparing our theoretical analysis with the experimental results of chemotaxis in bacteria Escherichia coli and eukaryote Dictyostelium discoideum revealed that noise in signal transduction systems limits the cells' chemotactic ability and contributes to their behavioral variability. Based on the kinetic properties of signaling molecules in living cells, the gain-fluctuation relation can quantitatively explain stochastic cellular behaviors.
Axonal noise as a source of synaptic variability
PLoS computational biology, 2014
Post-synaptic potential (PSP) variability is typically attributed to mechanisms inside synapses, yet recent advances in experimental methods and biophysical understanding have led us to reconsider the role of axons as highly reliable transmission channels. We show that in many thin axons of our brain, the action potential (AP) waveform and thus the Ca++ signal controlling vesicle release at synapses will be significantly affected by the inherent variability of ion channel gating. We investigate how and to what extent fluctuations in the AP waveform explain observed PSP variability. Using both biophysical theory and stochastic simulations of central and peripheral nervous system axons from vertebrates and invertebrates, we show that channel noise in thin axons (<1 µm diameter) causes random fluctuations in AP waveforms. AP height and width, both experimentally characterised parameters of post-synaptic response amplitude, vary e.g. by up to 20 mV and 0.5 ms while a single AP propagates in C-fibre axons. We show how AP height and width variabilities increase with a ¾ power-law as diameter decreases and translate these fluctuations into post-synaptic response variability using biophysical data and models of synaptic transmission. We find for example that for mammalian unmyelinated axons with 0.2 µm diameter (matching cerebellar parallel fibres) axonal noise alone can explain half of the PSP variability in cerebellar synapses. We conclude that axonal variability may have considerable impact on synaptic response variability. Thus, in many experimental frameworks investigating synaptic transmission through paired-cell recordings or extracellular stimulation of presynaptic neurons, causes of variability may have been confounded. We thereby show how bottom-up aggregation of molecular noise sources contributes to our understanding of variability observed at higher levels of biological organisation.
Control, exploitation and tolerance of intracellular noise
2002
insight review articles "For it is simply a fact of observation that the guiding principle in every cell is embodied in a single atomic association existing only in one copy (or sometimes two)-and a fact of observation that it results in producing events which are paragons of orderliness […] the situation is unprecedented, it is unknown anywhere else except in living matter.
International Journal of Modern Physics B, 2012
Rapid progress of experimental biology has provided a huge flow of quantitative data, which can be analyzed and understood only through the application of advanced techniques recently developed in theoretical sciences. On the other hand, synthetic biology enabled us to engineer biological models with reduced complexity. In this review we discuss that a multidisciplinary approach between this sciences can lead to deeper understanding of the underlying mechanisms behind complex processes in biology. Following the mini symposia "Noise and oscillations in biological systems" on Physcon 2011 we have collected different research examples from theoretical modeling, experimental and synthetic biology.