Biomedical subjects

C Jayaprakash

Publications and source records attributed to C Jayaprakash.

At least 19 recordsLinked to original sources

PubMed2005

NF-kappaB oscillations and cell-to-cell variability.

Oscillations in the transcriptional activator NF-kappaB localized in the nucleus have been observed when a cell is stimulated by an external agent. A negative feedback based on the protein IkappaB whose expression is controlled by NF-kappaB is known to be responsible for these oscillations. We study NF-kappaB oscillations, which have been observed both for cell populations by Hoffmann et al. [2002. The IkappaB-NF-kappaB signaling module: temporal control and selective gene activation. Science 298, 1241-1245] and for single cells by Nelson et al. [2004. Oscillations in NF-kappaB signaling control the dynamics of gene expression. Science 306, 704-708]. In order to study cell-to-cell variability we use Gillespie's algorithm, applied to a simplified version of the model proposed by Hoffmann et al. (2002). We consider the amounts of cellular NF-kappaB and activated IKK as external parameters. When these are fixed, we show that intrinsic fluctuations are small in a model with strong transcription, as is the case of the Hoffmann et al. (2002) model, whether transcription is quadratic or linear in the number of NF-kappaB molecules. Intrinsic fluctuations can however be large when transcription is weak, as we illustrate in a model variant. The effect of extrinsic fluctuations can be significant: cell-to-cell fluctuations of the initial amount of cellular NF-kappaB affect mainly the amplitude of nuclear NF-kappaB oscillations, at least when transcription is linear in the number of NF-kappaB molecules, while fluctuations in the amount of activated IKK affect both their amplitude and period, whatever the mode of transcription. In this case model results are in qualitative agreement with the considerable cell-to-cell variability of NF-kappaB oscillations observed by Nelson et al. (2004).

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PubMed2005

A feedforward loop motif in transcriptional regulation: induction and repression.

We study the dynamical behavior of a unit of three positive transcriptional regulators which occurs frequently in biological networks of yeast and bacteria as a feedforward loop. We investigate numerically a set of reactions incorporating the basic features of transcription and translation. We determine (i) how the feedforward loop motif functions as a computational element such as an AND gate in the presence of stochastic fluctuations, and (ii) the robustness of the motif when transcription at the primary level is suddenly repressed. We highlight the effective time-scales which underlie both of these aspects of the feedforward loop motif. We show how threshold behavior of the motif output arises as a function of the number of external inducers as well as the time over which the inducer acts. We discuss how individual cell behavior can deviate significantly from average behavior, due to intrinsic fluctuations in the small number of molecules present in a cell.

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PubMed2004

The linear noise approximation for molecular fluctuations within cells.

We study the applicability of Van Kampen's linear noise approximation to the calculation of fluctuations in cells due to small number of molecules for simple genetic systems not previously considered. These systems include dimer formation and feedback. We explain why the linear noise approximation can be surprisingly effective, but also illustrate how it fails in a simple example when a protein probability distribution is not purely Gaussian.

Cells↗

PubMed2003

The role of dimerization in noise reduction of simple genetic networks.

Fluctuations are an intrinsic property of genetic networks due to the small number of interacting molecules. We study the role of dimerization reactions in controlling these fluctuations in a simple genetic circuit with negative feedback. We compare two different pathways. In the dimeric pathway the proteins to be regulated form dimers in solution that afterward bind to an operator site and inhibit transcription. In the monomeric pathway monomers bind to the operator site and then recruit another monomer to form a dimer directly on the DNA. We find that while both pathways implement the same negative feedback mechanism, the protein number fluctuations in the dimeric pathway are drastically reduced compared to the monomeric pathway. This difference in the ability to reduce fluctuations may be of importance in the design of genetic networks.

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PubMed2003

Fluctuations and slow variables in genetic networks.

Computer simulations of large genetic networks are often extremely time consuming because, in addition to the biologically interesting translation and transcription reactions, many less interesting reactions like DNA binding and dimerizations have to be simulated. It is desirable to use the fact that the latter occur on much faster timescales than the former to eliminate the fast and uninteresting reactions and to obtain effective models of the slow reactions only. We use three examples of self-regulatory networks to show that the usual reduction methods where one obtains a system of equations of the Hill type fail to capture the fluctuations that these networks exhibit due to the small number of molecules; moreover, they may even miss describing the behavior of the average number of proteins. We identify the inclusion of fast-varying variables in the effective description as the cause for the failure of the traditional schemes. We suggest a different effective description, which entails the introduction of an additional species, not present in the original networks, that is slowly varying. We show that this description allows for a very efficient simulation of the reduced system while retaining the correct fluctuations and behavior of the full system. This approach ought to be applicable to a wide range of genetic networks.

Adaptation, Physiological↗

PubMed2002

Scale-invariant behavior in a spatial game of prisoners' dilemma.

A spatially extended version of the game of prisoner's dilemma, originally proposed by Nowak and May, is modified to include stochastic updating and found to exhibit scale-invariant behavior. Two critical regimes with different scaling behaviors are found; the corresponding exponents have been determined numerically. Spatially, the critical states are characterized by the existence of delicately balanced networks of defectors separating domains of cooperators; temporally, the evolution of the critical states following local perturbations is characterized by avalanches of various magnitudes, which cause restructuring of the networks of defectors on all scales.

Journal Article↗

PubMed2001

Synchronization in relaxation oscillator networks with conduction delays.

We study locally coupled networks of relaxation oscillators with excitatory connections and conduction delays and propose a mechanism for achieving zero phase-lag synchrony. Our mechanism is based on the observation that different rates of motion along different nullclines of the system can lead to synchrony in the presence of conduction delays. We analyze the system of two coupled oscillators and derive phase compression rates. This analysis indicates how to choose nullclines for individual relaxation oscillators in order to induce rapid synchrony. The numerical simulations demonstrate that our analytical results extend to locally coupled networks with conduction delays and that these networks can attain rapid synchrony with appropriately chosen nullclines and initial conditions. The robustness of the proposed mechanism is verified with respect to different nullclines, variations in parameter values, and initial conditions.

Animals↗

PubMed1999

Synchrony and desynchrony in integrate-and-fire oscillators.

Due to many experimental reports of synchronous neural activity in the brain, there is much interest in understanding synchronization in networks of neural oscillators and its potential for computing perceptual organization. Contrary to Hopfield and Herz (1995), we find that networks of locally coupled integrate-and-fire oscillators can quickly synchronize. Furthermore, we examine the time needed to synchronize such networks. We observe that these networks synchronize at times proportional to the logarithm of their size, and we give the parameters used to control the rate of synchronization. Inspired by locally excitatory globally inhibitory oscillator network (LEGION) dynamics with relaxation oscillators (Terman & Wang, 1995), we find that global inhibition can play a similar role of desynchronization in a network of integrate-and-fire oscillators. We illustrate that a LEGION architecture with integrate-and-fire oscillators can be similarly used to address image analysis.

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PubMed1996