Stochastic Modeling for the Expression of a Gene Regulated by Competing Transcription Factors

It is widely accepted that gene expression regulation is a stochastic event. The common approach for its computer simulation requires detailed information on the interactions of individual molecules, which is often not available for the analyses of biological experiments. As an alternative approach, we employed a more intuitive model to simulate the experimental result, the Markov-chain model, in which a gene is regulated by activators and repressors, which bind the same site in a mutually exclusive manner. Our stochastic simulation in the presence of both activators and repressors predicted a Hill-coefficient of the dose-response curve closer to the experimentally observed value than the calculated value based on the simple additive effects of activators alone and repressors alone. The simulation also reproduced the heterogeneity of gene expression levels among individual cells observed by Fluorescence Activated Cell Sorting analysis. Therefore, our approach may help to apply stochastic simulations to broader experimental data

Bistability versus Bimodal Distributions in Gene Regulatory Processes from Population Balance

In recent times, stochastic treatments of gene regulatory processes have appeared in the literature in which a cell exposed to a signaling molecule in its environment triggers the synthesis of a specific protein through a network of intracellular reactions. The stochastic nature of this process leads to a distribution of protein levels in a population of cells as determined by a Fokker-Planck equation. Often instability occurs as a consequence of two (stable) steady state protein levels, one at the low end representing the “off” state, and the other at the high end representing the “on” state for a given concentration of the signaling molecule within a suitable range. A consequence of such bistability has been the appearance of bimodal distributions indicating two different populations, one in the “off” state and the other in the “on” state. The bimodal distribution can come about from stochastic analysis of a single cell. However, the concerted action of the population altering the extracellular concentration in the environment of individual cells and hence their behavior can only be accomplished by an appropriate population balance model which accounts for the reciprocal effects of interaction between the population and its environment. In this study, we show how to formulate a population balance model in which stochastic gene expression in individual cells is incorporated. Interestingly, the simulation of the model shows that bistability is neither sufficient nor necessary for bimodal distributions in a population. The original notion of linking bistability with bimodal distribution from single cell stochastic model is therefore only a special consequence of a population balance model

Speed, Sensitivity, and Bistability in Auto-activating Signaling Circuits

Cells employ a myriad of signaling circuits to detect environmental signals and drive specific gene expression responses. A common motif in these circuits is inducible auto-activation: a transcription factor that activates its own transcription upon activation by a ligand or by post-transcriptional modification. Examples range from the two-component signaling systems in bacteria and plants to the genetic circuits of animal viruses such as HIV. We here present a theoretical study of such circuits, based on analytical calculations, numerical computations, and simulation. Our results reveal several surprising characteristics. They show that auto-activation can drastically enhance the sensitivity of the circuit's response to input signals: even without molecular cooperativity, an ultra-sensitive threshold response can be obtained. However, the increased sensitivity comes at a cost: auto-activation tends to severely slow down the speed of induction, a stochastic effect that was strongly underestimated by earlier deterministic models. This slow-induction effect again requires no molecular cooperativity and is intimately related to the bimodality recently observed in non-cooperative auto-activation circuits. These phenomena pose strong constraints on the use of auto-activation in signaling networks. To achieve both a high sensitivity and a rapid induction, an inducible auto-activation circuit is predicted to acquire low cooperativity and low fold-induction. Examples from Escherichia coli's two-component signaling systems support these predictions

The role of power in financial statement fraud schemes

In this paper, we investigate a large-scale financial statement fraud to better understand the process by which individuals are recruited to participate in financial statement fraud schemes. The case reveals that perpetrators often use power to recruit others to participate in fraudulent acts. To illustrate how power is used, we propose a model, based upon the classical French and Raven taxonomy of power, that explains how one individual influences another individual to participate in financial statement fraud. We also provide propositions for future research

The Germinal Center Kinase GCK-1 Is a Negative Regulator of MAP Kinase Activation and Apoptosis in the C. elegans Germline

The germinal center kinases (GCK) constitute a large, highly conserved family of proteins that has been implicated in a wide variety of cellular processes including cell growth and proliferation, polarity, migration, and stress responses. Although diverse, these functions have been attributed to an evolutionarily conserved role for GCKs in the activation of ERK, JNK, and p38 MAP kinase pathways. In addition, multiple GCKs from different species promote apoptotic cell death. In contrast to these paradigms, we found that a C. elegans GCK, GCK-1, functions to inhibit MAP kinase activation and apoptosis in the C. elegans germline. In the absence of GCK-1, a specific MAP kinase isoform is ectopically activated and oocytes undergo abnormal development. Moreover, GCK-1- deficient animals display a significant increase in germ cell death. Our results suggest that individual germinal center kinases act in mechanistically distinct ways and that these functions are likely to depend on organ- and developmental-specific contexts

INFLUENCE OF METAL GRAIN-SIZE ON SURFACE-ENHANCED RAMAN-SCATTERING

The surface roughness of nominally smooth and of randomly roughened thin silver films is characterized using scanning tunneling microscopy and the metal grain size is assessed using transmission electron microscopy. On each type of substrate used, glass or CaF2-roughened glass, the silver films are deposited either very slowly (approximately 0.15 nm s-1) or quite quickly (approximately 2.0 nm s-1). Only silver films deposited on CaF2-roughened glass yield measurable surface-enhanced Raman signals for benzoic acid; the enhancement is brought about by surface field amplification due to the excitation of delocalized surface-plasmon polaritons. However, the surface-enhanced Raman signals obtained from the slow-deposited silver films are significantly better (by about a factor of 3) than those obtained from the fast-deposited silver films on a given CaF2-roughened substrate. The explanation of this observation does not lie with different surface roughness; both types of film yield closely similar data on the scanning tunneling microscope. Rather, it is suggested that the relatively small grain size of the fast-deposited silver films leads to increased elastic scattering of surface-plasmon polaritons at the grain boundaries, with a consequent increase of internal damping. This results in a reduction of the scattered Raman signal.</p