Two G-proteins act in series to control stimulus-secretion coupling in mast cells: use of neomycin to distinguish between G-proteins controlling polyphosphoinositide phosphodiesterase and exocytosis

Provision of GTP (or other nucleotides capable of acting as ligands for activation of G-proteins) together with Ca2+ (at micromolar concentrations) is both necessary and sufficient to stimulate exocytotic secretion from mast cells permeabilized with streptolysin-O. GTP and its analogues, through their interactions with Gp, also activate polyphosphoinositide-phosphodiesterase (PPI-pde generating inositol 1,4,5-trisphosphate and diglyceride [DG]). We have used mast cells labeled with [3H]inositol to test whether the requirement for GTP in exocytosis is an expression of Gp activity through the generation of DG and consequent activation of protein kinase C, or whether GTP is required at a later stage in the stimulus secretion sequence. Neomycin (0.3 mM) inhibits activation of PPI-pde, but maximal secretion due to optimal concentrations of guanosine 5'-O-(3-thiotriphosphate) (GTP-gamma-S) can still be evoked in its presence. When ATP is also provided the concentration requirement for GTP-gamma-S in support of exocytosis is reduced. This sparing effect of ATP is nullified when the PPI-pde reaction is inhibited by neomycin. We argue that the sparing effect of ATP occurs as a result of enhancement of DG production and through its action as a phosphoryl donor in the reactions catalyzed by protein kinase C

Magic number 7 ±\pm 2 in networks of threshold dynamics

Information processing by random feed-forward networks consisting of units with sigmoidal input-output response is studied by focusing on the dependence of its outputs on the number of parallel paths M. It is found that the system leads to a combination of on/off outputs when $M \lesssim 7$, while for $M \gtrsim 7$, chaotic dynamics arises, resulting in a continuous distribution of outputs. This universality of the critical number $M \sim 7$ is explained by combinatorial explosion, i.e., dominance of factorial over exponential increase. Relevance of the result to the psychological magic number $7 \pm 2$ is briefly discussed.Comment: 6 pages, 5 figure

A Minimal Model of Signaling Network Elucidates Cell-to-Cell Stochastic Variability in Apoptosis

Signaling networks are designed to sense an environmental stimulus and adapt to it. We propose and study a minimal model of signaling network that can sense and respond to external stimuli of varying strength in an adaptive manner. The structure of this minimal network is derived based on some simple assumptions on its differential response to external stimuli. We employ stochastic differential equations and probability distributions obtained from stochastic simulations to characterize differential signaling response in our minimal network model. We show that the proposed minimal signaling network displays two distinct types of response as the strength of the stimulus is decreased. The signaling network has a deterministic part that undergoes rapid activation by a strong stimulus in which case cell-to-cell fluctuations can be ignored. As the strength of the stimulus decreases, the stochastic part of the network begins dominating the signaling response where slow activation is observed with characteristic large cell-to-cell stochastic variability. Interestingly, this proposed stochastic signaling network can capture some of the essential signaling behaviors of a complex apoptotic cell death signaling network that has been studied through experiments and large-scale computer simulations. Thus we claim that the proposed signaling network is an appropriate minimal model of apoptosis signaling. Elucidating the fundamental design principles of complex cellular signaling pathways such as apoptosis signaling remains a challenging task. We demonstrate how our proposed minimal model can help elucidate the effect of a specific apoptotic inhibitor Bcl-2 on apoptotic signaling in a cell-type independent manner. We also discuss the implications of our study in elucidating the adaptive strategy of cell death signaling pathways.Comment: 9 pages, 6 figure

A variational approach to the stochastic aspects of cellular signal transduction

Cellular signaling networks have evolved to cope with intrinsic fluctuations, coming from the small numbers of constituents, and the environmental noise. Stochastic chemical kinetics equations govern the way biochemical networks process noisy signals. The essential difficulty associated with the master equation approach to solving the stochastic chemical kinetics problem is the enormous number of ordinary differential equations involved. In this work, we show how to achieve tremendous reduction in the dimensionality of specific reaction cascade dynamics by solving variationally an equivalent quantum field theoretic formulation of stochastic chemical kinetics. The present formulation avoids cumbersome commutator computations in the derivation of evolution equations, making more transparent the physical significance of the variational method. We propose novel time-dependent basis functions which work well over a wide range of rate parameters. We apply the new basis functions to describe stochastic signaling in several enzymatic cascades and compare the results so obtained with those from alternative solution techniques. The variational ansatz gives probability distributions that agree well with the exact ones, even when fluctuations are large and discreteness and nonlinearity are important. A numerical implementation of our technique is many orders of magnitude more efficient computationally compared with the traditional Monte Carlo simulation algorithms or the Langevin simulations.Comment: 15 pages, 11 figure

Quantification of Cytokeratin 5 mRNA Expression in the Circulation of Healthy Human Subjects and after Lung Transplantation

Circulating epithelial progenitor cells are important for repair of the airway epithelium in a mouse model of tracheal transplantation. We therefore hypothesized that circulating epithelial progenitor cells would also be present in normal human subjects and could be important for repair of the airway after lung injury. As lung transplantation is associated with lung injury, which is severe early on and exacerbated during episodes of infection and rejection, we hypothesized that circulating epithelial progenitor cell levels could predict clinical outcome following lung transplantation.Quantitative Real Time PCR was performed to determine peripheral blood mRNA levels of cytokeratin 5, a previously characterized marker of circulating epithelial progenitor cells. Cytokeratin 5 levels were evaluated in healthy human subjects, in lung transplant recipients immediately post-transplant and serially thereafter, and in heart transplant recipients. All normal human subjects examined expressed cytokeratin 5 in their buffy coat in amounts that were not significantly influenced by age or gender. There was a profound, statistically significant decrease in cytokeratin 5 mRNA expression levels in lung transplant patients compared to healthy human subjects (p = 3.1x10(-13)) and to heart transplant recipients. There was a moderate negative correlation between improved circulating cytokeratin 5 mRNA levels in lung transplant recipients with recovering lung function, as measured by improved FEV1 values (rho = -0.39).Levels of cytokeratin 5 mRNA, a proxy marker for circulating epithelial progenitor cells, inversely correlated with disease status in lung transplant recipients. It may therefore serve as a biomarker of the clinical outcome of lung transplant patients and potentially other patients with airway injury

Effects of Plasma HIV RNA, CD4+ T Lymphocytes, and the Chemokine Receptors CCR5 and CCR2b on HIV Disease Progression in Hemophiliacs

We have investigated the effects of plasma HIV RNA, CD4+ T lymphocytes and chemokine receptors CCR5 and CCR2b on HIV disease progression in hemophiliacs. We prospectively observed during follow-up 207 HIV-infected hemophiliacs in the Hemophilia Growth and Development Study. Plasma HIV RNA was measured on cryopreserved plasma from enrollment using the Chiron Corporation bDNA (version 2.0) assay. Genotype variants CCR2b-641 and CCR5-Δ32 were detected using standard molecular techniques. Those with the mutant allele for CCR2b, and to a lesser extent CCR5, had lower plasma HIV RNA, and higher CD4+ T lymphocytes than did those without these genetic variants. After controlling for the effects of plasma HIV RNA and CD4+ T lymphocytes, those with the CCR2b mutant allele compared with those wild-type, had a trend toward a lower risk of progression to AIDS, adjusted relative hazard of 1.94 (95% confidence interval [CI], 0.9-4.18; p = .092), and AIDS-related death, relative hazard 1.97 (95% CI, 0.98-4.00; p = .059). We conclude that plasma HIV RNA, CD4+ T lymphocytes, and CCR genotypes are correlated, and the protective affect of CCR2b against HIV disease progression is not completely explained by plasma HIV RNA or CD4+ T-lymphocyte number

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.Comment: 25 page