Noise regulation by quorum sensing in low mRNA copy number systems

<p>Abstract</p> <p>Background</p> <p>Cells must face the ubiquitous presence of noise at the level of signaling molecules. The latter constitutes a major challenge for the regulation of cellular functions including communication processes. In the context of prokaryotic communication, the so-called quorum sensing (QS) mechanism relies on small diffusive molecules that are produced and detected by cells. This poses the intriguing question of how bacteria cope with the fluctuations for setting up a reliable information exchange.</p> <p>Results</p> <p>We present a stochastic model of gene expression that accounts for the main biochemical processes that describe the QS mechanism close to its activation threshold. Within that framework we study, both numerically and analytically, the role that diffusion plays in the regulation of the dynamics and the fluctuations of signaling molecules. In addition, we unveil the contribution of different sources of noise, intrinsic and transcriptional, in the QS mechanism.</p> <p>Conclusions</p> <p>The interplay between noisy sources and the communication process produces a repertoire of dynamics that depends on the diffusion rate. Importantly, the total noise shows a non-monotonic behavior as a function of the diffusion rate. QS systems seems to avoid values of the diffusion that maximize the total noise. These results point towards the direction that bacteria have adapted their communication mechanisms in order to improve the signal-to-noise ratio.</p

Computation of Steady-State Probability Distributions in Stochastic Models of Cellular Networks

Cellular processes are “noisy”. In each cell, concentrations of molecules are subject to random fluctuations due to the small numbers of these molecules and to environmental perturbations. While noise varies with time, it is often measured at steady state, for example by flow cytometry. When interrogating aspects of a cellular network by such steady-state measurements of network components, a key need is to develop efficient methods to simulate and compute these distributions. We describe innovations in stochastic modeling coupled with approaches to this computational challenge: first, an approach to modeling intrinsic noise via solution of the chemical master equation, and second, a convolution technique to account for contributions of extrinsic noise. We show how these techniques can be combined in a streamlined procedure for evaluation of different sources of variability in a biochemical network. Evaluation and illustrations are given in analysis of two well-characterized synthetic gene circuits, as well as a signaling network underlying the mammalian cell cycle entry

Stochastic Simulation of Biomolecular Networks in Dynamic Environments

This is the final version of the article. Available from Public Library of Science via the DOI in this record.Simulation of biomolecular networks is now indispensable for studying biological systems, from small reaction networks to large ensembles of cells. Here we present a novel approach for stochastic simulation of networks embedded in the dynamic environment of the cell and its surroundings. We thus sample trajectories of the stochastic process described by the chemical master equation with time-varying propensities. A comparative analysis shows that existing approaches can either fail dramatically, or else can impose impractical computational burdens due to numerical integration of reaction propensities, especially when cell ensembles are studied. Here we introduce the Extrande method which, given a simulated time course of dynamic network inputs, provides a conditionally exact and several orders-of-magnitude faster simulation solution. The new approach makes it feasible to demonstrate-using decision-making by a large population of quorum sensing bacteria-that robustness to fluctuations from upstream signaling places strong constraints on the design of networks determining cell fate. Our approach has the potential to significantly advance both understanding of molecular systems biology and design of synthetic circuits.MV acknowledges support under an MRC Biomedical Informatics Fellowship. PT acknowledges support by the Royal Commission for the Exhibition of 1851. RG acknowledges support from the Leverhulme Trust (RPG-2013-171). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Direct injection of anti-cancer drugs into endobronchial tumours for palliation of major airway obstruction.

Patients with tracheal or major airway obstruction due to inoperable carcinomas are at a high risk of developing respiratory failure or post-obstructive pneumonia, or both. This often leads to death in days or weeks. In such cases there is usually an urgent need to restore the airway. This report details the short-term results and techniques used for the treatment of airway obstruction by direct intratumoural injection of several anti-cancer drugs. A total of 93 patients with nearly complete extrinsic obstruction of at least one major airway were treated by injection of anti-cancer drugs directly into the endobronchial tumours or infiltrated bronchial mucosa through a flexible fiber-optic bronchoscope. At every session of treatment 1-3 ml each of 50 mg/ml 5-fluorouracil, 1 mg/ ml mitomycin, 5 mg/ml methotrexate, 10 mg/ml bleomycin and 2 mg/ml mitoxantrone were injected separately at different sites without pre-mixing. Local intratumoural chemotherapy relieved the obstruction in 81 of the 93 patients. Endoscopically visible tumours were reduced in size, and infiltrative changes were also improved. Obstruction was not relieved in 12 patients. The therapy was well tolerated and had no systemic side-effects, and no serious complications. Intratumoural chemotherapy can be considered a new life-saving palliative method in patients with life-threatening airway obstruction