An exact steady-state solution of the stochastic equations governing the behavior of a gene regulated by a self-generated proteomic atmosphere is presented. The solutions depend on an adiabaticity parameter measuring the relative rate of DNA-protein unbinding and protein degradation. The steady-state solution reveals deviations from the commonly used Ackers et al approximation based on the equilibrium law of mass action, allowing anticooperative behavior in the "nonadiabatic" limit of slow binding and unbinding rates. Noise from binding and unbinding events dominates the shot noise of protein synthesis and degradation up to quite high values of the adiabaticity parameter.

Bacteria serve as the central arena for understanding how gene networks and proteins process information and control cellular behaviors. Recently, much effort has been devoted to the investigation of specific bacteria gene circuits as functioning modules. The next challenge is the integrative modeling of complex cellular networks composed of many such modules. A tractable integrative model of the sophisticated decision-making signal transduction system that determines the fate between sporulation and competence is presented. This model provides an understanding of how information is sensed and processed to reach an ''informative'' decision in the context of cell state and signals from other cells. The competence module (ComK dynamics) is modeled as a stochastic switch whose transition rate is controlled by a quorum-sensing unit. The sporulation module (Spo0A dynamics) is modeled as a timer whose clock rate is adjusted by a stress-sensing unit. The interplay between these modules is mediated via the Rap assessment system, which gates the sensing units, and the AbrB-Rok decision module, which creates an opportunity for competence within a specific window of the sporulation timer. The timer is regulated via a special repressilator-like inhibition of Spo0A* by Spo0E, which is itself inhibited by AbrB. For some stress and input signals, this repressilator can generate a frustration state with large variations (fluctuations or oscillations) in Spo0A* and AbrB concentrations, which might serve an important role in generating cell variability. This integrative framework is a starting point that can be extended to include transition into cannibalism and the role of colony organization.

Our understanding of bacterial cell size control is based mainly on stress-free growth conditions in the laboratory [1-10]. In the real world, however, bacteria are routinely faced with stresses that produce long filamentous cell morphologies [11-28]. Escherichia coli is observed to filament in response to DNA damage [22-25], antibiotic treatment [11-14, 28], host immune systems [15, 16], temperature [17], starvation [20], and more [18, 19, 21], conditions which are relevant to clinical settings and food preservation [26]. This shape plasticity is considered a survival strategy [27]. Size control in this regime remains largely unexplored. Here we report that E. coli cells use a dynamic size ruler to determine division locations combined with an adder-like mechanism to trigger divisions. As filamentous cells increase in size due to growth, or decrease in size due to divisions, its multiple Fts division rings abruptly reorganize to remain one characteristic cell length away from the cell pole and two such length units away from each other. These rules can be explained by spatiotemporal oscillations of Min proteins. Upon removal of filamentation stress, the cells undergo a sequence of division events, randomly at one of the possible division sites, on average after the time required to grow one characteristic cell size. These results indicate that E. coli cells continuously keep track of absolute length to control size, suggest a wider relevance for the adder principle beyond the control of normally sized cells, and provide a new perspective on the function of the Fts and Min systems.

Because genetic networks function with few molecules, such systems are better described by stochastic models than by macroscopic kinetics. Stochastic simulations of a self-regulating gene are compared with analytical solutions of the master equations, showing how the dynamics depends on the average number of proteins in the system, the repression strength, and the relative speed of the binding/unbinding and synthesis/degradation events. Steady-state and transient probability distributions for the toggle switch along with typical trajectories show that strongly repressed systems are better candidates for "good switches."

The role of stochasticity and noise in controlling genetic circuits is investigated in the context of transitions into and from competence in Bacillus subtilis. Recent experiments have demonstrated that bistability is not necessary for this function, but that the existence of one stable fixed point (vegetation) and an excitable unstable one (competence) is sufficient. Stochasticity therefore plays a crucial role in this excitation. Noise can be generated by discrete events such as RNA and protein synthesis and their degradation. We consider an alternative noise source connected with the protein binding/unbinding to the DNA. A theoretical model that includes this ''nonadiabatic'' mechanism appears to produce a better agreement with experiments than models where only the adiabatic limit is considered, suggesting that this nonconventional stochasticity source may be important for biological functions.stochasticity ͉ nonadiabaticity ͉ gene networks ͉ competence

Human fungal infections may fail to respond to contemporary antifungal therapies in vivo despite in vitro fungal isolate drug susceptibility. Such a discrepancy between in vitro antimicrobial susceptibility and in vivo treatment outcomes is partially explained by microbes adopting a drug-resistant biofilm mode of growth during infection. The filamentous fungal pathogen Aspergillus fumigatus forms biofilms in vivo, and during biofilm growth it has reduced susceptibility to all three classes of contemporary antifungal drugs. Specific features of filamentous fungal biofilms that drive antifungal drug resistance remain largely unknown. In this study, we applied a fluorescence microscopy approach coupled with transcriptional bioreporters to define spatial and temporal oxygen gradients and single-cell metabolic activity within A. fumigatus biofilms. Oxygen gradients inevitably arise during A. fumigatus biofilm maturation and are both critical for, and the result of, A. fumigatus late-stage biofilm architecture. We observe that these self-induced hypoxic microenvironments not only contribute to filamentous fungal biofilm maturation but also drive resistance to antifungal treatment. Decreasing oxygen levels toward the base of A. fumigatus biofilms increases antifungal drug resistance. Our results define a previously unknown mechanistic link between filamentous fungal biofilm physiology and contemporary antifungal drug resistance. Moreover, we demonstrate that drug resistance mediated by dynamic oxygen gradients, found in many bacterial biofilms, also extends to the fungal kingdom. The conservation of hypoxic drug-resistant niches in bacterial and fungal biofilms is thus a promising target for improving antimicrobial therapy efficacy.

When gene regulatory networks operate in regimes where the number of protein molecules is so small that the molecular species are on the verge of extinction, the death and resurrection of the species greatly modifies the attractor landscape. Deterministic models and the diffusion approximation to the master equation break down at the limits of protein populations in a way very analogous to the breakdown of geometrical optics that occurs at distances <1 wavelength of light from edges. Stable stochastic attractors arise from extinction and resurrection events that are not predicted by the deterministic description. With this view, we explore the attractors of the regular toggle switch and the exclusive switch, focusing on the effects of cooperative binding and the production of protein in bursts. Our arguments suggest that the stability of lysogeny in the -phage may be influenced by such extinction phenomena.cooperativity ͉ regulation ͉ stochasticity

Sporulation vs. competence provides a prototypic example of collective cell fate determination. The decision is performed by the action of three modules: 1) A stochastic competence switch whose transition probability is regulated by population density, population stress and cell stress. 2) A sporulation timer whose clock rate is regulated by cell stress and population stress. 3) A decision gate that is coupled to the timer via a special repressilator-like loop. We show that the distinct circuit architecture of this gate leads to special dynamics and noise management characteristics: The gate opens a time-window of opportunity for competence transitions during which it generates oscillations that are turned into a chain of transition opportunities – each oscillation opens a short interval with high transition probability. The special architecture of the gate also leads to filtering of external noise and robustness against internal noise and variations in the circuit parameters.