Accurate Genetic Switch in Escherichia coli: Novel Mechanism of Regulation by Co-repressor

The glyphosate formulation Roundup® LB plus influences the global metabolome of pig gut microbiota in vitro

Glyphosate is the world's most widely used herbicide, and its potential side effects on the intestinal microbiota of various animals, from honeybees to livestock and humans, are currently under discussion. Pigs are among the most abundant livestock animals worldwide and an impact of glyphosate on their intestinal microbiota function can have serious consequences on their health, not to mention the economic effects. Recent studies that addressed microbiota-disrupting effects focused on microbial taxonomy but lacked functional information. Therefore, we chose an experimental design with a short incubation time in which effects on the community structure are not expected, but functional effects can be detected. We cultivated intestinal microbiota derived from pig colon in chemostats and investigated the acute effect of 228 mg/d glyphosate acid equivalents from Roundup® LB plus, a frequently applied glyphosate formulation. The applied glyphosate concentration resembles a worst-case scenario for an 8-9 week-old pig and relates to the maximum residue levels of glyphosate on animal fodder. The effects were determined on the functional level by metaproteomics, targeted and untargeted meta-metabolomics, while variations in community structure were analyzed by 16S rRNA gene profiling and on the single cell level by microbiota flow cytometry. Roundup® LB plus did not affect the community taxonomy or the enzymatic repertoire of the cultivated microbiota in general or on the expression of the glyphosate target enzyme 5-enolpyruvylshikimate-3-phosphate synthase in detail. On the functional level, targeted metabolite analysis of short chain fatty acids (SCFAs), free amino acids and bile acids did not reveal significant changes, whereas untargeted meta-metabolomics did identify some effects on the functional level. This multi-omics approach provides evidence for subtle metabolic effects of Roundup® LB plus under the conditions applied.

Time-dependent solutions for a stochastic model of gene expression with molecule production in the form of a compound Poisson process

We study a stochastic model of gene expression, in which protein production has a form of random bursts whose size distribution is arbitrary, whereas protein decay is a first-order reaction. We find exact analytical expressions for the time evolution of the cumulant-generating function for the most general case when both the burst size probability distribution and the model parameters depend on time in an arbitrary (e.g., oscillatory) manner, and for arbitrary initial conditions. We show that in the case of periodic external activation and constant protein degradation rate, the response of the gene is analogous to the resistor-capacitor low-pass filter, where slow oscillations of the external driving have a greater effect on gene expression than the fast ones. We also demonstrate that the nth cumulant of the protein number distribution depends on the nth moment of the burst size distribution. We use these results to show that different measures of noise (coefficient of variation, Fano factor, fractional change of variance) may vary in time in a different manner. Therefore, any biological hypothesis of evolutionary optimization based on the nonmonotonic dependence of a chosen measure of noise on time must justify why it assumes that biological evolution quantifies noise in that particular way. Finally, we show that not only for exponentially distributed burst sizes but also for a wider class of burst size distributions (e.g., Dirac delta and gamma) the control of gene expression level by burst frequency modulation gives rise to proportional scaling of variance of the protein number distribution to its mean, whereas the control by amplitude modulation implies proportionality of protein number variance to the mean squared.

Method for the analysis of contribution of sliding and hopping to a facilitated diffusion of DNA-binding protein: Application to in vivo data

DNA-binding protein searches for its target, a specific site on DNA, by means of diffusion. The search process consists of many recurrent steps of one-dimensional diffusion (sliding) along the DNA chain and three-dimensional diffusion (hopping) after dissociation of a protein from the DNA chain. Here we propose a computational method that allows extracting the contribution of sliding and hopping to the search process in vivo from the measurements of the kinetics of the target search by the lac repressor in Escherichia coli [P. Hammar et al., Science 336, 1595 (2012)]. The method combines lattice Monte Carlo simulations with the Brownian excursion theory and includes explicitly steric constraints for hopping due to the helical structure of DNA. The simulation results including all experimental data reveal that the in vivo target search is dominated by sliding. The short-range hopping to the same base pair interrupts one-dimensional sliding while long-range hopping does not contribute significantly to the kinetics of the search of the target in vivo.

Transcriptional leakage versus noise: a simple mechanism of conversion between binary and graded response in autoregulated genes

We study the response of an autoregulated gene to a range of concentrations of signal molecules. We show that transcriptional leakage and noise due to translational bursting have the opposite effects. In a positively autoregulated gene, increasing the noise converts the response from graded to binary, while increasing the leakage converts the response from binary to graded. Our findings support the hypothesis that, being a common phenomenon, leaky expression may be a relatively easy way for evolutionary tuning of the type of gene response without changing the type of regulation from positive to negative.

Optimal performance of the tryptophan operon of E. coli: a stochastic, dynamical, mathematical-modeling approach

In this work, we develop a detailed, stochastic, dynamical model for the tryptophan operon of E. coli, and estimate all of the model parameters from reported experimental data. We further employ the model to study the system performance, considering the amount of biochemical noise in the trp level, the system rise time after a nutritional shift, and the amount of repressor molecules necessary to maintain an adequate level of repression, as indicators of the system performance regime. We demonstrate that the level of cooperativity between repressor molecules bound to the first two operators in the trp promoter affects all of the above enlisted performance characteristics. Moreover, the cooperativity level found in the wild-type bacterial strain optimizes a cost-benefit function involving low biochemical noise in the tryptophan level, short rise time after a nutritional shift, and low number of regulatory molecules.

Binary and graded evolution in time in a simple model of gene induction

We solve analytically the model of gene expression induction which consists of three steps: gene activation, gene products synthesis, and product degradation. The solution is given as a time-dependent probability distribution for gene products. Following the distribution in time from the inactive state of the gene to the stationary state we observe binary or graded response depending solely on the ratio r of the gene activation rate to the rate of the gene product degradation. If r << 1 the response is binary and the continuous transition from binary to graded response occurs between r=0.1 and r=1. Therefore, if binary response is observed during relaxation to steady state, then the activation rate constant must be smaller than the degradation rate constant.

Cycling expression and cooperative operator interaction in the trp operon of Escherichia coli

Oscillatory behaviour in the tryptophan operon of an Escherichia coli mutant strain lacking the enzyme-inhibition regulatory mechanism has been observed by Bliss et al. but not confirmed by others. This behaviour could be important from the standpoint of synthetic biology, whose goals include the engineering of intracellular genetic oscillators. This work is devoted to investigating, from a mathematical modelling point of view, the possibility that the trp operon of the E. coli inhibition-free strain expresses cyclically. For that we extend a previously introduced model for the regulatory pathway of the tryptophan operon in Escherichia coli to account for the observed multiplicity and cooperativity of repressor binding sites. Thereafter we investigate the model dynamics using deterministic numeric solutions, stochastic simulations, and analytic studies. Our results suggest that a quasi-periodic behaviour could be observed in the trp operon expression level of single bacteria.

Noise-driven stem cell and progenitor population dynamics

BACKGROUND

The balance between maintenance of the stem cell state and terminal differentiation is influenced by the cellular environment. The switching between these states has long been understood as a transition between attractor states of a molecular network. Herein, stochastic fluctuations are either suppressed or can trigger the transition, but they do not actually determine the attractor states.

METHODOLOGY/PRINCIPAL FINDINGS

We present a novel mathematical concept in which stem cell and progenitor population dynamics are described as a probabilistic process that arises from cell proliferation and small fluctuations in the state of differentiation. These state fluctuations reflect random transitions between different activation patterns of the underlying regulatory network. Importantly, the associated noise amplitudes are state-dependent and set by the environment. Their variability determines the attractor states, and thus actually governs population dynamics. This model quantitatively reproduces the observed dynamics of differentiation and dedifferentiation in promyelocytic precursor cells.

CONCLUSIONS/SIGNIFICANCE

Consequently, state-specific noise modulation by external signals can be instrumental in controlling stem cell and progenitor population dynamics. We propose follow-up experiments for quantifying the imprinting influence of the environment on cellular noise regulation.

Predicting the asymmetric response of a genetic switch to noise

We present a simple analytical tool which gives an approximate insight into the stationary behavior of nonlinear systems undergoing the influence of a weak and rapid noise from one dominating source, e.g. the kinetic equations describing a genetic switch with the concentration of one substrate fluctuating around a constant mean. The proposed method allows for predicting the asymmetric response of the genetic switch to noise, arising from the noise-induced shift of stationary states. The method has been tested on an example model of the lac operon regulatory network: a reduced Yildirim-Mackey model with fluctuating extracellular lactose concentration. We calculate analytically the shift of the system's stationary states in the presence of noise. The results of the analytical calculation are in excellent agreement with the results of numerical simulation of the noisy system. The simulation results suggest that the structure of the kinetics of the underlying biochemical reactions protects the bistability of the lactose utilization mechanism from environmental fluctuations. We show that, in the consequence of the noise-induced shift of stationary states, the presence of fluctuations stabilizes the behavior of the system in a selective way: Although the extrinsic noise facilitates, to some extent, switching off the lactose metabolism, the same noise prevents it from switching on.