Effect Of Molecular Noise Research Articles

Effects of Molecular Noise on Cell Size Control.

Cells employ control strategies to maintain a stable size. Dividing at a target size (the "sizer" strategy) is thought to produce the tightest size distribution. However, this result follows from phenomenological models that ignore the molecular mechanisms required to implement the strategy. Here we investigate a simple mechanistic model for exponentially growing cells whose division is triggered at a molecular abundance threshold. We find that size noise inherits the molecular noise and is consequently minimized not by the sizer but by the "adder" strategy, where a cell divides after adding a target amount to its birth size. We derive a lower bound on size noise that agrees with publicly available data from six microfluidic studies on Escherichia coli bacteria.

IDESS: a toolbox for identification and automated design of stochastic gene circuits.

One of the main causes hampering predictability during the model identification and automated design of gene circuits in synthetic biology is the effect of molecular noise. Stochasticity may significantly impact the dynamics and function of gene circuits, specially in bacteria and yeast due to low mRNA copy numbers. Standard stochastic simulation methods are too computationally costly in realistic scenarios to be applied to optimization-based design or parameter estimation. In this work, we present IDESS (Identification and automated Design of Stochastic gene circuitS), a software toolbox for optimization-based design and model identification of gene regulatory circuits in the stochastic regime. This software incorporates an efficient approximation of the Chemical Master Equation as well as a stochastic simulation algorithm-both with GPU and CPU implementations-combined with global optimization algorithms capable of solving Mixed Integer Nonlinear Programming problems. The toolbox efficiently addresses two types of problems relevant in systems and synthetic biology: the automated design of stochastic synthetic gene circuits, and the parameter estimation for model identification of stochastic gene regulatory networks. IDESS runs under the MATLAB environment and it is available under GPLv3 license at https://doi.org/10.5281/zenodo.7788692.

A stochastic model of size control in the budding yeast cell cycle

BackgroundCell size is a key characteristic that significantly affects many aspects of cellular physiology. There are specific control mechanisms during cell cycle that maintain the cell size within a range from generation to generation. Such control mechanisms introduce substantial variabilities to important properties of the cell cycle such as growth and division. To quantitatively study the effect of such variability in progression through cell cycle, detailed stochastic models are required.ResultsIn this paper, a new hybrid stochastic model is proposed to study the effect of molecular noise and size control mechanism on the variabilities in cell cycle of the budding yeast Saccharomyces cerevisiae. The proposed model provides an accurate, yet computationally efficient approach for simulation of an intricate system by integrating the deterministic and stochastic simulation schemes. The developed hybrid stochastic model can successfully capture several key features of the cell cycle observed in experimental data. In particular, the proposed model: 1) confirms that the majority of noise in size control stems from low copy numbers of transcripts in the G1 phase, 2) identifies the size and time regulation modules in the size control mechanism, and 3) conforms with phenotypes of early G1 mutants in exquisite detail.ConclusionsHybrid stochastic modeling approach can be used to provide quantitative descriptions for stochastic properties of the cell cycle within a computationally efficient framework.

Effects of molecular noise on bistable protein distributions in rod-shaped bacteria.

The distributions of many proteins in rod-shaped bacteria are far from homogeneous. Often they accumulate at the cell poles or in the cell centre. At the same time, the copy number of proteins in a single cell is relatively small making the patterns noisy. To explore limits to protein patterns due to molecular noise, we studied a generic mechanism for spontaneous polar protein assemblies in rod-shaped bacteria, which are based on cooperative binding of proteins to the cytoplasmic membrane. For mono-polar assemblies, we find that the switching time between the two poles increases exponentially with the cell length and with the protein number. This feature could be beneficial to organelle maintenance in ageing bacteria.

Molecular noise induced circadian oscillation and coherence resonance in the gene network of biological clock

The molecular noise in the gene regulation network of biological clock in Drosophila was studied. Especially, we investigated the effect of molecular noise on the circadian rhythmic oscillation when the system is in the steady state region but only slightly away from the oscillating region. We show that (i) Though the prodution and the decay of the protein are stochastic with the stochastic time interval, the obvious circadian oscillation can be induced depending on the system intrinsic regulation mechanism. (ii) The coherence of molecular noise-induced oscillation is optimal under an appropriate molecular noise level, leading to the occurrence of coherence resonance.

Erratum: The effects of molecular noise and size control on variability in the budding yeast cell cycle

Nature 448, 947–951 (2007) In Fig. 1b of this Letter, the two labels ‘S/G2/M’ were inadvertently misplaced. The corrected Fig. 1b (in black and white) is shown below.

The effects of molecular noise and size control on variability in the budding yeast cell cycle

Molecular noise in gene expression can generate substantial variability in protein concentration. However, its effect on the precision of a natural eukaryotic circuit such as the control of cell cycle remains unclear. We use single-cell imaging of fluorescently labelled budding yeast to measure times from division to budding (G1) and from budding to the next division. The variability in G1 decreases with the square root of the ploidy through a 1N/2N/4N ploidy series, consistent with simple stochastic models for molecular noise. Also, increasing the gene dosage of G1 cyclins decreases the variability in G1. A new single-cell reporter for cell protein content allows us to determine the contribution to temporal G1 variability of deterministic size control (that is, smaller cells extending G1). Cell size control contributes significantly to G1 variability in daughter cells but not in mother cells. However, even in daughters, size-independent noise is the largest quantitative contributor to G1 variability. Exit of the transcriptional repressor Whi5 from the nucleus partitions G1 into two temporally uncorrelated and functionally distinct steps. The first step, which depends on the G1 cyclin gene CLN3, corresponds to noisy size control that extends G1 in small daughters, but is of negligible duration in mothers. The second step, whose variability decreases with increasing CLN2 gene dosage, is similar in mothers and daughters. This analysis decomposes the regulatory dynamics of the Start transition into two independent modules, a size sensing module and a timing module, each of which is predominantly controlled by a different G1 cyclin.