Plasmid stability analysis based on a new theoretical model employing stochastic simulations

نویسندگان

  • Olesia Werbowy
  • Sławomir Werbowy
  • Tadeusz Kaczorowski
چکیده

Here, we present a simple theoretical model to study plasmid stability, based on one input parameter which is the copy number of plasmids present in a host cell. The Monte Carlo approach was used to analyze random fluctuations affecting plasmid replication and segregation leading to gradual reduction in the plasmid population within the host cell. This model was employed to investigate maintenance of pEC156 derivatives, a high-copy number ColE1-type Escherichia coli plasmid that carries an EcoVIII restriction-modification system. Plasmid stability was examined in selected Escherichia coli strains (MG1655, wild-type; MG1655 pcnB, and hyper-recombinogenic JC8679 sbcA). We have compared the experimental data concerning plasmid maintenance with the simulations and found that the theoretical stability patterns exhibited an excellent agreement with those empirically tested. In our simulations, we have investigated the influence of replication fails (α parameter) and uneven partition as a consequence of multimer resolution fails (δ parameter), and the post-segregation killing factor (β parameter). All of these factors act at the same time and affect plasmid inheritance at different levels. In case of pEC156-derivatives we concluded that multimerization is a major determinant of plasmid stability. Our data indicate that even small changes in the fidelity of segregation can have serious effects on plasmid stability. Use of the proposed mathematical model can provide a valuable description of plasmid maintenance, as well as enable prediction of the probability of the plasmid loss.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Robust stability of stochastic fuzzy impulsive recurrent neural networks with\ time-varying delays

In this paper, global robust stability of stochastic impulsive recurrent neural networks with time-varyingdelays which are represented by the Takagi-Sugeno (T-S) fuzzy models is considered. A novel Linear Matrix Inequality (LMI)-based stability criterion is obtained by using Lyapunov functional theory to guarantee the asymptotic stability of uncertain fuzzy stochastic impulsive recurrent neural...

متن کامل

Implementation of VAT on Iran banking services in the context of dynamic stochastic general equilibrium model

In the Value Added Tax (VAT) system some goods and services, such as banking services, are exempted from taxes. Based on theoretical foundations, exempt treatment leads to several distortions and inefficiencies in the economy. In order to understand the importance of exemption on macroeconomic fluctuations as well as the fundamental role of financial intermediaries in economy shocks, this study...

متن کامل

A new approach based on alpha cuts for solving data envelopment analysis model with fuzzy stochastic inputs and outputs

Data Envelopment Analysis (DEA) is a widely used technique for measuring the relative efficiencies of homogenous Decision Making Units (DMUs) with multiple inputs and multiple outputs. These factors may be evaluated in fuzzy or stochastic environment. Hence, the classic structures of DEA model may be changed where in two fold fuzzy stochastic environment. For instances, linearity, feasibility a...

متن کامل

A new approach based on state conversion to stability analysis and control design of switched nonlinear cascade systems

In this paper, the problems of control and stabilization of switched nonlinear cascade systems is investigated. The so called simultaneous domination limitation (SDL) is introduced in previous works to assure the existence of a common quadratic Lyapunov function (CQLF) for switched nonlinear cascade systems. According to this idea, if all subsystems of a switched system satisfy the SDL, a CQLF ...

متن کامل

H∞ Sampled-Data Controller Design for Stochastic Genetic Regulatory Networks

Artificially regulating gene expression is an important step in developing new treatment for system-level disease such as cancer. In this paper, we propose a method to regulate gene expression based on sampled-data measurements of gene products concentrations. Inherent noisy behaviour of Gene regulatory networks are modeled with stochastic nonlinear differential equation. To synthesize feed...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره 12  شماره 

صفحات  -

تاریخ انتشار 2017