Possibilities of R programming language in simulating microbiological synthesis processes

• Published in: Journal of physics. Conference series Vol. 2090; no. 1; pp. 12002 - 12006
• Main Authors: Nikitina, Marina A., Chernukha, Irina M.
• Format: Journal Article
• Language: English
• Published: IOP Publishing 01.11.2021
• ISSN: 1742-6588; 1742-6596; 1742-6596
• DOI: 10.1088/1742-6596/2090/1/012002

Information technologies of biotechnological processes are based on the use of mathematical models to describe microbiological synthesis. Application of digital technologies in analysis of microbial growth patterns is mainly determined by the ability of modern programming languages to numerically integrate systems of differential equations describing the development of the microbial process in time. In Jupyter Notebook environment in the R programming language, the solution of the kinetic growth model of the E.coli microbial population was shown. Two solution methods were used - the one-step Runge-Kutta method of the fourth order of accuracy and the universal solver ODE (General Solver for Ordinary Differential Equations). Initial data of the problem in question: K s S 0 = 2 ( K s is substrate affinity S 0 constant for the biomass (microorganism), S 0 is initial concentration of substrate); replicating cells m a 0 = 0.01; total number of cells m 0 = 0.05; stoichiometric ratio Y s = 0.5; various ratios 1) 1 ) λ μ m = 0.0357 ; 2 ) λ μ m = 0.0714 ; 3 ) λ μ m = 0.1071 ; 4 ) λ μ m = 0.1428 ; 5 ) λ μ m = 0.2142 ( λ is specific growth rate of dividing cells, μ m is inactivation rate constant). As a result, the simulation and verification of microbial biomass growth process - its visual representation in the form of tabular and graphical data were carried out. In the process of simulation of E.coli growth the following peculiarity was revealed. In addition to cell division, a fairly intensive loss of their ability to divide occurs. This process is supposedly determinant in population development and limits the growth and ultimate density of the culture. Thus, information technology will help the researcher not only in studying the process, establishing patterns and predicting results, but also in making reasoned decisions.