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BABAK, L., SUPINOVA, P., BURDYCHOVA, R.: Growth models of Thermus aquaticus and Thermus scotoductus. Acta univ. agric. et silvic. Mendel. Brun., 2012, LX, No. 5, pp. 19–26 Members of the genus Thermus family are signifi ant producers of secondary metabolites, which are very commonly used in industry. Beside the productivity, it is also important to study the growth curve of each strain. The mathematical models which are commonly used to describe behavior of microbial strains under diff erent physical and chemical conditions can reduce measured data. In this study, the mathematical models which describe only the microbial count were used. For analysis, Verhulst model, von Bertalanff y model and Richards model were chosen. During the cultivation of Thermus aquaticus and Thermus scotoductus strains, optical density (OD) and concentration of microorganisms were measured. The mathematical models were fi tted to experimental data. The fi tting was made in program MATLAB. The coeffi cients of models and statistical evaluation of goodness of fi t of models were identifi ed from mathematical analyses. Graphs of individual models were plotted with prediction bounds. 95% confi dence levels were used to statistical evaluation of goodness of fi t of models and prediction bounds. Richards model was evaluted as the most corresponding with experimental data. Similar results were reached using Verhulst model. Von Bertalanff y model was not coresponded with experimental data. growth models, bacterial growth, Thermus aquaticus, Thermus scotoductus The fi rst discovery of representatives of the genus Thermus have been a stimulus for a detailed study of physiology of thermophilic bacteria. Its discovery was very simple, because the cultivation is very easy. It was used salt synthetic medium that proved suitable for the growth of algae found in hot springs (BROCK, 1978). Representatives of the genus Thermus are Gram-negative aerobic bacteria, however some newly isolated species grow in anaerobic environments where nitrates used as the fi nal electron acceptors. This genus does not form endospores (BALKWILL et al., 2004). The morphology of the organism is largely infl uenced by temperature and growth phase. The organism is usually present in fi bers when the temperature is above 75 °C. The fi bers are formed only in the stationary growth phase culture at 65 to 70 °C (BROCK, 1978). Members of the genus Thermus family are used to produce thermophilic compounds, especially enzymes, such as Taq polymerase (DNA polymerase), serine proteases, glucosidases, pullulanase (CEJKOVA, 2009). Because are these products mostly secondary metabolites, it is necessary to know the growth characteristics of microorganisms that can also be described by mathematical models. Taq is frequently used in polymerase chain reaction (PCR). Mathematical models are used to describe the behavior of microorganisms under diff erent physical or chemical conditions such as temperature, pH and water activity. In order to build these models, growth has to be measured and modeled. Microbial growth o en shows a lag phase in which the specifi c growth rate starts at a value of zero and then increases. The specifi c growth rate reaches to a maximal value in exponential phase. Then it is decreased of growth rate value and reached to zero in stationary phase. Investigators need adequate models to describe a growth curve and to reduce measured data. A number of models are found in the literature, such as the models of Verhulst, von Bertalanff y, Richards, and others. These models describe only the number of organisms and do not include the consumption of 20 L. Babak, P. Supinova, R. Burdychova substrate as a model based on the Monod equation would do (ZWIETERING et al., 1990). The objective of this work is to evaluate similarities and diff erences between the models and experimental data. It deals with the question of which model(s) can be used, on the basis of statistical evaluation. MATERIALS AND METHODS Microorganisms and medium Thermus aquaticus CCM 3486 and Thermus scotoductus CCM 4465, obtained from Czech collection of microorganisms (Brno, Czech Republic), was used throughout the study. All growth experiments were conducted in medium with composition: yeast extract 4 g, polypeptone 8 g, NaCl 2 g and distilled water 1 000 ml. Cultivation conditions Fermentation experiments were carried out using the bioreactor BioFlo/CelliGen 115. Parameters of cultivation were based on previously made by optimalization. Medium was regulated at pH = 6 for T. aquaticus and at pH = 7 for T. scotoductus. The temperature was maintained at 65 °C. Stirring was set at 150 rpm. Samples (10 ml) were taken at 1hour intervals. Determination of growth curves The optical density (OD) at 600 nm was measured using an Ultrospec cell density meter. The sample was centrifuged at 6 000 rpm for 6 min to determine the biomass concentration. The sediment was washed twice with distilled water. The washed sediment was quantitatively transferred to a dish and dried at 105 °C to constant weight. The concentration (c) was calculated as g of dry biomass by 1 liter of medium. Mathematical modeling Several sigmoidal function (Verhulst, Von Bertalanff y and Richards) were used to describe a bacterial growth curve. The modelling was performed using program MATLAB. The Verhulst logistic equation is also referred in the literature as the Verhulst-Pearl equation a er Verhulst, who fi rst introduced the curve, and Pearl, who used the curve to approximate population growth in the United States in 1920 (TSOULARIS, WALLACE, 2002). Logistic equation was created by adding “saturation” in the exponential equation. “Saturation” can appear in limitation of sources or of space to cultivation of microorganisms (KLAN, 1998). The new variable is found in logistic equation and it expresses carrying capacity: 1 dN N r N dt K           . By integrating the equation we obtain a solution: