A simple structured model for maintenance, biomass formation, and ajmalicine production by nondividing Catharanthus roseus cells

Dynamic modelling of growth and flavonoid production from Ocimum tenuiflorum suspension culture

A structured-segregated dynamic model for biomass growth, sucrose utilization and flavonoid production in Ocimum tenuiflorum suspension culture is proposed, considering a dynamic heterogeneous population of viable active, viable nonactive and dead cell. The sucrose hydrolysis (into glucose and fructose), substrate uptake by biomass and intracellular flavonoid production are modelled using Contois kinetics, a competitive double-substrate Monod, and Luedeking-Piret model, respectively. The conversion of active to viable-nonactive biomass has been formulated as a function of the total substrate and biomass concentrations. Parameters for the dynamic model are evaluated while minimizing the sum of square errors between modelled and measured biomass, cell viability, glucose, fructose and intracellular flavonoid contents. Bootstrap confidence intervals and dynamic relative sensitivity analysis of these model parameters are presented. The knowledge gained from the population-based model in plant suspension culture can provide the basic framework for prediction and optimization of the bioprocess system for phytochemical production.

First principle-based models in plant suspension cell cultures: a review

In this work, the development and application of published models for describing the behavior of plant cell cultures is reviewed. The structure of each type of model is analyzed and the new tendencies for the modeling of biotechnological processes that can be applied in plant cell cultures are presented. This review is a tool for clarifying the main features that characterize each type of model in the field of plant cell cultures and can be used as a support on the selection of the more suitable model type, taking into account the purpose of specific research.

Structured model and parameter estimation in plant cell cultures of Thevetia peruviana

In this work, a mechanistic model for predicting the dynamic behavior of extracellular and intracellular nutrients, biomass production, and the main metabolites involved in the central carbon metabolism in plant cell cultures of Thevetia peruviana is presented. The proposed model is the first mechanistic model implemented for plant cell cultures of this species, and includes 28 metabolites, 33 metabolic reactions, and 61 parameters. Given the over-parametrization of the model, its nonlinear nature and the strong correlation among the effects of the parameters, a parameter estimation routine based on identifiability analysis was implemented. This routine reduces the parameter's search space by selecting the most sensitive and linearly independent parameters. Results have shown that only 19 parameters are identifiable. Finally, the model was used for analyzing the fluxes distribution in plant cell cultures of T. peruviana. This analysis shows high uptake of phosphates and parallel uptake of glucose and fructose. Furthermore, it has pointed out the main central carbon metabolism routes for promoting biomass production in this cell culture.

Modeling of plant in vitro cultures: overview and estimation of biotechnological processes

Plant cell and tissue cultivations are of growing interest for the production of structurally complex and expensive plant-derived products, especially in pharmaceutical production. Problems with up-scaling, low yields, and high-priced process conditions result in an increased demand for models to provide comprehension, simulation, and optimization of production processes. In the last 25 years, many models have evolved in plant biotechnology; the majority of them are specialized models for a few selected products or nutritional conditions. In this article we review, delineate, and discuss the concepts and characteristics of the most commonly used models. Therefore, the authors focus on models for plant suspension and submerged hairy root cultures. The article includes a short overview of modeling and mathematics and integrated parameters, as well as the application scope for each model. The review is meant to help researchers better understand and utilize the numerous models published for plant cultures, and to select the most suitable model for their purposes.

A population balance equation model of aggregation dynamics in Taxus suspension cell cultures

The nature of plant cells to grow as multicellular aggregates in suspension culture has profound effects on bioprocess performance. Recent advances in the measurement of plant cell aggregate size allow for routine process monitoring of this property. We have exploited this capability to develop a conceptual model to describe changes in the aggregate size distribution that are observed over the course of a Taxus cell suspension batch culture. We utilized the population balance equation framework to describe plant cell aggregates as a particulate system, accounting for the relevant phenomenological processes underlying aggregation, such as growth and breakage. We compared model predictions to experimental data to select appropriate kernel functions, and found that larger aggregates had a higher breakage rate, biomass was partitioned asymmetrically following a breakage event, and aggregates grew exponentially. Our model was then validated against several datasets with different initial aggregate size distributions and was able to quantitatively predict changes in total biomass and mean aggregate size, as well as actual size distributions. We proposed a breakage mechanism where a fraction of biomass was lost upon each breakage event, and demonstrated that even though smaller aggregates have been shown to produce more paclitaxel, an optimum breakage rate was predicted for maximum paclitaxel accumulation. We believe this is the first model to use a segregated, corpuscular approach to describe changes in the size distribution of plant cell aggregates, and represents an important first step in the design of rational strategies to control aggregation and optimize process performance.

A predictive nutritional model for plant cells and hairy roots

A structured nutritional model is proposed to describe growth and nutritional behavior of Eschscholtzia californica suspension cells and Catharanthus roseus and Daucus carota hairy roots in in vitro culture. The model describes the cells specific growth rate from concentration of intracellular nutrients such as inorganic phosphate (Pi), nitrogen sources (NO(3) (-) and NH(4) (+)) and sugars. Two-level Michaelis-Menten kinetics are used to describe Pi and NO(3) (-) uptake and simple Michaelis-Menten kinetics for description of sugars uptake. Model parameters for each cell line were calibrated using data from batch cultures. The predictive capacity of the model was tested using data from medium exchange hairy root cultures. The model describes growth and nutritional behavior for the cell and hairy root lines. A sensitivity analysis was performed to identify critical model parameters and effect of initial conditions. The cell and hairy roots lines are also compared from their kinetic parameters. The kinetic model is efficient for describing and predicting growth and nutritional behaviors of suspension cells and hairy roots.

Biochemical engineering of the production of plant-specific secondary metabolites by cell suspension cultures

Plant cell culture has recently received much attention as a useful technology for the production of valuable plant-derived secondary metabolites such as paclitaxel and ginseng saponin. The numerous problems that yet bewilder the optimization and scale-up of this process have not been over emphasized. In spite of the great progress recorded in recent years towards the selection, design and optimization of bioreactor hardware, manipulation of environmental factors such as medium components, light irradiation, shear stress and O2 supply needs detailed investigations for each case. Recent advances in plant cell processes, including high-density suspension cultivation, continuous culture, process monitoring, modeling and control and scale-up, are also reviewed in this chapter. Further developments in bioreactor cultivation processes and in metabolic engineering of plant cells for metabolite production are expected in the near future.