A systems approach to plant bioprocess optimization

Integrative Modeling of Gene Expression and Metabolic Networks of Arabidopsis Embryos for Identification of Seed Oil Causal Genes

Fatty acids in crop seeds are a major source for both vegetable oils and industrial applications. Genetic improvement of fatty acid composition and oil content is critical to meet the current and future demands of plant-based renewable seed oils. Addressing this challenge can be approached by network modeling to capture key contributors of seed metabolism and to identify underpinning genetic targets for engineering the traits associated with seed oil composition and content. Here, we present a dynamic model, using an Ordinary Differential Equations model and integrated time-course gene expression data, to describe metabolic networks during Arabidopsis thaliana seed development. Through in silico perturbation of genes, targets were predicted in seed oil traits. Validation and supporting evidence were obtained for several of these predictions using published reports in the scientific literature. Furthermore, we investigated two predicted targets using omics datasets for both gene expression and metabolites from the seed embryo, and demonstrated the applicability of this network-based model. This work highlights that integration of dynamic gene expression atlases generates informative models which can be explored to dissect metabolic pathways and lead to the identification of causal genes associated with seed oil traits.

Modelling Cell Metabolism: A Review on Constraint-Based Steady-State and Kinetic Approaches

Studying cell metabolism serves a plethora of objectives such as the enhancement of bioprocess performance, and advancement in the understanding of cell biology, of drug target discovery, and in metabolic therapy. Remarkable successes in these fields emerged from heuristics approaches, for instance, with the introduction of effective strategies for genetic modifications, drug developments and optimization of bioprocess management. However, heuristics approaches have showed significant shortcomings, such as to describe regulation of metabolic pathways and to extrapolate experimental conditions. In the specific case of bioprocess management, such shortcomings limit their capacity to increase product quality, while maintaining desirable productivity and reproducibility levels. For instance, since heuristics approaches are not capable of prediction of the cellular functions under varying experimental conditions, they may lead to sub-optimal processes. Also, such approaches used for bioprocess control often fail in regulating a process under unexpected variations of external conditions. Therefore, methodologies inspired by the systematic mathematical formulation of cell metabolism have been used to address such drawbacks and achieve robust reproducible results. Mathematical modelling approaches are effective for both the characterization of the cell physiology, and the estimation of metabolic pathways utilization, thus allowing to characterize a cell population metabolic behavior. In this article, we present a review on methodology used and promising mathematical modelling approaches, focusing primarily to investigate metabolic events and regulation. Proceeding from a topological representation of the metabolic networks, we first present the metabolic modelling approaches that investigate cell metabolism at steady state, complying to the constraints imposed by mass conservation law and thermodynamics of reactions reversibility. Constraint-based models (CBMs) are reviewed highlighting the set of assumed optimality functions for reaction pathways. We explore models simulating cell growth dynamics, by expanding flux balance models developed at steady state. Then, discussing a change of metabolic modelling paradigm, we describe dynamic kinetic models that are based on the mathematical representation of the mechanistic description of nonlinear enzyme activities. In such approaches metabolic pathway regulations are considered explicitly as a function of the activity of other components of metabolic networks and possibly far from the metabolic steady state. We have also assessed the significance of metabolic model parameterization in kinetic models, summarizing a standard parameter estimation procedure frequently employed in kinetic metabolic modelling literature. Finally, some optimization practices used for the parameter estimation are reviewed.

Modeling Plant Metabolism: From Network Reconstruction to Mechanistic Models

Mathematical modeling of plant metabolism enables the plant science community to understand the organization of plant metabolism, obtain quantitative insights into metabolic functions, and derive engineering strategies for manipulation of metabolism. Among the various modeling approaches, metabolic pathway analysis can dissect the basic functional modes of subsections of core metabolism, such as photorespiration, and reveal how classical definitions of metabolic pathways have overlapping functionality. In the many studies using constraint-based modeling in plants, numerous computational tools are currently available to analyze large-scale and genome-scale metabolic networks. For ¹³C-metabolic flux analysis, principles of isotopic steady state have been used to study heterotrophic plant tissues, while nonstationary isotope labeling approaches are amenable to the study of photoautotrophic and secondary metabolism. Enzyme kinetic models explore pathways in mechanistic detail, and we discuss different approaches to determine or estimate kinetic parameters. In this review, we describe recent advances and challenges in modeling plant metabolism.

Green (cell) factories for advanced production of plant secondary metabolites

For centuries plants have been intensively utilized as reliable sources of food, flavoring, agrochemical and pharmaceutical ingredients. However, plant natural habitats are being rapidly lost due to climate change and agriculture. Plant biotechnology offers a sustainable method for the bioproduction of plant secondary metabolites using plant in vitro systems. The unique structural features of plant-derived secondary metabolites, such as their safety profile, multi-target spectrum and "metabolite likeness," have led to the establishment of many plant-derived drugs, comprising approximately a quarter of all drugs approved by the Food and Drug Administration and/or European Medicinal Agency. However, there are still many challenges to overcome to enhance the production of these metabolites from plant in vitro systems and establish a sustainable large-scale biotechnological process. These challenges are due to the peculiarities of plant cell metabolism, the complexity of plant secondary metabolite pathways, and the correct selection of bioreactor systems and bioprocess optimization. In this review, we present an integrated overview of the possible avenues for enhancing the biosynthesis of high-value marketable molecules produced by plant in vitro systems. These include metabolic engineering and CRISPR/Cas9 technology for the regulation of plant metabolism through overexpression/repression of single or multiple structural genes or transcriptional factors. The use of NMR-based metabolomics for monitoring metabolite concentrations and additionally as a tool to study the dynamics of plant cell metabolism and nutritional management is discussed here. Different types of bioreactor systems, their modification and optimal process parameters for the lab- or industrial-scale production of plant secondary metabolites are specified.

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.

Hosting the plant cells in vitro: recent trends in bioreactors

Biotechnological production of high-value metabolites and therapeutic proteins by plant in vitro systems has been considered as an attractive alternative of classical technologies. Numerous proof-of-concept studies have illustrated the feasibility of scaling up plant in vitro system-based processes while keeping their biosynthetic potential. Moreover, several commercial processes have been established so far. Though the progress on the field is still limited, in the recent years several bioreactor configurations has been developed (e.g., so-called single-use bioreactors) and successfully adapted for growing plant cells in vitro. This review highlights recent progress and limitations in the bioreactors for plant cells and outlines future perspectives for wider industrialization of plant in vitro systems as "green cell factories" for sustainable production of value-added molecules.

Analyzing the effect of decreasing cytosolic triosephosphate isomerase on Solanum tuberosum hairy root cells using a kinetic-metabolic model

A kinetic-metabolic model of Solanum tuberosum hairy roots is presented in the interest of understanding the effect on the plant cell metabolism of a 90% decrease in cytosolic triosephosphate isomerase (cTPI, EC 5.3.1.1) expression by antisense RNA. The model considers major metabolic pathways including glycolysis, pentose phosphate pathway, and TCA cycle, as well as anabolic reactions leading to lipids, nucleic acids, amino acids, and structural hexoses synthesis. Measurements were taken from shake flask cultures for six extracellular nutrients (sucrose, fructose, glucose, ammonia, nitrate, and inorganic phosphate) and 15 intracellular compounds including sugar phosphates (G6P, F6P, R5P, E4P) and organic acids (PYR, aKG, SUCC, FUM, MAL) and the six nutrients. From model simulations and experimental data it can be noted that plant cell metabolism redistributes metabolic fluxes to compensate for the cTPI decrease, leading to modifications in metabolites levels. Antisense roots showed increased exchanges between the pentose phosphate pathway and the glycolysis, an increased oxygen uptake and growth rate.

Effect of Antioxidants and Carbohydrates in Callus Cultures of Taxus brevifolia: Evaluation of Browning, Callus Growth, Total Phenolics and Paclitaxel Production

INTRODUCTION

To control the tissue browning phenomenon, callus growth, total phenolics and paclitaxel production, in the current investigation, we evaluated the effects of citric acid and ascorbic acid (as antioxidants) and glucose, fructose and sucrose in callus cultures of Taxus brevifolia.

METHODS

To obtain healthy callus/cell lines of Taxus brevifolia, the effects of two antioxidants ascorbic acid (100-1000 mg/L) and citric acid (50-500 mg/L), and three carbohydrates (glucose, fructose and sucrose (5-10 g/L)) were studied evaluating activities of polyphenol oxidase (PPO) and peroxidase (PO) enzymes, callus growth/browning, total phenolics and paclitaxel production.

RESULTS

These antioxidants (ascorbic acid and citric acid) failed to show significant effects on callus growth, browning intensity or paclitaxel production. However, the carbohydrates imposed significant effects on the parameters studied. High concentrations of both glucose and sucrose increased the browning intensity, thus decreased callus growth. Glucose increased paclitaxel production, but sucrose decreased it.

CONCLUSION

These results revealed that the browning phenomenon can be controlled through supplementation of the growth media with glucose, sucrose (5 g/L) and fructose (10 g/L), while increased paclitaxel production can be obtain by the optimized media supplemented with glucose (10 g/L), sucrose and fructose (5 g/L).