Abstract
Life on earth depends on dynamic chemical transformations that enable cellular functions, including electron transfer reactions, as well as synthesis and degradation of biomolecules. Biochemical reactions are coordinated in metabolic pathways that interact in a complex way to allow adequate regulation. Biotechnology, food, biofuel, agricultural, and pharmaceutical industries are highly interested in metabolic engineering as an enabling technology of synthetic biology to exploit cells for the controlled production of metabolites of interest. These approaches have only recently been extended to plants due to their greater metabolic complexity (such as primary and secondary metabolism) and highly compartmentalized cellular structures and functions (including plant-specific organelles) compared with bacteria and other microorganisms. Technological advances in analytical instrumentation in combination with advances in data analysis and modeling have opened up new approaches to engineer plant metabolic pathways and allow the impact of modifications to be predicted more accurately. In this article, we review challenges in the integration and analysis of large-scale metabolic data, present an overview of current bioinformatics methods for the modeling and visualization of metabolic networks, and discuss approaches for interfacing bioinformatics approaches with metabolic models of cellular processes and flux distributions in order to predict phenotypes derived from specific genetic modifications or subjected to different environmental conditions.
Highlights
One of the greatest challenges for scientists is to understand the genetics, physiology, and biochemistry of plants and the interaction of genes with the environment in order to provide strategies to manipulate these processes to improve plant growth and performance and to prevent diseases
Metabolic modeling for synthetic biology with their associated computational advances providing the path for data analysis, visualization, and integration to establish the relationships between the genome and gene products under certain conditions
Metabolites and their functionalities are indispensable in the interaction of a cell with the environment, and it has been argued that the metabolome of any biological system represents the final “read-out” of the expression of many genes in that system in a particular situation, and reflecting gene × environment relationships (Hill et al, 2014)
Summary
One of the greatest challenges for scientists is to understand the genetics, physiology, and biochemistry of plants and the interaction of genes with the environment in order to provide strategies to manipulate these processes to improve plant growth and performance and to prevent diseases. Given the tools introduced before, metabolite and pathway databases and repositories are valuable resources that can be used to manage, explore, and export knowledge about metabolites and reactions in meaningful ways They thereby deliver an encyclopedia on metabolic information as well as a base for integration of complex data into metabolic pathways in the context of graphical pathway representations (e.g., data about compound levels, reaction flow, enzyme activity, and gene expression, see Metabolomics Data Analysis and Visualization). Often these databases and repositories provide or allow building metabolic models which can be analyzed and simulated using mathematical modeling techniques, see Section “Methods for Metabolic Modeling in Plants.”. There are many tools and databases available for computational modeling and a standardized exchange of models is highly relevant; Section “Standards for Systems and Synthetic Biology” provides an introduction to major standards in systems in synthetic biology
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