Abstract
Metabolism is the set of biochemical reactions of an organism that enables it to assimilate nutrients from its environment and to generate building blocks for growth and proliferation. It forms a complex network that is intertwined with the many molecular and cellular processes that take place within cells. Systems biology aims to capture the complexity of cells, organisms, or communities by reconstructing models based on information gathered by high-throughput analyses (omics data) and prior knowledge. One type of model is a genome-scale metabolic model (GEM) that allows studying the distributions of metabolic fluxes, i.e., the “mass-flow” through the network of biochemical reactions. GEMs are nowadays widely applied and have been reconstructed for various microbial pathogens, either in a free-living state or in interaction with their hosts, with the aim to gain insight into mechanisms of pathogenicity. In this review, we first introduce the principles of systems biology and GEMs. We then describe how metabolic modeling can contribute to unraveling microbial pathogenesis and host–pathogen interactions, with a specific focus on oomycete plant pathogens and in particular Phytophthora infestans. Subsequently, we review achievements obtained so far and identify and discuss potential pitfalls of current models. Finally, we propose a workflow for reconstructing high-quality GEMs and elaborate on the resources needed to advance a system biology approach aimed at untangling the intimate interactions between plants and pathogens.
Highlights
The metabolism of an organism defines its capabilities to take up nutrients from the environment and to convert these into essential building blocks such as nucleic acids and amino acids (Lazar and Birnbaum, 2012)
We provide an overview of recent developments in this field and discuss challenges in reconstructing genome-scale metabolic model (GEM) in these organisms
Informative for predicting the pathogen’s metabolism during in planta growth. We addressed this by integrating our initial P. infestans GEM (Rodenburg et al, 2017) with a tomato GEM published by Yuan et al (2016), resulting in a multi-compartment metabolic model of the P. infestans–tomato interaction (Figure 2A; Rodenburg et al, 2019)
Summary
The metabolism of an organism defines its capabilities to take up nutrients from the environment and to convert these into essential building blocks such as nucleic acids and amino acids (Lazar and Birnbaum, 2012). Metabolism in Oomycete–Host Interactions forms a large, interconnected network that represents the routes by which an organism converts simple nutrients into complex metabolites and vice versa. This network is distributed over different subcellular compartments (organelles), and transporter proteins as well as channels facilitate the transport of metabolites across lipid bilayers that surround the cell and the organelles (Sahoo et al, 2014). The overall system is subject to many parameters, such as variability in substrate concentrations, temperature, or the pH, in the extracellular space and within cells Cells regulate this system to maintain homeostasis, i.e., the ability to perform important cellular functions despite variations (perturbations), which provides robustness (Eberl, 2018; Nijhout et al, 2018). We propose a workflow for reconstructing high-quality GEMs and lay out a number of challenges that need to be addressed for systems biology to provide its full potential to study the intimate interactions between plants and pathogens
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