Plant genome-scale reconstruction: from single cell to multi-tissue modelling and omics analyses
Graphical abstract
Introduction
Since the first Arabidopsis genome-scale metabolic reconstructions were released nearly a decade ago [1, 2], model reconstructions have been generated for several plant species, including industrial crops, and the range of applications expanded (Figure 1).
Plant genome-scale reconstructions have been adopted as system frameworks, in particular to facilitate multi-scale analyses and our understanding of complex metabolic processes in single cells, multi-tissues and at whole plant level. They have proven powerful tools for: first, examining the metabolic capabilities of single cells [1, 2, 3]; second, guiding systems-level metabolic pathway analysis [4, 5, 6]; third, understanding interactions of mesophyll and bundle sheath cells in C4 plants [7, 8]; fourth, investigating the interactions between light and dark metabolism in leaves [9•]; fifth, exploring C/N partitioning, resource allocation in a multi-tissue context considering diurnal cycle [10••]; and sixth, integrating multi-omics data in different plant tissues for multi-scale analyses [11, 12•, 13].
Here, we will review recent advances in plant metabolic reconstructions, modelling, multi-omics analyses and future perspectives for plant genome-scale modelling (Figure 2).
Section snippets
Plant genome-scale reconstructions
Genome-scale metabolic reconstructions are available for several plants and applications (Figure 1). Much of our understanding of plant metabolism builds on experiments performed with the model C3 plant, Arabidopsis thaliana. Several reconstructions have been developed for Arabidopsis [1, 2, 14, 15, 16], and these provided the basis for the development of reconstructions that describe the metabolism of industrial crops such as rice [11, 17], tomato [18] and of C4 grasses such maize [7, 19],
Modelling
A genome scale reconstruction seeks to capture all reactions in all tissues at all times, whereas a genome scale model seeks to capture the relevant reactions in a particular tissue and a particular context. The model network is a subset of the full reconstruction network, which can be extracted based on gene expression and the modelling context (Figure 2, step 2a). For example, several tissue specific models have been developed for Arabidopsis [14]. These networks are further constrained by
Multi-omics data integration and interpretation
Numerous omics studies have been performed on plant systems, including studies to investigate the regulatory response under abiotic stress [40, 41, 42], characterize mutants [43] and study leaf development in maize [4], examine plant disease resistance [44] and defence mechanisms [45, 46], investigate leaf senescence [13], and assess plant microbe interactions [47]. For these studies to become true plant systems biology studies, the challenge remains how to integrate these data into predictive
Conclusion and future perspectives
Recent progress of plant genome-scale metabolic reconstruction and modelling is an important achievement in plant systems biology. The framework helps us understand multicellular metabolism and has proven suitable for data interrogation and systemic analysis of several plant species, including industrial crops. The power of prediction is still compromised by incomplete annotation of compartmentation, transporters and secondary metabolism. Continued efforts are needed to improve metabolic
Conflict of interest
The authors declare that there is no conflict of interest.
References and recommended reading
Papers of particular interest, published within the period of review, have been highlighted as:
• of special interest
•• of outstanding interest
Acknowledgements
This research was funded by the Australian Government through the Australian Research Council (ARC) and the US Air Force through the Asian Office of Aerospace Research and Development (AOARD).
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