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A new tool allows researchers to probe the metabolic processes occurring within the leaves, stems, and roots of a key citrus crop, the clementine. The big picture goal of this research is to improve the yields, flavor and nutritional value of citrus and non-citrus crops, even in the face of increasingly harsh growing conditions and growing pest challenges.

To build the tool, the team—led by the University of California San Diego—focused on the clementine (Citrus clementina), which is a cross between a mandarin orange and a sweet orange.

The effort is expected to expand well beyond the clementine in order to develop actionable information for increasing the productivity and quality of a wide range of citrus and non-citrus crops. The strategy is to uncover—and then make use of—new insights into how plants respond, in terms of metabolic activities in specific parts of the plant or tree, to environmental factors like temperature, drought and disease.

The tool, and the comprehensive genome-scale model for Citrus clementina, were in the journal Proceedings of the National Academy of Sciences (PNAS).

The team is led by researchers at UC San Diego, in collaboration with researchers at UC Riverside and the Universidad Autónoma de Yucatán.

"Together we created a tool that will open the door for improved crop design and sustainable farming for Citrus clementina and a wide range of citrus and non-citrus crops," said UC San Diego professor Karsten Zengler, the corresponding author on the new paper.

At UC San Diego, Zengler holds affiliations in the Department of Bioengineering, the Department of Pediatrics, the Center for Microbiome Innovation, and the Program in Materials Science and Engineering.

"Our data-driven modeling approach represents a powerful tool for citrus breeding and farming and for the improvement of crop yield and quality, meeting the escalating demand for high-quality products in the global market," said Zengler.

The high-resolution genomic tool has been designed and built as a platform technology that can be expanded to help researchers improve a wide range of citrus and non-citrus crops. The actionable information is derived from a wide range of new mechanistic insights into how plant metabolism works within leaves, stems, roots and other tissues of key plant crops.

The highly curated and validated model of clementine metabolism, for example, contains 2,616 genes, 8,653 metabolites and 10,654 reactions.

"We generated seven biomass objective functions based on organ-specific metabolomics data for leaf, stem, root, and seed and experimentally validated the model—a challenge for a plant with an average lifespan of 50 years," said Zengler. "This model represents one of the largest genome-scale models that has been built for any organism, including for humans."

The model is called iCitrus2616. It captures Citrus clementina's metabolism with exceptional accuracy and enables simulating economically-relevant scenarios.

For example, the researchers show how specific nutrients can improve the production of starch and types of cellulose, which in turn can enhance the strength and rigidity of cell walls in citrus plants, which is useful for withstanding mechanical and drought stress.

The researchers also used the new tool to demonstrate how to increase flavor-related compounds in Citrus clementina such as flavonoids.

The team integrated organ-specific models for leaf, stem, and root into a whole plant model. Using this integrated whole-plant model, the researchers show how flavonoids and hormones are distributed through the entire plant.

Additionally, the team constrained the clementine metabolism model with gene expression data from symptomatic and asymptomatic leaf and root tissues across four seasons during citrus greening—which is caused by a bacterial infection. Citrus greening causes millions of dollars of agricultural damage annually.

This project has already revealed tissue-specific metabolic adaptations, including shifts in energy allocation, secondary metabolite production, and stress-response pathways under biotic stress and has provided a mechanistic understanding of disease progression.

The researchers note that this work represents a milestone in modeling higher organisms, specifically plants.

"I envision that these types of models will aid with crop breeding efforts in the near future. With these models, we are working to make critical plant breeding efforts more reliable and also faster," said Zengler.

"In preliminary follow-on research, we are already seeing examples of the positive impacts these models can have for data-driven strategies to optimize plant growth."