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Plant J. 2017 May;90(4):764-787. doi: 10.1111/tpj.13485. Epub 2017 Mar 30.

Integrated omics analysis of specialized metabolism in medicinal plants.

Author information

1
Graduate School of Pharmaceutical Sciences, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba, 260-8675, Japan.
2
RIKEN Center for Sustainable Resource Science, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, 230-0045, Japan.

Abstract

Medicinal plants are a rich source of highly diverse specialized metabolites with important pharmacological properties. Until recently, plant biologists were limited in their ability to explore the biosynthetic pathways of these metabolites, mainly due to the scarcity of plant genomics resources. However, recent advances in high-throughput large-scale analytical methods have enabled plant biologists to discover biosynthetic pathways for important plant-based medicinal metabolites. The reduced cost of generating omics datasets and the development of computational tools for their analysis and integration have led to the elucidation of biosynthetic pathways of several bioactive metabolites of plant origin. These discoveries have inspired synthetic biology approaches to develop microbial systems to produce bioactive metabolites originating from plants, an alternative sustainable source of medicinally important chemicals. Since the demand for medicinal compounds are increasing with the world's population, understanding the complete biosynthesis of specialized metabolites becomes important to identify or develop reliable sources in the future. Here, we review the contributions of major omics approaches and their integration to our understanding of the biosynthetic pathways of bioactive metabolites. We briefly discuss different approaches for integrating omics datasets to extract biologically relevant knowledge and the application of omics datasets in the construction and reconstruction of metabolic models.

KEYWORDS:

gene cluster; integrative omics; phytochemicals; synthetic biology; systems biology; traditional medicinal plants

PMID:
28109168
DOI:
10.1111/tpj.13485
[Indexed for MEDLINE]
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