Phytochemical Genomics on the Way

Abstract

This is a really exciting time for phytochemistry research. Plant scientists studying specialized plant metabolism (previously often known as ‘secondary metabolism’) can foresee tremendous advances in their understanding of the mechanisms underlying the production and function of an enormous variety of plant metabolites, and of their regulation and evolution. Such remarkable progress would never have been expected 10 years ago and has taken place in just the last few years (Yonekura-Sakakibara and Saito 2009). Two technological breakthroughs seem to have been the key triggers for this unforeseen progress: metabolomics and mass DNA sequencing. Metabolomics is <15 years old, yet the concept was immediately applied to the plant field as scientists realized its tremendous potential for understanding the capacity of plants for making a huge array of compounds (Bino et al. 2004). Metabolomics now makes possible comprehensive profiling of nearly all the metabolites that accumulate in plant cells (Saito and Matsuda 2010). The second technological breakthrough was ultra-high-throughput DNA sequencing, with so-called ‘next-generation DNA sequencers’ (Wang et al. 2009, Ozsolak and Milos 2011). Until the realization of this technology, no one would have anticipated genomics-based studies of hundreds of medicinal or exotic plant species— genomics was only for model plants or major crops, whose genome sequences could only be revealed by large international research consortia (or by huge well-funded undertakings). However, newly developed mass DNA sequencers have made comprehensive genome and transcriptome sequencing possible for ordinary phytochemical researchers who are investigating the synthesis of particular plant metabolites out of their own curiosity. By combining data sets from metabolomics and genomics/transcriptomics, one can understand relationships between metabolites and genes that allow the generation of testable hypotheses about the functions of genes and metabolites (Higashi and Saito 2013, Hur et al. 2013, Yonekura-Sakakibara et al. 2013). During this integration and hypothesis-generation phase, databases and bioinformatics play indispensable roles in reducing this ‘systems biology’ workload. Such studies will provide us with an understanding of the evolution of genes and pathways and hence in-depth fundamental insights into plant life. This special focus issue (SFI) on ‘Phytochemical Genomics’ is intended to serve as a synthesis of the most up to date information in this field, indicating not only current trends but also its future prospects. For this SFI of Plant and Cell Physiology, we invited one review article and six original articles reporting on the exciting and growing field of phytochemical genomics. The huge numbers of specialized metabolites produced in plants are mainly classified into three basic groups: alkaloids, terpenoids and phenolic compounds. Among alkaloids, benzylisoquinoline alkaloids (BIAs), including the narcotic analgesics codeine and morphine, are one of the groups of compounds most exploited for their medicinal properties. In this SFI, Hagel and Facchini (2013; see pp. 647–672) review recent advances in biosynthetic studies of BIAs including transcriptomics, proteomics and metabolomics; they also discuss the application of synthetic biology to the development of production by microbes as an alternative to plants as a potential commercial source of valuable BIAs. Another three deep transcritome analyses are reported in this SFI. Catharanthus roseus synthesizes numerous terpenoid indole alkaloids, such as the anticancer drugs vinblastine and vincristine. So far, pathway databases and metabolic networks reconstructed from omics sequence data have been mainly built for model plant species such as Arabidopis and rice. Van Moerkercke et al. (2013; see pp. 673–685) conducted a deep transcriptome analysis in the medicinal plant, C. roseus, and constructed a detailed metabolic pathway database ‘CathaCyc’ that contains 390 pathways with more than a thousand assigned enzymes. Yamazaki et al. (2013; see pp. 686–696) coupled the deep transcriptome analysis with untargeted metabolic profiling in Ophiorrhiza pumila, which produces the anti-cancer alkaloids camptothecin and anthraquinones. Yamazaki and colleagues compared both transcriptome and metabolome data sets in the alkaloid-producing hairy root with a cell suspension that does not produce alkaloids. Glycyrrhiza plants produce various phytochemicals, among them many different terpenoids and flavonoids. Among the phytochemicals, glycyrrhizin exhibits several sorts of pharmacological activity and is also used as a natural sweetener. Two cytochrome P450 monooxygenase (P450s) genes for glycyrrhizin biosynthesis have been recently identified (Seki et al. 2008, Seki et al. 2011). Ramilowski et al. (2013; see pp. 697–710) conducted deep transcriptome analysis in G. uralensis, and