Hao / Gu / Xiao Medicinal Plants

Chemistry, Biology and Omics
1. Auflage 2015
ISBN: 978-0-08-100103-5
Verlag: Elsevier Science & Techn.
Format: EPUB
Kopierschutz: 6 - ePub Watermark

E-Book, Englisch, 694 Seiten

Medicinal Plants: Chemistry, Biology and Omics reviews the phytochemistry, chemotaxonomy, molecular biology, and phylogeny of selected medicinal plant tribes and genera, and their relevance to drug efficacy. Medicinal plants provide a myriad of pharmaceutically active components, which have been commonly used in traditional Chinese medicine and worldwide for thousands of years. Increasing interest in plant-based medicinal resources has led to additional discoveries of many novel compounds, in various angiosperm and gymnosperm species, and investigations on their chemotaxonomy, molecular phylogeny and pharmacology. Chapters in this book explore the interrelationship within traditional Chinese medicinal plant groups and between Chinese species and species outside of China. Chapters also discuss the incongruence between chemotaxonomy and molecular phylogeny, concluding with chapters on systems biology and '-omics technologies (genomics, transcriptomics, proteomics, and metabolomics), and how they will play an increasingly important role in future pharmaceutical research. - Reviews best practice and essential developments in medicinal plant chemistry and biology - Discusses the principles and applications of various techniques used to discover medicinal compounds - Explores the analysis and classification of novel plant-based medicinal compounds - Includes case studies on pharmaphylogeny - Compares and integrates traditional knowledge and current perception of worldwide medicinal plants

Da-Cheng Hao is Associate Professor and Primary Investigator at the School of Environment and Chemical Engineering and the Biotechnology Institute, at Dalian Jiaotong University, in Dailan, China. He is a Guest Professor at the Institute of Medicinal Plant Development at the Chinese Academy of Medical Sciences, and has published widely in leading journals in the field. Dr Hao is the author of Medicinal Plants, published by Woodhead Publishing in 2015.

Autoren/Hrsg.

Hao, Da-Cheng

Gu, Xiao Jie

Xiao, Pei Gen

Leseproben

2 High-throughput sequencing in medicinal plant transcriptome studies
Abstract
Two alternative approaches, RNA-Seq and digital gene expression (DGE), to the medicinal plant transcriptome analysis are sequence-based and have become increasingly popular due to rapid developments in the high-throughput sequencing technologies. Among the high-throughput sequencing techniques, the 454 pyrosequencing and Illumina sequencing platforms are the first commercially available and relatively mature ones and thus widely used in various fields of medicinal plant transcriptome research. Metabolic pathway analysis of medicinal plants and molecular marker mining for the molecular breeding can be facilitated and accelerated by the smart use of RNA-Seq. DGE provides novel insights into the biochemical mechanisms in the medicinal plants. This review illustrates the great potential of high-throughput sequencing in the fields that are closely related to the drug discovery, drug development, and large-scale production of plant natural products and envisions its future development and applications in the medicinal plant transcriptome study. Keywords High-throughput sequencing Medicinal plant transcriptome 454 Pyrosequencing Illumina sequencing platform Drug development 2.1 Introduction
Research on plant-derived products employed in medicine has always been led by chemists and phytochemists; however, as the association between the secondary metabolites and the active genes that encode them is elucidated, the means by which genetics and genomics are applied will become more efficient in advancing natural product discoveries. Plants synthesize a myriad of secondary metabolites, the biochemical screening of which is viewed as indispensable for the discovery of novel chemicals that can be developed as drugs. Studies of their biosynthesis and the relevant genetic mechanism can facilitate the large-scale production of drugs via molecular breeding, metabolic engineering, and transgenic plants. RNA sequencing, which is more cost-effective and more feasible than the whole genome sequencing, is becoming a powerful tool in medicinal plant research and has accelerated the investigation of the plant gene expression. Roche 454 pyrosequencing and Illumina high-throughput sequencing are popular sequencing platforms in the medicinal plant transcriptome studies. Advances in the sequencing workflow, from sample preparation to data analysis, enable rapid profiling and deep investigation of the medicinal plant transcriptome. Good sequencing randomness is obtained in the high-throughput transcriptome sequencing (Figure 2.1), as the distribution of reads in the assembled unigenes is largely homogeneous. Protein-coding sequence (CDS) prediction, a necessary step in the functional annotation of genes based on the transcriptome data, can be performed based on the assembled unigenes (e.g., Figure 2.2). This chapter summarizes the recent progress in the application of high-throughput sequencing in the medicinal plant transcriptome studies. Figure 2.1 Sequencing randomness inferred from the reads distribution of the Salvia sclarea leaf transcriptome (Hao et al., 2015). (a) 0 h of 7.5 mM MeJA treatment; (b) 10 h; (c) 26 h. We sum the numbers of the reads aligned to different positions of the reference genes. Because genes have different lengths, we normalize the positions covered by the reads in the reference genes to relevant positions (i.e., ratio between the positions of reads on the reference genes and length of the genes). If randomness of mRNA fragmentation is ideal, there should be a roughly even distribution of reads in the reference genes. The horizontal coordinate is the relevant position from the 5' end to the 3' end, and the vertical coordinate is the corresponding reads number. Figure 2.2 Prediction of protein-coding sequence (CDS) from the assembled T. mairei unigenes. Unigenes are firstly aligned by BLASTX (E-value < 0.00001) to protein databases in the priority order of nr, Swiss-Prot, KEGG, and COG. Unigenes aligned to databases with higher priority will not enter the next circle. The alignments end when all circles are finished. Proteins with the highest ranks in BLAST results are taken to decide the coding region sequences of unigenes; then, the coding region sequences are translated into amino acid sequences with the standard codon table. Thus, both the nucleotide sequences (5'–3') and amino acid sequences of the unigene-coding region are acquired. Unigenes that cannot be aligned to any database are scanned by ESTScan (http://www.ch.embnet.org/software/ESTScan.html) to get the nucleotide sequence (5'–3') and amino acid sequence of the coding regions. (a) Length distribution of CDS predicted from BLAST results and by ESTScan. 1, 200; 2, 300; 3, 400; 4, 500; 5, 600; 6, 700; 7, 800; 8, 900; 9, 1000; 10, 1100; 11, 1200; 12, 1300; 13, 1400; 14, 1500; 15, 1600; 16, 1700; 17, 1800; 18, 1900; 19, 2000; 20, 2100; 21, 2200; 22, 2300; 23, 2400; 24, 2500; 25, 2600; 26, 2700; 27, 2800; 28, 2900; 29, 3000; 30, > 3000. (b) Gap (N) distribution of CDS predicted from BLAST results and by ESTScan. 1, 0; 2, 0.01; 3, 0.02; 4, 0.03; 5, 0.04; 6, 0.05; 7, 0.06; 8, 0.07; 9, 0.08; 10, 0.09; 11, 0.1; 12, 0.11; 13, 0.12; 14, 0.13; 15, 0.14; 16, 0.15; 17, 0.16; 18, 0.17; 19, 0.18; 20, 0.19; 21, 0.2; 22, 0.21; 23, 0.22; 24, 0.23; 25, 0.24; 26, 0.25; 27, 0.26; 28, 0.27; 29, 0.28; 30, 0.29; 31, 0.3; 32, > 0.3. 2.2 Metabolic pathway analysis
2.2.1 Terpenoid and saponin
Traditional Chinese medicinal plants have been used in disease prevention and treatment for thousands of years and currently constitute a rich source of medicinal compounds and drug candidates. The species-specific knowledge of plant metabolism has been obtained by determining the expression of the transcriptomes from some traditional Chinese medicinal plants. Artemisia annua (sweet wormwood or Qing Hao) has been used as a remedy by Chinese herbalists for more than 2000 years (Maude et al., 2010), but it was not subjected to scientific scrutiny until the 1970s. The most prominent antimalarial drug artemisinin, a sesquiterpene lactone, is produced in the glandular trichomes of A. annua. However, only limited genomic information was available in this nonmodel plant species. The A. annua glandular trichome transcriptome has been globally characterized using 454 pyrosequencing (Wang et al., 2009). By BLAST search against the NCBI nonredundant protein database, putative functions were assigned to over 28,573 unigenes, including previously undescribed enzymes likely involved in sesquiterpene biosynthesis. In higher plants, the terpenoid precursor isopentenyl diphosphate (IPP) can be produced from both MVA and MEP (methyl-d-erythritol 4-phosphate) pathway routes, which is then converted to its isomer dimethylallyl pyrophosphate (DMAPP). Unigenes encoding the MEP and MVA pathway enzymes and all the sesquiterpene artemisinin pathway enzymes were found in this pyrosequencing dataset. Unigenes corresponding to MEP pathway enzymes were two folds more abundant than MVA pathway transcripts, suggesting that the MEP pathway may serve as a major route for DMAPP/IPP production in the A. annua trichomes. Three unigenes annotated as sesquiterpene synthases were selected for RACE (rapid amplification of cDNA ends)-PCR to retrieve the full-length cDNAs, which provide the raw sequences for the further functional characterization of these enzymes. Moreover, large amounts of unigenes annotated as phenylpropanoid and flavonoid pathway enzymes were found in the assembled pyrosequencing expressed sequence tag (EST) collection. Almost all medicinal plants have little or no genomic data available. The new-generation high-throughput sequencing offers rapid characterization of the transcriptome and thus provides a comprehensive tool for gene discovery and elucidation of metabolic pathways. In 2010, the 454 pyrosequencing platform was used to produce EST databases from cDNA libraries derived from enriched glandular trichome preparations of the Artemis hybrid (Graham et al., 2010). Key genes associated with metabolic pathways and phenotypic traits such as trichome development and plant architecture that could affect artemisinin yield are found in the sequencing dataset, and their relative abundance in the different libraries are quantified. The CAP3 software was used in the transcriptome sequence clustering and de novo assembly of both A. annua and another Chinese medicinal plant Epimedium sagittatum (Yin Yang Huo in Chinese) (Zeng et al., 2010). Flavonoids are the major medicinal compounds of Epimedium species. Twenty-nine EST consensus sequences relating to the secondary metabolic process were found, including genes encoding key enzymes in the flavonoid biosynthetic pathway such as phenylalanine ammonia lyase (PAL), cinnamate 4-hydroxylase (C4H), 4-coumarate-CoA ligase (4CL), and uridine diphosphate glucose (UDPG)-flavonoid glucosyltransferase. Furthermore, more than 300 EST sequences representing transcription regulators were annotated. Functional studies of these genes will facilitate molecular modification, gene transformation, and metabolic engineering to enhance the target drug production. The nonmevalonate pathway or MEP/DOXP pathway of isoprenoid biosynthesis is an...