Using Gene Expression to Study Specialized Metabolism-A Practical Guide

Metabolic engineering of narrow-leafed lupin for the production of enantiomerically pure (-)-sparteine

The protein crops known as lupins have been bred to accumulate low levels of antinutritional alkaloids, neglecting their potential as sources of valuable metabolites. Here, we engineered narrow-leafed lupin (NLL) to accumulate large amounts of a single alkaloid of industrial interest called (-)-sparteine. While (-)-sparteine is recognized as a key auxiliary molecule in chiral synthesis, its variable price and limited availability have prevented its large-scale use. We identified two enzymes that initiate the conversion of (-)-sparteine to a variety of alkaloids accumulating in NLL. The first one is a cytochrome P450 monooxygenase belonging to family 71 (CYP71D189), and the second one is a short-chain dehydrogenase/reductase (SDR1). We screened a non-GMO NLL mutant library and isolated a knockout in CYP71D189. The knockout displayed an altered metabolic profile where (-)-sparteine accounted for 96% of the alkaloid content in the seeds (GC-MS basis). The (-)-sparteine isolated from the mutant seeds was enantiomerically pure (99% enantiomeric excess). Apart from the altered alkaloid profile, the mutant did not have any noticeable phenotype. Our work demonstrates that (-)-sparteine is the precursor of most QAs in NLL and expands the current uses of NLL as a crop.

Combining Short- and Long-Read Transcriptomes for Targeted Enzyme Discovery

The discovery of genes that code for a specific enzymatic activity is important in various fields of life science and provides valuable biotechnological tools. Many genes that contribute to the production of secondary metabolites and specialized metabolic pathways are still not identified. Due to the great diversity of metabolic functions found in nature and their rapid evolutionary adaptation, we need precise but high-throughput approaches for a targeted search based on minimal prior knowledge. In this chapter, we describe a transcriptomics pipeline that was used to search for candidate genes coding for a specific enzymatic activity in a nonmodel species. We generated and combined short- and long-read transcriptomic data to obtain reliable full-length transcript sequences along with information on allelic variation, isoform expression, and condition-specific expression. Based on protein domain annotations of coding sequences and transcriptomic data, we selected candidate genes for activity assays. We provide detailed instructions for analysis and quality control steps in our pipeline that can be applied to other biological questions.

Plant sesquiterpene lactones

Sesquiterpene lactones (STLs) are a prominent group of plant secondary metabolites predominantly found in the Asteraceae family and have multiple ecological roles and medicinal applications. This review describes the evolutionary and ecological significance of STLs, highlighting their roles in plant defence mechanisms against herbivory and as phytotoxins, alongside their function as environmental signalling molecules. We also cover the substantial role of STLs in medicine and their mode of action in health and disease. We discuss the biosynthetic pathways and the various modifications that make STLs one of the most diverse groups of metabolites. Finally, we discuss methods for identifying and predicting STL biosynthesis pathways. This article is part of the theme issue 'The evolution of plant metabolism'.

Evolution of plant metabolism: the state-of-the-art

Immense chemical diversity is one of the hallmark features of plants. This chemo-diversity is mainly underpinned by a highly complex and biodiverse biochemical machinery. Plant metabolic enzymes originated and were inherited from their eukaryotic and prokaryotic ancestors and further diversified by the unprecedentedly high rates of gene duplication and functionalization experienced in land plants. Unlike prokaryotic microbes, which display frequent horizontal gene transfer events and multiple inputs of energy and organic carbon, land plants predominantly rely on organic carbon generated from CO2 and have experienced relatively few gene transfers during their recent evolutionary history. As such, plant metabolic networks have evolved in a stepwise manner using existing networks as a starting point and under various evolutionary constraints. That said, until recently, the evolution of only a handful of metabolic traits had been extensively investigated and as such, the evolution of metabolism has received a fraction of the attention of, the evolution of development, for example. Advances in metabolomics and next-generation sequencing have, however, recently led to a deeper understanding of how a wide range of plant primary and specialized (secondary) metabolic pathways have evolved both as a consequence of natural selection and of domestication and crop improvement processes. This article is part of the theme issue 'The evolution of plant metabolism'.

LSTrAP-denovo: Automated Generation of Transcriptome Atlases for Eukaryotic Species Without Genomes

Despite the abundance of species with transcriptomic data, a significant number of species still lack sequenced genomes, making it difficult to study gene function and expression in these organisms. While de novo transcriptome assembly can be used to assemble protein-coding transcripts from RNA-sequencing (RNA-seq) data, the datasets used often only feature samples of arbitrarily selected or similar experimental conditions, which might fail to capture condition-specific transcripts. We developed the Large-Scale Transcriptome Assembly Pipeline for de novo assembled transcripts (LSTrAP-denovo) to automatically generate transcriptome atlases of eukaryotic species. Specifically, given an NCBI TaxID, LSTrAP-denovo can (1) filter undesirable RNA-seq accessions based on read data, (2) select RNA-seq accessions via unsupervised machine learning to construct a sample-balanced dataset for download, (3) assemble transcripts via over-assembly, (4) functionally annotate coding sequences (CDS) from assembled transcripts and (5) generate transcriptome atlases in the form of expression matrices for downstream transcriptomic analyses. LSTrAP-denovo is easy to implement, written in Python, and is freely available at https://github.com/pengkenlim/LSTrAP-denovo/.

PEO: Plant Expression Omnibus - a comparative transcriptomic database for 103 Archaeplastida

The Plant Expression Omnibus (PEO) is a web application that provides biologists with access to gene expression insights across over 100 plant species, ~60 000 manually annotated RNA-seq samples, and more than 4 million genes. The tool allows users to explore the expression patterns of genes across different organs, identify organ-specific genes, and discover top co-expressed genes for any gene of interest. PEO also provides functional annotations for each gene, allowing for the identification of genetic modules and pathways. PEO is designed to facilitate comparative kingdom-wide gene expression analysis and provide a valuable resource for plant biology research. We provide two case studies to demonstrate the utility of PEO in identifying candidate genes in pollen coat biosynthesis in Arabidopsis and investigating the biosynthetic pathway components of capsaicin in Capsicum annuum. The database is freely available at https://expression.plant.tools/.

Transcriptomic and metabolomic characterization of antibacterial activity of Melastoma dodecandrum

Antibacterial resistance poses a significant global threat, necessitating the discovery of new therapeutic agents. Plants are a valuable source of secondary metabolites with demonstrated anticancer and antibacterial properties. In this study, we reveal that Melastoma dodecandrum exhibits both bacteriostatic and bactericidal effects against Pseudomonas aeruginosa and Staphylococcus aureus. Treatment with plant extracts results in membrane damage and a reduction in P.aeruginosa swimming and swarming motility. A comparative analysis of bacterial transcriptomes exposed to M.dodecandrum extracts and four distinct antibiotics indicates that the extracts may trigger similar transcriptomic responses as triclosan, a fatty acid synthesis inhibitor. Activity-guided fractionation suggests that the antibacterial activity is not attributable to hydrolyzable tannins, but to unidentified minor compounds. Additionally, we identified 104 specialized metabolic pathways and demonstrated a high level of transcriptional coordination between these biosynthetic pathways and phytohormones, highlighting potential regulatory mechanisms of antibacterial metabolites in M.dodecandrum.

Medicinal plant genomics

Recent developments in plant genomics have enabled a comprehensive analysis of the medicinal potential of plants based on their gene repertoire. Genes of biosynthesis pathways can be discovered through comparative genomics and through integration of transcriptomic data. Data-driven discovery of specialized metabolites could accelerate research.

Comparative transcriptome analysis to identify putative genes involved in carvacrol biosynthesis pathway in two species of Satureja, endemic medicinal herbs of Iran

Satureja is rich in phenolic monoterpenoids, mainly carvacrol, that is of interest due to diverse biological activities including antifungal and antibacterial. However, limited information is available regarding the molecular mechanisms underlying carvacrol biosynthesis and its regulation for this wonderful medicinal herb. To identify the putative genes involved in carvacrol and other monoterpene biosynthesis pathway, we generated a reference transcriptome in two endemic Satureja species of Iran, containing different yields (Satureja khuzistanica and Satureja rechingeri). Cross-species differential expression analysis was conducted between two species of Satureja. 210 and 186 transcripts related to terpenoid backbone biosynthesis were identified for S. khuzistanica and S. rechingeri, respectively. 29 differentially expressed genes (DEGs) involved in terpenoid biosynthesis were identified, and these DEGs were significantly enriched in monoterpenoid biosynthesis, diterpenoid biosynthesis, sesquiterpenoid and triterpenoid biosynthesis, carotenoid biosynthesis and ubiquinone and other terpenoid-quinone biosynthesis pathways. Expression patterns of S. khuzistanica and S. rechingeri transcripts involved in the terpenoid biosynthetic pathway were evaluated. In addition, we identified 19 differentially expressed transcription factors (such as MYC4, bHLH, and ARF18) that may control terpenoid biosynthesis. We confirmed the altered expression levels of DEGs that encode carvacrol biosynthetic enzymes using quantitative real-time PCR (qRT-PCR). This study is the first report on de novo assembly and transcriptome data analysis in Satureja which could be useful for an understanding of the main constituents of Satureja essential oil and future research in this genus.

Transcriptome and Metabolome Profiling Provide Insights into Flavonoid Synthesis in Acanthus ilicifolius Linn

Acanthus ilicifolius is an important medicinal plant in mangrove forests, which is rich in secondary metabolites with various biological activities. In this study, we used transcriptomic analysis to obtain differentially expressed genes in the flavonoid metabolic pathway and metabolomic methods to detect changes in the types and content in the flavonoid metabolic synthesis pathway. The results showed that DEGs were identified in the mature roots vs. leaves comparison (9001 up-regulated and 8910 down-regulated), mature roots vs. stems comparison (5861 up-regulated and 7374 down-regulated), and mature stems vs. leaves comparison (10,837 up-regulated and 11,903 down-regulated). Furthermore, two AiCHS genes and four AiCHI genes were up-regulated in the mature roots vs. stems of mature A. ilicifolius, and were down-regulated in mature stems vs. leaves, which were highly expressed in the A. ilicifolius stems. A total of 215 differential metabolites were found in the roots vs. leaves of mature A. ilicifolius, 173 differential metabolites in the roots vs. stems, and 228 differential metabolites in the stems vs. leaves. The metabolomic results showed that some flavonoids in A. ilicifolius stems were higher than in the roots. A total of 18 flavonoid differential metabolites were detected in the roots, stems, and leaves of mature A. ilicifolius. In mature leaves, quercetin-3-O-glucoside-7-O-rhamnoside, gossypitrin, isoquercitrin, quercetin 3,7-bis-O-β-D-glucoside, and isorhamnetin 3-O-β-(2″-O-acetyl-β-D-glucuronide) were found in a high content, while in mature roots, di-O-methylquercetin and isorhamnetin were the major compounds. The combined analysis of the metabolome and transcriptome revealed that DEGs and differential metabolites were related to flavonoid biosynthesis. This study provides a theoretical basis for analyzing the molecular mechanism of flavonoid synthesis in A. ilicifolius and provides a reference for further research and exploitation of its medicinal value.

Comprehensive expression analyses of the ABCG subfamily reveal SvABCG17 as a potential transporter of lignin monomers in the model C4 grass Setaria viridis

Although several aspects of lignin metabolism have been extensively characterized, the mechanism(s) by which lignin monomers are transported across the plasma membrane remains largely unknown. Biochemical, proteomic, expression and co-expression analyses from several plant species support the involvement of active transporters, mainly those belonging to the ABC superfamily. Here, we report on the genome-wide characterization of the ABCG gene subfamily in the model C4 grass Setaria viridis and further identification of the members potentially involved in monolignol transport. A total of 48 genes encoding SvABCGs were found in the S. viridis genome, from which 21 SvABCGs were classified as full-size transporters and 27 as half-size transporters. Comprehensive analysis of the ABCG subfamily in S. viridis based on expression and co-expression analyses support a role for SvABCG17 in monolignol transport: (i) SvABCG17 is orthologous to AtABCG29, a monolignol transporter in Arabidopsis thaliana; (ii) SvABCG17 displays a similar expression profile to that of lignin biosynthetic genes in a set of different S. viridis tissues and along the elongating internode; (iii) SvABCG17 is highly co-expressed with lignin-related genes in a public transcriptomic database; (iv) SvABCG17displays particularly high expression in the top of the S. viridis elongating internode, a tissue undergoing active lignification; (v) SvABCG17 mRNA localization coincides with the histochemical pattern of lignin deposition; and (vi) the promoter of SvABCG17 is activated by secondary cell wall-associated transcription factors, especially by lignin-specific activators of the MYB family. Further studies might reveal further aspects of this potential monolignol transporter, including its real substrate specificity and whether it works redundantly with other ABC members during S. viridis lignification.

Metabolization and sequestration of plant specialized metabolites in insect herbivores: Current and emerging approaches

Herbivorous insects encounter diverse plant specialized metabolites (PSMs) in their diet, that have deterrent, anti-nutritional, or toxic properties. Understanding how they cope with PSMs is crucial to understand their biology, population dynamics, and evolution. This review summarizes current and emerging cutting-edge methods that can be used to characterize the metabolic fate of PSMs, from ingestion to excretion or sequestration. It further emphasizes a workflow that enables not only to study PSM metabolism at different scales, but also to tackle and validate the genetic and biochemical mechanisms involved in PSM resistance by herbivores. This review thus aims at facilitating research on PSM-mediated plant-herbivore interactions.

Non-target molecular network and putative genes of flavonoid biosynthesis in Erythrina velutina Willd., a Brazilian semiarid native woody plant

Erythrina velutina is a Brazilian native tree of the Caatinga (a unique semiarid biome). It is widely used in traditional medicine showing anti-inflammatory and central nervous system modulating activities. The species is a rich source of specialized metabolites, mostly alkaloids and flavonoids. To date, genomic information, biosynthesis, and regulation of flavonoids remain unknown in this woody plant. As part of a larger ongoing research goal to better understand specialized metabolism in plants inhabiting the harsh conditions of the Caatinga, the present study focused on this important class of bioactive phenolics. Leaves and seeds of plants growing in their natural habitat had their metabolic and proteomic profiles analyzed and integrated with transcriptome data. As a result, 96 metabolites (including 43 flavonoids) were annotated. Transcripts of the flavonoid pathway totaled 27, of which EvCHI, EvCHR, EvCHS, EvCYP75A and EvCYP75B1 were identified as putative main targets for modulating the accumulation of these metabolites. The highest correspondence of mRNA vs. protein was observed in the differentially expressed transcripts. In addition, 394 candidate transcripts encoding for transcription factors distributed among the bHLH, ERF, and MYB families were annotated. Based on interaction network analyses, several putative genes of the flavonoid pathway and transcription factors were related, particularly TFs of the MYB family. Expression patterns of transcripts involved in flavonoid biosynthesis and those involved in responses to biotic and abiotic stresses were discussed in detail. Overall, these findings provide a base for the understanding of molecular and metabolic responses in this medicinally important species. Moreover, the identification of key regulatory targets for future studies aiming at bioactive metabolite production will be facilitated.

Exploiting plant transcriptomic databases: Resources, tools, and approaches

There are now more than 300 000 RNA sequencing samples available, stemming from thousands of experiments capturing gene expression in organs, tissues, developmental stages, and experimental treatments for hundreds of plant species. The expression data have great value, as they can be re-analyzed by others to ask and answer questions that go beyond the aims of the study that generated the data. Because gene expression provides essential clues to where and when a gene is active, the data provide powerful tools for predicting gene function, and comparative analyses allow us to study plant evolution from a new perspective. This review describes how we can gain new knowledge from gene expression profiles, expression specificities, co-expression networks, differential gene expression, and experiment correlation. We also introduce and demonstrate databases that provide user-friendly access to these tools.

Identification of Gene Biomarkers for Tigilanol Tiglate Content in Fontainea picrosperma

Tigilanol tiglate (EBC-46) is a small-molecule natural product under development for the treatment of cancers in humans and companion animals. The drug is currently produced by purification from the Australian rainforest tree Fontainea picrosperma (Euphorbiaceae). As part of a selective-breeding program to increase EBC-46 yield from F. picrosperma plantations, we investigated potential gene biomarkers associated with biosynthesis of EBC-46. Initially, we identified individual plants that were either high (>0.039%) or low EBC-46 (<0.008%) producers, then assessed their differentially expressed genes within the leaves and roots of these two groups by quantitative RNA sequencing. Compared to low EBC-46 producers, high-EBC-46-producing plants were found to have 145 upregulated genes and 101 downregulated genes in leaves and 53 upregulated genes and 82 downregulated genes in roots. Most of these genes were functionally associated with defence, transport, and biosynthesis. Genes identified as expressed exclusively in either the high or low EBC-46-producing plants were further validated by quantitative PCR, showing that cytochrome P450 94C1 in leaves and early response dehydration 7.1 and 2-alkenal reductase in roots were consistently and significantly upregulated in high-EBC-46 producers. In summary, this study has identified biomarker genes that may be used in the selective breeding of F. picrosperma.

PlantNexus: A Gene Co-expression Network Database and Visualization Tool for Barley and Sorghum

Global gene co-expression networks (GCNs) are powerful tools for functional genomics whereby putative functions and regulatory mechanisms can be inferred by gene co-expression. Cereal crops, such as Hordeum vulgare (barley) and Sorghum bicolor (sorghum), are among the most important plants to civilization. However, co-expression network tools for these plants are lacking. Here, we have constructed global GCNs for barley and sorghum using existing RNA-seq data sets. Meta-information was manually curated and categorized by tissue type to also build tissue-specific GCNs. To enable GCN searching and visualization, we implemented a website and database named PlantNexus. PlantNexus is freely available at https://plantnexus.ohio.edu/.

Computational prediction of plant metabolic pathways

Uncovering genes encoding enzymes responsible for the biosynthesis of diverse plant metabolites is essential for metabolic engineering and production of plant metabolite-derived medicine. With the availability of multi-omics data for an ever-increasing number of plant species and the development of computational approaches, the metabolic pathways of many important plant compounds can be predicted, complementing a more traditional genetic and/or biochemical approach. Here, we summarize recent progress in predicting plant metabolic pathways using genome, transcriptome, proteome, interactome, and/or metabolome data, and the utility of integrating these data with machine learning to further improve metabolic pathway predictions.

Unlocking plant metabolic diversity: A (pan)-genomic view

Plants produce a remarkable diversity of structurally and functionally diverse natural chemicals that serve as adaptive compounds throughout their life cycles. However, unlocking this metabolic diversity is significantly impeded by the size, complexity, and abundant repetitive elements of typical plant genomes. As genome sequencing becomes routine, we anticipate that links between metabolic diversity and genetic variation will be strengthened. In addition, an ever-increasing number of plant genomes have revealed that biosynthetic gene clusters are not only a hallmark of microbes and fungi; gene clusters for various classes of compounds have also been found in plants, and many are associated with important agronomic traits. We present recent examples of plant metabolic diversification that have been discovered through the exploration and exploitation of various genomic and pan-genomic data. We also draw attention to the fundamental genomic and pan-genomic basis of plant chemodiversity and discuss challenges and future perspectives for investigating metabolic diversity in the coming pan-genomics era.

Flavonoids - flowers, fruit, forage and the future

Flavonoids are plant-specific secondary metabolites that arose early during land-plant colonisation, most likely evolving for protection from UV-B and other abiotic stresses. As plants increased in complexity, so too did the diversity of flavonoid compounds produced and their physiological roles. The most conspicuous are the pigments, including yellow aurones and chalcones, and the red/purple/blue anthocyanins, which provide colours to flowers, fruits and foliage. Anthocyanins have been particularly well studied, prompted by the ease of identifying mutants of genes involved in biosynthesis or regulation, providing an important model system to study fundamental aspects of genetics, gene regulation and biochemistry. This has included identifying the first plant transcription factor, and later resolving how multiple classes of transcription factor coordinate in regulating the production of various flavonoid classes - each with different activities and produced at differing developmental stages. In addition, dietary flavonoids from fruits/vegetables and forage confer human- and animal-health benefits, respectively. This has prompted strong interest in generating new plant varieties with increased flavonoid content through both traditional breeding and plant biotechnology. Gene-editing technologies provide new opportunities to study how flavonoids are regulated and produced and to improve the flavonoid content of flowers, fruits, vegetables and forages.

Tissue-type specific accumulation of the plastoglobular proteome, transcriptional networks, and plastoglobular functions

Plastoglobules are dynamic protein-lipid microcompartments in plastids enriched for isoprenoid-derived metabolites. Chloroplast plastoglobules support formation, remodeling, and controlled dismantling of thylakoids during developmental transitions and environmental responses. However, the specific molecular functions of most plastoglobule proteins are still poorly understood. This review harnesses recent co-mRNA expression data from combined microarray and RNA-seq information in ATTED-II on an updated inventory of 34 PG proteins, as well as proteomics data across 30 Arabidopsis tissue types from ATHENA. Hierarchical clustering based on relative abundance for the plastoglobule proteins across non-photosynthetic and photosynthetic tissue types showed their coordinated protein accumulation across Arabidopsis parts, tissue types, development, and senescence. Evaluation of mRNA-based forced networks at different coefficient thresholds identified a central hub with seven plastoglobule proteins and four peripheral modules. Enrichment of specific nuclear transcription factors (e.g. Golden2-like) and support for crosstalk between plastoglobules and the plastid gene expression was observed, and specific ABC1 kinases appear part of a light signaling network. Examples of other specific findings are that FBN7b is involved with upstream steps of tetrapyrrole biosynthesis and that ABC1K9 is involved in starch metabolism. This review provides new insights into the functions of plastoglobule proteins and an improved framework for experimental studies.