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Taxonomic tree of the 31 investigated plant species. The tree is based on NCBI taxonomy and highlights some of the investigated plant families and their taxonomic relationship.
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The existence of Metabolic Gene Clusters (MGCs) in plant genomes has recently raised increased interest. Thus far, MGCs were commonly identified for pathways of specialized metabolism, mostly those associated with terpene type products. For efficient identification of novel MGCs, computational approaches are essential. Here, we present PhytoClust;...
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Celery (Apium graveolens L.) is a plant belonging to the Apiaceae family, and a popular vegetable worldwide because of its abundant nutrients and various medical functions. Although extensive genetic and molecular biological studies have been conducted on celery, its genomic data remain unclear. Given the significance of celery and the growing dema...
Citations
... BGCs typically gather a variety of modifying enzymes, including cytochrome P450 monooxygenases, glycosyltransferases, acyltransferases, methyltransferases, dioxygenases, carboxylesterases, dehydrogenases/reductases, as well as transaminases among others. Based on these features, algorithms such as PlantiSMASH and PhytoClust have been developed to locally detect typical combinations of enzymes and, consequently, predict specialized BGCs in plants [3,4], thus highlighting how mining genomes could illuminate plant chemodiversity (reviewed in Ref. [5]). As a prominent example, a recent PlantiSMASH-guided approach successfully led to the genomics-driven elucidation of the pathway for the biosynthesis of saponin adjuvants from the soapbark tree ( Figure 1). ...
... Furthermore, the study of metabolic gene clusters, which are groups of co-localized and potentially coregulated non-homologous genes involved in specific metabolic pathways, has gained attention (Nützmann et al., 2016;Töpfer et al., 2017). While these clusters have long been observed in microbial genetics, their existence in plant metabolic pathways has only recently been explored (Zheng et al., 2002;Rocha, 2008;Koonin, 2009). ...
Glyceollins, a family of phytoalexins elicited in legume species, play crucial roles in environmental stress response (e.g., defending against pathogens) and human health. However, little is known about the genetic basis of glyceollin elicitation. In the present study, we employed a metabolite-based genome-wide association (mGWA) approach to identify candidate genes involved in glyceollin elicitation in genetically diverse and understudied wild soybeans subjected to soybean cyst nematode. In total, eight SNPs on chromosomes 3, 9, 13, 15, and 20 showed significant associations with glyceollin elicitation. Six genes fell into two gene clusters that encode glycosyltransferases in the phenylpropanoid pathway and were physically close to one of the significant SNPs (ss715603454) on chromosome 9. Additionally, transcription factors (TFs) genes such as MYB and WRKY were also found as promising candidate genes within close linkage to significant SNPs on chromosome 9. Notably, four significant SNPs on chromosome 9 show epistasis and a strong signal for selection. The findings describe the genetic foundation of glyceollin biosynthesis in wild soybeans; the identified genes are predicted to play a significant role in glyceollin elicitation regulation in wild soybeans. Additionally, how the epistatic interactions and selection influence glyceollin variation in natural populations deserves further investigation to elucidate the molecular mechanism of glyceollin biosynthesis.
... With the increasing projects of plant genomes sequencing, an expanding number of biosynthetic gene clusters (BGC), coding enzymes involved in biosynthesis of specialized metabolisms (for instance BIAs), are being discovered [66,67]. Presently, computational methods like METACLUSTER [68], plantiSMASH [69] or PhytoClust [70] enable the anticipation of BGCs, offering a promising avenue for uncovering novel aspects of plant metabolism and potential new pharmaceutics. Further they can be used in synthetic biology approaches for heterologous metabolites production (see Herbgenomics as an approach in enhanced Papaveraceae biopharmaceutical production) [57]. ...
Herbal medicines were widely used in ancient and modern societies as remedies for human ailments. Notably, the Papaveraceae family includes well-known species, such as Papaver somniferum and Chelidonium majus, which possess medicinal properties due to their latex content. Latex-bearing plants are a rich source of diverse bioactive compounds, with applications ranging from narcotics to analgesics and relaxants. With the advent of high-throughput technologies and advancements in sequencing tools, an opportunity exists to bridge the knowledge gap between the genetic information of herbs and the regulatory networks underlying their medicinal activities. This emerging discipline, known as herbgenomics, combines genomic information with other -omics studies to unravel the genetic foundations, including essential gene functions and secondary metabolite biosynthesis pathways. Furthermore, exploring the genomes of various medicinal plants enables the utilization of modern genetic manipulation techniques, such as Clustered Regularly-Interspaced Short Palindromic Repeats (CRISPR/Cas9) or RNA interference. This technological revolution has facilitated systematic studies of model herbs, targeted breeding of medicinal plants, the establishment of gene banks and the adoption of synthetic biology approaches. In this article, we provide a comprehensive overview of the recent advances in genomic, transcriptomic, proteomic and metabolomic research on species within the Papaveraceae family. Additionally, it briefly explores the potential applications and key opportunities offered by the -omics perspective in the pharmaceutical industry and the agrobiotechnology field.
... Various metabolic gene clusters (MGCs) are co-localized on the genome. These often represent groups of genes involved in the biosynthesis of SMs (Topfer et al., 2017). Chromatin state analysis can be employed to identify the conservation and diversity among co-expressed genes. ...
... EFs of order sebacinales helps the host plant in enhancing its growth, development and stress tolerance potential, is revealed by this approach (Weiss et al., 2011). Several bioinformatic tools, such as plantiSMASH , phyto cluster (Töpfer et al., 2017), and clusterfinder (Schläpfer et al., 2017;Chavali and Rhee, 2018), have been developed to predict plant biosynthetic gene clusters (BGCs) using plant genomic sequences, protein annotations, and gene expression profiles. This facilitates the identification of plant secondary metabolites, which can have important implications in fields such as drug discovery and agriculture. ...
Endophytic fungi comprise host-associated fungal communities which thrive within the tissues of host plants and produce a diverse range of secondary metabolites with various bioactive attributes. The metabolites such as phenols, polyketides, saponins, alkaloids help to mitigate biotic and abiotic stresses, fight against pathogen attacks and enhance the plant immune system. We present an overview of the association of endophytic fungal communities with a plant host and discuss molecular mechanisms induced during their symbiotic interaction. The overview focuses on the secondary metabolites (especially those of terpenoid nature) secreted by endophytic fungi and their respective function. The recent advancement in multi-omics approaches paved the way for identification of these metabolites and their characterization via comparative analysis of extensive omics datasets. This study also elaborates on the role of diverse endophytic fungi associated with key agricultural crops and hence important for sustainability of agriculture.
... Biosynthetic gene clusters (BGCs) in Musaceae species were identified by plantiSMASH v1.0 (Plant Secondary Metabolite Analysis Shell) [88]. The libraries used in PhytoClust [89] were also used when running the plantiSMASH tool to enhance BGC identifications. ...
Background
Musa beccarii (Musaceae) is a banana species native to Borneo, sometimes grown as an ornamental plant. The basic chromosome number of Musa species is x = 7, 10, or 11; however, M. beccarii has a basic chromosome number of x = 9 (2n = 2x = 18), which is the same basic chromosome number of species in the sister genera Ensete and Musella. Musa beccarii is in the section Callimusa, which is sister to the section Musa. We generated a high-quality chromosome-scale genome assembly of M. beccarii to better understand the evolution and diversity of genomes within the family Musaceae.
Findings
The M. beccarii genome was assembled by long-read and Hi-C sequencing, and genes were annotated using both long Iso-seq and short RNA-seq reads. The size of M. beccarii was the largest among all known Musaceae assemblies (∼570 Mbp) due to the expansion of transposable elements and increased 45S ribosomal DNA sites. By synteny analysis, we detected extensive genome-wide chromosome fusions and fissions between M. beccarii and the other Musa and Ensete species, far beyond those expected from differences in chromosome number. Within Musaceae, M. beccarii showed a reduced number of terpenoid synthase genes, which are related to chemical defense, and enrichment in lipid metabolism genes linked to the physical defense of the cell wall. Furthermore, type III polyketide synthase was the most abundant biosynthetic gene cluster (BGC) in M. beccarii. BGCs were not conserved in Musaceae genomes.
Conclusions
The genome assembly of M. beccarii is the first chromosome-scale genome assembly in the Callimusa section in Musa, which provides an important genetic resource that aids our understanding of the evolution of Musaceae genomes and enhances our knowledge of the pangenome.
... Other omics analyses such as genomics can provide complementary structural as well as functional information about plant specialized metabolites. In some cases, groups of chromosomally clustered biosynthetic genes in the plant genome together encode for the production of a metabolite: PlantiSmash (Kautsar et al. 2017(Kautsar et al. , 2018, PhytoClust (Töpfer et al. 2017), PlantClusterFinder (Schläpfer et al. 2017), and CycloNovo (Behsaz et al. 2020) recognize such gene clusters based on specific rules that detect core biosynthetic enzymes that are responsible for the creation of basic scaffolds such as terpenes and peptides. "Unclustered" pathways can be predicted through the identification of coexpression modules from transcriptomics data, which has been shown to constitute a powerful approach to identifying biosynthetic genes involved in the same pathway (Wisecaver et al. 2017). ...
Plants contain manifold and structurally diverse specialized metabolites, also referred to as natural products. Many plant compound classes have important biological functions such as stimulating plant growth, maintaining plant health, and recruitment of a functional root microbiome. Analytical methods to study and map these specialized metabolites have been developed for a while. In recent years, mass spectrometry‐based metabolomics technologies have been maturing and they are capturing increasingly information‐dense spectral data. To couple structural information to the spectral and statistical metabolomics data to allow for biochemical interpretation, computational metabolomics tools are needed. In this chapter, we show how plant chemical diversity is increasingly captured through the coupling of untargeted mass spectrometry‐based metabolomics acquisition methods and computational metabolomics workflows that perform metabolome mining and annotation. By showcasing examples from three different plant chemistry studies, it is shown how metabolomics data is transferred into information‐rich molecular networks that enable us to answer key biological questions by linking plant taxonomy and herbivore resistance phenotypes to the plant specialized metabolite contents. We conclude that the further development and widespread implementation and democratization of computational metabolomics workflows will be needed to prepare metabolomics for the “big data” era that is looming on the horizon.
... For example, whilst Martin et al (2010) have identified some sesquiterpene synthase encoding genes in grape, their analysis was based on biochemical reactions, with no description of gene cluster organization underlying the identified enzymes. In recent years, many terpene synthases have been successfully characterised from plants, fungi and bacteria using whole genome sequencing (Medema and Osbourn 2016;Nützmann et al 2016;Töpfer et al 2017;Polturak and Osbourn 2021;. In this context, our study employed in silico genome mining to explore the diversity and the phylogenetic relationship of the terpene biosynthetic gene clusters across three plant genomes: grape (V. ...
Plants represent a rich repository of taxonomically restricted, yet chemically diverse, secondary metabolites that are synthesised via specific metabolic pathways. Enzyme specificity and biosynthetic gene clustering are the bottleneck of secondary metabolite evolution. As economically important food crops, grape, strawberry, and olive produce many pharmaceutically important molecules; however, their specific biosynthetic pathways remain inaccessible. Our genomic-based analysis of these three species reveal the biosynthetic diversity of their specialised secondary metabolites. We found over 20 BGCs predicted, most of which were characterised in two species, grape and strawberry. Gene annotation of the biosynthetic candidate genes predicted the production of many medically and industrially important compounds including cycloartenol, nerolidol, farnesene and valencene. Although most of the predicted clusters are concentrated in specific genomic positions, some have shown gene duplications in their clusters, which is suggestive of pseudogenes or misassembled genomes. Our genome mining and putative functional analysis of the biosynthetic genes annotated in the three species indicated the evolutionary processes that have shaped their current genetic structure and the structural diversity of their chemical compositions. Revealing the biogenetic background of these natural molecules is a step forward towards the expansion of their chemical diversification via engineering their biosynthetic genes heterologously, as well as the identification of their role in the interaction between those plants and their biotic and abiotic conditions.
... In the post-genomic era, the availability of reference genomes expedited identification of MGCs in plants using genomic mining. Recently, computer algorithms such as Plantismash [146], Phytoclust [147] and PlantClusterFinder [148] have been developed to predict MGCs encoding potential biosynthetic pathways of secondary metabolites. A large number of potential MGCs have been found in plants encoding unknown biosynthetic pathways, highlighting the limitation of our knowledge of what and how plants can produce chemically. ...
Globally, medicinal plant natural products (PNPs) are a major source of substances used in traditional and modern medicine. As we human race face tremendous public health challenge posed by emerging infectious diseases, antibiotic resistance and surging drug prices etc., harnessing the healing power of medicinal plants gifted from mother nature is more urgent than ever in helping us survive future challenge in a sustainable way. PNP research efforts in pre-genomic era focus on discovering bioactive molecules with pharmaceutical activities, and identifying individual genes responsible for biosynthesis. Critically, systemic biological, multi- and inter-disciplinary approaches integrating and interrogating all accessible data from genomics, metabolomics, structural biology and chemical informatics, are necessary to accelerate the full characterization of biosynthetic and regulatory circuitry for producing PNPs in medicinal plants. In this review, we attempt to provide a brief update on the current research of PNPs in medicinal plants by focusing on how different state-of-the-art biotechnologies facilitate their discovery, the molecular basis of their biosynthesis, as well as synthetic biology. Finally, we humbly provide a foresight of the research trend for understanding the biology of medicinal plants in the coming decades.
... Unfortunately, classical genome mining has been mainly applied to bacterial and fungal genomes, and only recently plant genomes are also starting to be explored [54]. Thus, some platforms have been recently created to identify BGCs using plant genomes such as PhytoClust [55] and plantiSMASH [56]. Nevertheless, additional research is still required in this field. ...
Engineering microbial biofactories for the transformation of industrial residues into value-added products represents a significant step towards sustainability. This chapter has two main goals: first, to review the current approaches that can be used to engineering synthetic biofactories of relevance for white biotechnology, and second, to provide clear examples of how these biofactories represent an excellent platform to transform industrial residues in value-added products. Several technologies to engineering microbial biofactories (e.g., BioBricks design, pathway engineering, modular assembly, and chassis fine-tuning) will be discussed using a multiscale approach from genes to biofactories. The relevance of omics databases for the identification of novel biological components (genome mining) and fine-tuning their expression will be also discussed. Finally, several examples will be provided to highlight the relevance of engineering microorganisms as biofactories for a sustainable future.
https://www.elsevier.com/books/genomics-and-the-global-bioeconomy/patrinos/978-0-323-91601-1
