Dataset Information

Terzyme: a tool for identification and analysis of the plant terpenome.

ABSTRACT: Background:Terpenoid hydrocarbons represent the largest and most ancient group of phytochemicals, such that the entire chemical library of a plant is often referred to as its 'terpenome'. Besides having numerous pharmacological properties, terpenes contribute to the scent of the rose, the flavors of cinnamon and the yellow of sunflowers. Rapidly increasing -omics datasets provide an unprecedented opportunity for terpenome detection, paving the way for automated web resources dedicated to phytochemical predictions in genomic data. Results:We have developed Terzyme, a predictive algorithm for identification, classification and assignment of broad substrate unit to terpene synthase (TPS) and prenyl transferase (PT) enzymes, known to generate the enormous structural and functional diversity of terpenoid compounds across the plant kingdom. Terzyme uses sequence information, plant taxonomy and machine learning methods for predicting TPSs and PTs in genome and proteome datasets. We demonstrate a significant enrichment of the currently identified terpenome by running Terzyme on more than 40 plants. Conclusions:Terzyme is the result of a rigorous analysis of evolutionary relationships between hundreds of characterized sequences of TPSs and PTs with known specificities, followed by analysis of genome-wide gene distribution patterns, ontology based clustering and optimization of various parameters for building accurate profile Hidden Markov Models. The predictive webserver and database is freely available at http://nipgr.res.in/terzyme.html and would serve as a useful tool for deciphering the species-specific phytochemical potential of plant genomes.

SUBMITTER: Priya P

PROVIDER: S-EPMC5761147 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Terzyme: a tool for identification and analysis of the plant terpenome.

Priya Piyush P Yadav Archana A Chand Jyoti J Yadav Gitanjali G

Plant methods 20180110

<h4>Background</h4>Terpenoid hydrocarbons represent the largest and most ancient group of phytochemicals, such that the entire chemical library of a plant is often referred to as its 'terpenome'. Besides having numerous pharmacological properties, terpenes contribute to the scent of the rose, the flavors of cinnamon and the yellow of sunflowers. Rapidly increasing -omics datasets provide an unprecedented opportunity for terpenome detection, paving the way for automated web resources dedicated to ...[more]

PMID: 29339971

Similar Datasets

Project description:BackgroundMicroRNAs (miRNAs) have been known to play an important role in several biological processes in both animals and plants. Although several tools for miRNA and target identification are available, the number of tools tailored towards plants is limited, and those that are available have specific functionality, lack graphical user interfaces, and restrict the number of input sequences. Large-scale computational identifications of miRNAs and/or targets of several plants have been also reported. Their methods, however, are only described as flow diagrams, which require programming skills and the understanding of input and output of the connected programs to reproduce.ResultsTo overcome these limitations and programming complexities, we proposed C-mii as a ready-made software package for both plant miRNA and target identification. C-mii was designed and implemented based on established computational steps and criteria derived from previous literature with the following distinguishing features. First, software is easy to install with all-in-one programs and packaged databases. Second, it comes with graphical user interfaces (GUIs) for ease of use. Users can identify plant miRNAs and targets via step-by-step execution, explore the detailed results from each step, filter the results according to proposed constraints in plant miRNA and target biogenesis, and export sequences and structures of interest. Third, it supplies bird's eye views of the identification results with infographics and grouping information. Fourth, in terms of functionality, it extends the standard computational steps of miRNA target identification with miRNA-target folding and GO annotation. Fifth, it provides helper functions for the update of pre-installed databases and automatic recovery. Finally, it supports multi-project and multi-thread management.ConclusionsC-mii constitutes the first complete software package with graphical user interfaces enabling computational identification of both plant miRNA genes and miRNA targets. With the provided functionalities, it can help accelerate the study of plant miRNAs and targets, especially for small and medium plant molecular labs without bioinformaticians. C-mii is freely available at http://www.biotec.or.th/isl/c-mii for both Windows and Ubuntu Linux platforms.

Project description:Tens of thousands of terpenoids are present in both terrestrial and marine plants, as well as fungi. In the last 5-10 years, however, it has become evident that terpenes are also produced by numerous bacteria, especially soil-dwelling Gram-positive organisms such as Streptomyces and other Actinomycetes. Although some microbial terpenes, such as geosmin, the degraded sesquiterpene responsible for the smell of moist soil, the characteristic odor of the earth itself, have been known for over 100 years, few terpenoids have been identified by classical structure- or activity-guided screening of bacterial culture extracts. In fact, the majority of cyclic terpenes from bacterial species have only recently been uncovered by the newly developed techniques of "genome mining". In this new paradigm for biochemical discovery, bacterial genome sequences are first analyzed with powerful bioinformatic tools, such as the BLASTP program or Profile Hidden Markov models, to screen for and identify conserved protein sequences harboring a characteristic set of universally conserved functional domains typical of all terpene synthases. Of particular importance is the presence of variants of two universally conserved domains, the aspartate-rich DDXX(D/E) motif and the NSE/DTE triad, (N/D)DXX(S/T)XX(K/R)(D/E). Both domains have been implicated in the binding of the essential divalent cation, typically Mg(2+), that is required for cyclization of the universal acyclic terpene precursors, such as farnesyl and geranyl diphosphate. The low level of overall sequence similarity among terpene synthases, however, has so far precluded any simple correlation of protein sequence with the structure of the cyclized terpene product. The actual biochemical function of a cryptic bacterial (or indeed any) terpene synthase must therefore be determined by direct experiment. Two common approaches are (i) incubation of the expressed recombinant protein with acyclic allylic diphosphate substrates and identification of the resultant terpene hydrocarbon or alcohol and (ii) in vivo expression in engineered bacterial hosts that can support the production of terpene metabolites. One of the most attractive features of the coordinated application of genome mining and biochemical characterization is that the discovery of natural products is directly coupled to the simultaneous discovery and exploitation of the responsible biosynthetic genes and enzymes. Bacterial genome mining has proved highly rewarding scientifically, already uncovering more than a dozen newly identified cyclic terpenes (many of them unique to bacteria), as well as several novel cyclization mechanisms. Moreover, bioinformatic analysis has identified more than 120 presumptive genes for bacterial terpene synthases that are now ripe for exploration. In this Account, we review a particularly rich vein we have mined in the genomes of two model Actinomycetes, Streptomyces coelicolor and Streptomyces avermitilis, from which the entire set of terpenoid biosynthetic genes and pathways have now been elucidated. In addition, studies of terpenoid biosynthetic gene clusters have revealed a wealth of previously unknown oxidative enzymes, including cytochromes P450, non-heme iron-dependent dioxygenases, and flavin monooxygenases. We have shown that these enzymes catalyze a variety of unusual biochemical reactions, including two-step ketonization of methylene groups, desaturation-epoxidation of secondary methyl groups, and pathway-specific Baeyer-Villiger oxidations of cyclic ketones.

Project description:Extensins (EXTs) are a family of plant cell wall hydroxyproline-rich glycoproteins (HRGPs) that are implicated to play important roles in plant growth, development, and defense. Structurally, EXTs are characterized by the repeated occurrence of serine (Ser) followed by three to five prolines (Pro) residues, which are hydroxylated as hydroxyproline (Hyp) and glycosylated. Some EXTs have Tyrosine (Tyr)-X-Tyr (where X can be any amino acid) motifs that are responsible for intramolecular or intermolecular cross-linkings. EXTs can be divided into several classes: classical EXTs, short EXTs, leucine-rich repeat extensins (LRXs), proline-rich extensin-like receptor kinases (PERKs), formin-homolog EXTs (FH EXTs), chimeric EXTs, and long chimeric EXTs. To guide future research on the EXTs and understand evolutionary history of EXTs in the plant kingdom, a bioinformatics study was conducted to identify and classify EXTs from 16 fully sequenced plant genomes, including Ostreococcus lucimarinus, Chlamydomonas reinhardtii, Volvox carteri, Klebsormidium flaccidum, Physcomitrella patens, Selaginella moellendorffii, Pinus taeda, Picea abies, Brachypodium distachyon, Zea mays, Oryza sativa, Glycine max, Medicago truncatula, Brassica rapa, Solanum lycopersicum, and Solanum tuberosum, to supplement data previously obtained from Arabidopsis thaliana and Populus trichocarpa. A total of 758 EXTs were newly identified, including 87 classical EXTs, 97 short EXTs, 61 LRXs, 75 PERKs, 54 FH EXTs, 38 long chimeric EXTs, and 346 other chimeric EXTs. Several notable findings were made: (1) classical EXTs were likely derived after the terrestrialization of plants; (2) LRXs, PERKs, and FHs were derived earlier than classical EXTs; (3) monocots have few classical EXTs; (4) Eudicots have the greatest number of classical EXTs and Tyr-X-Tyr cross-linking motifs are predominantly in classical EXTs; (5) green algae have no classical EXTs but have a number of long chimeric EXTs that are absent in embryophytes. Furthermore, phylogenetic analysis was conducted of LRXs, PERKs and FH EXTs, which shed light on the evolution of three EXT classes.

Dataset Information

Terzyme: a tool for identification and analysis of the plant terpenome.

Publications

Terzyme: a tool for identification and analysis of the plant terpenome.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets