Isabel Desgagné-Penix

Transcriptome analysis based on next-generation sequencing of non-model plants producing specialized metabolites of biotechnological interest.

Plants produce a vast array of specialized metabolites, many of which are used as pharmaceuticals, flavors, fragrances, and other high-value fine chemicals. However, most of these compounds occur in non-model plants for which genomic sequence information is not yet available. The production of a large amount of nucleotide sequence data using next-generation technologies is now relatively fast and cost-effective, especially when using the latest Roche-454 and Illumina sequencers with enhanced base-calling accuracy. To investigate specialized metabolite biosynthesis in non-model plants we have established a data-mining framework, employing next-generation sequencing and computational algorithms, to construct and analyze the transcriptomes of 75 non-model plants that produce compounds of interest for biotechnological applications. After sequence assembly an extensive annotation approach was applied to assign functional information to over 800,000 putative transcripts. The annotation is based on direct searches against public databases, including RefSeq and InterPro. Gene Ontology (GO), Enzyme Commission (EC) annotations and associated Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway maps are also collected. As a proof-of-concept, the selection of biosynthetic gene candidates associated with six specialized metabolic pathways is described. A web-based BLAST server has been established to allow public access to assembled transcriptome databases for all 75 plant species of the PhytoMetaSyn Project (www.phytometasyn.ca).

Integration of deep transcriptome and proteome analyses reveals the components of alkaloid metabolism in opium poppy cell cultures

BackgroundPapaver somniferum (opium poppy) is the source for several pharmaceutical benzylisoquinoline alkaloids including morphine, the codeine and sanguinarine. In response to treatment with a fungal elicitor, the biosynthesis and accumulation of sanguinarine is induced along with other plant defense responses in opium poppy cell cultures. The transcriptional induction of alkaloid metabolism in cultured cells provides an opportunity to identify components of this process via the integration of deep transcriptome and proteome databases generated using next-generation technologies.ResultsA cDNA library was prepared for opium poppy cell cultures treated with a fungal elicitor for 10 h. Using 454 GS-FLX Titanium pyrosequencing, 427,369 expressed sequence tags (ESTs) with an average length of 462 bp were generated. Assembly of these sequences yielded 93,723 unigenes, of which 23,753 were assigned Gene Ontology annotations. Transcripts encoding all known sanguinarine biosynthetic enzymes were identified in the EST database, 5 of which were represented among the 50 most abundant transcripts. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) of total protein extracts from cell cultures treated with a fungal elicitor for 50 h facilitated the identification of 1,004 proteins. Proteins were fractionated by one-dimensional SDS-PAGE and digested with trypsin prior to LC-MS/MS analysis. Query of an opium poppy-specific EST database substantially enhanced peptide identification. Eight out of 10 known sanguinarine biosynthetic enzymes and many relevant primary metabolic enzymes were represented in the peptide database.ConclusionsThe integration of deep transcriptome and proteome analyses provides an effective platform to catalogue the components of secondary metabolism, and to identify genes encoding uncharacterized enzymes. The establishment of corresponding transcript and protein databases generated by next-generation technologies in a system with a well-defined metabolite profile facilitates an improved linkage between genes, enzymes, and pathway components. The proteome database represents the most relevant alkaloid-producing enzymes, compared with the much deeper and more complete transcriptome library. The transcript database contained full-length mRNAs encoding most alkaloid biosynthetic enzymes, which is a key requirement for the functional characterization of novel gene candidates.

Integration of deep transcript and targeted metabolite profiles for eight cultivars of opium poppy

Recent advances in DNA sequencing technology and analytical mass spectrometry are providing unprecedented opportunities to develop the functional genomics resources required to investigate complex biological processes in non-model plants. Opium poppy produces a wide variety of benzylisoquinoline alkaloids (BIAs), including the pharmaceutical compounds codeine, morphine, noscapine and papaverine. A functional genomics platform to identify novel BIA biosynthetic and regulatory genes in opium poppy has been established based on the differential metabolite profile of eight selected cultivars. Stem cDNA libraries from each of the eight opium poppy cultivars were subjected to 454 pyrosequencing and searchable expressed sequence tag databases were created from the assembled reads. These deep and integrated metabolite and transcript databases provide a nearly complete representation of the genetic and metabolic variances responsible for the differential occurrence of specific BIAs in each cultivar as demonstrated using the biochemically well characterized pathway from tyrosine to morphine. Similar correlations between the occurrence of specific transcripts and alkaloids effectively reveals candidate genes encoding uncharacterized biosynthetic enzymes as shown using cytochromes P450 potentially involved in the formation of papaverine and noscapine.

Transcriptome analysis of 20 taxonomically related benzylisoquinoline alkaloid-producing plants

BackgroundBenzylisoquinoline alkaloids (BIAs) represent a diverse class of plant specialized metabolites sharing a common biosynthetic origin beginning with tyrosine. Many BIAs have potent pharmacological activities, and plants accumulating them boast long histories of use in traditional medicine and cultural practices. The decades-long focus on a select number of plant species as model systems has allowed near or full elucidation of major BIA pathways, including those of morphine, sanguinarine and berberine. However, this focus has created a dearth of knowledge surrounding non-model species, which also are known to accumulate a wide-range of BIAs but whose biosynthesis is thus far entirely unexplored. Further, these non-model species represent a rich source of catalyst diversity valuable to plant biochemists and emerging synthetic biology efforts.ResultsIn order to access the genetic diversity of non-model plants accumulating BIAs, we selected 20 species representing 4 families within the Ranunculales. RNA extracted from each species was processed for analysis by both 1) Roche GS-FLX Titanium and 2) Illumina GA/HiSeq platforms, generating a total of 40 deep-sequencing transcriptome libraries. De novo assembly, annotation and subsequent full-length coding sequence (CDS) predictions indicated greater success for most species using the Illumina-based platform. Assembled data for each transcriptome were deposited into an established web-based BLAST portal (www.phytometasyn.ca) to allow public access. Homology-based mining of libraries using BIA-biosynthetic enzymes as queries yielded ~850 gene candidates potentially involved in alkaloid biosynthesis. Expression analysis of these candidates was performed using inter-library FPKM normalization methods. These expression data provide a basis for the rational selection of gene candidates, and suggest possible metabolic bottlenecks within BIA metabolism. Phylogenetic analysis was performed for each of 15 different enzyme/protein groupings, highlighting many novel genes with potential involvement in the formation of one or more alkaloid types, including morphinan, aporphine, and phthalideisoquinoline alkaloids. Transcriptome resources were used to design and execute a case study of candidate N-methyltransferases (NMTs) from Glaucium flavum, which revealed predicted and novel enzyme activities.ConclusionsThis study establishes an essential resource for the isolation and discovery of 1) functional homologues and 2) entirely novel catalysts within BIA metabolism. Functional analysis of G. flavum NMTs demonstrated the utility of this resource and underscored the importance of empirical determination of proposed enzymatic function. Publically accessible, fully annotated, BLAST-accessible transcriptomes were not previously available for most species included in this report, despite the rich repertoire of bioactive alkaloids found in these plants and their importance to traditional medicine. The results presented herein provide essential sequence information and inform experimental design for the continued elucidation of BIA metabolism.

Transcriptome and metabolome profiling of Narcissus pseudonarcissus ‘King Alfred’ reveal components of Amaryllidaceae alkaloid metabolism

Amaryllidaceae alkaloids (AAs) represent a diverse class of plant specialized metabolites and many display potent pharmacological activities. The AA metabolic pathway is poorly understood and resources are minimal. To enable AA pathway elucidation and novel biosynthetic enzymes discovery, we generated comprehensive metabolomic and corresponding transcriptomic datasets from different tissues of Narcissus pseudonarcissus ‘King Alfred’. In this study, we performed untargeted UPLC-QTOF-MS metabolite analysis from different tissues, which generated exhaustive list of compounds, including several AAs, most predominant and diverse in bulbs. RNA sequencing of N. pseudonarcissus ‘King Alfred’ bulbs yielded 195,347 transcripts, after assembly. Top expressed genes belong to process like metabolism, survival, and defense including alkaloid biosynthetic genes. The transcriptome contained complete sequences for all proposed genes encoding AA-biosynthetic enzymes such as tyrosine decarboxylase (TYDC1 and TYDC2), phenylalanine ammonia-lyase (PAL1 and PAL2) and phenolic acids hydroxylases (C4H and C3H) to name a few. Furthermore, transcriptome data were validated using RT-qPCR analysis and expression study in different tissues of N. pseudonarcissus ‘King Alfred’ was performed. Here, we present the first comprehensive metabolome and transcriptome study from N. pseudonarcissus ‘King Alfred’ providing invaluable resources for metabolic engineering and biotechnological applications.

DNA distribution pattern and metabolite profile of wild edible lobster mushroom (Hypomyces lactifluorum/Russula brevipes)

Lobster mushroom is a wild edible mushroom with potential commercial value. It is the product resulting of the infection, most commonly of Russula brevipes, by Hypomyces lactifluorum. This study undertook quantitative polymerase chain reaction analysis of tissues sampled at different infection stages to investigate R. brevipes - H. lactifluorum interaction. We followed the colonization of R. brevipes sporocarps by H. lactifluorum that leads to the edible lobster mushrooms. In parallel, metabolomics analysis was performed to detect differences in metabolite profile among non-infected R. brevipes sporocarp and lobster mushroom. The results show that H. lactifluorum DNA is not restricted to the margin but is distributed relatively evenly across the sporocarp of the lobster mushroom. Russula brevipes DNA was also present throughout the sporocarp but was less abundant at the margins and increased inwards. Russula brevipes DNA also declined as the infection progressed. Metabolomics analysis revealed that the flesh of lobster mushroom, which remains identical in appearance to the flesh of the host, undergoes transformation that alters its metabolite profile, most notably of lipids and terpene compounds. These results define a parasitic relationship between the two species that entails a decline of R. brevipes DNA and a modification of its metabolite profile.