PICA: Pixel Intensity Correlation Analysis for Deconvolution and Metabolite Identification in Mass Spectrometry Imaging.

In-source fragmentation (ISF) is a naturally occurring phenomenon in various ion sources including soft ionization techniques such as matrix-assisted laser desorption/ionization (MALDI). It has traditionally been minimized as it makes the dataset more complex and often leads to mis-annotation of metabolites. Here, we introduce an approach termed PICA (for pixel intensity correlation analysis) that takes advantage of ISF in MALDI imaging to increase confidence in metabolite identification. In PICA, the extraction and association of in-source fragments to their precursor ion results in "pseudo-MS/MS spectra" that can be used for identification. We examined PICA using three different datasets, two of which were published previously and included validated metabolites annotation. We show that highly colocalized ions possessing Pearson correlation coefficient (PCC) ≥ 0.9 for a given precursor ion are mainly its in-source fragments, natural isotopes, adduct ions, or multimers. These ions provide rich information for their precursor ion identification. In addition, our results show that moderately colocalized ions (PCC < 0.9) may be structurally related to the precursor ion, which allows for the identification of unknown metabolites through known ones. Finally, we propose three strategies to reduce the total computation time for PICA in MALDI imaging. To conclude, PICA provides an efficient approach to extract and group ions stemming from the same metabolites in MALDI imaging and thus allows for high-confidence metabolite identification.

The metabolic and proteomic repertoires of periderm tissue in skin of the reticulated Sikkim cucumber fruit.

Suberized and/or lignified (i.e. lignosuberized) periderm tissue appears often on surface of fleshy fruit skin by mechanical damage caused following environmental cues or developmental programs. The mechanisms underlying lignosuberization remain largely unknown to date. Here, we combined an assortment of microscopical techniques with an integrative multi-omics approach comprising proteomics, metabolomics and lipidomics to identify novel molecular components involved in fruit skin lignosuberization. We chose to investigate the corky Sikkim cucumber (Cucumis sativus var. sikkimensis) fruit. During development, the skin of this unique species undergoes massive cracking and is coated with a thick corky layer, making it an excellent model system for revealing fundamental cellular machineries involved in fruit skin lignosuberization. The large-scale data generated provides a significant source for the field of skin periderm tissue formation in fleshy fruit and suberin metabolism.

Return of the Lemnaceae: duckweed as a model plant system in the genomics and postgenomics era.

The aquatic Lemnaceae family, commonly called duckweed, comprises some of the smallest and fastest growing angiosperms known on Earth. Their tiny size, rapid growth by clonal propagation, and facile uptake of labeled compounds from the media were attractive features that made them a well-known model for plant biology from 1950 to 1990. Interest in duckweed has steadily regained momentum over the past decade, driven in part by the growing need to identify alternative plants from traditional agricultural crops that can help tackle urgent societal challenges, such as climate change and rapid population expansion. Propelled by rapid advances in genomic technologies, recent studies with duckweed again highlight the potential of these small plants to enable discoveries in diverse fields from ecology to chronobiology. Building on established community resources, duckweed is reemerging as a platform to study plant processes at the systems level and to translate knowledge gained for field deployment to address some of society's pressing needs. This review details the anatomy, development, physiology, and molecular characteristics of the Lemnaceae to introduce them to the broader plant research community. We highlight recent research enabled by Lemnaceae to demonstrate how these plants can be used for quantitative studies of complex processes and for revealing potentially novel strategies in plant defense and genome maintenance.

The Metabolomic-Gut-Clinical Axis of Mankai Plant-Derived Dietary Polyphenols.

BACKGROUND: Polyphenols are secondary metabolites produced by plants to defend themselves from environmental stressors. We explored the effect of Wolffia globosa 'Mankai', a novel cultivated strain of a polyphenol-rich aquatic plant, on the metabolomic-gut clinical axis in vitro, in-vivo and in a clinical trial. METHODS: We used mass-spectrometry-based metabolomics methods from three laboratories to detect Mankai phenolic metabolites and examined predicted functional pathways in a Mankai artificial-gut bioreactor. Plasma and urine polyphenols were assessed among the 294 DIRECT-PLUS 18-month trial participants, comparing the effect of a polyphenol-rich green-Mediterranean diet (+1240 mg/polyphenols/day, provided by Mankai, green tea and walnuts) to a walnuts-enriched (+440 mg/polyphenols/day) Mediterranean diet and a healthy controlled diet. RESULTS: Approximately 200 different phenolic compounds were specifically detected in the Mankai plant. The Mankai-supplemented bioreactor artificial gut displayed a significantly higher relative-abundance of 16S-rRNA bacterial gene sequences encoding for enzymes involved in phenolic compound degradation. In humans, several Mankai-related plasma and urine polyphenols were differentially elevated in the green Mediterranean group compared with the other groups (p < 0.05) after six and 18 months of intervention (e.g., urine hydroxy-phenyl-acetic-acid and urolithin-A; plasma Naringenin and 2,5-diOH-benzoic-acid). Specific polyphenols, such as urolithin-A and 4-ethylphenol, were directly involved with clinical weight-related changes. CONCLUSIONS: The Mankai new plant is rich in various unique potent polyphenols, potentially affecting the metabolomic-gut-clinical axis.

Isolation of a gene cluster from Armillaria gallica for the synthesis of armillyl orsellinate-type sesquiterpenoids.

Melleolides and armillyl orsellinates are protoilludene-type aryl esters that are synthesized exclusively by parasitic fungi of the globally distributed genus Armillaria (Agaricomycetes, Physalacriaceae). Several of these compounds show potent antimicrobial and cytotoxic activities, making them promising leads for the development of new antibiotics or drugs for the treatment of cancer. We recently cloned and characterized the Armillaria gallica gene Pro1 encoding protoilludene synthase, a sesquiterpene cyclase catalyzing the pathway-committing step to all protoilludene-type aryl esters. Fungal enzymes representing secondary metabolic pathways are sometimes encoded by gene clusters, so we hypothesized that the missing steps in the pathway to melleolides and armillyl orsellinates might be identified by cloning the genes surrounding Pro1. Here we report the isolation of an A. gallica gene cluster encoding protoilludene synthase and four cytochrome P450 monooxygenases. Heterologous expression and functional analysis resulted in the identification of protoilludene-8α-hydroxylase, which catalyzes the first committed step in the armillyl orsellinate pathway. This confirms that ∆-6-protoilludene is a precursor for the synthesis of both melleolides and armillyl orsellinates, but the two pathways already branch at the level of the first oxygenation step. Our results provide insight into the synthesis of these valuable natural products and pave the way for their production by metabolic engineering. KEY POINTS: • Protoilludene-type aryl esters are bioactive metabolites produced by Armillaria spp. • The pathway-committing step to these compounds is catalyzed by protoilludene synthase. • We characterized CYP-type enzymes in the cluster and identified novel intermediates.

Pathways to defense metabolites and evading fruit bitterness in genus Solanum evolved through 2-oxoglutarate-dependent dioxygenases.

The genus Solanum comprises three food crops (potato, tomato, and eggplant), which are consumed on daily basis worldwide and also producers of notorious anti-nutritional steroidal glycoalkaloids (SGAs). Hydroxylated SGAs (i.e. leptinines) serve as precursors for leptines that act as defenses against Colorado Potato Beetle (Leptinotarsa decemlineata Say), an important pest of potato worldwide. However, SGA hydroxylating enzymes remain unknown. Here, we discover that 2-OXOGLUTARATE-DEPENDENT-DIOXYGENASE (2-ODD) enzymes catalyze SGA-hydroxylation across various Solanum species. In contrast to cultivated potato, Solanum chacoense, a widespread wild potato species, has evolved a 2-ODD enzyme leading to the formation of leptinines. Furthermore, we find a related 2-ODD in tomato that catalyzes the hydroxylation of the bitter α-tomatine to hydroxytomatine, the first committed step in the chemical shift towards downstream ripening-associated non-bitter SGAs (e.g. esculeoside A). This 2-ODD enzyme prevents bitterness in ripe tomato fruit consumed today which otherwise would remain unpleasant in taste and more toxic.

DLEMMA-MS-Imaging for Identification of Spatially Localized Metabolites and Metabolic Network Map Reconstruction.

Regardless of major advances in mass spectrometry imaging (MSI), there are three intrinsic limitations associated with MSI, including intricate molecular identification, low molecular coverage, and incapability to obtain "true" spatial distribution due to isobaric and particularly isomeric ions interference. We developed a novel approach that integrates in vivo dual isotope labeling of precursor metabolites with MSI (DLEMMA-MS-Imaging) for identification of spatially localized metabolite and metabolic network map reconstruction. In a proof-of-concept study, we identified 59 and 6 novel metabolites in lemna and tomato fruit, respectively. Significantly, 20-30% of the identified metabolites were found to contain at least one structural isomer that displays a different distribution pattern. The notable feature of this approach is the ability to differentiate localization of structural isomers, hence, providing the "true" distribution of molecules of interest.

Short-chain dehydrogenase/reductase governs steroidal specialized metabolites structural diversity and toxicity in the genus Solanum.

Thousands of specialized, steroidal metabolites are found in a wide spectrum of plants. These include the steroidal glycoalkaloids (SGAs), produced primarily by most species of the genus Solanum, and metabolites belonging to the steroidal saponins class that are widespread throughout the plant kingdom. SGAs play a protective role in plants and have potent activity in mammals, including antinutritional effects in humans. The presence or absence of the double bond at the C-5,6 position (unsaturated and saturated, respectively) creates vast structural diversity within this metabolite class and determines the degree of SGA toxicity. For many years, the elimination of the double bond from unsaturated SGAs was presumed to occur through a single hydrogenation step. In contrast to this prior assumption, here, we show that the tomato GLYCOALKALOID METABOLISM25 (GAME25), a short-chain dehydrogenase/reductase, catalyzes the first of three prospective reactions required to reduce the C-5,6 double bond in dehydrotomatidine to form tomatidine. The recombinant GAME25 enzyme displayed 3ß-hydroxysteroid dehydrogenase/Δ5,4 isomerase activity not only on diverse steroidal alkaloid aglycone substrates but also on steroidal saponin aglycones. Notably, GAME25 down-regulation rerouted the entire tomato SGA repertoire toward the dehydro-SGAs branch rather than forming the typically abundant saturated α-tomatine derivatives. Overexpressing the tomato GAME25 in the tomato plant resulted in significant accumulation of α-tomatine in ripe fruit, while heterologous expression in cultivated eggplant generated saturated SGAs and atypical saturated steroidal saponin glycosides. This study demonstrates how a single scaffold modification of steroidal metabolites in plants results in extensive structural diversity and modulation of product toxicity.

Current Challenges in Plant Eco-Metabolomics.

The relatively new research discipline of Eco-Metabolomics is the application of metabolomics techniques to ecology with the aim to characterise biochemical interactions of organisms across different spatial and temporal scales. Metabolomics is an untargeted biochemical approach to measure many thousands of metabolites in different species, including plants and animals. Changes in metabolite concentrations can provide mechanistic evidence for biochemical processes that are relevant at ecological scales. These include physiological, phenotypic and morphological responses of plants and communities to environmental changes and also interactions with other organisms. Traditionally, research in biochemistry and ecology comes from two different directions and is performed at distinct spatiotemporal scales. Biochemical studies most often focus on intrinsic processes in individuals at physiological and cellular scales. Generally, they take a bottom-up approach scaling up cellular processes from spatiotemporally fine to coarser scales. Ecological studies usually focus on extrinsic processes acting upon organisms at population and community scales and typically study top-down and bottom-up processes in combination. Eco-Metabolomics is a transdisciplinary research discipline that links biochemistry and ecology and connects the distinct spatiotemporal scales. In this review, we focus on approaches to study chemical and biochemical interactions of plants at various ecological levels, mainly plant⁻organismal interactions, and discuss related examples from other domains. We present recent developments and highlight advancements in Eco-Metabolomics over the last decade from various angles. We further address the five key challenges: (1) complex experimental designs and large variation of metabolite profiles; (2) feature extraction; (3) metabolite identification; (4) statistical analyses; and (5) bioinformatics software tools and workflows. The presented solutions to these challenges will advance connecting the distinct spatiotemporal scales and bridging biochemistry and ecology.

Transcriptome and Metabolic Profiling Provides Insights into Betalain Biosynthesis and Evolution in Mirabilis jalapa.

Betalains are tyrosine-derived pigments that occur solely in one plant order, the Caryophyllales, where they largely replace the anthocyanins in a mutually exclusive manner. In this study, we conducted multi-species transcriptome and metabolic profiling in Mirabilis jalapa and additional betalain-producing species to identify candidate genes possibly involved in betalain biosynthesis. Among the candidates identified, betalain-related cytochrome P450 and glucosyltransferase-type genes, which catalyze tyrosine hydroxylation or (hydroxy)cinnamoyl-glucose formation, respectively, were further functionally characterized. We detected the expression of genes in the flavonoid/anthocyanin biosynthetic pathways as well as their metabolite intermediates in betalain-accumulating M. jalapa flowers, and found that the anthocyanin-related gene ANTHOCYANIDIN SYNTHASE (MjANS) is highly expressed in the betalain-accumulating petals. However, it appears that MjANS contains a significant deletion in a region spanning the corresponding enzyme active site. These findings provide novel insights into betalain biosynthesis and a possible explanation for how anthocyanins have been lost in this plant species. Our study also implies a complex, non-uniform history for the loss of anthocyanin production across betalain producers, previously assumed to be strictly due to diminished expression of anthocyanin-related genes.

Label-free deep shotgun proteomics reveals protein dynamics during tomato fruit tissues development.

Current innovations in mass-spectrometry-based technologies allow deep coverage of protein expression. Despite its immense value and in contrast to transcriptomics, only a handful of studies in crop plants engaged with global proteome assays. Here, we present large-scale shotgun proteomics profiling of tomato fruit across two key tissues and five developmental stages. A total of 7738 individual protein groups were identified and reliably measured at least in one of the analyzed tissues or stages. The depth of our assay enabled identification of 61 differentially expressed transcription factors, including renowned ripening-related regulators and elements of ethylene signaling. Significantly, we measured proteins involved in 83% of all predicted enzymatic reactions in the tomato metabolic network. Hence, proteins representing almost the complete set of reactions in major metabolic pathways were identified, including the cytosolic and plastidic isoprenoid and the phenylpropanoid pathways. Furthermore, the data allowed us to discern between protein isoforms according to expression patterns, which is most significant in light of the weak transcript-protein expression correspondence. Finally, visualization of changes in protein abundance associated with a particular process provided us with a unique view of skin and flesh tissues in developing fruit. This study adds a new dimension to the existing genomic, transcriptomic and metabolomic resources. It is therefore likely to promote translational and post-translational research in tomato and additional species, which is presently focused on transcription.

The WEIZMASS spectral library for high-confidence metabolite identification.

Annotation of metabolites is an essential, yet problematic, aspect of mass spectrometry (MS)-based metabolomics assays. The current repertoire of definitive annotations of metabolite spectra in public MS databases is limited and suffers from lack of chemical and taxonomic diversity. Furthermore, the heterogeneity of the data prevents the development of universally applicable metabolite annotation tools. Here we present a combined experimental and computational platform to advance this key issue in metabolomics. WEIZMASS is a unique reference metabolite spectral library developed from high-resolution MS data acquired from a structurally diverse set of 3,540 plant metabolites. We also present MatchWeiz, a multi-module strategy using a probabilistic approach to match library and experimental data. This strategy allows efficient and high-confidence identification of dozens of metabolites in model and exotic plants, including metabolites not previously reported in plants or found in few plant species to date.

Analysis of steroidal alkaloids and saponins in Solanaceae plant extracts using UPLC-qTOF mass spectrometry.

Plants of the Solanaceae family are renowned for the production of cholesterol-derived steroidal glycosides, including the nitrogen containing glycoalkaloids and steroidal saponins. In this chapter we describe the use of UPLC (Ultra Performance Liquid Chromatography) coupled with qTOF (Quadrupole Time-of-Flight) mass spectrometry for profiling of these two large classes of semipolar metabolites. The presented method includes an optimized sample preparation protocol, a procedure for high resolution chromatographic separation and metabolite detection using the TOF mass spectrometer which provides high resolution and mass accuracy. A detailed description for non-targeted data analysis and a strategy for putative identification of steroidal glycosides from complex extracts based on interpretation of mass fragmentation patterns is also provided. The described methodology allows profiling and putative identification of multiple steroidal glycoside compounds from the assortment of Solanaceae species producing these molecules.

The challenges of cellular compartmentalization in plant metabolic engineering.

The complex metabolic networks in plants are highly compartmentalized and biochemical steps of a single pathway can take place in multiple subcellular locations. Our knowledge regarding reactions and precursor compounds in the various cellular compartments has increased in recent years due to innovations in tracking the spatial distribution of proteins and metabolites. Nevertheless, to date only few studies have integrated subcellular localization criteria in metabolic engineering attempts. Here, we highlight the crucial factors for subcellular-localization-based strategies in plant metabolic engineering including substrate availability, enzyme targeting, the role of transporters, and multigene transfer approaches. The availability of compartmentalized metabolic network models for plants in the near future will greatly advance the integration of localization constraints in metabolic engineering experiments and aid in predicting their outcomes.

Cloning and characterization of an Armillaria gallica cDNA encoding protoilludene synthase, which catalyzes the first committed step in the synthesis of antimicrobial melleolides.

Melleolides and related fungal sesquiterpenoid aryl esters are antimicrobial and cytotoxic natural products derived from cultures of the Homobasidiomycetes genus Armillaria. The initial step in the biosynthesis of all melleolides involves cyclization of the universal sesquiterpene precursor farnesyl diphosphate to produce protoilludene, a reaction catalyzed by protoilludene synthase. We achieved the partial purification of protoilludene synthase from a mycelial culture of Armillaria gallica and found that 6-protoilludene was its exclusive reaction product. Therefore, a further isomerization reaction is necessary to convert the 6-7 double bond into the 7-8 double bond found in melleolides. We expressed an A. gallica protoilludene synthase cDNA in Escherichia coli, and this also led to the exclusive production of 6-protoilludene. Sequence comparison of the isolated sesquiterpene synthase revealed a distant relationship to other fungal terpene synthases. The isolation of the genomic sequence identified the 6-protoilludene synthase to be present as a single copy gene in the genome of A. gallica, possessing an open reading frame interrupted with eight introns.

Development of carbon plasma-coated multiwell plates for high-throughput mass spectrometric analysis of highly lipophilic fermentation products.

Classical approaches to strain improvement and metabolic engineering rely on rapid qualitative and quantitative analyses of the metabolites of interest. As an analytical tool, mass spectrometry (MS) has proven to be efficient and nearly universally applicable for timely screening of metabolites. Furthermore, gas chromatography (GC)/MS- and liquid chromatography (LC)/MS-based metabolite screens can often be adapted to high-throughput formats. We recently engineered a Saccharomyces cerevisiae strain to produce taxa-4(5),11(12)-diene, the first pathway-committing biosynthetic intermediate for the anticancer drug Taxol, through the heterologous and homologous expression of several genes related to isoprenoid biosynthesis. To date, GC/MS- and LC/MS-based high-throughput methods have been inherently difficult to adapt to the screening of isoprenoid-producing microbial strains due to the need for extensive sample preparation of these often highly lipophilic compounds. In the current work, we examined different approaches to the high-throughput analysis of taxa-4(5),11(12)-diene biosynthesizing yeast strains in a 96-deep-well format. Carbon plasma coating of standard 96-deep-well polypropylene plates allowed us to circumvent the inherent solvent instability of commonly used deep-well plates. In addition, efficient adsorption of the target isoprenoid product by the coated plates allowed rapid and simple qualitative and quantitative analyses of the individual cultures.