FlavonoidSearch: A system for comprehensive flavonoid annotation by mass spectrometry

LC-MS/DIA-based strategy for comprehensive flavonoid profiling: an Ocotea spp. applicability case

We introduce a liquid chromatography - mass spectrometry with data-independent acquisition (LC-MS/DIA)-based strategy, specifically tailored to achieve comprehensive and reliable glycosylated flavonoid profiling. This approach facilitates in-depth and simultaneous exploration of all detected precursors and fragments during data processing, employing the widely-used open-source MZmine 3 software. It was applied to a dataset of six Ocotea plant species. This framework suggested 49 flavonoids potentially newly described for these plant species, alongside 45 known features within the genus. Flavonols kaempferol and quercetin, both exhibiting O-glycosylation patterns, were particularly prevalent. Gas-phase fragmentation reactions further supported these findings. For the first time, the apigenin flavone backbone was also annotated in most of the examined Ocotea species. Apigenin derivatives were found mainly in the C-glycoside form, with O. porosa displaying the highest flavone : flavonol ratio. The approach also allowed an unprecedented detection of kaempferol and quercetin in O. porosa species, and it has underscored the untapped potential of LC-MS/DIA data for broad and reliable flavonoid profiling. Our study annotated more than 50 flavonoid backbones in each species, surpassing the current literature.

Metabolome analysis reveals that cyclic adenosine diphosphate ribose contributes to the regulation of differentiation in mice adipocyte

Adipocytes play a key role in energy storage and homeostasis. Although the role of transcription factors in adipocyte differentiation is known, the effect of endogenous metabolites of low molecular weight remains unclear. Here, we analyzed time-dependent changes in the levels of these metabolites throughout adipocyte differentiation, using metabolome analysis, and demonstrated that there is a positive correlation between cyclic adenosine diphosphate ribose (cADPR) and Pparγ mRNA expression used as a marker of differentiation. We also found that the treatment of C3H10T1/2 adipocytes with cADPR increased the mRNA expression of those marker genes and the accumulation of triglycerides. Furthermore, inhibition of ryanodine receptors (RyR), which are activated by cADPR, caused a significant reduction in mRNA expression levels of the marker genes and triglyceride accumulation in adipocytes. Our findings show that cADPR accelerates adipocytic differentiation via RyR pathway.

Alternative Identification of Glycosides Using MS/MS Matching with an In Silico-Modified Aglycone Mass Spectra Library

Glycosylation of metabolites serves multiple purposes. Adding sugars makes metabolites more water soluble and improves their biodistribution, stability, and detoxification. In plants, the increase in melting points enables storing otherwise volatile compounds that are released by hydrolysis when needed. Classically, glycosylated metabolites were identified by mass spectrometry (MS/MS) using [M-sugar] neutral losses. Herein, we studied 71 pairs of glycosides with their respective aglycones, including hexose, pentose, and glucuronide moieties. Using liquid chromatography (LC) coupled to electrospray ionization high-resolution mass spectrometry, we detected the classic [M-sugar] product ions for only 68% of glycosides. Instead, we found that most aglycone MS/MS product ions were conserved in the MS/MS spectra of their corresponding glycosides, even when no [M-sugar] neutral losses were observed. We added pentose and hexose units to the precursor masses of an MS/MS library of 3057 aglycones to enable rapid identification of glycosylated natural products with standard MS/MS search algorithms. When searching unknown compounds in untargeted LC-MS/MS metabolomics data of chocolate and tea, we structurally annotated 108 novel glycosides in standard MS-DIAL data processing. We uploaded this new in silico-glycosylated product MS/MS library to GitHub to enable users to detect natural product glycosides without authentic chemical standards.

Global Metabolome of Palmer Amaranth (Amaranthus palmeri) Populations Highlights the Specificity and Inducibility of Phytochemical Responses to Abiotic Stress

Commonalities in adaptive responses to abiotic stressors could contribute to the development of cross-resistance in weeds. The degree to which herbicide-induced changes in weeds parallel those induced by other abiotic stress remains unknown. We investigated the specificity of metabolic perturbations induced by glyphosate and drought across three glyphosate-resistant (GR) and two glyphosate-susceptible (GS) biotypes of Palmer amaranth (Amaranthus palmeri) using global metabolomics approaches. Compared to GS-biotypes, in the absence of stress, the GR-biotypes had a higher abundance of primary metabolites, including sugars, nonaromatic amino acids, and organic acids. However, despite having a higher 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) gene copy number that could upregulate the phenylpropanoid metabolism, the nonstressed GR-biotypes were less abundant in specialized (secondary) metabolites. Under glyphosate stress, 80% of metabolites, including shikimate, that accumulated in GS-biotypes also increased in the GR-biotypes. However, glyphosate triggered the preferential accumulation of glycosides of dihydroxylated and methoxylated flavanols with higher antioxidant potential, and ferulic acid derivatives, specifically in GR-biotypes. The disruption of the shikimate pathway and the accumulation of phenylpropanoids upon glyphosate exposure suggest that the stress response of GR-biotypes could be partly induced. This differential response was less evident in other phytochemical classes and under drought, highlighting that the phytochemical responses are stress-specific rather than biotype-specific.

Lysine-targeting inhibition of amyloid β oligomerization by a green perilla-derived metastable chalcone in vitro and in vivo

Oligomers of amyloid β (Aβ) represent an early aggregative form that causes neurotoxicity in the pathogenesis of Alzheimer's disease (AD). Thus, preventing Aβ aggregation is important for preventing AD. Despite intensive studies on dietary compounds with anti-aggregation properties, some identified compounds are susceptible to autoxidation and/or hydration upon incubation in water, leaving unanswered issues regarding which active structures in metastable compounds are actually responsible for the inhibition of Aβ aggregation. In this study, we observed the site-specific inhibition of 42-mer Aβ (Aβ42) oligomerization by the green perilla-derived chalcone 2',3'-dihydroxy-4',6'-dimethoxychalcone (DDC), which was converted to its decomposed flavonoids (dDDC, 1-3) via nucleophilic aromatic substitution with water molecules. DDC suppressed Aβ42 fibrillization and slowed the transformation of the β-sheet structure, which is rich in Aβ42 aggregates. To validate the contribution of dDDC to the inhibitory effects of DDC on Aβ42 aggregation, we synthesized 1-3 and identified 3, a catechol-type flavonoid, as one of the active forms of DDC. ¹H-¹⁵N SOFAST-HMQC NMR revealed that 1-3 as well as DDC could interact with residues between His13 and Leu17, which were near the intermolecular β-sheet (Gln15-Ala21). The nucleation in Aβ42 aggregates involves the rate-limiting formation of low-molecular-weight oligomers. The formation of a Schiff base with dDDC at Lys16 and Lys28 in the dimer through autoxidation of dDDC was associated with the suppression of Aβ42 nucleation. Of note, in two AD mouse models using immunoaffinity purification-mass spectrometry, adduct formation between dDDC and brain Aβ was observed in a similar manner as reported in vitro. The present findings unraveled the lysine-targeting inhibitory mechanism of metastable dietary ingredients regarding Aβ oligomerization.

The Thing Metabolome Repository family (XMRs): comparable untargeted metabolome databases for analyzing sample-specific unknown metabolites

The identification of unknown chemicals has emerged as a significant issue in untargeted metabolome analysis owing to the limited availability of purified standards for identification; this is a major bottleneck for the accumulation of reusable metabolome data in systems biology. Public resources for discovering and prioritizing the unknowns that should be subject to practical identification, as well as further detailed study of spending costs and the risks of misprediction, are lacking. As such a resource, we released databases, Food-, Plant- and Thing-Metabolome Repository (http://metabolites.in/foods, http://metabolites.in/plants, and http://metabolites.in/things, referred to as XMRs) in which the sample-specific localization of unknowns detected by liquid chromatography-mass spectrometry in a wide variety of samples can be examined, helping to discover and prioritize the unknowns. A set of application programming interfaces for the XMRs facilitates the use of metabolome data for large-scale analysis and data mining. Several applications of XMRs, including integrated metabolome and genome analyses, are presented. Expanding the concept of XMRs will accelerate the identification of unknowns and increase the discovery of new knowledge.

Metabolomics application for the design of an optimal diet

Precision nutrition is an emerging branch of nutrition science that aims to use modern omics technologies (genomics, proteomics, and metabolomics) to assess an individual's response to specific foods or dietary patterns and thereby determine the most effective diet or lifestyle interventions to prevent or treat specific diseases. Metabolomics is vital to nearly every aspect of precision nutrition. It can be targeted or untargeted, and it has many applications. Indeed, it can be used to comprehensively characterize the thousands of chemicals in foods, identify food by-products in human biofluids or tissues, characterize nutrient deficiencies or excesses, monitor biochemical responses to dietary interventions, track long- or short-term dietary habits, and guide the development of nutritional therapies. Indeed, metabolomics can be coupled with genomics and proteomics to study and advance the field of precision nutrition. Integrating omics with epidemiological and clinical data will begin to define the beneficial effects of human food metabolites. In this review, we present the metabolome and its relationship to precision nutrition. Moreover, we describe the different techniques used in metabolomics and present how metabolomics has been applied to advance the field of precision nutrition by providing notable examples and cases.

Metabolomics reveals inosine 5'-monophosphate is increased during mice adipocyte browning

Adipocyte browning is one of the potential strategies for the prevention of obesity-related metabolic syndromes, but it is a complex process. Although previous studies make it increasingly clear that several transcription factors and enzymes are essential to induce browning, it is unclear what dynamic and metabolic changes occur in induction of browning. Here, we analyzed the effect of a beta-adrenergic receptor agonist (CL316243, accelerator of browning) on metabolic change in mice adipose tissue and plasma using metabolome analysis and speculated that browning is regulated partly by inosine 5′-monophosphate (IMP) metabolism. To test this hypothesis, we investigated whether Ucp-1, a functional marker of browning, mRNA expression is influenced by IMP metabolism using immortalized adipocytes. Our study showed that mycophenolic acid, an IMP dehydrogenase inhibitor, increases the mRNA expression of Ucp-1 in immortalized adipocytes. Furthermore, we performed a single administration of mycophenolate mofetil, a prodrug of mycophenolic acid, to mice and demonstrated that mycophenolate mofetil induces adipocyte browning and miniaturization of adipocyte size, leading to adipose tissue weight loss. These findings showed that IMP metabolism has a significant effect on adipocyte browning, suggesting that the regulator of IMP metabolism has the potential to prevent obesity.

Structure-based identification and pathway elucidation of flavonoids in Camptotheca acuminate

Flavonoid metabolism in Camptotheca acuminate remained an untapped area for years. A tandem MS approach was used and focused on the mining and characterizing of flavonoids in mature C. acuminate. Fifteen new flavonoids and forty-three known flavonoids, including fifteen flavone analogs, sixteen flavonol analogs, seven flavanone analogs, six chalcone analogs, four xanthone analogs, ten flavane analogs were mined and identified based on their MS/MS fragments. Fifty-three of them were firstly characterized in C. acuminate. Eight biosynthetic precursors for these flavonoids were also identified. We constructed a specific metabolic map for flavonoids according to their relative contents in the flowers, fruits, stems, and leaves of C. acuminate. Furthermore, the most probable genes involved in chalcone biosynthesis, flavonoid hydroxylation, methylation, and glycosylation were further mined and fished in the gene reservoir of C. acuminate according to their conserved domains and co-expression analysis. These findings enable us to acquire a better understanding of versatile flavonoid metabolism in C. acuminate.

foodMASST a mass spectrometry search tool for foods and beverages

There is a growing interest in unraveling the chemical complexity of our diets. To help the scientific community gain insight into the molecules present in foods and beverages that we ingest, we created foodMASST, a search tool for MS/MS spectra (of both known and unknown molecules) against a growing metabolomics food and beverage reference database. We envision foodMASST will become valuable for nutrition research and to assess the potential uniqueness of dietary biomarkers to represent specific foods or food classes.

Updates on the chemistry, processing characteristics, and utilization of tea flavonoids in last two decades (2001-2021)

Tea flavonoids are widely recognized as critical flavor contributors and crucial health-promoting bioactive compounds, and have long been the focus of research worldwide in food science. The aim of this review paper is to summarize the major progress in tea flavonoid chemistry, their dynamics of constituents and concentrations during tea processing as well as storage, and their health functions studied between 2001 and 2021. Moreover, the utilization of tea flavonoids in the human body has also been discussed for a detailed understanding of their uptake, metabolism, and interaction with the gut microbiota. Many novel tea flavonoids have been identified, including novel A- and B-ring substituted flavan-3-ol derivatives, condensed and oxidized flavan-3-ol derivatives, and glycosylated and methylated flavonoids, and are found to be closely associated with the characteristic color, flavor, and health benefits of tea. Flavoalkaloids exist widely in various teas, particularly 8-C N-ethyl-2-pyrrolidinone-substituted flavan-3-ols. Tea flavonoids behave significantly difference in constituents and concentrations depending on tea cultivars, plantation conditions, multiple stresses, the tea-specified manufacturing steps, and even the long-term storage period. Tea flavonoids exhibit multiple health-promoting effects, particularly their anti-inflammatory in alleviating metabolic syndromes. Interaction of tea flavonoids with the gut microbiota plays vital roles in their health function.

Untargeted metabotyping to study phenylpropanoid diversity in crop plants

Plant genebanks constitute a key resource for breeding to ensure crop yield under changing environmental conditions. Because of their roles in a range of stress responses, phenylpropanoids are promising targets. Phenylpropanoids comprise a wide array of metabolites; however, studies regarding their diversity and the underlying genes are still limited for cereals. The assessment of barley diversity via genotyping-by-sequencing is in rapid progress. Exploring these resources by integrating genetic association studies to in-depth metabolomic profiling provides a valuable opportunity to study barley phenylpropanoid metabolism; but poses a challenge by demanding large-scale approaches. Here, we report an LC-PDA-MS workflow for barley high-throughput metabotyping. Without prior construction of a species-specific library, this method produced phenylpropanoid-enriched metabotypes with which the abundance of putative metabolic features was assessed across hundreds of samples in a single-processed data matrix. The robustness of the analytical performance was tested using a standard mix and extracts from two selected cultivars: Scarlett and Barke. The large-scale analysis of barley extracts showed (1) that barley flag leaf profiles were dominated by glycosylation derivatives of isovitexin, isoorientin, and isoscoparin; (2) proved the workflow's capability to discriminate within genotypes; (3) highlighted the role of glycosylation in barley phenylpropanoid diversity. Using the barley S42IL mapping population, the workflow proved useful for metabolic quantitative trait loci purposes. The protocol can be readily applied not only to explore the barley phenylpropanoid diversity represented in genebanks but also to study species whose profiles differ from those of cereals: the crop Helianthus annuus (sunflower) and the model plant Arabidopsis thaliana.

LC-Q-TOF-MS/MS detection of food flavonoids: principle, methodology, and applications

Flavonoids have been attracting increasing research interest because of their multiple health promoting effects. However, many flavonoids with similar structures are present in foods, often at low concentrations, which increases the difficulty of their separation and identification. Liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (LC-Q-TOF-MS/MS) has become one of the most widely used techniques for flavonoid detection. LC-Q-TOF-MS/MS can achieve highly efficient separation by LC; it also provides structural information regarding flavonoids by Q-TOF-MS/MS. This review presents a comprehensive summary of the scientific principles and detailed methodologies (e.g., qualitative determination, quantitative determination, and data processing) of LC-Q-TOF-MS/MS specifically for food flavonoids. It also discusses the recent applications of LC-Q-TOF-MS/MS in determination of flavonoid types and contents in agricultural products, changes in their structures and contents during food processing, and metabolism in vivo after consumption. Moreover, it proposes necessary technological improvements and potential applications. This review would facilitate the scientific understanding of theory and technique of LC-Q-TOF-MS/MS for flavonoid detection, and promote its applications in food and health industry.

Identification of α-Glucosidase Inhibitors from Leaf Extract of Pepper (Capsicum spp.) through Metabolomic Analysis

Metabolomics and in vitro α-glucosidase inhibitory (AGI) activities of pepper leaves were used to identify bioactive compounds and select genotypes for the management of type 2 diabetes mellitus (T2DM). Targeted metabolite analysis using UPLC-DAD-QToF-MS was employed and identified compounds that belong to flavone and hydroxycinnamic acid derivatives from extracts of pepper leaves. A total of 21 metabolites were detected from 155 samples and identified based on MS fragmentations, retention time, UV absorbance, and previous reports. Apigenin-O-(malonyl) hexoside, luteolin-O-(malonyl) hexoside, and chrysoeriol-O-(malonyl) hexoside were identified for the first time from pepper leaves. Pepper genotypes showed a huge variation in their inhibitory activity against α-glucosidase enzyme(AGE) ranging from 17% to 79%. Genotype GP38 with inhibitory activity of 79% was found to be more potent than the positive control acarbose (70.8%.). Orthogonal partial least square (OPLS) analyses were conducted for the prediction of the AGI activities of pepper leaves based on their metabolite composition. Compounds that contributed the most to the bioactivity prediction model (VIP >1.5), showed a strong inhibitory potency. Caffeoyl-putrescine was found to show a stronger inhibitory potency (IC₅₀ = 145 µM) compared to acarbose (IC₅₀ = 197 µM). The chemometric procedure combined with high-throughput AGI screening was effective in selecting polyphenols of pepper leaf for T2DM management.

De novo biosynthesis of garbanzol and fustin in Streptomyces albus based on a potential flavanone 3-hydroxylase with 2-hydroxylase side activity

Flavonoids are important plant secondary metabolites, which were shown to have antioxidant, anti-inflammatory or antiviral activities. Heterologous production of flavonoids in engineered microbial cell factories is an interesting alternative to their purification from plant material representing the natural source. The use of engineered bacteria allows to produce specific compounds, independent of soil, climatic or other plant-associated production parameters. The initial objective of this study was to achieve an engineered production of two interesting flavanonols, garbanzol and fustin, using Streptomyces albus as the production host. Unexpectedly, the engineered strain produced several flavones and flavonols in the absence of the additional expression of a flavone synthase (FNS) or flavonol synthase (FLS) gene. It turned out that the heterologous flavanone 3-hydroxylase (F3H) has a 2-hydroxylase side activity, which explains the observed production of 7,4'-dihydroxyflavone, resokaempferol, kaempferol and apigenin, as well as the biosynthesis of the extremely rare 2-hydroxylated intermediates 2-hydroxyliquiritigenin, 2-hydroxynaringenin and probably licodione. Other related metabolites, such as quercetin, dihydroquercetin and eriodictyol, have also been detected in culture extracts of this recombinant strain. Hence, the enzymatic versatility of S. albus can be conveniently exploited for the heterologous production of a large diversity of plant metabolites of the flavonoid family.

Metabolome analysis revealed that soybean-Aspergillus oryzae interaction induced dynamic metabolic and daidzein prenylation changes

Several isoflavonoids are well known for their ability to act as soybean phytoalexins. However, the overall effects of the soybean-Aspergillus oryzae interaction on metabolism remain largely unknown. The aim of this study is to reveal an overview of nutritive and metabolic changes in germinated and A. oryzae-elicited soybeans. The levels of individual nutrients were measured using the ustulation, ashing, Kjeldahl, and Folch methods. The levels of individual amino acids were measured using high-performance liquid chromatography. Low-molecular-weight compounds were measured through metabolome analysis using liquid chromatography-mass spectrometry. Although the levels of individual nutrients and amino acids were strongly influenced by the germination process, the elicitation process had little effect on the change in the contents of individual nutrients and amino acids. However, after analyzing approximately 700 metabolites using metabolome analysis, we found that the levels of many of the metabolites were strongly influenced by soybean-A. oryzae interactions. In particular, the data indicate that steroid, terpenoid, phenylpropanoid, flavonoid, and fatty acid metabolism were influenced by the elicitation process. Furthermore, we demonstrated that not the germination process but the elicitation process induced daidzein prenylation, suggesting that the soybean-A. oryzae interactions produce various phytoalexins that are valuable for health promotion and/or disease prevention.

Mass Spectral Filtering by Mass-Remainder Analysis (MARA) at High Resolution and Its Application to Metabolite Profiling of Flavonoids

Flavonoids represent an important class of secondary metabolites because of their potential health benefits and functions in plants. We propose a novel method for the comprehensive flavonoid filtering and screening based on direct infusion mass spectrometry (DIMS) analysis. The recently invented data mining procedure, the multi-step mass-remainder analysis (M-MARA) technique is applied for the effective mass spectral filtering of the peak rich spectra of natural herb extracts. In addition, our flavonoid-filtering algorithm facilitates the determination of the elemental composition. M-MARA flavonoid-filtering uses simple mathematical and logical operations and thus, it can easily be implemented in a regular spreadsheet software. A huge benefit of our method is the high speed and the low demand for computing power and memory that enables the real time application even for tandem mass spectrometric analysis. Our novel method was applied for the electrospray ionization (ESI) DIMS spectra of various herb extract, and the filtered mass spectral data were subjected to chemometrics analysis using principal component analysis (PCA).

Higher dimensional metabolomics using stable isotope labeling for identifying the missing specialized metabolism in plants

The exact mechanics of specialized metabolism and its importance throughout plant evolution remain mysterious. Specialized metabolites and their corresponding biosynthetic genes are crucial to understand the reason for the prevalence of certain metabolism. Even though mass spectrometry-based metabolomics has enabled us to acquire data about the structural properties of unknown specialized metabolites as well as known metabolites and their corresponding isomers/analogs, extensive analytical approaches are still required. Herein, we review the most advanced analytical approaches using stable isotope labeling that can be used to identify the unknown specialized metabolites.

Profiling of quercetin glycosides and acyl glycosides in sun-dried peperoni di Senise peppers (Capsicum annuum L.) by a combination of LC-ESI(-)-MS/MS and polarity prediction in reversed-phase separations

Interest in targeted profiling of quercetin glycoconjugates occurring in edible foodstuffs continues to expand because of their recognized beneficial health effects. Quercetin derivatives encompass several thousands of chemically distinguishable compounds, among which there are several compounds with different glycosylations and acylations. Since reference standards and dedicated databases are not available, the mass spectrometric identification of quercetin glycoconjugates is challenging. A targeted liquid chromatography (LC) coupled with tandem mass spectrometry (MS/MS) was applied for screening quercetin glycoconjugates in edible peperoni di Senise peppers (Capsicum annuum L.), protected by the European Union with the mark PGI (i.e., Protected Geographical Indication), and cultivated in Basilicata (Southern Italy). Chromatographic separation was accomplished by reversed-phase liquid chromatography (RPLC) using water/acetonitrile as the mobile phase and detection was performed on a linear ion trap mass spectrometer fitted with an electrospray ionization (ESI) source operating in negative ion mode. A correlation between experimental RP chromatographic retention time and those predicted by partition coefficients (log P) along with MS/MS data and an in-house developed database (named QUEdb) provided deep coverage for sixteen quercetin glycoconjugates. Among them, eleven quercetin glycoconjugates were already described in the literature and five were reported for the first time. These last acyl glycosidic quercetin derivatives were tentatively identified as quercetin-(galloyl-rhamnoside)-hexoside, [C₃₄H₃₃O₂₀]^- at m/z 761.1; quercetin-(sinapoyl-hexoside)-rhamnoside, [C₃₈H₃₉O₂₀]^- at m/z 815.4; quercetin-(galloyl-caffeoyl-hexoside)-rhamnoside, [C₄₃H₃₉O₂₃]^- at m/z 923.0; quercetin-(feruloyl-hexoside)-rhamnoside, [C₃₇H₃₇O₁₉]^- at m/z 785.1; and quercetin-(succinyl-rhamnoside)-rhamnoside, [C₃₁H₃₃O₁₈]^- at m/z 693.1. Graphical abstract.

Metabolite database for root, tuber, and banana crops to facilitate modern breeding in understudied crops

Roots, tubers, and bananas (RTB) are vital staples for food security in the world's poorest nations. A major constraint to current RTB breeding programmes is limited knowledge on the available diversity due to lack of efficient germplasm characterization and structure. In recent years large-scale efforts have begun to elucidate the genetic and phenotypic diversity of germplasm collections and populations and, yet, biochemical measurements have often been overlooked despite metabolite composition being directly associated with agronomic and consumer traits. Here we present a compound database and concentration range for metabolites detected in the major RTB crops: banana (Musa spp.), cassava (Manihot esculenta), potato (Solanum tuberosum), sweet potato (Ipomoea batatas), and yam (Dioscorea spp.), following metabolomics-based diversity screening of global collections held within the CGIAR institutes. The dataset including 711 chemical features provides a valuable resource regarding the comparative biochemical composition of each RTB crop and highlights the potential diversity available for incorporation into crop improvement programmes. Particularly, the tropical crops cassava, sweet potato and banana displayed more complex compositional metabolite profiles with representations of up to 22 chemical classes (unknowns excluded) than that of potato, for which only metabolites from 10 chemical classes were detected. Additionally, over 20% of biochemical signatures remained unidentified for every crop analyzed. Integration of metabolomics with the on-going genomic and phenotypic studies will enhance 'omics-wide associations of molecular signatures with agronomic and consumer traits via easily quantifiable biochemical markers to aid gene discovery and functional characterization.

Multiple Virtual Screening Strategies for the Discovery of Novel Compounds Active Against Dengue Virus: A Hit Identification Study

Dengue infection is caused by a mosquito-borne virus, particularly in children, which may even cause death. No effective prevention or therapeutic agents to cure this disease are available up to now. The dengue viral envelope (E) protein was discovered to be a promising target for inhibition in several steps of viral infection. Structure-based virtual screening has become an important technique to identify first hits in a drug screening process, as it is possible to reduce the number of compounds to be assayed, allowing to save resources. In the present study, pharmacophore models were generated using the common hits approach (CHA), starting from trajectories obtained from molecular dynamics (MD) simulations of the E protein complexed with the active inhibitor, flavanone (FN5Y). Subsequently, compounds presented in various drug databases were screened using the LigandScout 4.2 program. The obtained hits were analyzed in more detail by molecular docking, followed by extensive MD simulations of the complexes. The highest-ranked compound from this procedure was then synthesized and tested on its inhibitory efficiency by experimental assays.

Comparison of Chemical Compositions, Antioxidant, and Anti-Photoaging Activities of Paeonia suffruticosa Flowers at Different Flowering Stages

Paeonia suffruticosa is an ornamental, edible, and medicinal plant. The ethanolic extracts of P. suffruticosa bud and flower were examined for their antioxidant, anti-photoaging, and phytochemical properties prior to chemometric analysis. The results showed that the bud ethanolic extract (BEE) and the flower (the early flowering stage) ethanolic extract (FEE) had better antioxidant activities, and significantly increased the activities of superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) and reduced the levels of tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) in the skin tissues. In total, 68 compounds, including 20 flavonoids, 15 phenolic derivatives, 12 terpenoids, 9 fatty acids, and 12 others were identified or tentatively identified by ultra-fast liquid chromatography quadrupole time-of-flight mass spectrometry (UFLC-Q-TOF-MS). Gallic acid, 1,2,3,4,6-O-pentagalloyl glucose, paeoniflorin, and oxypaeoniflorin were predominant compounds in the extracts. Taken together, P. suffruticosa flowers are a candidate for functional material in food and health related industries, and their optimal time to harvest is before the early flowering stage.

Mass Spectral Similarity Networking and Gas-Phase Fragmentation Reactions in the Structural Analysis of Flavonoid Glycoconjugates

Flavonoids represent an important class of natural products with a central role in plant physiology and human health. Their accurate annotation using untargeted mass spectrometry analysis still relies on differentiating similar chemical scaffolds through spectral matching to reference library spectra. In this work, we combined molecular network analysis with rules for fragment reactions and chemotaxonomy to enhance the annotation of similar flavonoid glyconjugates. Molecular network topology progressively propagated the flavonoid chemical functionalization according to collision-induced dissociation (CID) reactions, as the following chemical attributes: aglycone nature, saccharide type and number, and presence of methoxy substituents. This structure-based distribution across the spectral networks revealed the chemical composition of flavonoids across intra- and interspecies and guided the putatively assignment of 64 isomers and isobars in the Chrysobalanaceae plant species, most of which are not accurately annotated by automated untargeted MS² matching. These proof of concept results demonstrate how molecular networking progressively grouped structurally related molecules according to their product ion scans, abundances, and ratios. The approach can be extrapolated to other classes of metabolites sharing similar structures and diagnostic fragments from tandem mass spectrometry.

The Origin and Evolution of Plant Flavonoid Metabolism

During their evolution, plants have acquired the ability to produce a huge variety of compounds. Unlike the specialized metabolites that accumulate in limited numbers of species, flavonoids are widely distributed in the plant kingdom. Therefore, a detailed analysis of flavonoid metabolism in genomics and metabolomics is an ideal way to investigate how plants have developed their unique metabolic pathways during the process of evolution. More comprehensive and precise metabolite profiling integrated with genomic information are helpful to emerge unexpected gene functions and/or pathways. The distribution of flavonoids and their biosynthetic genes in the plant kingdom suggests that flavonoid biosynthetic pathways evolved through a series of steps. The enzymes that form the flavonoid scaffold structures probably first appeared by recruitment of enzymes from primary metabolic pathways, and later, enzymes that belong to superfamilies such as 2-oxoglutarate-dependent dioxygenase, cytochrome P450, and short-chain dehydrogenase/reductase modified and varied the structures. It is widely accepted that the first two enzymes in flavonoid biosynthesis, chalcone synthase, and chalcone isomerase, were derived from common ancestors with enzymes in lipid metabolism. Later enzymes acquired their function by gene duplication and the subsequent acquisition of new functions. In this review, we describe the recent progress in metabolomics technologies for flavonoids and the evolution of flavonoid skeleton biosynthetic enzymes to understand the complicate evolutionary traits of flavonoid metabolism in plant kingdom.

UHPLC-MS Analyses of Plant Flavonoids

Flavonoids are a class of specialized metabolites found in many different plant species. They protect against UV radiation, scavenge reactive oxygen species, are involved in plant defense responses, and are associated with plant-microorganism interactions. They have also been reported to possess health-promoting effects including anti-inflammatory, antioxidant, anticancer activity, and antihypertensive effects. Flavonoids encompass >10,000 structures where the types and amounts depend on the plant species, developmental stage, organ, and growth conditions. The diversity of flavonoid structures represents a significant challenge in the analysis of plant flavonoids. Many analytical techniques have been developed to detect and quantify flavonoids, and the most productive of these techniques use liquid chromatography (LC) coupled to mass spectrometry (MS) to analyze flavonoids due to the excellent combination of selectivity and sensitivity of MS. In addition, mass spectral libraries have been constructed to further aid flavonoid identification. Here, the use of ultra-high pressure liquid chromatography coupled to mass spectrometry (UHPLC-MS) in plant flavonoid analyses, with an emphasis on sample extraction, flavonoid separation, and MS detection, is described. © 2018 by John Wiley & Sons, Inc.

Comparative multi-omics analysis reveals diverse latex-based defense strategies against pests among latex-producing organs of the fig tree (Ficus carica)

Latexes in immature fruit, young petioles and lignified trunks of fig trees protect the plant using toxic proteins and metabolites in various organ-dependent ways. Latexes from plants contain high amounts of toxic proteins and metabolites, which attack microbes and herbivores after exudation at pest-induced wound sites. The protein and metabolite constituents of latexes are highly variable, depending on the plant species and organ. To determine the diversity of latex-based defense strategies in fig tree (Ficus carica) organs, we conducted comparative proteomic, transcriptomic and metabolomic analyses on latexes isolated from immature fruit, young petioles and lignified trunks of F. carica after constructing a unigene sequence library using RNA-seq data. Trypsin inhibitors were the most abundant proteins in petiole latex, while cysteine proteases ("ficins") were the most abundant in immature fruit and trunk latexes. Galloylglycerol, a possible defense-related metabolite, appeared to be highly accumulated in all three latexes. The expression levels of pathogenesis-related proteins were highest in the latex of trunk, suggesting that this latex had adapted a defensive role against microbe attacks. Although young petioles and immature fruit are both unlignified soft organs, and potential food for herbivorous insects, unigenes for the sesquiterpenoid pathway, which likely produces defense-associated volatiles, and the phenylpropanoid pathway, which produces toxic furanocoumarins, were expressed less in immature fruit latex. This difference may indicate that while petioles and fruit protect the plant from attack by herbivores, the fruit must also attract insect pollinators at younger stages and animals after ripening. We also suggest possible candidate transcription factors and signal transduction proteins that are involved in the differential expression of the unigenes.

Advances in computational metabolomics and databases deepen the understanding of metabolisms

Mass spectrometry (MS)-based metabolomics is the popular platform for metabolome analyses. Computational techniques for the processing of MS raw data, for example, feature detection, peak alignment, and the exclusion of false-positive peaks, have been established. The next stage of untargeted metabolomics would be to decipher the mass fragmentation of small molecules for the global identification of human-, animal-, plant-, and microbiota metabolomes, resulting in a deeper understanding of metabolisms. This review is an update on the latest computational metabolomics including known/expected structure databases, chemical ontology classifications, and mass spectrometry cheminformatics for the interpretation of mass fragmentations and for the elucidation of unknown metabolites. The importance of metabolome 'databases' and 'repositories' is also discussed because novel biological discoveries are often attributable to the accumulation of data, to relational databases, and to their statistics. Lastly, a practical guide for metabolite annotations is presented as the summary of this review.