Bioactive Compounds in Citrus Species with Potential for the Treatment of Chronic Venous Disease: A Review.

Chronic venous disease (CVD) significantly impacts global health, presenting a complex challenge in medical management. Despite its prevalence and the burden it places on healthcare systems, CVD remains underdiagnosed and undertreated. This review aims to provide a comprehensive analysis of the bioactive compounds in the Citrus genus, exploring their therapeutic potential in CVD treatment and addressing the gap in current treatment modalities. A narrative review methodology was adopted, focusing on the pharmacological effects of Citrus-derived bioactive compounds, including flavonoids and terpenes. Additionally, the review introduced the DBsimilarity method for analyzing the chemical space and structural similarities among Citrus compounds. The review highlights the Citrus genus as a rich source of pharmacologically active compounds, notably flavonoids and terpenes, which exhibit significant anti-inflammatory, antioxidant, and veno-protective properties. Some of these compounds have been integrated into existing therapies, underscoring their potential for CVD management. The DBsimilarity analysis further identified many clusters of compounds with more than 85% structural similarity. Citrus-derived bioactive compounds offer promising therapeutic potential for managing CVD, showcasing significant anti-inflammatory, antioxidant, and veno-protective effects. The need for further comparative studies, as well as safety and efficacy investigations specific to CVD treatment, is evident. This review underlines the importance of advancing our understanding of these natural compounds and encouraging the development of novel treatments and formulations for effective CVD management. The DBsimilarity method's introduction provides a novel approach to exploring the chemical diversity within the Citrus genus, opening new pathways for pharmacological research.

Unlocking Biological Activity and Metabolomics Insights: Primary Screening of Cyanobacterial Biomass from a Tropical Reservoir.

Cyanobacterial harmful algal blooms can pose risks to ecosystems and human health worldwide due to their capacity to produce natural toxins. The potential dangers associated with numerous metabolites produced by cyanobacteria remain unknown. Only select classes of cyanopeptides have been extensively studied with the aim of yielding substantial evidence regarding their toxicity, resulting in their inclusion in risk management and water quality regulations. Information about exposure concentrations, co-occurrence, and toxic impacts of several cyanopeptides remains largely unexplored. We used liquid chromatography-mass spectrometry (LC-MS)-based metabolomic methods associated with chemometric tools (NP Analyst and Data Fusion-based Discovery), as well as an acute toxicity essay, in an innovative approach to evaluate the association of spectral signatures and biological activity from natural cyanobacterial biomass collected in a eutrophic reservoir in southeastern Brazil. Four classes of cyanopeptides were revealed through metabolomics: microcystins, microginins, aeruginosins, and cyanopeptolins. The bioinformatics tools showed high bioactivity correlation scores for compounds of the cyanopeptolin class (0.54), in addition to microcystins (0.54-0.58). These results emphasize the pressing need for a comprehensive evaluation of the (eco)toxicological risks associated with different cyanopeptides, considering their potential for exposure. Our study also demonstrated that the combined use of LC-MS/MS-based metabolomics and chemometric techniques for ecotoxicological research can offer a time-efficient strategy for mapping compounds with potential toxicological risk. Environ Toxicol Chem 2024;00:1-10. © 2024 SETAC.

Wnt7b acts in concert with Wnt5a to regulate tissue elongation and planar cell polarity via noncanonical Wnt signaling.

Intercellular signaling mediated by evolutionarily conserved planar cell polarity (PCP) proteins aligns cell polarity along the tissue plane and drives polarized cell behaviors during tissue morphogenesis. Accumulating evidence indicates that the vertebrate PCP pathway is regulated by noncanonical, ß-catenin-independent Wnt signaling; however, the signaling components and mechanisms are incompletely understood. In the mouse hearing organ, both PCP and noncanonical Wnt (ncWnt) signaling are required in the developing auditory sensory epithelium to control cochlear duct elongation and planar polarity of resident sensory hair cells (HCs), including the shape and orientation of the stereociliary hair bundle essential for sound detection. We have recently discovered a Wnt/G-protein/PI3K pathway that coordinates HC planar polarity and intercellular PCP signaling. Here, we identify Wnt7b as a ncWnt ligand acting in concert with Wnt5a to promote tissue elongation in diverse developmental processes. In the cochlea, Wnt5a and Wnt7b are redundantly required for cochlear duct coiling and elongation, HC planar polarity, and asymmetric localization of core PCP proteins Fzd6 and Dvl2. Mechanistically, Wnt5a/Wnt7b-mediated ncWnt signaling promotes membrane recruitment of Daple, a nonreceptor guanine nucleotide exchange factor for Gαi, and activates PI3K/AKT and ERK signaling, which promote asymmetric Fzd6 localization. Thus, ncWnt and PCP signaling pathways have distinct mutant phenotypes and signaling components, suggesting that they act as separate, parallel pathways with nonoverlapping functions in cochlear morphogenesis. NcWnt signaling drives tissue elongation and reinforces intercellular PCP signaling by regulating the trafficking of PCP-specific Frizzled receptors.

PyINETA: Open-source platform for INADEQUATE-JRES integration in NMR metabolomics.

Annotating compounds with high confidence is a critical element in metabolomics. 13C-detection NMR experiment INADEQUATE (incredible natural abundance double-quantum transfer experiment) stands out as a powerful tool for structural elucidation, whereas this valuable experiment is not often included in metabolomics studies. This is partly due to the lack of community platform that provides structural information based INADEQUATE. Also, it is often the case that a single study uses various NMR experiments synergistically to improve the quality of information or balance total NMR experiment time, but there is no public platform that can integrate the outputs of INADEQUATE and other NMR experiments either. Here, we introduce PyINETA, Python-based INADEQUATE network analysis. PyINETA is an open-source platform that provides structural information of molecules using INADEQUATE, conducts database search, and integrates information of INADEQUATE and a complementary NMR experiment 13C J-resolved experiment (13C-JRES). Those steps are carried out automatically, and PyINETA keeps track of all the pipeline parameters and outputs, ensuring the transparency of annotation in metabolomics. Our evaluation of PyINETA using a model mouse study showed that our pipeline successfully integrated INADEQUATE and 13C-JRES. The results showed that 13C-labeled amino acids that were fed to mice were transferred to different tissues, and, also, they were transformed to other metabolites. The distribution of those compounds was tissue-specific, showing enrichment of particular metabolites in liver, spleen, pancreas, muscle, or lung. The value of PyINETA was not limited to those known compounds; PyINETA also provided fragment information for unknown compounds. PyINETA is available on NMRbox.

Prevalence and Magnitude of Olfactory Dysfunction in Allergic Rhinitis.

BACKGROUND: Although allergic rhinitis (AR) can negatively impact the ability to smell, the degree to which this occurs is not clear and prevalence estimates vary among studies. This study had 4 main objectives: (1) To estimate the prevalence and the degree of olfactory dysfunction in AR patients; (2) To compare olfactory perception between AR patients with different persistence and severity of symptoms and determine if olfactory testing may aid in differentiating among Allergic Rhinitis and its Impact on Asthma (ARIA) groups; (3) To determine whether allergic reactions to different allergens differentially impact olfactory function, and (4) Verify possible changes in the olfactory epithelium (OE) caused by AR. METHODS: One hundred thirty-three patients with AR and one hundred controls were tested. The main outcome was the score in University of Pennsylvania Smell Identification Test (UPSIT®). The OE was examined using immunofluorescence markers for neuronal activity, apoptosis, oxidative stress, signal transduction, eosinophils, and epithelial thickness. RESULTS: Prevalence of olfactory dysfunction in the AR patients was higher (AR: 42.9% vs controls: 9%, P < .001). No difference was found either between intermittent and persistent disease cases (P = .58) or between cases with mild and those with moderate/severe symptomatology (P = .33). Lower olfactory capacity was not associated with the reaction to more (P = .48) or diverse types of allergens (Ps > .05). Although not significant, patients with AR had a greater amount of eosinophilia and a lower amount of cAMP (cyclic adenosine monophosphate) in the OE. CONCLUSION: The study highlights a higher prevalence of olfactory dysfunction in AR patients compared to controls, but olfactory testing may not effectively differentiate AR severity or allergen sensitivities. Although trends suggest potential pathophysiological changes in the OE of AR patients, further research is needed to validate these findings.

Dereplication of calystegines in food plants and wild Solanum Brazilian fruits.

Calystegines are potent glycosidase inhibitors with therapeutic potential and are constituents of food and feed with potential toxic effects. This study aims to target calystegines and other nitrogenous substances in food plants. Hydroalcoholic extracts from Solanum tuberosum, Ipomoea batatas, S. lycocarpum, and fruit from S. lycopersicum, S. aethiopicum, S. paniculatum, S. crinitum, and S. acanthodes were analyzed by liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) using an acidic HILIC column. The dereplication approach included data processing using MZMine2, FBMN-GNPS, and structure elucidation and interpretation of the organized data. The calystegines A3, A5, B2, and C1 were identified, and several potential new calystegine analogues: three may correspond to new calystegines of the A-group, one glycosyl derivative of calystegine A3, and two glycosyl derivatives of the B-group. These findings help to direct the search for new calystegines. In addition, the dereplication approach enabled the annotation of 22 other nitrogen compounds.

Analytical Determination of Serotonin Exocytosis in Human Platelets with BDD-on-Quartz MEA Devices.

Amperometry is arguably the most widely used technique for studying the exocytosis of biological amines. However, the scarcity of human tissues, particularly in the context of neurological diseases, poses a challenge for exocytosis research. Human platelets, which accumulate 90% of blood serotonin, release it through exocytosis. Nevertheless, single-cell amperometry with encapsulated carbon fibers is impractical due to the small size of platelets and the limited number of secretory granules on each platelet. The recent technological improvements in amperometric multi-electrode array (MEA) devices allow simultaneous recordings from several high-performance electrodes. In this paper, we present a comparison of three MEA boron-doped diamond (BDD) devices for studying serotonin exocytosis in human platelets: (i) the BDD-on-glass MEA, (ii) the BDD-on-silicon MEA, and (iii) the BDD on amorphous quartz MEA (BDD-on-quartz MEA). Transparent electrodes offer several advantages for observing living cells, and in the case of platelets, they control activation/aggregation. BDD-on-quartz offers the advantage over previous materials of combining excellent electrochemical properties with transparency for microscopic observation. These devices are opening exciting perspectives for clinical applications.

Unusual Sesquiterpenes from Streptomyces olindensis DAUFPE 5622.

In nature, the vast majority of sesquiterpenes are produced by type I mechanisms, and glycosylated sesquiterpenes are rare in actinobacteria. Streptomyces olindensis DAUFPE 5622 produces the sesquiterpenes olindenones A-G, a new class of rearranged drimane sesquiterpenes. Olindenones B-D are oxygenated derivatives of olindenone A, while olindenones E-G are analogs glycosylated with dideoxysugars. 13C-isotope labeling studies demonstrated olindenone A biosynthesis occurs via the methylerythritol phosphate (MEP) pathway and suggested the rearrangement is only partially concerted. Based on the structures, one potential mechanism of olindenone A formation proceeds by cyclization of the linear terpenoid precursor, likely occurring via a terpene cyclase-mediated type II mechanism whereby the terminal alkene of the precursor is protonated, triggering carbocation-driven cyclization followed by rearrangement. Diphosphate hydrolysis may occur either before or after cyclization. Although a biosynthetic route is proposed, the terpene cyclase gene responsible for producing olindenones currently remains unidentified.

High-speed countercurrent chromatography with offline detection by electrospray mass spectrometry and nuclear magnetic resonance detection as a tool to resolve complex mixtures: A practical approach using Coffea arabica leaf extract.

INTRODUCTION: Many secondary metabolites isolated from plants have been described in the literature owing to their important biological properties and possible pharmacological applications. However, the identification of compounds present in complex plant extracts has remained a great scientific challenge, is often laborious, and requires a long research time with high financial cost. OBJECTIVES: The aim of this study was to develop a method that allows the identification of secondary metabolites in plant extracts with a high degree of confidence in a short period of time. MATERIAL AND METHODS: In this study, an ethanolic extract of Coffea arabica leaves was used to validate the proposed method. Countercurrent chromatography was chosen as the initial step for extraction fractionation using gradient elution. Resulting fractions presented a variation of compounds concentrations, allowing for statistical total correlation spectroscopy (STOCSY) calculations between liquid chromatography coupled with high-resolution tandem mass spectrometry (LC-HRMS/MS) and NMR across fractions. RESULTS: The proposed method allowed the identification of 57 compounds. Of the annotated compounds, 20 were previously described in the literature for the species and 37 were reported for the first time. Among the inedited compounds, we identified flavonoids, alkaloids, phenolic acids, coumarins, and terpenes. CONCLUSION: The proposed method presents itself as a valid alternative for the study of complex extracts in an effective, fast, and reliable way that can be reproduced in the study of other extracts.

Data Base similarity (DBsimilarity) of natural products to aid compound identification on MS and NMR pipelines, similarity networking, and more.

INTRODUCTION: We developed Data Base similarity (DBsimilarity), a user-friendly tool designed to organize structure databases into similarity networks, with the goal of facilitating the visualization of information primarily for natural product chemists who may not have coding experience. METHOD: DBsimilarity, written in Jupyter Notebooks, converts Structure Data File (SDF) files into Comma-Separated Values (CSV) files, adds chemoinformatics data, constructs an MZMine custom database file and an NMRfilter candidate list of compounds for rapid dereplication of MS and 2D NMR data, calculates similarities between compounds, and constructs CSV files formatted into similarity networks for Cytoscape. RESULTS: The Lotus database was used as a source for Ginkgo biloba compounds, and DBsimilarity was used to create similarity networks including NPClassifier classification to indicate biosynthesis pathways. Subsequently, a database of validated antibiotics from natural products was combined with the G. biloba compounds to identify promising compounds. The presence of 11 compounds in both datasets points to possible antibiotic properties of G. biloba, and 122 compounds similar to these known antibiotics were highlighted. Next, DBsimilarity was used to filter the NPAtlas database (selecting only those with MIBiG reference) to identify potential antibacterial compounds using the ChEMBL database as a reference. It was possible to promptly identify five compounds found in both databases and 167 others worthy of further investigation. CONCLUSION: Chemical and biological properties are determined by molecular structures. DBsimilarity enables the creation of interactive similarity networks using Cytoscape. It is also in line with a recent review that highlights poor biological plausibility and unrealistic chromatographic behaviors as significant sources of errors in compound identification.

Advances in Microbial NMR Metabolomics.

Confidently, nuclear magnetic resonance (NMR) is the most informative technique in analytical chemistry and its use as an analytical platform in metabolomics is well proven. This chapter aims to present NMR as a viable tool for microbial metabolomics discussing its fundamental aspects and applications in metabolomics using some chosen examples.

NMR as a tool for compound identification in mixtures.

INTRODUCTION: Natural products and metabolomics are intrinsically linked through efforts to analyze complex mixtures for compound annotation. Although most studies that aim for compound identification in mixtures use MS as the main analysis technique, NMR has complementary advances that are worth exploring for enhanced structural confidence. OBJECTIVE: This review aimed to showcase a portfolio of the main tools available for compound identification using NMR. MATERIALS AND METHODS: COLMAR, SMART-NMR, MADByTE, and NMRfilter are presented using examples collected from real samples from the perspective of a natural product chemist. Data are also made available through Zenodo so that readers can test each case presented here. CONCLUSION: The acquisition of 1 H NMR, HSQC, TOCSY, HSQC-TOCSY, and HMBC data for all samples and fractions from a natural products study is strongly suggested. The same is valid for MS analysis to create a bridged analysis between both techniques in a complementary manner. The use of NOAH supersequences has also been suggested and demonstrated to save NMR time.

Forty years of the adrenal chromaffin cell through ISCCB meetings around the world.

This historical review focuses on the evolution of the knowledge accumulated during the last two centuries on the biology of the adrenal medulla gland and its chromaffin cells (CCs). The review emerged in the context of a series of meetings that started on the Spanish island of Ibiza in 1982 with the name of the International Symposium on Chromaffin Cell Biology (ISCCB). Hence, the review is divided into two periods namely, before 1982 and from this year to 2022, when the 21st ISCCB meeting was just held in Hamburg, Germany. The first historical period extends back to 1852 when Albert Kölliker first described the fine structure and function of the adrenal medulla. Subsequently, the adrenal staining with chromate salts identified the CCs; this was followed by the establishment of the embryological origin of the adrenal medulla, and the identification of adrenaline-storing vesicles. By the end of the nineteenth century, the basic morphology, histochemistry, and embryology of the adrenal gland were known. The twentieth century began with breakthrough findings namely, the experiment of Elliott suggesting that adrenaline was the sympathetic neurotransmitter, the isolation of pure adrenaline, and the deciphering of its molecular structure and chemical synthesis in the laboratory. In the 1950s, Blaschko isolated the catecholamine-storing vesicles from adrenal medullary extracts. This switched the interest in CCs as models of sympathetic neurons with an explosion of studies concerning their functions, i.e., uptake of catecholamines by chromaffin vesicles through a specific coupled transport system; the identification of several vesicle components in addition to catecholamines including chromogranins, ATP, opioids, and other neuropeptides; the calcium-dependence of the release of catecholamines; the underlying mechanism of exocytosis of this release, as indicated by the co-release of proteins; the cross-talk between the adrenal cortex and the medulla; and the emission of neurite-like processes by CCs in culture, among other numerous findings. The 1980s began with the introduction of new high-resolution techniques such as patch-clamp, calcium probes, marine toxins-targeting ion channels and receptors, confocal microscopy, or amperometry. In this frame of technological advances at the Ibiza ISCCB meeting in 1982, 11 senior researchers in the field predicted a notable increase in our knowledge in the field of CCs and the adrenal medulla; this cumulative knowledge that occurred in the last 40 years of history of the CC is succinctly described in the second part of this historical review. It deals with cell excitability, ion channel currents, the exocytotic fusion pore, the handling of calcium ions by CCs, the kinetics of exocytosis and endocytosis, the exocytotic machinery, and the life cycle of secretory vesicles. These concepts together with studies on the dynamics of membrane fusion with super-resolution imaging techniques at the single-protein level were extensively reviewed by top scientists in the field at the 21st ISCCB meeting in Hamburg in the summer of 2022; this frontier topic is also briefly reviewed here. Many of the concepts arising from those studies contributed to our present understanding of synaptic transmission. This has been studied in physiological or pathophysiological conditions, in CCs from animal disease models. In conclusion, the lessons we have learned from CC biology as a peripheral model for brain and brain disease pertain more than ever to cutting-edge research in neurobiology. In the 22nd ISCCB meeting in Israel in 2024 that Uri Asheri is organizing, we will have the opportunity of seeing the progress of the questions posed in Ibiza, and on other questions that undoubtedly will arise.

Multielectrode Arrays as a Means to Study Exocytosis in Human Platelets.

Platelets are probably the most accessible human cells to study exocytosis by amperometry. These cell fragments accumulate biological amines, serotonin in particular, using similar if not the same mechanisms as those employed by sympathetic, serotoninergic, and histaminergic neurons. Thus, platelets have been widely recognized as a model system to study certain neurological and psychiatric diseases. Platelets release serotonin by exocytosis, a process that entails the fusion of a secretory vesicle to the plasma membrane and that can be monitored directly by classic single cell amperometry using carbon fiber electrodes. However, this is a tedious technique because any given platelet releases only 4-8 secretory δ-granules. Here, we introduce and validate a diamond-based multielectrode array (MEA) device for the high-throughput study of exocytosis by human platelets. This is probably the first reported study of human tissue using an MEA, demonstrating that they are very interesting laboratory tools to assess alterations to exocytosis in neuropsychiatric diseases. Moreover, these devices constitute a valuable platform for the rapid testing of novel drugs that act on secretory pathways in human tissues.

The dynamic nature of exocytosis from large secretory vesicles. A view from electrochemistry and imaging.

In this brief review, we discuss the factors that modulate the quantum size and the kinetics of exocytosis. We also discuss the determinants which motivate the type of exocytosis from the so-called kiss-and-run to full fusion and along the intermediate mode of partial release. Kiss-and-run release comprises the transient opening of a nanometer (approx. 2 nm diameter) fusion pore between vesicle and plasma membrane allowing a small amount of release. Partial release comprises a larger more extended opening of the pore to allow a larger fraction of released vesicle content and is what is observed as normal full release in most electrochemical measurements. Partial release appears to be dominant in dense core vesicles and perhaps synaptic vesicles. The concept of partial release leads to the fraction released as a plastic component of exocytosis. Partial vesicular distension and the kinetics of exocytosis can be modulated by second messengers, physiological modulators, and drugs. This concept adds a novel point of regulation for the exocytotic process.

Direct deduction of chemical class from NMR spectra.

This paper presents a proof-of-concept method for classifying chemical compounds directly from NMR data without performing structure elucidation. This can help to reduce the time in finding good structure candidates, as in most cases matching must be done by a human engineer, or at the very least a process for matching must be meaningfully interpreted by one. The method identified as suitable for classification is a convolutional neural network (CNN). Other methods, including clustering and image registration, have not been found to be suitable for the task in a comparative analysis. The result shows that deep learning can offer solutions to spectral interpretation problems.

Online Detection of Catecholamine Release from the Perfused Rat Adrenal Gland.

Retrogradely perfused adrenal glands have historically served for establishing many of our current knowledge on the stimulus-secretion coupling process. Although the use of intact adrenals has largely been switched to isolated chromaffin cells, adrenal glands are still a very valuable tool to characterize physiological and pharmacological questions. Even more, this is an excellent preparation for studying the splanchnic nerve/chromaffin cell interaction. In this chapter, we will provide the ways to (i) perform retrograde perfusion of isolated rat adrenals, (ii) the method to apply electrical splanchnic nerve stimulation, and (iii) the preparation of adrenals to conduct online electrochemical detection of catecholamine release.

Data Fusion-based Discovery (DAFdiscovery) pipeline to aid compound annotation and bioactive compound discovery across diverse spectral data.

INTRODUCTION: Data Fusion-based Discovery (DAFdiscovery) is a pipeline designed to help users combine mass spectrometry (MS), nuclear magnetic resonance (NMR), and bioactivity data in a notebook-based application to accelerate annotation and discovery of bioactive compounds. It applies Statistical Total Correlation Spectroscopy (STOCSY) and Statistical HeteroSpectroscopy (SHY) calculation in their data using an easy-to-follow Jupyter Notebook. METHOD: Different case studies are presented for benchmarking, and the resultant outputs are shown to aid natural products identification and discovery. The goal is to encourage users to acquire MS and NMR data from their samples (in replicated samples and fractions when available) and to explore their variance to highlight MS features, NMR peaks, and bioactivity that might be correlated to accelerated bioactive compound discovery or for annotation-identification studies. RESULTS: Different applications were demonstrated using data from different research groups, and it was shown that DAFdiscovery reproduced their findings using a more straightforward method. CONCLUSION: DAFdiscovery has proven to be a simple-to-use method for different situations where data from different sources are required to be analyzed together.

An anchored experimental design and meta-analysis approach to address batch effects in large-scale metabolomics.

Untargeted metabolomics studies are unbiased but identifying the same feature across studies is complicated by environmental variation, batch effects, and instrument variability. Ideally, several studies that assay the same set of metabolic features would be used to select recurring features to pursue for identification. Here, we developed an anchored experimental design. This generalizable approach enabled us to integrate three genetic studies consisting of 14 test strains of Caenorhabditis elegans prior to the compound identification process. An anchor strain, PD1074, was included in every sample collection, resulting in a large set of biological replicates of a genetically identical strain that anchored each study. This enables us to estimate treatment effects within each batch and apply straightforward meta-analytic approaches to combine treatment effects across batches without the need for estimation of batch effects and complex normalization strategies. We collected 104 test samples for three genetic studies across six batches to produce five analytical datasets from two complementary technologies commonly used in untargeted metabolomics. Here, we use the model system C. elegans to demonstrate that an augmented design combined with experimental blocks and other metabolomic QC approaches can be used to anchor studies and enable comparisons of stable spectral features across time without the need for compound identification. This approach is generalizable to systems where the same genotype can be assayed in multiple environments and provides biologically relevant features for downstream compound identification efforts. All methods are included in the newest release of the publicly available SECIMTools based on the open-source Galaxy platform.

Combining high-speed countercurrent chromatography three-phase solvent system with electrospray ionization-mass spectrometry and nuclear magnetic resonance to profile the unconventional food plant Syzygium malaccense.

Syzygium malaccense (L.) Merr. & L.M. Perry is a native tree to Malaysia, but also occurs in other tropical regions of the world, including Brazil. The increasing interest in the consumption of its leaves motivated the investigation of compounds of the plant. Metabolite profiling of S. malaccense leaves was achieved by high-speed countercurrent chromatography (HSCCC) fractionation coupled off-line to electrospray mass-spectrometry (ESI-MS) detection and nuclear magnetic resonance (NMR) analysis. The ethanolic leaf extract was submitted to HSCCC using a three-phase solvent system (TPSS) composed by n-hexane - ethyl acetate - acetonitrile - H2O (2:1:1:1, v/v). The stepwise gradient elution was employed due to the extract's chemical complexity. HSCCC fractions were further analyzed by ESI-MS/MS using a flow injection experiment and by NMR acquiring 1H, HSQC and HMBC spectra. MS based dereplication was achieved by comparing acquired data to those available in public and commercial databases. Results were also correlated to previously isolated compounds described for the Syzygium genus. This process led to the annotation of 90 compounds. The NMR data provided structural confirmation and substitution patterns for some of them. Extract chemical composition is characterized by having flavonoids, benzoic acids, hydroxycinnamic acids, quinic acids, hydrolizable tannins, fatty acids, anacardic acids and others primary metabolites. Most of these compounds were described for the first time in the plant. This approach greatly facilitates phytochemical analysis and could be applied to improve metabolite discovery in other studies.