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.

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.

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.

Exploring correlations between MS and NMR for compound identification using essential oils: A pilot study.

INTRODUCTION: In this era of 'omics' technology in natural products studies, the complementary aspects of mass spectrometry (MS)- and nuclear magnetic resonance (NMR)-based techniques must be taken into consideration. The advantages of using both analytical platforms are reflected in a higher confidence of results especially when using replicated samples where correlation approaches can be used to statistically link results from MS to NMR. OBJECTIVES: Demonstrate the use of Statistical Total Correlation (STOCSY) for linking results from MS and NMR data to reach higher confidence in compound identification. METHODOLOGY: Essential oil samples of Melaleuca alternifolia and M. rhaphiophylla (Myrtaceae) were used as test objects. Aliquots of 10 samples were collected for GC-MS and NMR data acquisition [proton (1 H)-NMR, and carbon-13 (13 C)-NMR as well as two-dimensional (2D) heteronuclear single quantum correlation (HSQC), heteronuclear multiple-bond correlation (HMBC), and HSQC-total correlated spectroscopy (TOCSY) NMR]. The processed data was imported to Matlab where STOCSY was applied. RESULTS: STOCSY calculations led to the confirmation of the four main constituents of the sample-set. The identification of each was accomplished using; MS spectra, retention time comparison, 13 C-NMR data, and scalar correlations of the 2D NMR spectra. CONCLUSION: This study provides a pipeline for high confidence in compound identification using a set of essential oils samples as test objects for demonstration.

Applying NMR compound identification using NMRfilter to match predicted to experimental data.

INTRODUCTION: Metabolomics is the approach of choice to guide the understanding of biological systems and its molecular intricacies, but compound identification is yet a bottleneck to be overcome. OBJECTIVE: To assay the use of NMRfilter for confidence compound identification based on chemical shift predictions for different datasets. RESULTS: We found comparable results using the lead tool COLMAR and NMRfilter. Then, we successfully assayed the use of HMBC to add confidence to the identified compounds. CONCLUSIONS: NMRfilter is currently under development to become a stand-alone interactive software for high-confidence NMR compound identification and this communication gathers part of its application capabilities.

An integrated approach for mixture analysis using MS and NMR techniques.

We suggest an improved software pipeline for mixture analysis. The improvements include combining tandem MS and 2D NMR data for a reliable identification of the constituents in an algorithm based on network analysis aiming for a robust and reliable identification routine. An important part of this pipeline is the use of open-data repositories, although it is not totally reliant on them. The NMR identification step emphasizes robustness and is less sensitive towards changes in data acquisition and processing than existing methods. The process starts with LC-ESI-MSMS based molecular network dereplication using data from the GNPS collaborative collection. We identify closely related structures by propagating structure elucidation through edges in the network. Those identified compounds are added on top of a candidate list for the following NMR filtering method that predicts HSQC and HMBC NMR data. The similarity of the predicted spectra of the set of closely related structures to the measured spectra of the mixture sample is taken as one indication of the most likely candidates for its compounds. The other indication is the match of the spectra to clusters built by a network analysis from the spectra of the mixture. The sensitivity gap between NMR and MS is anticipated and it will be reflected naturally by the eventual identification of fewer compounds, but with a higher confidence level, after the NMR analysis step. The contributions of the paper are an algorithm combining MS and NMR spectroscopy and a robust nJCH network analysis to explore the complementary aspects of both techniques. This delivers good results, even if a perfect computational separation of the compounds in the mixture is not possible. All of the scripts are freely available to aid studies such as with plants, marine organisms, and microorganism natural product chemistry and metabolomics, as those are the driving forces for this project.

Preparative mass-spectrometry profiling of minor concentrated metabolites in Salicornia gaudichaudiana Moq by high-speed countercurrent chromatography and off-line electrospray mass-spectrometry injection.

Salicornia species have just been introduced to the European market as a vegetable named 'samphire', 'green asparagus', or 'sea asparagus'. Due to its increasing attention, and associated value, minor compounds of Salicornia gaudichaudiana Moq were investigated. The use of countercurrent chromatography and mass spectrometry enabled the search for known, as well as potentially novel natural products. Their identification was achieved based on molecular weights and mass-spectrometric fragmentation data. Low detection limits enabled the visualization of all compounds with their identification in almost real time close to the preparative countercurrent chromatography experiment. A list of known natural products from Salicornia genus guided the identification process of compounds occurring in Salicornia gaudichaudiana Moq by tandem mass spectrometry fragment comparison. The natural product classes were divided into four groups: chlorogenic acid derivatives; flavonoid derivatives; pentacyclic triterpenoid saponins; and other compounds.

High-Resolution α-Glucosidase Inhibition Profiling Combined with HPLC-HRMS-SPE-NMR for Identification of Antidiabetic Compounds in Eremanthus crotonoides (Asteraceae).

α-Glucosidase inhibitors decrease the cleavage- and absorption rate of monosaccharides from complex dietary carbohydrates, and represent therefore an important class of drugs for management of type 2 diabetes. In this study, a defatted ethyl acetate extract of Eremanthus crotonoides leaves with an inhibitory concentration (IC50) of 34.5 µg/mL towards α-glucosidase was investigated by high-resolution α-glucosidase inhibition profiling combined with HPLC-HRMS-SPE-NMR. This led to identification of six α-glucosidase inhibitors, namely quercetin (16), trans-tiliroside (17), luteolin (19), quercetin-3-methyl ether (20), 3,5-di-O-caffeoylquinic acid n-butyl ester (26) and 4,5-di-O-caffeoylquinic acid n-butyl ester (29). In addition, nineteen other metabolites were identified. The most active compounds were the two regioisomeric di-O-caffeoylquinic acid derivatives 26 and 29, with IC50 values of 5.93 and 5.20 µM, respectively. This is the first report of the α-glucosidase inhibitory activity of compounds 20, 26, and 29, and the findings support the important role of Eremanthus species as novel sources of new drugs and/or herbal remedies for treatment of type 2 diabetes.

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.

Antioxidant action of propolis on mouse lungs exposed to short-term cigarette smoke.

Propolis is a natural product with antioxidant properties. In this study, we tested the efficacy of propolis against acute lung inflammation (ALI) caused by cigarette smoke (CS). C57BL6 male mice were exposed to CS and treated with propolis (200mg/kg orally, CS+P) or only with propolis (P). A Control group treated with propolis was sham-smoked (Control+P). We collected the lungs for histological and biochemical analyses. We observed an increase in alveolar macrophages and neutrophils in the CS group compared with the Control+P. These counts reduced in the CS+P group compared to the CS group. The treatment with propolis normalized all biochemical parameters in the CS+P group compared with the CS group, including nitrite, myeloperoxidase level, antioxidant enzyme activities (superoxide dismutase, catalase and glutathione peroxidase), reduced glutathione/oxidized glutathione ratio and malondialdehyde. Additionally, TNF-α expression reduced in the CS+P group when compared with the CS group. These data imply a potential antioxidant and anti-inflammatory role for propolis with regard to ALI caused by CS in mice.

Salbutamol extraction from urine and its stability in different solutions: identification of methylation products and validation of a quantitative analytical method.

Salbutamol is commonly used in asthma treatment, being considered a short-effect bronchodilator. This drug poses special interest in certain fields of chemical analysis, such as food, clinical and doping analyses, in which it needs to be analyzed with quantitative precision and accuracy. Salbutamol, however, is known to degrade under certain conditions and this is critical if quantitative results must be generated. The present work aimed to investigate salbutamol extraction from urine samples, to determine whether salbutamol is unstable in other solvents as well as in urine samples, to elucidate the structures of the possible degradation products and to validate an analytical method using the extraction procedure evaluated. Stability investigations were performed in urine at different pH values, in methanol and acetone at different temperatures. Semi-preparative liquid chromatography was performed for the isolation of degradation products, and gas chromatography coupled to mass spectrometry as well as nuclear magnetic resonance were used for identification. Three unreported methylation products were detected in methanolic solutions and had their structures elucidated. Urine samples showed a reduction in salbutamol concentration of up to 25.8% after 5 weeks. These results show that special care must be taken regarding salbutamol quantitative analyses, since degradation either in standard solutions or in urine could lead to incorrect values.

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.

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.

Antileukemic Properties of Sesquiterpene Lactones: A Systematic Review.

This review summarizes the reported molecular mechanisms underlying the antileukemic property of Sesquiterpene Lactones (SLs). This systematic review was registered in the PROSPERO database and conducted following the PRISMA Statements. The MeSH terms, Sesquiterpenes, Lactones and Leukemia were used in four databases (Pubmed, Web of Science, Scopus and Bireme). There were 281 studies selected, but after exclusions, due to replication (n = 172) or not following PECOS criteria (n = 24), 148 studies remained. Of the 148 articles, only 22 were submitted to quality assessment and were scored in high level if more than two techniques, to elucidate antileukemic properties, were described, and then data were extracted. The studies mostly used human leukemia cell lines including primary and established cells, with or without chemotherapy resistance. The SLs used were obtained principally from plants. The antileukemic properties of SLs were extracted from 22 high level studies. They included cell death induction, mainly by apoptosis, as well as cell differentiation, cell cycle disruption, leukemia cancer stem cell growth inhibition and NF-κB pathway inhibition; the latter is a promising therapeutic target for lymphoid malignancies. We concluded that, in spite of the necessity of better toxicological profile characterization of SLs, the antileukemic properties of these compounds support the proposal that the SLs are promising candidates for the treatment of leukemia.

Isolation of phenolics from Rhizophora mangle by combined counter-current chromatography and gel-filtration.

Nine phenolic compounds, quercetin, epi-catechin, catechin, 4-hydroxybenzoic acid, kaempferol 3-O-ß-glucopyranoside, quercetin 3-O-ß-glucopyranoside, quercetin 3-O-6"-trans-coumaroyl-ß-glucoside, kaempferol 3-O-ß-rutinoside and quercetin 3-O-ß-rutinoside, were isolated from the EtOAc leaf extract of Rhizophora mangle (Rhizophoraceae) combining counter-current chromatography (CCC) and gel-filtration. A solvent system of n-hexane-ethyl acetate-methanol-water (1.5:6:1.5:6) was employed at the preliminary stage of EtOAc extract fractionation as it was shown to contain compounds that differed highly in their hydrophobicity. The obtained fractions were further purified by either CCC or gel-filtration depending on their complexity. The isolated compounds were analyzed by NMR spectroscopy and the proposed structures were confirmed by HRES/ESI/TOF MS. Some of these compounds were isolated and/or identified for the first time in R. mangle.

The adjuvanticity of Chiococca alba saponins increases with the length and hydrophilicity of their sugar chains.

The saponins of Chiococca alba are triterpene bidesmosides that contain glycidic moieties attached to the C-3 and C-28 carbon of their aglycone. We describe that their adjuvant potential increases in direct relationship to the length and hydrophilicity of the C-28 attached sugar chain which contains: arabinose-rhamnose in the CA2, arabinose-rhamnose-xylose in the CA3X; arabinose-rhamnose-apiose in the CA3 and arabinose-rhamnose-apiose-apiose in the CA4 saponin. The hydrophile/lipophile balance calculated for CA2 was 12.7, for CA3 and CA3X was 15.8 and for CA4 19.9. All saponins were formulated with the FML antigen for mice prophylaxis against visceral leishmaniasis. The immune response was studied using an ELISA-antibody assay and monitoring of the intradermal response (IDR) to Leishmania antigens, the cytokine expression in supernatants and the intracellular staining of in vitro cultured splenocytes. After challenge, significant increases of IgG and IgG2a antibodies were noted only in the CA4 vaccinated mice that showed extended IDR, higher IFN-γ production by CD8+ and TNF-α production by CD4+ T cells, higher TNF-α secretion and the highest reduction of the parasite load (78%). The increases in IDR, CD4-TNF-α, CD8-IFN-γ and CD8-TNF-α by the CA4 vaccine were strong correlates of protection and were significantly correlated to the decrease of parasite load (p=-0.007). Protection generated by the CA4 vaccine was mainly mediated by a CD4+ T cell and a TNF-α driven response with a lower contribution of CD8+ T cells, as confirmed by an in vivo depletion with monoclonal antibodies and by vaccination assays in TNF-α-receptor knock-out mice. Our results confirm that the superiority of the CA4 saponin is related to the higher hydrophilicity of its longer carbohydrate chain. C. alba saponins were non-toxic and only the xylose-containing saponin CA3X was hemolytic (HD(50)=87 µg/ml). The increase in sugar units of the saponins is positively correlated to the increase of IDR and to the decrease of parasite load.

Effects of Euterpe oleracea Mart. (AÇAÍ) extract in acute lung inflammation induced by cigarette smoke in the mouse.

Short term inhalation of cigarette smoke (CS) induces significant lung inflammation due to an imbalance of oxidant/antioxidant mechanisms. Açai fruit (Euterpe oleracea) has significant antioxidant and anti-inflammatory actions. The present study aimed to determine whether oral administration of an açai stone extract (ASE) could reduce lung inflammation induced by CS. Thirty C57BL/6 mice were assigned to three groups (n=10 each): the Control+A group was exposed to ambient air and treated orally with ASE 300 mg/kg/day; the CS group was exposed to smoke from 6 cigarettes per day for 5 days; and the CS+A group was exposed to smoke from 6 cigarettes per day for 5 days and treated orally with ASE (300 mg/kg/day). On day 6, all mice were sacrificed. After bronchoalveolar lavage, the lungs were removed for histological and biochemical analyses. The CS group exhibited increases in alveolar macrophage (AMs) and neutrophil numbers (PMNs), myeloperoxidase (MPO), superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase activities (GPx), TNF-α expression, and nitrites levels in lung tissue when compared with the control ones (p<0.001 for all parameters). The AMs, PMNs, MPO, SOD, CAT, GPx and nitrite were significantly reduced by oral administration of ASE when compared with CS group (p<0.001 for all parameters, with exception of AMs p<0.01). The present results suggested that systemic administration of an ASE extract could reduce the inflammatory and oxidant actions of CS. Thus, the results of this study in mice should stimulate future studies on ASE as a potential agent to protect against CS-induced inflammation in humans.