Application of feature-based molecular networking and MassQL for the MS/MS fragmentation study of depsipeptides.

The Feature-based Molecular Networking (FBMN) is a well-known approach for mapping and identifying structures and analogues. However, in the absence of prior knowledge about the molecular class, assessing specific fragments and clusters requires time-consuming manual validation. This study demonstrates that combining FBMN and Mass Spec Query Language (MassQL) is an effective strategy for accelerating the decoding mass fragmentation pathways and identifying molecules with comparable fragmentation patterns, such as beauvericin and its analogues. To accomplish this objective, a spectral similarity network was built from ESI-MS/MS experiments of Fusarium oxysporum at various collision energies (CIDs) and paired with a MassQL search query for conserved beauvericin ions. FBMN analysis revealed that sodiated and protonated ions clustered differently, with sodiated adducts needing more collision energy and exhibiting a distinct fragmentation pattern. Based on this distinction, two sets of particular fragments were discovered for the identification of these hexadepsipeptides: ([M + H]+) m/z 134, 244, 262, and 362 and ([M + Na]+) m/z 266, 284 and 384. By using these fragments, MassQL accurately found other analogues of the same molecular class and annotated beauvericins that were not classified by FBMN alone. Furthermore, FBMN analysis of sodiated beauvericins at 70 eV revealed subclasses with distinct amino acid residues, allowing distinction between beauvericins (beauvericin and beauvericin D) and two previously unknown structural isomers with an unusual methionine sulfoxide residue. In summary, our integrated method revealed correlations between adduct types and fragmentation patterns, facilitated the detection of beauvericin clusters, including known and novel analogues, and allowed for the differentiation between structural isomers.

Dereplication of Lantana trifolia L. leaves and fruits by UFLC-DAD-(+)-ESI-MS/MS and its antifungal and cytotoxic activities.

INTRODUCTION: Lantana trifolia L. (Verbenaceae) is a shrubby plant. In folk medicine, its leaves are used in the form of infusions and syrups to treat angina, coughs, and colds; they are also applied as tranquilizer. Previous studies have reported the antimicrobial potential of the compounds present in L. trifolia leaves. OBJECTIVES: To report the anti-Candida activities of the fractions obtained from the fruits and leaves of two L. trifolia specimens. METHODS: The L. trifolia fractions were submitted to UFLC-DAD-(+)-ESI-MS/MS, and the data were analyzed by using multivariate statistical tools (PCA, PLS-DA) and spectral similarity analyses based on molecular networking, which aided dereplication of the bioactive compounds. Additionally, NMR analyses were performed to confirm the chemical structure of some of the major compounds in the fractions. RESULTS: The ethyl acetate fractions presented MIC values lower than 100 µg mL-1 against the three Candida strains evaluated herein (C. albicans, C. tropicalis, and C. glabrata). Fractions FrPo AcOEt, FrPe AcOEt, and FrPe nBut had MIC values of 1.46, 2.93, and 2.93 µg mL-1 against C. glabrata, respectively. These values resembled the MIC value of amphotericin B, the positive control (0.5-1.0 µg mL-1), against this same strain. Cytotoxicity was measured and used to calculate the selectivity index. CONCLUSION: On the basis of our data, the most active fractions in the antifungal assay were more selective against C. glabrata than against non-infected cells. The analytical approach adopted here allowed us to annotate 29 compounds, nine of which were bioactive (PLS-DA results) and belong to the class of phenolic compounds.

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.

In vitro metabolism of the new antifungal dapaconazole using liver microsomes.

Dapaconazole is a new antifungal imidazole that has been shown a high efficacy against several pathogenic fungi. This study aimed to investigate the interspecies variation in the in vitro metabolic profiles and in vivo hepatic clearance (CLH,in vivo) prediction of dapaconazole using liver microsomes from male Sprague Dawley rat, male Beagle dog and mixed gender human using a liquid chromatography coupled to tandem mass spectrometry (UHPLC-MS/MS) method. In addition, the produced metabolites were identified by ultra-high-performance liquid chromatography with quadrupole time-of-flight mass spectrometer (UHPLC-QTOF-MS/MS). The microsomal protein concentration of 0.1 mg/mL and the incubation time of 10 min were employed for the kinetics determination, resulting in a sigmoidal kinetic profile for all species evaluated. The predicted CLH,in vivo was 6.5, 11.6 and 7.5 mL/min/kg for human, rat and dog, respectively. Furthermore, five metabolized products were identified. These findings provide preliminary information for understanding dapaconazole metabolism and the interspecies differences in catalytic behaviours, supporting the choice of a suitable laboratory animal for future pharmacokinetics and metabolism studies.

Non-target molecular network and putative genes of flavonoid biosynthesis in Erythrina velutina Willd., a Brazilian semiarid native woody plant.

Erythrina velutina is a Brazilian native tree of the Caatinga (a unique semiarid biome). It is widely used in traditional medicine showing anti-inflammatory and central nervous system modulating activities. The species is a rich source of specialized metabolites, mostly alkaloids and flavonoids. To date, genomic information, biosynthesis, and regulation of flavonoids remain unknown in this woody plant. As part of a larger ongoing research goal to better understand specialized metabolism in plants inhabiting the harsh conditions of the Caatinga, the present study focused on this important class of bioactive phenolics. Leaves and seeds of plants growing in their natural habitat had their metabolic and proteomic profiles analyzed and integrated with transcriptome data. As a result, 96 metabolites (including 43 flavonoids) were annotated. Transcripts of the flavonoid pathway totaled 27, of which EvCHI, EvCHR, EvCHS, EvCYP75A and EvCYP75B1 were identified as putative main targets for modulating the accumulation of these metabolites. The highest correspondence of mRNA vs. protein was observed in the differentially expressed transcripts. In addition, 394 candidate transcripts encoding for transcription factors distributed among the bHLH, ERF, and MYB families were annotated. Based on interaction network analyses, several putative genes of the flavonoid pathway and transcription factors were related, particularly TFs of the MYB family. Expression patterns of transcripts involved in flavonoid biosynthesis and those involved in responses to biotic and abiotic stresses were discussed in detail. Overall, these findings provide a base for the understanding of molecular and metabolic responses in this medicinally important species. Moreover, the identification of key regulatory targets for future studies aiming at bioactive metabolite production will be facilitated.

Time-related multivariate strategy for the comprehensive evaluation of microbial chemical data.

INTRODUCTION: In microbial metabolomics, the use of multivariate data analysis (MDVA) has not been comprehensively explored regarding the different techniques available and the information that each gives about the metabolome. To overcome these limitations, here we show the use of Fusarium oxysporum cultured in the presence of exogenous alkaloids as a model system to demonstrate a comprehensive strategy for metabolic profiling. MATHERIALS AND METHODS: F. oxysporum was harvested on different days of incubation after alkaloidal addition, and the chemical profiles were compared using LC-MS data and MDVA. We show significant innovation to evaluate the chemical production of microbes during their life cycle by utilizing the full capabilities of Partial Least Square (PLS) with microbial-specific modeling that considers incubation days, media culture availability, and growth rate in solid media. RESULTS AND DISCUSSCION: Results showed that the treatment of the Y-data and the use of both PLS regression and discrimination (PLSr and PLS-DA) inferred complemental chemical information. PLSr revealed the metabolites that are produced/consumed during fungal growth, whereas PLS-DA focused on metabolites that are only consumed/produced at a specific period. Both regression and classificatory analysis were equally important to identify compounds that are regulated and/or selectively produced as a response to the presence of the alkaloids. Lastly, we report the annotation of analogs from the piperidine alkaloids biotransformed by F. oxysporum as a defense response to the toxic plant metabolites. These molecules do not show the antimicrobial potential of their precursors in the fungal extracts and were rapidly produced and consumed within 4 days of microbial growth.

Combination of GC-MS Molecular Networking and Larvicidal Effect against Aedes aegypti for the Discovery of Bioactive Substances in Commercial Essential Oils.

Dengue is a neglected disease, present mainly in tropical countries, with more than 5.2 million cases reported in 2019. Vector control remains the most effective protective measure against dengue and other arboviruses. Synthetic insecticides based on organophosphates, pyrethroids, carbamates, neonicotinoids and oxadiazines are unattractive due to their high degree of toxicity to humans, animals and the environment. Conversely, natural-product-based larvicides/insecticides, such as essential oils, present high efficiency, low environmental toxicity and can be easily scaled up for industrial processes. However, essential oils are highly complex and require modern analytical and computational approaches to streamline the identification of bioactive substances. This study combined the GC-MS spectral similarity network approach with larvicidal assays as a new strategy for the discovery of potential bioactive substances in complex biological samples, enabling the systematic and simultaneous annotation of substances in 20 essential oils through LC50 larvicidal assays. This strategy allowed rapid intuitive discovery of distribution patterns between families and metabolic classes in clusters, and the prediction of larvicidal properties of acyclic monoterpene derivatives, including citral, neral, citronellal and citronellol, and their acetate forms (LC50 < 50 µg/mL).

Erythrina velutina Willd. alkaloids: Piecing biosynthesis together from transcriptome analysis and metabolite profiling of seeds and leaves.

Introduction: Natural products of pharmaceutical interest often do not reach the drug market due to the associated low yields and difficult extraction. Knowledge of biosynthetic pathways is a key element in the development of biotechnological strategies for plant specialized metabolite production. Erythrina species are mainly used as central nervous system depressants in folk medicine and are important sources of bioactive tetracyclic benzylisoquinoline alkaloids (BIAs), which can act on several pathology-related biological targets. Objectives: In this sense, in an unprecedented approach used with a non-model Fabaceae species grown in its unique arid natural habitat, a combined transcriptome and metabolome analyses (seeds and leaves) is presented. Methods: The Next Generation Sequencing-based transcriptome (de novo RNA sequencing) was carried out in a NextSeq 500 platform. Regarding metabolite profiling, the High-resolution Liquid Chromatography was coupled to DAD and a micrOTOF-QII mass spectrometer by using electrospray ionization (ESI) and Time of Flight (TOF) analyzer. The tandem MS/MS data were processed and analyzed through Molecular Networking approach. Results: This detailed macro and micromolecular approach applied to seeds and leaves of E. velutina revealed 42 alkaloids, several of them unique. Based on the combined evidence, 24 gene candidates were put together in a putative pathway leading to the singular alkaloid diversity of this species. Conclusion: Overall, these results could contribute by indicating potential biotechnological targets for modulation of erythrina alkaloids biosynthesis as well as improve molecular databases with omic data from a non-model medicinal plant, and reveal an interesting chemical diversity of Erythrina BIA harvested in Caatinga.

Soya agricultural waste as a rich source of isoflavones.

Soybeans are among the world's major crops responsible for food and biodiesel production, as well as a major source of isoflavones - a class of high value-added bioactive compounds. As estimated 460 million tonnes of soya residues (branches, leaves, roots, and pods) will be produced in the 2018/2019 harvest, and 20-40% of this waste must be removed from the field to ensure soil quality and minimize environmental impacts. This work investigated the potential occurrence and content of isoflavones in soya agricultural waste collected directly from the ground after mechanically harvesting. We also assessed the extraction performances of ethanol and acetone for these materials as an alternative to acetonitrile, a problematic solvent from an environmental point of view. Considerable amounts of isoflavones were found in soya agricultural waste collected directly from the ground when compared to soybeans (2.71 ± 0.27, 0.57 ± 0.1, 0.30 ± 0.05 and 2.09 ± 0.24 kg of isoflavones/tonne of leaves, branches, pods, and soybeans, respectively). The greener ethanol and acetone performed well for a broad range of compounds. This is an example in which appreciable amounts of high value-added compounds are wasted. Since isoflavones are considered phytoestrogens, their recovery from part of this waste might avoid potential contamination of soil and groundwater.

Fragmentation study of clerodane diterpenes from Casearia species by tandem mass spectrometry (quadrupole time-of-flight and ion trap).

RATIONALE: Clerodane-type diterpenes from Casearia species show important pharmacological activites such as antitumor, antimicrobial and anti-inflamatory. There are several mass spectrometry (MS)-based methods for identification of diterpenes; however, there is still a lack of MS procedures capable of providing characteristic fragmentation pathways for a rapid and unambiguous elucidation of casearin-like compounds. METHODS: Casearin-like compounds were investigated by electrospray ionization tandem mass spectrometry (ESI-MS/MS). The fragmentation studies were carried out by tandem mass spectrometry in space (quadrupole time-of-flight (QTOF)) using different collision energies and also by tandem mass spectrometry in time (QIT) by selective isolation of product ions. RESULTS: Casearin-like compounds presented a predominance of sodium- and potassium-cationized precursor ions. Both QIT and QTOF techniques provided sequential neutral losses of esters related to the R1 to R5 substituents linked to the nucleus of the clerodane diterpenes. The fragmentation pathway is initiated with a cleavage of the ester moieties R2 followed by the elimination of the ester groups R3 , both losing neutral carboxylic acids. Using QIT, it was also possible to observe the cleavage of the ester groups R1 or R5 by MS4 experiments. CONCLUSIONS: Through a rational analysis of the fragmentation mechanisms of Casearia diterpenes it was possible to suggest an annotation strategy based on the sequential cleavages of the ester groups related to the R2 , R3 and R5 substituents. These results will assist studies of the dereplication and metabolomics involving casearin-like compounds present in complex extracts of Casearia species.

Plant Metabolomics Using NMR Spectroscopy.

The major goal in plant metabolomics is to study complex extracts for the purposes of metabolic exploration and natural products discovery. To achieve this goal, plant metabolomics relies on accurate and selective acquisition of all possible chemical information, which includes maximization of the number of detected metabolites and their correct molecular assignment. Nuclear magnetic resonance (NMR) spectroscopy has been recognized as a powerful platform for obtaining the metabolite profiles of plant extracts. In this chapter, we provide a workflow for targeted and untargeted metabolite profiling of plant extracts using both 1D and 2D NMR methods. The protocol includes sample preparation, instrument operation, data processing, multivariate analysis, biomarker elucidation, and metabolite quantitation. It also addresses the annotation of plant metabolite peaks considering NMR's capabilities to cover a broad range of metabolites and elucidate structures for unknown compounds.

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.

Integrating Molecular Network and Culture Media Variation to Explore the Production of Bioactive Metabolites by Vibrio diabolicus A1SM3.

Vibrio diabolicus A1SM3 strain was isolated from a sediment sample from Manaure Solar Saltern in La Guajira and the produced crude extracts have shown antibacterial activity against methicillin-resistant Staphylococcus aureus and cytotoxic activity against human lung cell line. Thus, the aim of this research was to identify the main compound responsible for the biological activity observed and to systematically study how each carbon and nitrogen source in the growth media, and variation of the salinity, affect its production. For the characterization of the bioactive metabolites, 15 fractions obtained from Vibrio diabolicus A1SM3 crude extract were analyzed by HPLC-MS/MS and their activity was established. The bioactive fractions were dereplicated with Antibase and Marinlit databases, which combined with nuclear magnetic resonance (NMR) spectra and fragmentation by MS/MS, led to the identification of 2,2-di(3-indolyl)-3-indolone (isotrisindoline), an indole-derivative antibiotic, previously isolated from marine organisms. The influence of the variations of the culture media in isotrisindoline production was established by molecular network and MZmine showing that the media containing starch and peptone at 7% NaCl was the best culture media to produce it. Also, polyhydroxybutyrates (PHB) identification was established by MS/MS mainly in casamino acids media, contributing to the first report on PHB production by this strain.

Improvement of bioactive metabolite production in microbial cultures-A systems approach by OSMAC and deconvolution-based 1 HNMR quantification.

Traditionally, the screening of metabolites in microbial matrices is performed by monocultures. Nonetheless, the absence of biotic and abiotic interactions generally observed in nature still limit the chemical diversity and leads to "poorer" chemical profiles. Nowadays, several methods have been developed to determine the conditions under which cryptic genes are activated, in an attempt to induce these silenced biosynthetic pathways. Among those, the one strain, many compounds (OSMAC) strategy has been applied to enhance metabolic production by a systematic variation of growth parameters. The complexity of the chemical profiles from OSMAC experiments has required increasingly robust and accurate techniques. In this sense, deconvolution-based 1 HNMR quantification have emerged as a promising methodology to decrease complexity and provide a comprehensive perspective for metabolomics studies. Our present work shows an integrated strategy for the increased production and rapid quantification of compounds from microbial sources. Specifically, an OSMAC design of experiments (DoE) was used to optimize the microbial production of bioactive fusaric acid, cytochalasin D and 3-nitropropionic acid, and Global Spectral Deconvolution (GSD)-based 1 HNMR quantification was carried out for their measurement. The results showed that OSMAC increased the production of the metabolites by up to 33% and that GSD was able to extract accurate NMR integrals even in heavily coalescence spectral regions. Moreover, GSD-1 HNMR quantification was reproducible for all species and exhibited validated results that were more selective and accurate than comparative methods. Overall, this strategy up-regulated important metabolites using a reduced number of experiments and provided fast analyte monitor directly in raw extracts.

Leishmanicidal Effects of Piperlongumine (Piplartine) and Its Putative Metabolites.

Piperlongumine is an amide alkaloid found in Piperaceae species that shows a broad spectrum of biological properties, including antitumor and antiparasitic activities. Herein, the leishmanicidal effect of piperlongumine and its derivatives produced by a biomimetic model using metalloporphyrins was investigated. The results showed that IC50 values of piperlongumine in promastigote forms of Leishmania infantum and Leishmania amazonensis were 7.9 and 3.3 µM, respectively. The IC50 value of piperlongumine in the intracellular amastigote form of L. amazonensis was 0.4 µM, with a selectivity index of 25. The piperlongumine biomimetic derivatives, Ma and Mb, also showed leishmanicidal effects. We also carried out an in vitro metabolic degradation study showing that Ma is the most stable piperlongumine derivative in rat liver microsome incubations. The results presented here indicate that piperlongumine is a potential leishmanicidal candidate and support the biomimetic approach for development of new antileishmanial derivatives.

NuBBEDB: an updated database to uncover chemical and biological information from Brazilian biodiversity.

The intrinsic value of biodiversity extends beyond species diversity, genetic heritage, ecosystem variability and ecological services, such as climate regulation, water quality, nutrient cycling and the provision of reproductive habitats it is also an inexhaustible source of molecules and products beneficial to human well-being. To uncover the chemistry of Brazilian natural products, the Nuclei of Bioassays, Ecophysiology and Biosynthesis of Natural Products Database (NuBBEDB) was created as the first natural product library from Brazilian biodiversity. Since its launch in 2013, the NuBBEDB has proven to be an important resource for new drug design and dereplication studies. Consequently, continuous efforts have been made to expand its contents and include a greater diversity of natural sources to establish it as a comprehensive compendium of available biogeochemical information about Brazilian biodiversity. The content in the NuBBEDB is freely accessible online (https://nubbe.iq.unesp.br/portal/nubbedb.html) and provides validated multidisciplinary information, chemical descriptors, species sources, geographic locations, spectroscopic data (NMR) and pharmacological properties. Herein, we report the latest advancements concerning the interface, content and functionality of the NuBBEDB. We also present a preliminary study on the current profile of the compounds present in Brazilian territory.

In Vitro Metabolism of Artepillin C by Rat and Human Liver Microsomes.

Artepillin C, a natural product present in the Brazilian green propolis, has several biological properties. Among these properties, the antitumor action of this product is noteworthy and makes it a promising drug candidate for the treatment of several types of cancer. This paper describes the in vitro metabolism of Artepillin C in rat and human liver microsomes. The rat model suggested a sigmoidal profile for the metabolism, adapted to the Hill's kinetic model. The enzymatic kinetic parameters were as follows: maximal velocity = 0.757 ± 0.021 µmol/mg protein/min, Hill coefficient = 10.90 ± 2.80, and substrate concentration at which half-maximal velocity of a Hill enzyme is achieved = 33.35 ± 0.55 µM. Based on these results, the calculated in vitro intrinsic clearance for Artepillin C was 16.63 ± 1.52 µL/min/mg protein. The in vitro metabolism assay conducted on the human model did not fit any enzymatic kinetic model. Two novel metabolites were formed in both mammal microsomal models and their chemical structures were elucidated for the first time. The main human cytochrome P450 isoforms involved in Artepillin C metabolism had been identified, and the results suggest a majority contribution of CYP2E1 and CYP2C9 in the formation of the two metabolites.

Dereplication of Natural Products Using GC-TOF Mass Spectrometry: Improved Metabolite Identification by Spectral Deconvolution Ratio Analysis.

Dereplication based on hyphenated techniques has been extensively applied in plant metabolomics, thereby avoiding re-isolation of known natural products. However, due to the complex nature of biological samples and their large concentration range, dereplication requires the use of chemometric tools to comprehensively extract information from the acquired data. In this work we developed a reliable GC-MS-based method for the identification of non-targeted plant metabolites by combining the Ratio Analysis of Mass Spectrometry deconvolution tool (RAMSY) with Automated Mass Spectral Deconvolution and Identification System software (AMDIS). Plants species from Solanaceae, Chrysobalanaceae and Euphorbiaceae were selected as model systems due to their molecular diversity, ethnopharmacological potential, and economical value. The samples were analyzed by GC-MS after methoximation and silylation reactions. Dereplication was initiated with the use of a factorial design of experiments to determine the best AMDIS configuration for each sample, considering linear retention indices and mass spectral data. A heuristic factor (CDF, compound detection factor) was developed and applied to the AMDIS results in order to decrease the false-positive rates. Despite the enhancement in deconvolution and peak identification, the empirical AMDIS method was not able to fully deconvolute all GC-peaks, leading to low MF values and/or missing metabolites. RAMSY was applied as a complementary deconvolution method to AMDIS to peaks exhibiting substantial overlap, resulting in recovery of low-intensity co-eluted ions. The results from this combination of optimized AMDIS with RAMSY attested to the ability of this approach as an improved dereplication method for complex biological samples such as plant extracts.