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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.

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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.

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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.

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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.

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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.

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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).

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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.

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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.

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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.

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