Publications by authors named "Ricardo M Borges"

Specialized or secondary metabolites are small molecules of biological origin, often showing potent biological activities with applications in agriculture, engineering and medicine. Usually, the biosynthesis of these natural products is governed by sets of co-regulated and physically clustered genes known as biosynthetic gene clusters (BGCs). To share information about BGCs in a standardized and machine-readable way, the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard and repository was initiated in 2015.

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Article Synopsis
  • Robust annotation of compounds is essential in metabolomics, and the INADEQUATE NMR experiment is a powerful yet underused tool for structural elucidation due to the lack of community platforms integrating it with other NMR methods.
  • * PyINETA is introduced as an open-source platform that automates the use of INADEQUATE for structural analysis, integrates it with the C-resolved experiment (C-JRES), and maintains a transparent annotation pipeline.
  • * Evaluation of PyINETA in a mouse study demonstrated its capability to track the distribution of C-labeled amino acids across different tissues, revealing specific metabolite enrichment in organs like the liver and spleen.*
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Covering: 2010 to 2023Cyanobacterial natural products are a diverse group of molecules with promising biotechnological applications. This review examines the chemical diversity of 995 cyanobacterial metabolites reported from 2010 to 2023. A computational analysis using similarity networking was applied to visualize the chemical space and to compare the diversity of cyanobacterial metabolites among taxonomic orders and environmental sources.

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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.

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Article Synopsis
  • Chronic venous disease (CVD) is a significant global health issue that is often underdiagnosed and undertreated, requiring better medical management and understanding of its treatment options.
  • The review examines bioactive compounds from a specific genus, focusing on their therapeutic potential for CVD, particularly highlighting flavonoids and terpenes that possess anti-inflammatory, antioxidant, and veno-protective properties.
  • The innovative DBsimilarity method is introduced to analyze the structural similarities among these compounds, suggesting a rich source for developing novel therapies, while emphasizing the need for further research on safety and efficacy in CVD treatment.
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Annotating compounds with high confidence is a critical element in metabolomics. C-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.

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Article Synopsis
  • Understanding plant metabolites across the plant kingdom is challenging due to their vast diversity.
  • Researchers created the plantMASST reference database with data from 19,075 plant extracts, covering 246 botanical families, 1,469 genera, and 2,793 species.
  • This database enhances research on plant molecules, supporting drug discovery, biosynthesis, taxonomy, and ecology related to herbivore interactions.*
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In nature, the vast majority of sesquiterpenes are produced by type I mechanisms, and glycosylated sesquiterpenes are rare in actinobacteria. 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.

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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.

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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.

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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.

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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.

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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.

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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).

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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.

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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.

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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.

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Beneficial microorganisms for corals (BMCs) ameliorate environmental stress, but whether they can prevent mortality and the underlying host response mechanisms remains elusive. Here, we conducted omics analyses on the coral exposed to bleaching conditions in a long-term mesocosm experiment and inoculated with a selected BMC consortium or a saline solution placebo. All corals were affected by heat stress, but the observed "post-heat stress disorder" was mitigated by BMCs, signified by patterns of dimethylsulfoniopropionate degradation, lipid maintenance, and coral host transcriptional reprogramming of cellular restructuration, repair, stress protection, and immune genes, concomitant with a 40% survival rate increase and stable photosynthetic performance by the endosymbiotic algae.

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In the present study, sea urchin Sterechinus neumayeri tissues were used for the passive biomonitoring of toxic and trace elements at the Comandante Ferraz Station, Antarctica and compared to a pristine region (Botany). As, Ba, Br, Ca, Co, Cr, Fe, K, Na, Rb, Sc, Se and Zn concentrations were determined by instrumental neutron activation analysis (INAA), while toxic metals (Cd, Hg, Ni and Pb), and Cu were determined by atomic absorption spectrometry (GF-AAS). The findings were compared to other organisms commonly applied for biomonitoring purposes and to the sediment concentrations of each sampling region.

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Generating properly differentiated embryonic structures in vitro from pluripotent stem cells remains a challenge. Here we show that instruction of aggregates of mouse embryonic stem cells with an experimentally engineered morphogen signalling centre, that functions as an organizer, results in the development of embryo-like entities (embryoids). In situ hybridization, immunolabelling, cell tracking and transcriptomic analyses show that these embryoids form the three germ layers through a gastrulation process and that they exhibit a wide range of developmental structures, highly similar to neurula-stage mouse embryos.

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A primary goal of metabolomics studies is to fully characterize the small-molecule composition of complex biological and environmental samples. However, despite advances in analytical technologies over the past two decades, the majority of small molecules in complex samples are not readily identifiable due to the immense structural and chemical diversity present within the metabolome. Current gold-standard identification methods rely on reference libraries built using authentic chemical materials ("standards"), which are not available for most molecules.

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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.

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Fermented aqueous extracts of L. are widely used for cancer treatment in complementary medicine. The high molecular weight compounds viscotoxins and lectins are considered to be the main active substances in the extracts.

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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.

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