Dr. Denise M . Selegato | European Molecular Biology Laboratory (original) (raw)

Papers by Dr. Denise M . Selegato

Metabolomics, 2022

Introduction In microbial metabolomics, the use of multivariate data analysis (MDVA) has not been... more 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 microbialspecific 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.

Metabolomics has played a central role in various areas of plant sciences, offering new perspecti... more Metabolomics has played a central role in various areas of plant sciences, offering new perspectives for the advancement of agriculture, drug discovery, chemical ecology and taxonomy. Plant metabolomics (identification and quantification) aims to understand the relationship between biological systems and genetic, pathological and or environmental stimuli in terms of differential expression of the metabolism. Owing to the unique challenges, such studies require multidisciplinary skills involving biology, chemistry, statistics, and computer science for the extraction and complete understanding of information. In this sense, this review summarizes the main procedures that involve the steps of plant metabolomic study (design of experiments, sample preparation, analytical methods and data analysis), providing a comprehensive overview, showing the main challenges and limitations and possible solutions for the different approaches used.

Methods in molecular biology, 2019

The major goal in plant metabolomics is to study complex extracts for the purposes of metabolic e... more 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.

Journal of Advanced Research, 2021

Abstract Introduction Natural products of pharmaceutical interest often do not reach the drug mar... more Abstract 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. The scarce studies regarding non-model plants impair advances in this field. Erythrina spp. are mainly used as central nervous system depressants in folk medicine and are important sources of bioactive tetracyclic benzylisoquinoline alkaloids, which can act on several pathology-related biological targets. Objective: Herein the purpose is to employ combined transcriptome and metabolome analyses (seeds and leaves) of a non-model medicinal Fabaceae species grown in its unique arid natural habitat. The study tries to propose a putative biosynthetic pathway for the bioactive alkaloids by using an omic integrated approach. Methods: The Next Generation Sequencing-based transcriptome (de novo RNA sequencing) was carried out in a Illumina NextSeq 500 platform. Regarding the targeted metabolite profiling, Nuclear Magnetic Resonance and the High-Performance Liquid Chromatography coupled to a micrOTOF-QII, High Resolution Mass Spectrometer, were used. Results: This detailed macro and micromolecular approach applied to seeds and leaves of E. velutina revealed 42 alkaloids by metabolome tools. 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: These results contribute by indicating potential biotechnological targets erythrina alkaloids biosynthesis as well as to improve molecular databases with omic data from a non-model medicinal plant. Furthermore, they reveal an interesting chemical diversity in Erythrina velutina harvested in Caatinga. Last, but not least, this data may also contribute to tap Brazilian biodiversity in a rational and sustainable fashion, promoting adequate public policies for preservation and protection of sensitive areas within the Caatinga.

Magnetic Resonance in Chemistry, 2019

Traditionally, the screening of metabolites in microbial matrices is performed by monocultures. N... more 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 1HNMR 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 1HNMR 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‐1HNMR 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.

Molecules, 2019

Biodiversity is key for maintenance of life and source of richness. Nevertheless, concepts such a... more Biodiversity is key for maintenance of life and source of richness. Nevertheless, concepts such as phenotype expression are also pivotal to understand how chemical diversity varies in a living organism. Sesquiterpene pyridine alkaloids (SPAs) and quinonemethide triterpenes (QMTs) accumulate in root bark of Celastraceae plants. However, despite their known bioactive traits, there is still a lack of evidence regarding their ecological functions. Our present contribution combines analytical tools to study clones and individuals of Maytenus ilicifolia (Celastraceae) kept alive in an ex situ collection and determine whether or not these two major biosynthetic pathways could be switched on simultaneously. The relative concentration of the QMTs maytenin (1) and pristimerin (2), and the SPA aquifoliunin E1 (3) were tracked in raw extracts by HPLC-DAD and 1H-NMR. Hierarchical Clustering Analysis (HCA) was used to group individuals according their ability to accumulate these metabolites. Semi...

Journal of the Brazilian Chemical Society, 2016

Frontiers in Molecular Biosciences, 2016

Journal of the Brazilian Chemical Society, 2016

ChemPhysChem, 2020

Conformational variability and heterogeneity are crucial determinants of the function of biologic... more Conformational variability and heterogeneity are crucial determinants of the function of biological macromolecules. The possibility of accessing this information experimentally suffers from severe under-determination of the problem, since there are a few experimental observables to be accounted for by a (potentially) infinite number of available conformational states. Several computational methods have been proposed over the years in order to circumvent this theoretically insurmountable obstacle. A large share of these strategies is based on reweighting an initial conformational ensemble which arises from, for example, molecular simulations of different qualities and levels of theory. In this work, we compare the outcome of three reweighting approaches based on radically different views of the conformational heterogeneity problem, namely Maximum Entropy, Maximum Parsimony and Maximum Occurrence, and we do so using the same experimental data. In this comparison, we find both expected as well as unexpected similarities.

Journal of Advanced Research, 2021

Introduction: Natural products of pharmaceutical interest often do not reach the drug market due ... more 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. The scarce studies regarding non-model plants impair advances in this field. Erythrina spp. are mainly used as central nervous system depressants in folk medicine and are important sources of bioactive tetracyclic benzylisoquinoline alkaloids, which can act on several pathology-related biological targets. Objective: Herein the purpose is to employ combined transcriptome and metabolome analyses (seeds and leaves) of a non-model medicinal Fabaceae species grown in its unique arid natural habitat. The study tries to propose a putative biosynthetic pathway for the bioactive alkaloids by using an omic integrated approach. Methods: The Next Generation Sequencing-based transcriptome (de novo RNA sequencing) was carried out in a Illumina NextSeq 500 platform. Regarding the targeted metabolite profiling, Nuclear Magnetic Resonance and the High-Performance Liquid Chromatography coupled to a micrOTOF-QII, High Resolution Mass Spectrometer, were used. Results: This detailed macro and micromolecular approach applied to seeds and leaves of E. velutina revealed 42 alkaloids by metabolome tools. 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: These results contribute by indicating potential biotechnological targets Erythrina alkaloids biosynthesis as well as to improve molecular databases with omic data from a non-model medicinal plant. Furthermore, they reveal an interesting chemical diversity in Erythrina velutina harvested in Caatinga. Last, but not least, this data may also contribute to tap Brazilian biodiversity in a rational and sustainable fashion, promoting adequate public policies for preservation and protection of sensitive areas within the Caatinga.

Quìmica Nova, 2020

PLANT METABOLOMICS: METHODS AND CHALLENGES. Metabolomics has played a central role in various are... more PLANT METABOLOMICS: METHODS AND CHALLENGES. Metabolomics has played a central role in various areas of plant sciences, offering new perspectives for the advancement of agriculture, drug discovery, chemical ecology and taxonomy. Plant metabolomics (identification and quantification) aims to understand the relationship between biological systems and genetic, pathological and or environmental stimuli in terms of differential expression of the metabolism. Owing to the unique challenges, such studies require multidisciplinary skills involving biology, chemistry, statistics, and computer science for the extraction and complete understanding of information. In this sense, this review summarizes the main procedures that involve the steps of plant metabolomic study (design of experiments, sample preparation, analytical methods and data analysis), providing a comprehensive overview, showing the main challenges and limitations and possible solutions for the different approaches used.

Molecules, 2019

Biodiversity is key for maintenance of life and source of richness. Nevertheless, concepts such a... more Biodiversity is key for maintenance of life and source of richness. Nevertheless, concepts such as phenotype expression are also pivotal to understand how chemical diversity varies in a living organism. Sesquiterpene pyridine alkaloids (SPAs) and quinonemethide triterpenes (QMTs) accumulate in root bark of Celastraceae plants. However, despite their known bioactive traits, there is still a lack of evidence regarding their ecological functions. Our present contribution combines analytical tools to study clones and individuals of Maytenus ilicifolia (Celastraceae) kept alive in an ex situ collection and determine whether or not these two major biosynthetic pathways could be switched on simultaneously. The relative concentration of the QMTs maytenin (1) and pristimerin (2), and the SPA aquifoliunin E1 (3) were tracked in raw extracts by HPLC-DAD and 1 H-NMR. Hierarchical Clustering Analysis (HCA) was used to group individuals according their ability to accumulate these metabolites. Semi-quantitative analysis showed an extensive occurrence of QMT in most individuals, whereas SPA was only detected in minor abundance in five samples. Contrary to QMTs, SPAs did not accumulate extensively, contradicting the hypothesis of two different biosynthetic pathways operating simultaneously. Moreover, the production of QMT varied significantly among samples of the same ex situ collection, suggesting that the terpene contents in root bark extracts were not dependent on abiotic effects. HCA results showed that QMT occurrence was high regardless of the plant age. This data disproves the hypothesis that QMT biosynthesis was age-dependent. Furthermore, clustering analysis did not group clones nor same-age samples together, which might reinforce the hypothesis over gene regulation of the biosynthesis pathways. Indeed, plants from the ex situ collection produced bioactive compounds in a singular manner, which postulates that rhizosphere environment could offer ecological triggers for phenotypical plasticity.

Magnetic Resonance in Chemistry, 2019

Traditionally, the screening of metabolites in microbial matrices is performed by monocultures. N... more 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 1HNMR 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 1HNMR 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‐1HNMR 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.

Metabolomics, 2019

Introduction: The increase in multidrug resistance and lack of efficacy in malaria therapy has pr... more Introduction: The increase in multidrug resistance and lack of efficacy in malaria therapy has propelled the urgent discovery of new antiplasmodial drugs, reviving the screening of secondary metabolites from traditional medicine. In plant metabo-lomics, NMR-based strategies are considered a golden method providing both a holistic view of the chemical profiles and a correlation between the metabolome and bioactivity, becoming a corner stone of drug development from natural products.
Objective: Create a multivariate model to identify antiplasmodial metabolites from 1 H NMR data of two African medicinal plants, Keetia leucantha and K. venosa.
Methods: The extracts of twigs and leaves of Keetia species were measured by 1HNMR and the spectra were submitted to orthogonal partial least squares (OPLS) for antiplasmodial correlation.
Results: Unsupervised 1 H NMR analysis showed that the effect of tissues was higher than species and that triterpenoids signals were more associated to Keetia twigs than leaves. OPLS-DA based on Keetia species correlated triterpene signals to K. leucantha, exhibiting a higher concentration of triterpenoids and phenylpropanoid-conjugated triterpenes than K. venosa. In vitro antiplasmodial correlation by OPLS, validated for all Keetia samples, revealed that phenylpropanoid-conjugated triterpenes were highly correlated to the bioactivity, while the acyclic squalene was found as the major metabolite in low bioactivity samples.
Conclusion: NMR-based metabolomics combined with supervised multivariate data analysis is a powerful strategy for the identification of bioactive metabolites in plant extracts. Moreover, combination of statistical total correlation spectroscopy with 2D NMR allowed a detailed analysis of different triterpenes, overcoming the challenge posed by their structure similarity and coalescence in the aliphatic region.

Frontiers in Molecular Biosciences, 2016

Dereplication based on hyphenated techniques has been extensively applied in plant metabolomics, ... more 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.

Journal of the Brazilian Chemical Society, 2017

Senna spectabilis (syn Cassia spectabilis) is one of the most important species within the Fabace... more Senna spectabilis (syn Cassia spectabilis) is one of the most important species within the Fabaceae family, natively found in Central and South America, as well as parts of Asia and Africa. Due to the extensive geographical distribution, this fast-growing tree produces a wide variety of bioactive secondary metabolites, being of special interest for chemical and pharmacological studies. Phytochemical investigations have shown that S. spectabilis produces over 40 constituents from different biosynthetic pathways, including piperidine alkaloids, pentacyclic terpenoids and anthraquinones, displaying antiproliferative, antitumoral and antifungal activities. Moreover, studies have also been conducted to identify endophytic and rizhospheric microorganisms associated to S. spectabilis and their chemical composition, enabling further elucidation of cadinane sesquiterpenoids, cytochalasins, depsipeptides and dibenzopirones. This review aims to provide an updated summary of the main features of S. spectabilis, compiling all currently available information on the chemical and pharmacological composition of its parts and its associated microorganisms.

Metabolomics, 2022

Introduction In microbial metabolomics, the use of multivariate data analysis (MDVA) has not been... more 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 microbialspecific 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.

Metabolomics has played a central role in various areas of plant sciences, offering new perspecti... more Metabolomics has played a central role in various areas of plant sciences, offering new perspectives for the advancement of agriculture, drug discovery, chemical ecology and taxonomy. Plant metabolomics (identification and quantification) aims to understand the relationship between biological systems and genetic, pathological and or environmental stimuli in terms of differential expression of the metabolism. Owing to the unique challenges, such studies require multidisciplinary skills involving biology, chemistry, statistics, and computer science for the extraction and complete understanding of information. In this sense, this review summarizes the main procedures that involve the steps of plant metabolomic study (design of experiments, sample preparation, analytical methods and data analysis), providing a comprehensive overview, showing the main challenges and limitations and possible solutions for the different approaches used.

Methods in molecular biology, 2019

The major goal in plant metabolomics is to study complex extracts for the purposes of metabolic e... more 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.

Journal of Advanced Research, 2021

Abstract Introduction Natural products of pharmaceutical interest often do not reach the drug mar... more Abstract 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. The scarce studies regarding non-model plants impair advances in this field. Erythrina spp. are mainly used as central nervous system depressants in folk medicine and are important sources of bioactive tetracyclic benzylisoquinoline alkaloids, which can act on several pathology-related biological targets. Objective: Herein the purpose is to employ combined transcriptome and metabolome analyses (seeds and leaves) of a non-model medicinal Fabaceae species grown in its unique arid natural habitat. The study tries to propose a putative biosynthetic pathway for the bioactive alkaloids by using an omic integrated approach. Methods: The Next Generation Sequencing-based transcriptome (de novo RNA sequencing) was carried out in a Illumina NextSeq 500 platform. Regarding the targeted metabolite profiling, Nuclear Magnetic Resonance and the High-Performance Liquid Chromatography coupled to a micrOTOF-QII, High Resolution Mass Spectrometer, were used. Results: This detailed macro and micromolecular approach applied to seeds and leaves of E. velutina revealed 42 alkaloids by metabolome tools. 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: These results contribute by indicating potential biotechnological targets erythrina alkaloids biosynthesis as well as to improve molecular databases with omic data from a non-model medicinal plant. Furthermore, they reveal an interesting chemical diversity in Erythrina velutina harvested in Caatinga. Last, but not least, this data may also contribute to tap Brazilian biodiversity in a rational and sustainable fashion, promoting adequate public policies for preservation and protection of sensitive areas within the Caatinga.

Magnetic Resonance in Chemistry, 2019

Traditionally, the screening of metabolites in microbial matrices is performed by monocultures. N... more 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 1HNMR 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 1HNMR 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‐1HNMR 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.

Molecules, 2019

Biodiversity is key for maintenance of life and source of richness. Nevertheless, concepts such a... more Biodiversity is key for maintenance of life and source of richness. Nevertheless, concepts such as phenotype expression are also pivotal to understand how chemical diversity varies in a living organism. Sesquiterpene pyridine alkaloids (SPAs) and quinonemethide triterpenes (QMTs) accumulate in root bark of Celastraceae plants. However, despite their known bioactive traits, there is still a lack of evidence regarding their ecological functions. Our present contribution combines analytical tools to study clones and individuals of Maytenus ilicifolia (Celastraceae) kept alive in an ex situ collection and determine whether or not these two major biosynthetic pathways could be switched on simultaneously. The relative concentration of the QMTs maytenin (1) and pristimerin (2), and the SPA aquifoliunin E1 (3) were tracked in raw extracts by HPLC-DAD and 1H-NMR. Hierarchical Clustering Analysis (HCA) was used to group individuals according their ability to accumulate these metabolites. Semi...

Journal of the Brazilian Chemical Society, 2016

Frontiers in Molecular Biosciences, 2016

Journal of the Brazilian Chemical Society, 2016

ChemPhysChem, 2020

Conformational variability and heterogeneity are crucial determinants of the function of biologic... more Conformational variability and heterogeneity are crucial determinants of the function of biological macromolecules. The possibility of accessing this information experimentally suffers from severe under-determination of the problem, since there are a few experimental observables to be accounted for by a (potentially) infinite number of available conformational states. Several computational methods have been proposed over the years in order to circumvent this theoretically insurmountable obstacle. A large share of these strategies is based on reweighting an initial conformational ensemble which arises from, for example, molecular simulations of different qualities and levels of theory. In this work, we compare the outcome of three reweighting approaches based on radically different views of the conformational heterogeneity problem, namely Maximum Entropy, Maximum Parsimony and Maximum Occurrence, and we do so using the same experimental data. In this comparison, we find both expected as well as unexpected similarities.

Journal of Advanced Research, 2021

Introduction: Natural products of pharmaceutical interest often do not reach the drug market due ... more 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. The scarce studies regarding non-model plants impair advances in this field. Erythrina spp. are mainly used as central nervous system depressants in folk medicine and are important sources of bioactive tetracyclic benzylisoquinoline alkaloids, which can act on several pathology-related biological targets. Objective: Herein the purpose is to employ combined transcriptome and metabolome analyses (seeds and leaves) of a non-model medicinal Fabaceae species grown in its unique arid natural habitat. The study tries to propose a putative biosynthetic pathway for the bioactive alkaloids by using an omic integrated approach. Methods: The Next Generation Sequencing-based transcriptome (de novo RNA sequencing) was carried out in a Illumina NextSeq 500 platform. Regarding the targeted metabolite profiling, Nuclear Magnetic Resonance and the High-Performance Liquid Chromatography coupled to a micrOTOF-QII, High Resolution Mass Spectrometer, were used. Results: This detailed macro and micromolecular approach applied to seeds and leaves of E. velutina revealed 42 alkaloids by metabolome tools. 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: These results contribute by indicating potential biotechnological targets Erythrina alkaloids biosynthesis as well as to improve molecular databases with omic data from a non-model medicinal plant. Furthermore, they reveal an interesting chemical diversity in Erythrina velutina harvested in Caatinga. Last, but not least, this data may also contribute to tap Brazilian biodiversity in a rational and sustainable fashion, promoting adequate public policies for preservation and protection of sensitive areas within the Caatinga.

Quìmica Nova, 2020

PLANT METABOLOMICS: METHODS AND CHALLENGES. Metabolomics has played a central role in various are... more PLANT METABOLOMICS: METHODS AND CHALLENGES. Metabolomics has played a central role in various areas of plant sciences, offering new perspectives for the advancement of agriculture, drug discovery, chemical ecology and taxonomy. Plant metabolomics (identification and quantification) aims to understand the relationship between biological systems and genetic, pathological and or environmental stimuli in terms of differential expression of the metabolism. Owing to the unique challenges, such studies require multidisciplinary skills involving biology, chemistry, statistics, and computer science for the extraction and complete understanding of information. In this sense, this review summarizes the main procedures that involve the steps of plant metabolomic study (design of experiments, sample preparation, analytical methods and data analysis), providing a comprehensive overview, showing the main challenges and limitations and possible solutions for the different approaches used.

Molecules, 2019

Biodiversity is key for maintenance of life and source of richness. Nevertheless, concepts such a... more Biodiversity is key for maintenance of life and source of richness. Nevertheless, concepts such as phenotype expression are also pivotal to understand how chemical diversity varies in a living organism. Sesquiterpene pyridine alkaloids (SPAs) and quinonemethide triterpenes (QMTs) accumulate in root bark of Celastraceae plants. However, despite their known bioactive traits, there is still a lack of evidence regarding their ecological functions. Our present contribution combines analytical tools to study clones and individuals of Maytenus ilicifolia (Celastraceae) kept alive in an ex situ collection and determine whether or not these two major biosynthetic pathways could be switched on simultaneously. The relative concentration of the QMTs maytenin (1) and pristimerin (2), and the SPA aquifoliunin E1 (3) were tracked in raw extracts by HPLC-DAD and 1 H-NMR. Hierarchical Clustering Analysis (HCA) was used to group individuals according their ability to accumulate these metabolites. Semi-quantitative analysis showed an extensive occurrence of QMT in most individuals, whereas SPA was only detected in minor abundance in five samples. Contrary to QMTs, SPAs did not accumulate extensively, contradicting the hypothesis of two different biosynthetic pathways operating simultaneously. Moreover, the production of QMT varied significantly among samples of the same ex situ collection, suggesting that the terpene contents in root bark extracts were not dependent on abiotic effects. HCA results showed that QMT occurrence was high regardless of the plant age. This data disproves the hypothesis that QMT biosynthesis was age-dependent. Furthermore, clustering analysis did not group clones nor same-age samples together, which might reinforce the hypothesis over gene regulation of the biosynthesis pathways. Indeed, plants from the ex situ collection produced bioactive compounds in a singular manner, which postulates that rhizosphere environment could offer ecological triggers for phenotypical plasticity.

Magnetic Resonance in Chemistry, 2019

Traditionally, the screening of metabolites in microbial matrices is performed by monocultures. N... more 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 1HNMR 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 1HNMR 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‐1HNMR 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.

Metabolomics, 2019

Introduction: The increase in multidrug resistance and lack of efficacy in malaria therapy has pr... more Introduction: The increase in multidrug resistance and lack of efficacy in malaria therapy has propelled the urgent discovery of new antiplasmodial drugs, reviving the screening of secondary metabolites from traditional medicine. In plant metabo-lomics, NMR-based strategies are considered a golden method providing both a holistic view of the chemical profiles and a correlation between the metabolome and bioactivity, becoming a corner stone of drug development from natural products.
Objective: Create a multivariate model to identify antiplasmodial metabolites from 1 H NMR data of two African medicinal plants, Keetia leucantha and K. venosa.
Methods: The extracts of twigs and leaves of Keetia species were measured by 1HNMR and the spectra were submitted to orthogonal partial least squares (OPLS) for antiplasmodial correlation.
Results: Unsupervised 1 H NMR analysis showed that the effect of tissues was higher than species and that triterpenoids signals were more associated to Keetia twigs than leaves. OPLS-DA based on Keetia species correlated triterpene signals to K. leucantha, exhibiting a higher concentration of triterpenoids and phenylpropanoid-conjugated triterpenes than K. venosa. In vitro antiplasmodial correlation by OPLS, validated for all Keetia samples, revealed that phenylpropanoid-conjugated triterpenes were highly correlated to the bioactivity, while the acyclic squalene was found as the major metabolite in low bioactivity samples.
Conclusion: NMR-based metabolomics combined with supervised multivariate data analysis is a powerful strategy for the identification of bioactive metabolites in plant extracts. Moreover, combination of statistical total correlation spectroscopy with 2D NMR allowed a detailed analysis of different triterpenes, overcoming the challenge posed by their structure similarity and coalescence in the aliphatic region.

Frontiers in Molecular Biosciences, 2016

Dereplication based on hyphenated techniques has been extensively applied in plant metabolomics, ... more 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.

Journal of the Brazilian Chemical Society, 2017

Senna spectabilis (syn Cassia spectabilis) is one of the most important species within the Fabace... more Senna spectabilis (syn Cassia spectabilis) is one of the most important species within the Fabaceae family, natively found in Central and South America, as well as parts of Asia and Africa. Due to the extensive geographical distribution, this fast-growing tree produces a wide variety of bioactive secondary metabolites, being of special interest for chemical and pharmacological studies. Phytochemical investigations have shown that S. spectabilis produces over 40 constituents from different biosynthetic pathways, including piperidine alkaloids, pentacyclic terpenoids and anthraquinones, displaying antiproliferative, antitumoral and antifungal activities. Moreover, studies have also been conducted to identify endophytic and rizhospheric microorganisms associated to S. spectabilis and their chemical composition, enabling further elucidation of cadinane sesquiterpenoids, cytochalasins, depsipeptides and dibenzopirones. This review aims to provide an updated summary of the main features of S. spectabilis, compiling all currently available information on the chemical and pharmacological composition of its parts and its associated microorganisms.

NMR-Based Metabolomics, 2019

The major goal in plant metabolomics is to study complex extracts for the purposes of metabolic e... more 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) spec-troscopy 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.