New Dereplication Method Applied to NMR-Based Metabolomics on Different<i>Fusarium</i>Species Isolated from Rhizosphere of<i>Senna spectabilis</i>

Selegato, Denise Medeiros; Freire, Rafael Teixeira; Tannús, Alberto; Castro‐Gamboa, Ian

doi:10.5935/0103-5053.20160139

Cited by 6 publications

(5 citation statements)

References 20 publications

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“…Furthermore, for samples from the incubation days between 8 and 12, there was also a pronounced increase in intensity of bin 13. This bin ( m/z 806.3995 [M + Na] + and m/z 784.4146 [M + H] + ; t R 19.85 min) corresponds to a known Fusarium metabolite named beauvericin (CAS number 26048–05-5), which is a depsipeptide encountered in many strains of Fusarium and already reported for this strain of F. oxysporum in previous works (Selegato et al, 2016 ) . Although this mycotoxin was produced regardless of the presence of the alkaloids, its production was increased in the presence of (–)-cassine and (–)-spectaline, showing positive modulation during stress.…”

Section: Resultssupporting

confidence: 56%

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

et al. 2022

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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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Section: Resultssupporting

confidence: 56%

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

et al. 2022

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“…To assess the ability of MS/MS Molecular Networking to detect beauvericin analogues and distinguish their fragmentation patterns in different collision energies (25, 50 and 70 eV), a fragmentation study was established by the untargeted tandem mass spectrometry of F. oxysporum extract based on the fast data-independent acquisition (DIA) function of QToF mass spectrometer. This Fusarium extract has been previously reported to produce beauvericin ( Selegato et al, 2016 ) and the DIA setting allowed the automatic analysis and detection of known and unknown analogs that range in structural features and concentration in these fungal cultures.…”

Section: Resultsmentioning

confidence: 99%

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

Selegato,

Zanatta,

Pilon

et al. 2023

Front. Mol. Biosci.

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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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“…An example can be given by the development of a new computational method that analyses 1 H NMR data from F. solani and F. oxysporum isolated from Senna spectabilis's rhizosphere through principal component analysis (PCA), allowing compound dereplication, even in highly similar profiles. As a result, the method, associated with other NMR experiments and information from an in-house Fusarium's metabolite library, was able to distinguish different mycotoxins produced by both fungi, identifying fusaric acid and beauvericin for F. oxysporum and the depsipeptide HA23 from Fusarium solani (Selegato et al, 2016).…”

Section: Computational Toolsmentioning

confidence: 99%

Twenty-five years of natural products research in NuBBE

Mannochio-Russo,

Pires dos Santos,

Bueno

et al. 2023

Front. Nat. Prod.

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The richness of Brazilian biodiversity translates into a valuable collection of molecules with biological properties that range from ecological functions to pharmacological properties. For over 25 years, the Nucleus of Bioassays, Biosynthesis, and Ecophysiology of Natural Products (NuBBE) has conducted extensive investigations into the chemical entities of numerous plant and microorganism species, resulting in the discovery of over a thousand natural compounds spanning various chemical classes (such as shikimate derivatives, phenylpropanoids, terpenoids, alkaloids, and peptides). The research goals within the natural products field encompass phytochemical studies, investigations of endophytic fungi and marine organisms, biosynthetic studies, medicinal chemistry, and the development of innovative methodologies. This comprehensive review article aims to offer valuable insights into the multifaceted research endeavors conducted in NuBBE. In this way, accomplishments, perspectives, and opportunities for advancing natural products research in Brazil are highlighted, seeking to inspire and motivate other research groups in the field of natural products–especially those located in emerging countries with rich biodiversity.

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New Dereplication Method Applied to NMR-Based Metabolomics on DifferentFusariumSpecies Isolated from Rhizosphere ofSenna spectabilis

Cited by 6 publications

References 20 publications

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

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

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

Twenty-five years of natural products research in NuBBE

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