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      Diving into the Molecular Diversity of Aplysina cavernicola’s Exometabolites: Contribution of Bromo-Spiroisoxazoline Alkaloids

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          Abstract

          Sponges are prolific producers of specialized metabolites with unique structural scaffolds. Their chemical diversity has always inspired natural product chemists working in drug discovery. As part of their metabolic filter-feeding activities, sponges are known to release molecules, possibly including their specialized metabolites. These released “ Exo- Metabolites” (EMs) may be considered as new chemical reservoirs that could be collected from the water column while preserving marine biodiversity. The present work aims to determine the proportion and diversity of specialized EMs released by the sponge Aplysina cavernicola (Vacelet 1959). This Mediterranean sponge produces bromo-spiroisoxazoline alkaloids that are widely distributed in the Aplysinidae family. Aquarium experiments were designed to facilitate a continuous concentration of dissolved and diluted metabolites from the seawater around the sponges. Mass Spectrometry (MS)-based metabolomics combined with a dereplication pipeline were performed to investigate the proportion and identity of brominated alkaloids released as EMs. Chemometric analysis revealed that brominated features represented 12% of the total sponge’s EM features. Consequently, a total of 13 bromotyrosine alkaloids were reproducibly detected as EMs. The most abundant ones were aerothionin, purealidin L, aerophobin 1, and a new structural congener, herein named aplysine 1. Their structural identity was confirmed by NMR analyses following their isolation. MS-based quantification indicated that these major brominated EMs represented up to 1.0 ± 0.3% w/w of the concentrated seawater extract. This analytical workflow and collected results will serve as a stepping stone to characterize the composition of A. cavernicola’s EMs and those released by other sponges through in situ experiments, leading to further evaluate the biological properties of such EMs.

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          Cytoscape: a software environment for integrated models of biomolecular interaction networks.

          Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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            Universal solvation model based on solute electron density and on a continuum model of the solvent defined by the bulk dielectric constant and atomic surface tensions.

            We present a new continuum solvation model based on the quantum mechanical charge density of a solute molecule interacting with a continuum description of the solvent. The model is called SMD, where the "D" stands for "density" to denote that the full solute electron density is used without defining partial atomic charges. "Continuum" denotes that the solvent is not represented explicitly but rather as a dielectric medium with surface tension at the solute-solvent boundary. SMD is a universal solvation model, where "universal" denotes its applicability to any charged or uncharged solute in any solvent or liquid medium for which a few key descriptors are known (in particular, dielectric constant, refractive index, bulk surface tension, and acidity and basicity parameters). The model separates the observable solvation free energy into two main components. The first component is the bulk electrostatic contribution arising from a self-consistent reaction field treatment that involves the solution of the nonhomogeneous Poisson equation for electrostatics in terms of the integral-equation-formalism polarizable continuum model (IEF-PCM). The cavities for the bulk electrostatic calculation are defined by superpositions of nuclear-centered spheres. The second component is called the cavity-dispersion-solvent-structure term and is the contribution arising from short-range interactions between the solute and solvent molecules in the first solvation shell. This contribution is a sum of terms that are proportional (with geometry-dependent proportionality constants called atomic surface tensions) to the solvent-accessible surface areas of the individual atoms of the solute. The SMD model has been parametrized with a training set of 2821 solvation data including 112 aqueous ionic solvation free energies, 220 solvation free energies for 166 ions in acetonitrile, methanol, and dimethyl sulfoxide, 2346 solvation free energies for 318 neutral solutes in 91 solvents (90 nonaqueous organic solvents and water), and 143 transfer free energies for 93 neutral solutes between water and 15 organic solvents. The elements present in the solutes are H, C, N, O, F, Si, P, S, Cl, and Br. The SMD model employs a single set of parameters (intrinsic atomic Coulomb radii and atomic surface tension coefficients) optimized over six electronic structure methods: M05-2X/MIDI!6D, M05-2X/6-31G, M05-2X/6-31+G, M05-2X/cc-pVTZ, B3LYP/6-31G, and HF/6-31G. Although the SMD model has been parametrized using the IEF-PCM protocol for bulk electrostatics, it may also be employed with other algorithms for solving the nonhomogeneous Poisson equation for continuum solvation calculations in which the solute is represented by its electron density in real space. This includes, for example, the conductor-like screening algorithm. With the 6-31G basis set, the SMD model achieves mean unsigned errors of 0.6-1.0 kcal/mol in the solvation free energies of tested neutrals and mean unsigned errors of 4 kcal/mol on average for ions with either Gaussian03 or GAMESS.
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              Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking.

              The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry (MS) techniques are well-suited to high-throughput characterization of NP, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social Molecular Networking (GNPS; http://gnps.ucsd.edu), an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS, crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of 'living data' through continuous reanalysis of deposited data.
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                Author and article information

                Journal
                ACS Omega
                ACS Omega
                ao
                acsodf
                ACS Omega
                American Chemical Society
                2470-1343
                16 November 2022
                29 November 2022
                : 7
                : 47
                : 43068-43083
                Affiliations
                []IMBE, UMR CNRS 7263, IRD 237, Aix Marseille Université, Avignon Université, Endoume Marine Station , Chemin de la batterie des lions, 13007 Marseille, France
                []Aix Marseille Université, CNRS, Centrale Marseille, FSCM-Spectropole ,Service 511, Campus Saint-Jérome, 13397 Marseille, France
                [§ ]College of Pharmacy, Yeungnam University , Gyeongsan-si, Gyeongsangbuk-do 38541, South Korea
                []IMBE, UMR CNRS 7263, IRD 237, Aix Marseille Université, Avignon Université, Faculté de Pharmacie , 27 Boulevard Jean Moulin, 13385 Marseille, Cedex 5, France
                Author notes
                [* ]Email: charlotte.simmler@ 123456imbe.fr . Tel: +033 4.13.94.50.49.
                Author information
                https://orcid.org/0000-0003-4583-5389
                https://orcid.org/0000-0001-9156-5194
                https://orcid.org/0000-0002-3374-2508
                https://orcid.org/0000-0002-8523-4476
                https://orcid.org/0000-0003-0695-7260
                https://orcid.org/0000-0001-5502-0736
                https://orcid.org/0000-0003-4790-4878
                https://orcid.org/0000-0001-8930-338X
                https://orcid.org/0000-0002-6923-2630
                Article
                10.1021/acsomega.2c05415
                9713894
                36467926
                783b940d-6886-49d1-a962-e68081ebc89f
                © 2022 The Authors. Published by American Chemical Society

                Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works ( https://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 23 August 2022
                : 26 October 2022
                Funding
                Funded by: Agence Nationale de la Recherche, doi 10.13039/501100001665;
                Award ID: ANR-20-CE43-0003-01
                Funded by: Centre National de la Recherche Scientifique, doi 10.13039/501100004794;
                Award ID: NA
                Categories
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                Custom metadata
                ao2c05415
                ao2c05415

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