MS and NMR data of in situ Captured Marine Exometabolites

This folder contains the raw data pertaining to the article In Situ Capture and Real Time Enrichment of Marine Chemical Diversity  
https://doi.org/10.1021/acscentsci.3c00661
Data are organized in folders corresponding to each figure. Briefly, this folder contains  the raw mass spectrometry (MS) data, the cytoscape files of the full molecular network (Fig3), the xcel spreadsheets of annotated MS spectra related to each investigated specialized exometabolites from the Mediterranean sponges Aplysina cavernicola (AC, Fig4), Spongia officinalis (SO, Fig5), and Agelas oroides (AO, Fig6), the raw 1H NMR data from each sponge exometabolite (EM) extract with their corresponding crude extract (CR).

All MS2 data were acquired on a Bruker Impact II qTOF (ESI positive, collision energy 20-40eV) also deposited here : MSV000091465
SIRIUS software and CANOPUS were used to further annotate the chemodiversity of captured marine EMs
All NMR data were acquired on a BRUKER avance II+  instrument (600 MHz, cryoprobe) in CD3OD
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References related to in silico MS annotation tools:

Kai Dührkop, Louis-Félix Nothias, Markus Fleischauer, Raphael Reher, Marcus Ludwig, Martin A. Hoffmann, Daniel Petras, William H. Gerwick, Juho Rousu, Pieter C. Dorrestein and Sebastian Böcker Systematic classification of unknown metabolites using high-resolution fragmentation mass spectra. Nature Biotechnology, 2020.  https://doi.org/10.1038/s41587-020-0740-8
Yannick Djoumbou Feunang, Roman Eisner, Craig Knox, Leonid Chepelev, Janna Hastings, Gareth Owen, Eoin Fahy, Christoph Steinbeck, Shankar Subramanian, Evan Bolton, Russell Greiner, David S. Wishart ClassyFire: automated chemical classification with a comprehensive, computable taxonomy J Cheminf, 8, 2016.  https://doi.org/10.1186/s13321-016-0174-y
Kim, Hyun Woo and Wang, Mingxun and Leber, Christopher A. and Nothias, Louis-Félix and Reher, Raphael and Kang, Kyo Bin and van der Hooft, Justin J. J. and Dorrestein, Pieter C. and Gerwick, William H. and Cottrell, Garrison W. NPClassifier: A Deep Neural Network-Based Structural Classification Tool for Natural Products. Journal of Natural Products, 84, 2021. https://doi.org/10.1021/acs.jnatprod.1c00399