Multiomics and Machine Learning for the Discovery and Classification of Marine Specialized Metabolites

A special issue of Marine Drugs (ISSN 1660-3397).

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 2366

Special Issue Editors


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Guest Editor
Institute of Pharmaceutical Biology and Biotechnology, University of Marburg, Marburg, Germany
Interests: specialized metabolites; structure elucidation; drug discovery; chemical ecology; (native) metabolomics; NMR spectroscopy; G protein modulators
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Guest Editor
Institute for Insect Biotechnology, Justus-Liebig-University Giessen, Giessen, 35392, Germany
Interests: specialized metabolites; biosynthesis; drug discovery; anti-infectives Interests: antibiotics; heterologous expression; metabolomics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Once neglected, marine organisms have been demonstrated to be a fruitful source of marine-specialized metabolites with unique structures and bioactivities.

Third-generation sequencing techniques and open source FAIR metabolomics databases such as MASSIVE offer vast amounts of highly complementary data. Recent efforts linking metabolomics and genomics data have resulted in the paired-omics database that has started various multiomics research projects.

Additionally, analytical NMR and MS methods for the classification of whole metabolomes, as well as the structure elucidation of prioritized specialized metabolites, have been revolutionized by the implementation of machine learning techniques.

This Special Issue invites articles from both multiomics- and machine learning-driven studies on marine organisms, with a focus on marine-specialized metabolites discovery and metabolome classification. High-quality metabolomics-based studies are also welcome.

Prof. Dr. Raphael Reher
Prof. Dr. Till F. Schäberle
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Marine Drugs is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • marine-specialized metabolites
  • multiomics
  • machine learning
  • metabolomics
  • genome mining
  • bioinformatics
  • natural products

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Published Papers (1 paper)

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Research

12 pages, 2403 KiB  
Article
Overexpression of Global Regulator SCrp Leads to the Discovery of New Angucyclines in Streptomyces sp. XS-16
by Xiao Xu, Falei Zhang, Luning Zhou, Yimin Chang, Qian Che, Tianjiao Zhu, Dehai Li and Guojian Zhang
Mar. Drugs 2023, 21(4), 240; https://doi.org/10.3390/md21040240 - 14 Apr 2023
Cited by 1 | Viewed by 1990
Abstract
Six angucyclines including three unreported compounds (13) were isolated from Streptomyces sp. XS-16 by overexpressing the native global regulator of SCrp (cyclic AMP receptor). The structures were characterized based on nuclear magnetic resonance (NMR) and spectrometry analysis and assisted [...] Read more.
Six angucyclines including three unreported compounds (13) were isolated from Streptomyces sp. XS-16 by overexpressing the native global regulator of SCrp (cyclic AMP receptor). The structures were characterized based on nuclear magnetic resonance (NMR) and spectrometry analysis and assisted by electronic circular dichroism (ECD) calculations. All compounds were tested for their antitumor and antimicrobial activities, and compound 1 showed different inhibitory activities against various tumor cell lines with IC50 values ranging from 0.32 to 5.33 μM. Full article
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