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Marnix H Medema  - - - 
Top co-authors See all
Arnold J.M. Driessen

381 shared publications

Molecular Microbiology, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, 9747 AG Groningen, The Netherlands

Huimin Zhao

290 shared publications

Department of Biochemistry

Pieter C. Dorrestein

250 shared publications

University of California, San Diego

Oscar P. Kuipers

244 shared publications

Department of Molecular Genetics, University of Groningen, Groningen, The Netherlands

Sang Hyun Sung

224 shared publications

College of Pharmacy, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea

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Publication Record
Distribution of Articles published per year 
(2009 - 2019)
Total number of journals
published in
 
34
 
Publications See all
Article 0 Reads 0 Citations The antiSMASH database version 2: a comprehensive resource on secondary metabolite biosynthetic gene clusters. Kai Blin, Victòria Pascal Andreu, Emmanuel L C De Los Santos... Published: 08 January 2019
Nucleic Acids Research, doi: 10.1093/nar/gky1060
DOI See at publisher website PubMed View at PubMed ABS Show/hide abstract
Natural products originating from microorganisms are frequently used in antimicrobial and anticancer drugs, pesticides, herbicides or fungicides. In the last years, the increasing availability of microbial genome data has made it possible to access the wealth of biosynthetic clusters responsible for the production of these compounds by genome mining. antiSMASH is one of the most popular tools in this field. The antiSMASH database provides pre-computed antiSMASH results for many publicly available microbial genomes and allows for advanced cross-genome searches. The current version 2 of the antiSMASH database contains annotations for 6200 full bacterial genomes and 18,576 bacterial draft genomes and is available at https://antismash-db.secondarymetabolites.org/.
Article 0 Reads 0 Citations Mining bacterial genomes to reveal secret synergy Mohammad Alanjary, Marnix H. Medema Published: 28 December 2018
Journal of Biological Chemistry, doi: 10.1074/jbc.h118.006669
DOI See at publisher website
PREPRINT-CONTENT 0 Reads 0 Citations Comprehensive mass spectrometry-guided plant specialized metabolite phenotyping reveals metabolic diversity in the cosmo... Kyo Bin Kang, Madeleine Ernst, Justin J. J. Van Der Hooft, R... Published: 07 November 2018
bioRxiv, doi: 10.1101/463620
DOI See at publisher website ABS Show/hide abstract
Plants produce a myriad of specialized metabolites to overcome their sessile habit and combat biotic as well as abiotic stresses. Evolution has shaped specialized metabolite diversity, which drives many other aspects of plant biodiversity. However, until recently, large-scale studies investigating specialized metabolite diversity in an evolutionary context have been limited by the impossibility to identify chemical structures of hundreds to thousands of compounds in a time-feasible manner. Here, we introduce a workflow for large-scale, semi-automated annotation of specialized metabolites, and apply it for over 1000 metabolites of the cosmopolitan plant family Rhamnaceae. We enhance the putative annotation coverage dramatically, from 2.5 % based on spectral library matches alone to 42.6 % of total MS/MS molecular features extending annotations from well-known plant compound classes into the dark plant metabolomics matter. To gain insights in substructural diversity within the plant family, we also extract patterns of co-occurring fragments and neutral losses, so-called Mass2Motifs, from the dataset; for example, only the Ziziphoid clade developed the triterpenoid biosynthetic pathway, whereas the Rhamnoid clade predominantly developed diversity in flavonoid glycosides, including 7-O-methyltransferase activity. Our workflow provides the foundations towards the automated, high-throughput chemical identification of massive metabolite spaces, and we expect it to revolutionize our understanding of plant chemoevolutionary mechanisms.
PREPRINT-CONTENT 1 Read 2 Citations A computational framework for systematic exploration of biosynthetic diversity from large-scale genomic data Jorge Navarro-Muñoz, Nelly Selem-Mojica, Michael Mullowney, ... Published: 17 October 2018
bioRxiv, doi: 10.1101/445270
DOI See at publisher website
Article 0 Reads 13 Citations Structure and function of the global topsoil microbiome Mohammad Bahram, Falk Hildebrand, Sofia K. Forslund, Jennife... Published: 01 August 2018
Nature, doi: 10.1038/s41586-018-0386-6
DOI See at publisher website
Article 2 Reads 1 Citation A standardized workflow for submitting data to the Minimum Information about a Biosynthetic Gene cluster (MIBiG) reposit... Samuel C. Epstein, Louise K. Charkoudian, Marnix H. Medema Published: 11 July 2018
Standards in Genomic Sciences, doi: 10.1186/s40793-018-0318-y
DOI See at publisher website PubMed View at PubMed ABS Show/hide abstract
Microorganisms utilize complex enzymatic pathways to biosynthesize structurally complex and pharmacologically relevant molecules. These pathways are encoded by gene clusters and are found in a diverse set of organisms. The Minimum Information about a Biosynthetic Gene cluster repository facilitates standardized and centralized storage of experimental data on these gene clusters and their molecular products, by utilizing user-submitted data to translate scientific discoveries into a format that can be analyzed computationally. This accelerates the processes of connecting genes to chemical structures, understanding biosynthetic gene clusters in the context of environmental diversity, and performing computer-assisted design of synthetic gene clusters. Here, we present a Standard Operating Procedure, Excel templates, a tutorial video, and a collection of relevant review literature to support scientists in their efforts to submit data into MiBIG. Further, we provide tools to integrate gene cluster annotation projects into the classroom environment, including workflows and assessment materials.
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