Computational genomics of specialized metabolism : From natural product discovery to microbiome ecology

Microbial and plant specialized metabolites, also known as natural products, are key mediators of microbe-microbe and host-microbe interactions and constitute a rich resource for drug development. In the past decade, genome mining has emerged as a prominent strategy for natural product discovery. Initially, such mining was performed on the basis of individual microbial genome sequences. Now, these efforts are being scaled up to fully genome-sequenced strain collections, pan-genomes of bacterial genera, and large sets of metagenome-assembled genomes from microbial communities. The Medema research group aims to play a leading role in these developments by developing and applying computational approaches to identify, classify, and prioritize specialized metabolite biosynthetic gene clusters and pathways and to connect them to specific molecules and microbiome-associated phenotypes. Moreover, we are extending the scope of genome mining from microbes to plants, which will allow more comprehensive interpretation of the chemical language between hosts and microbes in a microbiome setting.

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Bibliographic Details
Main Author: Medema, Marnix H.
Format: Article/Letter to editor biblioteca
Language:English
Subjects:Bioinformatics, Biosynthetic gene cluster, Microbiome, Natural products, Specialized metabolism,
Online Access:https://research.wur.nl/en/publications/computational-genomics-of-specialized-metabolism-from-natural-pro
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spelling dig-wur-nl-wurpubs-5365612024-09-23 Medema, Marnix H. Article/Letter to editor mSystems 3 (2018) 2 ISSN: 2379-5077 Computational genomics of specialized metabolism : From natural product discovery to microbiome ecology 2018 Microbial and plant specialized metabolites, also known as natural products, are key mediators of microbe-microbe and host-microbe interactions and constitute a rich resource for drug development. In the past decade, genome mining has emerged as a prominent strategy for natural product discovery. Initially, such mining was performed on the basis of individual microbial genome sequences. Now, these efforts are being scaled up to fully genome-sequenced strain collections, pan-genomes of bacterial genera, and large sets of metagenome-assembled genomes from microbial communities. The Medema research group aims to play a leading role in these developments by developing and applying computational approaches to identify, classify, and prioritize specialized metabolite biosynthetic gene clusters and pathways and to connect them to specific molecules and microbiome-associated phenotypes. Moreover, we are extending the scope of genome mining from microbes to plants, which will allow more comprehensive interpretation of the chemical language between hosts and microbes in a microbiome setting. en application/pdf https://research.wur.nl/en/publications/computational-genomics-of-specialized-metabolism-from-natural-pro 10.1128/mSystems.00182-17 https://edepot.wur.nl/447217 Bioinformatics Biosynthetic gene cluster Microbiome Natural products Specialized metabolism https://creativecommons.org/licenses/by/4.0/ Wageningen University & Research
institution WUR NL
collection DSpace
country Países bajos
countrycode NL
component Bibliográfico
access En linea
databasecode dig-wur-nl
tag biblioteca
region Europa del Oeste
libraryname WUR Library Netherlands
language English
topic Bioinformatics
Biosynthetic gene cluster
Microbiome
Natural products
Specialized metabolism
Bioinformatics
Biosynthetic gene cluster
Microbiome
Natural products
Specialized metabolism
spellingShingle Bioinformatics
Biosynthetic gene cluster
Microbiome
Natural products
Specialized metabolism
Bioinformatics
Biosynthetic gene cluster
Microbiome
Natural products
Specialized metabolism
Medema, Marnix H.
Computational genomics of specialized metabolism : From natural product discovery to microbiome ecology
description Microbial and plant specialized metabolites, also known as natural products, are key mediators of microbe-microbe and host-microbe interactions and constitute a rich resource for drug development. In the past decade, genome mining has emerged as a prominent strategy for natural product discovery. Initially, such mining was performed on the basis of individual microbial genome sequences. Now, these efforts are being scaled up to fully genome-sequenced strain collections, pan-genomes of bacterial genera, and large sets of metagenome-assembled genomes from microbial communities. The Medema research group aims to play a leading role in these developments by developing and applying computational approaches to identify, classify, and prioritize specialized metabolite biosynthetic gene clusters and pathways and to connect them to specific molecules and microbiome-associated phenotypes. Moreover, we are extending the scope of genome mining from microbes to plants, which will allow more comprehensive interpretation of the chemical language between hosts and microbes in a microbiome setting.
format Article/Letter to editor
topic_facet Bioinformatics
Biosynthetic gene cluster
Microbiome
Natural products
Specialized metabolism
author Medema, Marnix H.
author_facet Medema, Marnix H.
author_sort Medema, Marnix H.
title Computational genomics of specialized metabolism : From natural product discovery to microbiome ecology
title_short Computational genomics of specialized metabolism : From natural product discovery to microbiome ecology
title_full Computational genomics of specialized metabolism : From natural product discovery to microbiome ecology
title_fullStr Computational genomics of specialized metabolism : From natural product discovery to microbiome ecology
title_full_unstemmed Computational genomics of specialized metabolism : From natural product discovery to microbiome ecology
title_sort computational genomics of specialized metabolism : from natural product discovery to microbiome ecology
url https://research.wur.nl/en/publications/computational-genomics-of-specialized-metabolism-from-natural-pro
work_keys_str_mv AT medemamarnixh computationalgenomicsofspecializedmetabolismfromnaturalproductdiscoverytomicrobiomeecology
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