New Approaches to Detect Biosynthetic Gene Clusters in the Environment
Microorganisms in the environment can produce a diverse range of secondary metabolites (SM), which are also known as natural products. Bioactive SMs have been crucial in the development of antibiotics and can also act as useful compounds in the biotechnology industry. These natural products are enco...
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doaj-5d18bed27e774802a915873e688065422020-11-24T21:16:00ZengMDPI AGMedicines2305-63202019-02-01613210.3390/medicines6010032medicines6010032New Approaches to Detect Biosynthetic Gene Clusters in the EnvironmentRay Chen0Hon Lun Wong1Brendan Paul Burns2School of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney 2052, AustraliaSchool of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney 2052, AustraliaSchool of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney 2052, AustraliaMicroorganisms in the environment can produce a diverse range of secondary metabolites (SM), which are also known as natural products. Bioactive SMs have been crucial in the development of antibiotics and can also act as useful compounds in the biotechnology industry. These natural products are encoded by an extensive range of biosynthetic gene clusters (BGCs). The developments in omics technologies and bioinformatic tools are contributing to a paradigm shift from traditional culturing and screening methods to bioinformatic tools and genomics to uncover BGCs that were previously unknown or transcriptionally silent. Natural product discovery using bioinformatics and omics workflow in the environment has demonstrated an extensive distribution of BGCs in various environments, such as soil, aquatic ecosystems and host microbiome environments. Computational tools provide a feasible and culture-independent route to find new secondary metabolites where traditional approaches cannot. This review will highlight some of the advances in the approaches, primarily bioinformatic, in identifying new BGCs, especially in environments where microorganisms are rarely cultured. This has allowed us to tap into the huge potential of microbial dark matter.https://www.mdpi.com/2305-6320/6/1/32natural productsbiosynthetic gene clusterssecondary metabolitesantiSMASH |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ray Chen Hon Lun Wong Brendan Paul Burns |
spellingShingle |
Ray Chen Hon Lun Wong Brendan Paul Burns New Approaches to Detect Biosynthetic Gene Clusters in the Environment Medicines natural products biosynthetic gene clusters secondary metabolites antiSMASH |
author_facet |
Ray Chen Hon Lun Wong Brendan Paul Burns |
author_sort |
Ray Chen |
title |
New Approaches to Detect Biosynthetic Gene Clusters in the Environment |
title_short |
New Approaches to Detect Biosynthetic Gene Clusters in the Environment |
title_full |
New Approaches to Detect Biosynthetic Gene Clusters in the Environment |
title_fullStr |
New Approaches to Detect Biosynthetic Gene Clusters in the Environment |
title_full_unstemmed |
New Approaches to Detect Biosynthetic Gene Clusters in the Environment |
title_sort |
new approaches to detect biosynthetic gene clusters in the environment |
publisher |
MDPI AG |
series |
Medicines |
issn |
2305-6320 |
publishDate |
2019-02-01 |
description |
Microorganisms in the environment can produce a diverse range of secondary metabolites (SM), which are also known as natural products. Bioactive SMs have been crucial in the development of antibiotics and can also act as useful compounds in the biotechnology industry. These natural products are encoded by an extensive range of biosynthetic gene clusters (BGCs). The developments in omics technologies and bioinformatic tools are contributing to a paradigm shift from traditional culturing and screening methods to bioinformatic tools and genomics to uncover BGCs that were previously unknown or transcriptionally silent. Natural product discovery using bioinformatics and omics workflow in the environment has demonstrated an extensive distribution of BGCs in various environments, such as soil, aquatic ecosystems and host microbiome environments. Computational tools provide a feasible and culture-independent route to find new secondary metabolites where traditional approaches cannot. This review will highlight some of the advances in the approaches, primarily bioinformatic, in identifying new BGCs, especially in environments where microorganisms are rarely cultured. This has allowed us to tap into the huge potential of microbial dark matter. |
topic |
natural products biosynthetic gene clusters secondary metabolites antiSMASH |
url |
https://www.mdpi.com/2305-6320/6/1/32 |
work_keys_str_mv |
AT raychen newapproachestodetectbiosyntheticgeneclustersintheenvironment AT honlunwong newapproachestodetectbiosyntheticgeneclustersintheenvironment AT brendanpaulburns newapproachestodetectbiosyntheticgeneclustersintheenvironment |
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