Please use this identifier to cite or link to this item: http://dx.doi.org/10.14279/depositonce-14885
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Main Title: Beyond the biosynthetic gene cluster paradigm: Genome-wide coexpression networks connect clustered and unclustered transcription factors to secondary metabolic pathways
Author(s): Kwon, Min Jin
Steiniger, Charlotte
Cairns, Timothy C.
Wisecaver, Jennifer H.
Lind, Abigail L.
Pohl, Carsten
Regner, Carmen
Rokas, Antonis
Meyer, Vera
Type: Article
URI: https://depositonce.tu-berlin.de/handle/11303/16111
http://dx.doi.org/10.14279/depositonce-14885
License: https://creativecommons.org/licenses/by/4.0/
Abstract: Fungal secondary metabolites are widely used as therapeutics and are vital components of drug discovery programs. A major challenge hindering discovery of novel secondary metabolites is that the underlying pathways involved in their biosynthesis are transcriptionally silent under typical laboratory growth conditions, making it difficult to identify the transcriptional networks that they are embedded in. Furthermore, while the genes participating in secondary metabolic pathways are typically found in contiguous clusters on the genome, known as biosynthetic gene clusters (BGCs), this is not always the case, especially for global and pathway-specific regulators of pathways’ activities. To address these challenges, we used 283 genome-wide gene expression data sets of the ascomycete cell factory Aspergillus niger generated during growth under 155 different conditions to construct two gene coexpression networks based on Spearman’s correlation coefficients (SCCs) and on mutual rank-transformed Pearson’s correlation coefficients (MR-PCCs). By mining these networks, we predicted six transcription factors, named MjkA to MjkF, to regulate secondary metabolism in A. niger. Overexpression of each transcription factor using the Tet-On cassette modulated the production of multiple secondary metabolites. We found that the SCC and MR-PCC approaches complemented each other, enabling the delineation of putative global (SCC) and pathway-specific (MR-PCC) transcription factors. These results highlight the potential of coexpression network approaches to identify and activate fungal secondary metabolic pathways and their products. More broadly, we argue that drug discovery programs in fungi should move beyond the BGC paradigm and focus on understanding the global regulatory networks in which secondary metabolic pathways are embedded.
Subject(s): filamentous fungi
Aspergillus niger
secondary metabolite gene clusters
gene coexpression
correlation network
natural product
specialized metabolism
genetic network
gene regulation
Issue Date: 15-Sep-2021
Date Available: 11-Jan-2022
Language Code: en
DDC Class: 570 Biowissenschaften; Biologie
Sponsor/Funder: DFG, 404295023, Etablierung eines innovativen Ko-Kultivierungssystems zur Hochdurchsatzidentifizierung von antimikrobiellen Wirkstoffen
EC/FP7/607332/EU/Quantitative Biology for Fungal Secondary Metabolite Producers/QUANTFUNG
Journal Title: Microbiology Spectrum
Publisher: ASM
Volume: 9
Issue: 2
Article Number: e00898-21
Publisher DOI: 10.1128/Spectrum.00898-21
EISSN: 2165-0497
TU Affiliation(s): Fak. 3 Prozesswissenschaften » Inst. Biotechnologie » FG Angewandte und Molekulare Mikrobiologie
Appears in Collections:Technische Universität Berlin » Publications

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