Beyond the biosynthetic gene cluster paradigm: Genome-wide coexpression networks connect clustered and unclustered transcription factors to secondary metabolic pathways

dc.contributor.authorKwon, Min Jin
dc.contributor.authorSteiniger, Charlotte
dc.contributor.authorCairns, Timothy C.
dc.contributor.authorWisecaver, Jennifer H.
dc.contributor.authorLind, Abigail L.
dc.contributor.authorPohl, Carsten
dc.contributor.authorRegner, Carmen
dc.contributor.authorRokas, Antonis
dc.contributor.authorMeyer, Vera
dc.date.accessioned2022-01-11T14:32:03Z
dc.date.available2022-01-11T14:32:03Z
dc.date.issued2021-09-15
dc.description.abstractFungal 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.en
dc.description.sponsorshipDFG, 404295023, Etablierung eines innovativen Ko-Kultivierungssystems zur Hochdurchsatzidentifizierung von antimikrobiellen Wirkstoffenen
dc.description.sponsorshipEC/FP7/607332/EU/Quantitative Biology for Fungal Secondary Metabolite Producers/QUANTFUNGen
dc.identifier.eissn2165-0497
dc.identifier.urihttps://depositonce.tu-berlin.de/handle/11303/16111
dc.identifier.urihttp://dx.doi.org/10.14279/depositonce-14885
dc.language.isoenen
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subject.ddc570 Biowissenschaften; Biologiede
dc.subject.otherfilamentous fungien
dc.subject.otherAspergillus nigeren
dc.subject.othersecondary metabolite gene clustersen
dc.subject.othergene coexpressionen
dc.subject.othercorrelation networken
dc.subject.othernatural producten
dc.subject.otherspecialized metabolismen
dc.subject.othergenetic networken
dc.subject.othergene regulationen
dc.titleBeyond the biosynthetic gene cluster paradigm: Genome-wide coexpression networks connect clustered and unclustered transcription factors to secondary metabolic pathwaysen
dc.typeArticleen
dc.type.versionpublishedVersionen
dcterms.bibliographicCitation.articlenumbere00898-21en
dcterms.bibliographicCitation.doi10.1128/Spectrum.00898-21en
dcterms.bibliographicCitation.issue2en
dcterms.bibliographicCitation.journaltitleMicrobiology Spectrumen
dcterms.bibliographicCitation.originalpublishernameASMen
dcterms.bibliographicCitation.originalpublisherplaceBirmingham, Ala.en
dcterms.bibliographicCitation.volume9en
tub.accessrights.dnbfreeen
tub.affiliationFak. 3 Prozesswissenschaften::Inst. Biotechnologie::FG Angewandte und Molekulare Mikrobiologiede
tub.affiliation.facultyFak. 3 Prozesswissenschaftende
tub.affiliation.groupFG Angewandte und Molekulare Mikrobiologiede
tub.affiliation.instituteInst. Biotechnologiede
tub.publisher.universityorinstitutionTechnische Universität Berlinen

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