Resistance Gene-Guided Genome Mining: Serial Promoter Exchanges in <i>Aspergillus nidulans</i> Reveal the Biosynthetic Pathway for Fellutamide B, a Proteasome Inhibitor

Yeh, Hsu-Hua; Ahuja, Manmeet; Chiang, Yun‐Wei; Oakley, C. Elizabeth; Moore, Shauna; Yoon, Olivia; Hajovsky, Heather; Bok, Jin-Woo; Keller, Nancy P.; Wang, Clay C. C.; Oakley, Berl R.

doi:10.1021/acschembio.6b00213

Cited by 99 publications

(104 citation statements)

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“…In order to do this we based the pipeline 94 on the assumption that the resistance gene is found within a cluster and is a copy -a 95 paralog -of an essential gene. This pattern and the resulting resistance mechanism 96 has previously been described in two different cases in fungi (13,16). 97 We have used complete and draft quality whole genome sequences, mainly from 98 the 300 Aspergillus sequencing project (5,6).…”

Section: Ms Submission Template Msystems Submission Template Msystemsmentioning

confidence: 95%

“…13 We have developed a pipeline FRIGG (Fungal ResIstance Gene-directed Genome 14 mining) identifying putative resistance genes found in biosynthetic gene clusters based 15 on homology patterns of the cluster genes. The FRIGG pipeline has been run using 51 16 Aspergillus and Penicillium genomes, identifying 72 unique protein families with putative 17 resistance genes using various settings in the pipeline. The pipeline was also able to 18 identify the characterized resistance gene inpE from the Fellutamide B cluster thereby 19 validating the approach.…”

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“…73 An illustration of the general mechanism can be seen on Figure 1C, where two ver-74 sions of an enzyme is present and one version is affected by the secondary metabolite 75 (the target) whereas the other version is slightly different, but still with the same func-76 tion, is not inhibited by the secondary metabolite (the resistance gene). Even though 77 only a few examples of this mechanism have been identified and verified in filamentous 78 fungi so far (13,16,17,18), it is possible that this resistance mechanism is more widely 79 distributed. We have therefore developed a Fungal ResIstance Gene-directed Genome 80 mining (FRIGG) pipeline identifying putative bio-active clusters with resistance genes.…”

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Resistance Gene-Directed Genome Mining of 50 Aspergillus species

Kjærbølling

Vesth

Andersen

2018

Preprint

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Fungal secondary metabolites are a rich source of valuable natural prod-5 ucts. Genome sequencing have revealed an enormous potential from predicted biosyn-6 thetic gene clusters. It is however currently a time consuming task and an unfeasible 7 task to characterize all biosynthetic gene cluster and to identify possible uses of the 8 compounds. A rational approach is needed to identify promising gene clusters respon-9 sible for producing valuable compounds. Several valuable bioactive clusters have been 10 shown to include a resistance gene which is a paralog of the target gene inhibited by 11 the compound. This mechanism can be used to design a rational approach selecting 12 those clusters. 13 We have developed a pipeline FRIGG (Fungal ResIstance Gene-directed Genome 14 mining) identifying putative resistance genes found in biosynthetic gene clusters based 15 on homology patterns of the cluster genes. The FRIGG pipeline has been run using 51 16 Aspergillus and Penicillium genomes, identifying 72 unique protein families with putative 17 resistance genes using various settings in the pipeline. The pipeline was also able to 18 identify the characterized resistance gene inpE from the Fellutamide B cluster thereby 19 validating the approach. 20 We have successfully developed an approach identifying putative valuable bio-21 active clusters based on a specific resistance mechanism. This approach will be highly 22 ms Submission Template mSystems Submission Template mSystems Submission Template mSystems Submission Template mSystems Submission Template mSystems Submission Tem 1 Kjaerbølling et al. number of secondary metabolite gene clusters than the number of characterized 41 secondary metabolites thus revealing a much larger potential (2, 3, 4, 1). The number 42 of sequenced genomes is ever increasing mainly due to large sequencing efforts such as 43 the 1000 Fungal Genomes Project of the Department of Energy Joint Genomes Initiative 44 (http://1000.fungalgenomes.org/home/) and the 300 Aspergillus genome project (5, 6) 45 and therefore the number of predicted secondary metabolite gene clusters is steadily 46 increasing. 47 Despite progress in molecular tools and methods for characterization of secondary 48 metabolite gene clusters, it is still a time-consuming task, making it unfeasible to 49 investigate all predicted secondary metabolite gene clusters. Therefore only a small 50 fraction of the predicted clusters are characterized and investigated experimentally. 51 With the plethora of predicted secondary metabolite gene clusters (clusters) and the 52 aim of discovering novel bio-active compounds useful as drugs, the question emerges: 53 How do we select the most interesting predicted clusters producing potential valuable 54 drugs such as anti-fungicides, anti-cancer drugs and anti-microbial compounds? To 55 meet this need we have created a pipeline FRIGG (Fungal ResIstance Gene-directed 56 Genome mining) identifying clusters producing likely bio-active compounds based on 57 resistance genes. Many bio-active...

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Section: Ms Submission Template Msystems Submission Template Msystemsmentioning

confidence: 95%

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Resistance Gene-Directed Genome Mining of 50 Aspergillus species

Kjærbølling

Vesth

Andersen

2018

Preprint

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“…Although SirAD up-regulated the SM genes found in Sets 2 and 3 during the late growth phase, >50% of the genes in 11 SM gene clusters were not up-regulated in SirAD, and these clusters included genes that synthesize AUS/ DAUS, orcinols and F9775 (ORS/F9775), ASP, CIC, microperfuranone (MIC), EPD, 2,4-dihydroxy-6-[(3E,5E,7E)-2-oxonona-3,5,7-trienyl] benzaldehyde (DOTB) (Ahuja and Chiang, 2012), 2-ethyl-4,6-dihydroxy-3,5-dimethylbenzaldehyde (EDD) (Ahuja and Chiang, 2012) and fellutamide B (INP) (Yeh et al, 2016), predicted NRPS (AN10297), and predicted PKS (AN8910) (Figs. 2B, D, and Table S3).…”

Section: Supplementary Materialsmentioning

confidence: 99%

Sirtuin A regulates secondary metabolite production by <i>Aspergillus nidulans</i>

Itoh

Shigemoto

Oinuma

et al. 2017

J. Gen. Appl. Microbiol.

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“…Improved understanding of SM biosynthesis has led to the development of various bioinformatic tools and strategies for the prioritisation of BGCs for genome mining, increasing the chance of discovery of novel molecules or molecules with desired bioactivities 6,7 . Current strategies for activating specific BGCs typically involve promoter exchange of all individual genes in the BGC with strong promoters 8 . If a BGC contains a transcription factor (TF) gene, overexpression via promoter exchange can activate expression of the entire BGC 9 .…”

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confidence: 99%

CRISPR-mediated activation of biosynthetic gene clusters for bioactive molecule discovery in filamentous fungi

Roux

Woodcraft

et al. 2020

Preprint

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7Accessing the full biosynthetic potential encoded in the genomes of fungi is limited by the low 8 expression of many biosynthetic gene clusters (BGCs) under standard culture conditions. In 9 this work, we develop a fungal CRISPR activation (CRISPRa) system for targeted upregulation 10 of biosynthetic genes, which could accelerate the emerging genomics-driven approach to 11 bioactive secondary metabolite discovery. We construct a fungal CRISPR/dLbCas12a-VPR 12 system and demonstrate activation of a fluorescent reporter in Aspergillus nidulans. Then, we 13 target the native nonribosomal peptide synthetase-like (NRPS-like) gene micA in both 14 chromosomal and episomal contexts, achieving increases in production of the compound 15 microperfuranone. Finally, multi-gene CRISPRa leads to the discovery of the mic cluster 16 product as dehydromicroperfuranone. Additionally, we demonstrate the utility of the variant 17 LbCas12a D156R -VPR for CRISPRa at lower culture temperatures. This is the first 18 demonstration of CRISPRa in filamentous fungi, providing a framework for CRISPR-mediated 19 transcriptional activation of fungal BGCs. 20 activation (CRISPRa)-mediated approach for BGC activation in filamentous fungi (Fig. 1a). In 49 CRISPRa systems, DNase-deactivated RNA-guided CRISPR/dCas ribonucleoprotein 50 complexes linked to activation effectors are targeted to gene regulatory regions to increase 51 gene expression [17][18][19] . Taking advantage of the streamlined CRISPR RNA (crRNA) cloning 52 and multiplexing capabilities, CRISPRa of BGCs has the potential to greatly accelerate fungal 53 genome mining. CRISPRa has already been used to tune the expression of biosynthetic 54 pathways 20,21 , including in ascomycetous yeasts 22,23 . However, to our knowledge, CRISPRa 55has not yet been demonstrated in filamentous fungi. 56In this work, we develop a suite of fungal CRISPRa vectors based on both dLbCas12a from 57Lachnospiraceae bacterium Cas12a (previously known as Cpf1) 19 , and dSpCas9 from 58Streptococcus pyogenes fused to the tripartite VPR activator 18 , and test them in A. nidulans. 59We further explore the application of our CRISPR/dLbCas12a-VPR system for fungal BGC 60 activation as a tool to fuel bioactive molecule discovery. 61 Results 62 Construction and testing of fungal CRISPRa systems 63To develop a CRISPRa system for filamentous fungi, we constructed and tested 64 CRISPR/dLbCas12a-VPR-and CRISPR/dSpCas9-VPR-based systems in the model 65 organism and chassis A. nidulans. To evaluate alternative strategies for expressing either 66 3 dCas effector, we created parent strains with a chromosomally integrated dCas-VPR 67 expression cassette and compared their performance with entirely AMA1-episomally encoded 68 systems. The AMA1 sequence acts as an extrachromosomal vector replicator and confers 69 increased transformation frequency in several filamentous fungi species 24 . AMA1-bearing 70 vectors are found at multiple copies per nucleus although their genetic stability has been 71 reported to be limited under non...

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Resistance Gene-Guided Genome Mining: Serial Promoter Exchanges in Aspergillus nidulans Reveal the Biosynthetic Pathway for Fellutamide B, a Proteasome Inhibitor

Cited by 99 publications

References 38 publications

Resistance Gene-Directed Genome Mining of 50 Aspergillus species

Resistance Gene-Directed Genome Mining of 50 Aspergillus species

Sirtuin A regulates secondary metabolite production by <i>Aspergillus nidulans</i>

CRISPR-mediated activation of biosynthetic gene clusters for bioactive molecule discovery in filamentous fungi

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