Resistance Gene-Directed Genome Mining of 50 Aspergillus species

Abstract

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...

Acrophiarin (antibiotic S31794/F‐1) from Penicillium arenicola shares biosynthetic features with both Aspergillus‐ and Leotiomycete‐type echinocandins

“…pachycristatus ) and fellutamide‐like gene clusters in other unrelated ascomycetes, including Spathularia flavida (Leotiomycetes, Rhytismatales), Bisporella sp. (Leotiomycetes, Helotiales) and Lobaria pulmonaria (Lecanoromycetes, Peltigerales) indicating that the fellutamide family of lipopeptides may more widespread than previously recognized (Shigemori et al ., ; Lee and Hong, ; Xu et al ., ; Wu et al ., ; Kjærbølling et al ., ). Because the products of these BGCs in these latter fungi are unknown, we refer to them as fellutamide‐like BGCs.…”

Identification of the Antifungal Metabolite Chaetoglobosin P From Discosia rubi Using a Cryptococcus neoformans Inhibition Assay: Insights Into Mode of Action and Biosynthesis

“…In both D. rubi and S. maydis , the BGC-associated copy of twf1 was the only copy that could be detected in any of the three genomes. Thus, in these fungi, the twf1 gene did not follow the canonical pattern where upregulation of a divergent BGC-associated resistance gene compensates for a separate primary housekeeping gene ( Kjærbølling et al, 2019 ). Immediate proximity to a chaetoglobosin BGC would facilitate coregulation with metabolite production.…”

A Collaborative Tale of Diagnosing and Treating Chronic Pulmonary Aspergillosis, from the Perspectives of Clinical Microbiologists, Surgical Pathologists, and Infectious Disease Clinicians

“…While there are ongoing efforts to develop pipelines to detect resistance genes by the identification of secondary metabolic gene clusters harboring potential resistance genes [ 111 ], it is important to also note the limitations of WGS. First, a pure isolate is required, and thus, this cannot be performed directly from the clinical specimen.…”