Biosynthesis of Antibacterial Iron-Chelating Tropolones in Aspergillus nidulans as Response to Glycopeptide-Producing Streptomycetes

The soil microbiome comprises numerous filamentous fungi and bacteria that mutually react and challenge each other by the production of bioactive secondary metabolites. Herein, we show in liquid co-cultures that the presence of filamentous Streptomycetes producing antifungal glycopeptide antibiotics induces the production of the antibacterial and iron-chelating tropolones anhydrosepedonin (1) and antibiotic C (2) in the mold Aspergillus nidulans. Additionally, the biosynthesis of the related polyketide tripyrnidone (5) was induced, whose novel tricyclic scaffold we elucidated by NMR and HRESIMS data. The corresponding biosynthetic polyketide synthase-encoding gene cluster responsible for the production of these compounds was identified. The tropolones as well as tripyrnidone (5) are produced by genes that belong to the broad reservoir of the fungal genome for the synthesis of different secondary metabolites, which are usually silenced under standard laboratory conditions. These molecules might be part of the bacterium-fungus competition in the complex soil environment, with the bacterial glycopeptide antibiotic as specific environmental trigger for fungal induction of this cluster.

Evidence of the Involvement of a Cyclase Gene in the Biosynthesis of Ochratoxin A in Aspergillus carbonarius

Ochratoxin A (OTA) is a well-known mycotoxin with wide distribution in food and feed. Fungal genome sequencing has great utility for identifying secondary metabolites gene clusters for known and novel compounds. A comparative analysis of the OTA-biosynthetic cluster in A. steynii, A. westerdijkiae, A. niger, A. carbonarius, and P. nordicum has revealed a high synteny in OTA cluster organization in five structural genes (otaA, otaB, ota, otaR1, and otaD). Moreover, a recent detailed comparative genome analysis of Aspergilli OTA producers led to the identification of a cyclase gene, otaY, located in the OTA cluster between the otaA and otaB genes, encoding for a predicted protein with high similarity to SnoaLs domain. These proteins have been shown to catalyze ring closure steps in the biosynthesis of polyketide antibiotics produced in Streptomyces. In the present study, we demonstrated an upregulation of the cyclase gene in A. carbonarius under OTA permissive conditions, consistent with the expression trends of the other OTA cluster genes and their role in OTA biosynthesis by complete gene deletion. Our results pointed out the involvement of a cyclase gene in OTA biosynthetic pathway for the first time. They represent a step forward in the understanding of the molecular basis of OTA biosynthesis in A. carbonarius.

A high-quality fungal genome assembly resolved from a sample accidentally contaminated by multiple taxa

Contamination in sequenced genomes is a relatively common problem and several methods to remove non-target sequences have been devised. Typically, the target and contaminating organisms reside in different kingdoms, simplifying their separation. The authors present the case of a genome for the ascomycete fungus Teratosphaeria eucalypti, contaminated by another ascomycete fungus and a bacterium. Approaching the problem as a low-complexity metagenomics project, the authors used two available software programs, BlobToolKit and anvi'o, to filter the contaminated genome. Both the de novo and reference-assisted approaches yielded a high-quality draft genome assembly for the target fungus. Incorporating reference sequences increased assembly completeness and visualization elucidated previously unknown genome features. The authors suggest that visualization should be routine in any sequencing project, regardless of suspected contamination.

Diversity, multifaceted evolution, and facultative saprotrophism in the European Batrachochytrium salamandrivorans epidemic

While emerging fungi threaten global biodiversity, the paucity of fungal genome assemblies impedes thoroughly characterizing epidemics and developing effective mitigation strategies. Here, we generate de novo genomic assemblies for six outbreaks of the emerging pathogen Batrachochytrium salamandrivorans (Bsal). We reveal the European epidemic currently damaging amphibian populations to comprise multiple, highly divergent lineages demonstrating isolate-specific adaptations and metabolic capacities. In particular, we show extensive gene family expansions and acquisitions, through a variety of evolutionary mechanisms, and an isolate-specific saprotrophic lifecycle. This finding both explains the chytrid’s ability to divorce transmission from host density, producing Bsal’s enigmatic host population declines, and is a key consideration in developing successful mitigation measures.

Synthaser: a CD-Search enabled Python toolkit for analysing domain architecture of fungal secondary metabolite megasynth(et)ases

Background Fungi are prolific producers of secondary metabolites (SMs), which are bioactive small molecules with important applications in medicine, agriculture and other industries. The backbones of a large proportion of fungal SMs are generated through the action of large, multi-domain megasynth(et)ases such as polyketide synthases (PKSs) and nonribosomal peptide synthetases (NRPSs). The structure of these backbones is determined by the domain architecture of the corresponding megasynth(et)ase, and thus accurate annotation and classification of these architectures is an important step in linking SMs to their biosynthetic origins in the genome. Results Here we report synthaser, a Python package leveraging the NCBI’s conserved domain search tool for remote prediction and classification of fungal megasynth(et)ase domain architectures. Synthaser is capable of batch sequence analysis, and produces rich textual output and interactive visualisations which allow for quick assessment of the megasynth(et)ase diversity of a fungal genome. Synthaser uses a hierarchical rule-based classification system, which can be extensively customised by the user through a web application (http://gamcil.github.io/synthaser). We show that synthaser provides more accurate domain architecture predictions than comparable tools which rely on curated profile hidden Markov model (pHMM)-based approaches; the utilisation of the NCBI conserved domain database also allows for significantly greater flexibility compared to pHMM approaches. In addition, we demonstrate how synthaser can be applied to large scale genome mining pipelines through the construction of an Aspergillus PKS similarity network. Conclusions Synthaser is an easy to use tool that represents a significant upgrade to previous domain architecture analysis tools. It is freely available under a MIT license from PyPI (https://pypi.org/project/synthaser) and GitHub (https://github.com/gamcil/synthaser).

Widespread bacterial diversity within the bacteriome of fungi

Knowledge of associations between fungal hosts and their bacterial associates has steadily grown in recent years as the number and diversity of examinations have increased, but current knowledge is predominantly limited to a small number of fungal taxa and bacterial partners. Here, we screened for potential bacterial associates in over 700 phylogenetically diverse fungal isolates, representing 366 genera, or a tenfold increase compared with previously examined fungal genera, including isolates from several previously unexplored phyla. Both a 16 S rDNA-based exploration of fungal isolates from four distinct culture collections spanning North America, South America and Europe, and a bioinformatic screen for bacterial-specific sequences within fungal genome sequencing projects, revealed that a surprisingly diverse array of bacterial associates are frequently found in otherwise axenic fungal cultures. We demonstrate that bacterial associations with diverse fungal hosts appear to be the rule, rather than the exception, and deserve increased consideration in microbiome studies and in examinations of microbial interactions.

Synthaser: A CD-search Enabled Python Toolkit for Analysing Domain Architecture of Fungal Secondary Metabolite Megasynth(Et)ases and Beyond

Background: Fungi are prolific producers of secondary metabolites (SMs), which are bioactive small molecules with important applications in medicine, agriculture and other industries. The backbones of a large proportion of fungal SMs are generated through the action of large, multi-domain megasynth(et)ases such as polyketide synthases (PKSs) and nonribosomal peptide synthetases (NRPSs). The structure of these backbones is determined by the domain architecture of the corresponding megasynth(et)ase, and thus accurate annotation and classification of these architectures is an important step in linking SMs to their biosynthetic origins in the genome. Results: Here we report synthaser, a Python package leveraging the NCBI's conserved domain search tool for remote prediction and classification of fungal megasynth(et)ase domain architectures. synthaser is capable of batch sequence analysis, and produces rich textual output and interactive visualisations which allow for quick assessment of the megasynth(et)ase diversity of a fungal genome. synthaser uses a hierarchical rule-based classification system, which can be extensively customised by the user through a web application (http://gamcil.github.io/synthaser). We show that synthaser provides more accurate domain architecture predictions than comparable tools which rely on curated profile hidden Markov model (pHMM)-based approaches; the utilisation of the NCBI conserved domain database also allows for significantly greater flexibility compared to pHMM approaches. In addition, we demonstrate how synthaser can be applied to large scale genome mining pipelines through the construction of an Aspergillus PKS similarity network. Conclusions: synthaser is an easy to use tool that represents a significant upgrade to previous domain architecture analysis tools. synthaser is freely available under a MIT license from PyPI (https://pypi.org/project/synthaser) and GitHub (https://github.com/gamcil/synthaser). Keywords: secondary metabolism, domain architecture, polyketide synthase, nonribosomal peptide synthetase, bioinformatics, software

Analysis of wild plant pathogen populations reveals a signal of adaptation in genes evolving for survival in agriculture in the beet rust pathogen (Uromyces beticola)

Improvements in crop resistance to pathogens can reduce yield losses and address global malnourishment today. Gene-for-gene -type interactions can identify new sources of resistance but genetic resistance is often short lived. Ultimately an understanding of how pathogens rapidly adapt will allow us to both increase resistance gene durability and more effectively target chemical treatments. Until recently all agricultural pathogens were living on wild hosts. To understand crop pathogen evolution, we compared genetic diversity in agricultural and wild populations. Wild reservoirs may be the source of emergent pathogen lineages, but here we outline a strategy for comparison of wild and agricultural pathogen populations to highlight genes adapting to agriculture. To address this, we have selected and developed the beet rust system (Beta vulgaris, Uromyces beticola, respectively) as our wild-agricultural model. Our hypothesis is that pathogen adaptation to agricultural crops will be evident as divergence in comparisons of wild and agricultural plant pathogen populations. We sampled isolates in both the wild and agriculture, sequenced and assembled and annotated a large fungal genome and analysed genetic diversity in 42 re-sequenced rust isolates. We found population differentiation between isolates in the wild compared to a predominantly agricultural group. Fungal effector genes are co-evolving with host resistance and are important for successful colonisation. We predicted (and found) that these exhibit a greater signal of diversification and adaptation and more importantly displayed increased wild agricultural divergence. Finding a signal of adaptation in these genes highlights this as an important strategy to identify genes which are key to pathogen success, that analysis of agricultural isolates alone cannot.

Plant and Fungal Genome Editing to Enhance Plant Disease Resistance Using the CRISPR/Cas9 System

Crop production has been substantially reduced by devastating fungal and oomycete pathogens, and these pathogens continue to threaten global food security. Although chemical and cultural controls have been used for crop protection, these involve continuous costs and time and fungicide resistance among plant pathogens has been increasingly reported. The most efficient way to protect crops from plant pathogens is cultivation of disease-resistant cultivars. However, traditional breeding approaches are laborious and time intensive. Recently, the CRISPR/Cas9 system has been utilized to enhance disease resistance among different crops such as rice, cacao, wheat, tomato, and grape. This system allows for precise genome editing of various organisms via RNA-guided DNA endonuclease activity. Beyond genome editing in crops, editing the genomes of fungal and oomycete pathogens can also provide new strategies for plant disease management. This review focuses on the recent studies of plant disease resistance against fungal and oomycete pathogens using the CRISPR/Cas9 system. For long-term plant disease management, the targeting of multiple plant disease resistance mechanisms with CRISPR/Cas9 and insights gained by probing fungal and oomycete genomes with this system will be powerful approaches.

Telomere Roles in Fungal Genome Evolution and Adaptation

Telomeres form the ends of linear chromosomes and usually comprise protein complexes that bind to simple repeated sequence motifs that are added to the 3′ ends of DNA by the telomerase reverse transcriptase (TERT). One of the primary functions attributed to telomeres is to solve the “end-replication problem” which, if left unaddressed, would cause gradual, inexorable attrition of sequences from the chromosome ends and, eventually, loss of viability. Telomere-binding proteins also protect the chromosome from 5′ to 3′ exonuclease action, and disguise the chromosome ends from the double-strand break repair machinery whose illegitimate action potentially generates catastrophic chromosome aberrations. Telomeres are of special interest in the blast fungus, Pyricularia, because the adjacent regions are enriched in genes controlling interactions with host plants, and the chromosome ends show enhanced polymorphism and genetic instability. Previously, we showed that telomere instability in some P. oryzae strains is caused by novel retrotransposons (MoTeRs) that insert in telomere repeats, generating interstitial telomere sequences that drive frequent, break-induced rearrangements. Here, we sought to gain further insight on telomeric involvement in shaping Pyricularia genome architecture by characterizing sequence polymorphisms at chromosome ends, and surrounding internalized MoTeR loci (relics) and interstitial telomere repeats. This provided evidence that telomere dynamics have played historical, and likely ongoing, roles in shaping the Pyricularia genome. We further demonstrate that even telomeres lacking MoTeR insertions are poorly preserved, such that the telomere-adjacent sequences exhibit frequent presence/absence polymorphism, as well as exchanges with the genome interior. Using TERT knockout experiments, we characterized chromosomal responses to failed telomere maintenance which suggested that much of the MoTeR relic-/interstitial telomere-associated polymorphism could be driven by compromised telomere function. Finally, we describe three possible examples of a phenomenon known as “Adaptive Telomere Failure,” where spontaneous losses of telomere maintenance drive rapid accumulation of sequence polymorphism with possible adaptive advantages. Together, our data suggest that telomere maintenance is frequently compromised in Pyricularia but the chromosome alterations resulting from telomere failure are not as catastrophic as prior research would predict, and may, in fact, be potent drivers of adaptive polymorphism.